case study sustainable technologies

Top 10 Sustainability Case Studies & Success Stories in 2024

We adhere to clear ethical standards and follow an objective methodology . The brands with links to their websites fund our research.

Environmental and social practices have a significant impact on the long-term success of businesses. Some businesses outperform others in this area, giving them a competitive advantage. We will present ten sustainability success stories to executives searching for methods to close the sustainability gap between themselves and outperformers. 

We take a holistic approach to sustainability when presenting these case studies, seeing environmental and social challenges as a part of maintaining a sustainable business (see Figure 1). We also recognize that, while technology can aid in the improvement of corporate sustainability, changing business processes can be just as successful. As a result, we will provide a variety of scenarios that fully demonstrate the ESG framework .

1. UPS ORION: Improve transportation efficiency

Transportation activities accounted for almost 30% of US greenhouse gas (GHG) emissions. (See Figure 2). For a company like UPS, which distributes goods across regions, transportation activities make up the bulk of GHG emissions. As a result, enhancing transportation efficiency is crucial for organizations like UPS to remain sustainable.

As a solution, UPS adopted an AI system called ORION which is a route optimizer that aims to minimize the number of turns during the delivery. Initiation began in 2012 and up today UPS has been working on developing it.

ORION saves UPS 10 million gallons of fuel per year, which means that in addition to the financial benefits, it decreases UPS’s carbon footprint by 100,000 metric tonnes per year, or the equivalent to removing more than 20,000 cars from the roads.

There are public cloud route optimizer systems which businesses can deploy without building hardware. These tools help firms to use their software as a service by paying a subscription cost.

To learn more about ensuring supply chain sustainability with technology you can read our Top 5 Technologies Improving Supply Chain Sustainability article.

Figure 2: US GHG emissions.

2. IKEA IWAY: Make business with ESG oriented corporations

Supplier code of conducts are established guidelines that require other businesses to demonstrate their operations’ social and environmental impacts. The objective is to reward companies that meet strong ESG standards. It is also one of the positive governance indications for organizations, as we highlighted in our ESG metrics article .

IWAY is the supplier code of conduct of IKEA forcing suppliers to meet certain environmental and humanitarian qualities to work with. The initiative has been in place for over 20 years, and over that time, IKEA has refined it based on their prior experiences. IWAY six is the most recent version of IKEA’s supplier code of conduct, which evaluates:

• Core worker rights.
• Safety of the working place.
• Life-work balance of employees.
• Water and waste management of potential suppliers.
• Prevention of child labour. 

3. General Electric digital wind farm: Produce green energy efficiently

Wind turbine productivity varies greatly depending on the design, weather conditions, and geography of the location it is deployed. Using IoT and digital twins to collect data on each wind turbine and simulate possible modifications such as adjusting the direction of the wind turbine can assist corporations in locating their wind turbines in a wind farm more effectively (see Figure 3).

Furthermore, the performance of wind turbines declines with time and may require maintenance; employing sensors and digital twins can assist in determining the appropriate time for repair.

Figure 3: How digital twins can optimize wind turbine productivity.

The General Electric’s (GE) digital wind farms are based on these two elements. GE optimized over 15,000 turbines using sensors and digital twins technologies. Each wind farm can create up to 10% more green energy as a result of the digital wind farm initiative, which helps to enhance our worldwide green energy mix.

4. Swire Properties green building: Minimize GHG emissions

Swire Properties is a construction company that operates in China and especially in the Hong Kong area. In 2018, the company built One Taikoo Place which is a green building that aims to reduce GHG emissions of Swire Properties in order to align with sustainability goals of the company’s stakeholders.

Swire properties use 3D modeling techniques to optimize the building’s energy efficiency. Reduce electricity consumption by using smart lighting systems with sunshine and motion sensors. A biodiesel generation system has been installed in the building, which converts waste food oil into biodiesel. Swire Properties additionally uses low carbon embedded materials and a lot of recycled materials in their construction.

Swire Properties was able to cut GHG emissions intensity throughout their portfolio by nearly 20% because of the usage of digital technologies and low carbon integrated materials.

5. H&M Let’s Close the Gap: Deposit scheme for gathering raw material

In 2021, we consumed 1.7 times more resources than Earth generates annually because our economic outlook is based on production, use and disposal. Such an economy is not sustainable and that is the reason why the concept of circular economy (CE) is trending nowadays.

The most basic principles of CE is to use trash as a raw material for production through innovation, recycling, or repairing and reusing existing products.

H&M’s “Let’s Close the Gap” project began in 2013 as a CE best practice that collects and categorizes discarded clothing from customers. If the garment is in decent condition, they will restore it and find a new owner for it. If a garment reaches the end of its useful life, H&M will recycle it and reuse the material in new goods.

Customers who bring in their old clothes are rewarded with tokens that can be used to get a discount at H&M shops. Incentivizing customers creates a complete CE loop.

In 2019, 57% of H&M’s raw materials were sustainable, according to Forbes. By 2030, the company hopes to improve it 100 percent.

6. Gusto: Hiring female engineers to close gender inequality gap

Gender inequality remains a major social issue despite all the improvements. There are two common types of gender disparity in the workplace. The first is gender pay disparity, which occurs when companies pay male employees more and provide better working conditions than female employees in the same position. 

The second is occupational segregation, in which women are hired for non-technical jobs while men hold the majority of leadership roles. This was the situation at software firm Gusto, where female engineers made up slightly more than 5% of the engineering team at the beginning of 2015. 

Julia Lee , one of Gusto’s first female engineers, claimed that other engineers did not accept her ideas because she was a “female engineer.” Gusto initiated an HR drive to reduce gender inequality by prioritizing the recruitment of female engineers, prohibiting female workers from scrolling, and deleting masculine job ads like “ninja rockstar coder.”

Gusto was able to improve its female engineer ratio to roughly 20% by the end of 2015 thanks to the campaign. The average ratio among software businesses’ engineering teams was 12% in 2013, therefore this was a significant improvement in a short period of time.  

7. HSBC: ESG concerned green finance

Finance companies can help speed up the transition to sustainable business practices by supporting initiatives run by responsible businesses. By the end of 2025, HSBC has committed to investing $100 billion in sustainability projects. HSBC already has funded sustainability projects that require more than $50 billion in investment as of 2019, indicating that the corporation is on track to meet its objective.

HSBC created an ESG risk evaluation framework to assure funding for green projects in 2019. Since then, the framework has been improved. In 2021, HSBC’s ESG practices were rewarded with an AA rating by MSCI.

HSBC is also working toward a goal of using 100% renewable energy as their source of electricity by 2030. Company reduces its consumption of paper, and single used plastics for coffee and beverages.

For more information about best ESG practices you can read our Top 6 ESG Reporting Best Practices article.

8. Signify light-as-a-Service: Enhance production stewardship

The product-service system ( PSS ) is a business model in which producers acquire a product over its lifetime and rent or lease it to the users. PSS ensures product stewardship since the product always becomes the asset of the company. It encourages producers to provide high-quality, repairable items in order to extend the product’s useful life. As a result, it helps to close the circularity gap by ensuring better use of natural resources.

Signify, a luminaire producer, adopts such a business strategy where it demands a subscription fee according to usage period of their lightning systems. PSS allows Signify claims that PSS allows them to produce 0 luminaire waste and drops maintenance costs around 60%.

9. Airbus additive manufacturing: Manufacture lighter planes with 3D printing

AIMultiple expects that additive manufacturing will disruptive for the airplane manufacturing since:

• It speeds up the manufacturing of parts compared to traditional molding techniques.
• It is cheaper due to effective use of raw materials and time reduction of production.
• It enables the manufacturing of lighter parts by up to 45% , resulting in lighter planes that burn less fuel. According to Airbus, additive manufacturing technology can reduce an A320 plane’s annual GHG emissions by around 465,000 metric tons, which is roughly the same as eliminating 100,000 automobiles from the road for a year. (An average car emits 4.6 tonnes of GHG per year). 

To effectively use 3D printers Airbus partnered with Materialise , a Belgium-based technology company  that specialize in additive manufacturing.

For more information regarding improving corporate sustainability by digital transformation you can read our Top 4 Digital Technologies that Improve Corporate Sustainability article.

10. Tata Power: Solar plants on the roofs

Rooftops offer a lot of empty space that can be used to install solar panels. Such initiatives have been taken in various parts of the world. Tata Power does it in India and generates green electricity by using idle places of buildings.

In 2021, Tata Power was able to spread their program throughout 90 Indian cities, producing 421 million watts of electricity, which is equivalent to nearly 40 thousand homes’ yearly electricity use in the US. (The average annual power usage for a residential utility customer in the US was 10,715 kWh in 2020, according to the EIA .).

We expect that in the near future the cooperation between energy and construction companies will enhance the use of idle places in buildings in a more effective way. Such an industrial symbiosis reduces both sectors’ ESG risk.

For more information on the top carbon footprint calculators, check our article, Top 7 Carbon Footprint Calculator Software/Tools for Businesses .

To learn more about corporate sustainability you can contact with us:

This article was drafted by former AIMultiple industry analyst Görkem Gençer.

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4 ways big data can help fight climate change in 2024, top 6 circular economy best practices for businesses in 2024, 5 ways to reduce corporate carbon footprint in 2024.

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A wonderful collection of case studies on corporate sustainability. I enjoyed the read. I am convicted to delve into promoting sustainability in Africa.

Hello, James! Thank you for your feedback. Awesome! That’s a great cause to pursue.

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Case Studies of 15 Sustainable Tech Companies

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• Key Takeaways

Renewable Energy Growth: According to Statista , renewable energy’s share in the global power production is projected to increase significantly by 2025, showcasing the impact of sustainable tech.

Market Value: Gartner reports that the global market for environmentally sustainable technology is set to see substantial growth, underscoring the sector’s increasing economic influence.

Consumer Demand: SEMRush analysis reveals a surge in online searches related to sustainable products, indicating growing consumer interest in eco-friendly solutions.

Sustainable technology companies are at the forefront of addressing environmental challenges, showcasing the vital role of innovation in achieving sustainability.

The economic viability of these companies demonstrates that environmental sustainability and business success are not mutually exclusive but rather complementary.

In the face of escalating environmental challenges, a wave of innovative companies is rising, championing the cause of sustainability through groundbreaking technology. These sustainable tech companies are not merely operating within the tech industry; these tech companies are redefining it, proving that business success and environmental stewardship can go hand in hand. By pioneering solutions that range from renewable energy to waste reduction, these companies are setting the stage for a future where technology acts as a force for positive environmental change, offering hope and actionable pathways towards a more sustainable planet.

1. Tesla, Inc.: Pioneering the Future of Sustainable Transport

• Innovations in Electric Vehicles

Tesla, Inc. has revolutionized the automotive industry with its range of electric vehicles (EVs). Leading the charge towards a sustainable future, Tesla’s EVs are renowned for their exceptional performance, safety, and zero emissions. The company’s commitment to innovation is evident in its continuous improvements in battery technology, driving range, and charging infrastructure. Tesla’s Model S, Model 3, Model X, and Model Y have set new standards for electric mobility, combining luxury with sustainability.

• Renewable Energy Storage Solutions

Beyond vehicles, Tesla is at the forefront of renewable energy storage solutions. The Powerwall, Powerpack, and Megapack batteries aim to store renewable energy efficiently, making it accessible for homes, businesses, and utility-scale projects even when the sun isn’t shining or the wind isn’t blowing. This technology is crucial for transitioning to a grid powered by renewable sources, as it addresses the issue of energy reliability and security.

• Solar Roof and Solar Energy Products

Tesla’s Solar Roof and traditional solar panels represent significant advancements in harnessing solar energy for residential and commercial use. The Solar Roof, in particular, integrates solar cells seamlessly into roof tiles, combining aesthetics with functionality. These products are designed to reduce dependency on fossil fuels by making renewable energy generation more accessible and attractive to a broader audience.

• Global Supercharger Network

To support its EVs , Tesla has built an extensive Global Supercharger Network, allowing Tesla vehicle owners to charge their cars quickly and conveniently over long distances. This network is a critical component of Tesla’s strategy to make electric vehicle ownership as convenient as possible, addressing one of the main concerns potential buyers have about EVs: range anxiety.

• Commitment to Zero Emissions

Tesla’s overarching mission is to accelerate the world’s transition to sustainable energy. Through its electric vehicles, energy storage, and solar products, the company is not only reducing the carbon footprint of transportation but also leading by example in the corporate world. Tesla’s efforts have sparked significant changes in the automotive and energy sectors, pushing more companies to consider sustainability in their operations and product offerings.

Tesla, Inc.’s impact on the sustainable technology landscape is profound. Through continuous innovation and a relentless drive towards sustainability, Tesla is not just a company; it’s a catalyst for change in the global pursuit of a cleaner, greener future.

2. Vestas Wind Systems: Pioneering the Future of Wind Energy

• Innovations in Wind Turbine Technology

Vestas Wind Systems stands at the forefront of wind energy innovation, revolutionizing how wind turbines harness and generate power. With a focus on efficiency and durability, Vestas’ turbines are designed to maximize energy capture in diverse climates and terrains. Their cutting-edge blade design and intelligent turbine control systems represent significant advancements, reducing the cost of energy and making wind power more accessible and sustainable worldwide.

• Global Wind Power Installations

As a testament to their commitment to sustainability, Vestas has installed wind turbines in over 80 countries, contributing significantly to the global shift towards renewable energy. Their projects range from vast, multi-turbine wind farms to single installations, each tailored to meet the energy needs of the community it serves. This global footprint not only highlights Vestas’ technical expertise but also their role in promoting sustainable energy across the world.

• Sustainable Manufacturing Processes

Sustainability at Vestas extends beyond their products to encompass their entire manufacturing process. The company prioritizes the use of recyclable materials, strives for zero waste in production, and implements energy-efficient practices in their facilities. By focusing on reducing the environmental impact of their operations, Vestas sets a benchmark for sustainability in the manufacturing sector, ensuring that their turbines are produced with minimal environmental footprint.

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• Wind Power Accessibility

Vestas is committed to making wind power accessible to all, working to lower the cost of wind energy and advocating for policies that support renewable energy development. Their initiatives aim to democratize access to clean energy, enabling communities, businesses, and governments to transition away from fossil fuels. Through innovation and advocacy, Vestas plays a crucial role in making sustainable energy a viable option for everyone, regardless of location or economic status.

• Reducing Carbon Footprint

The ultimate goal of Vestas Wind Systems is to contribute to a significant reduction in the global carbon footprint through the adoption of wind power. By displacing fossil fuel-based electricity generation with clean, renewable wind energy, Vestas helps to cut CO2 emissions and combat climate change. Their efforts not only contribute to a healthier planet but also to a more sustainable and secure energy future for generations to come.

3. SolarCity: A Leader in Solar Energy

• Solar Panel Installation and Efficiency

SolarCity, now a subsidiary of Tesla, Inc., has revolutionized the solar energy industry with its commitment to making solar power accessible and affordable for homeowners across the United States. Their state-of-the-art solar panels are designed for maximum efficiency, capturing sunlight even on cloudy days. This ensures that households can generate more electricity, reducing their reliance on fossil fuels and lowering their carbon footprint. SolarCity’s innovative approach to installation, including sleek, integrated designs and hassle-free setup, has made solar energy a viable option for a wide demographic, contributing significantly to the growth of renewable energy adoption.

• Affordable Solar Solutions for Homes

One of SolarCity’s key achievements is its ability to offer solar energy solutions at an affordable price. Through a variety of financing options, including leasing and power purchase agreements (PPAs), SolarCity has removed the financial barriers that once made solar energy inaccessible to the average consumer. Customers can now enjoy the benefits of solar energy with little to no upfront costs, paying for the power they produce at rates lower than traditional utility prices. This model not only promotes sustainable energy but also encourages more homeowners to transition to solar power, amplifying the impact on environmental conservation.

• Grid Services and Solar Energy Storage

Beyond solar panel installations, SolarCity is pioneering in the realm of grid services and solar energy storage. Their development of the Powerwall, a home battery system, allows users to store excess solar energy generated during the day for use at night or during power outages. This technology not only enhances the efficiency and reliability of solar energy systems but also plays a crucial role in stabilizing the electrical grid. By allowing homes to operate independently of the grid or supply energy back to it, SolarCity is at the forefront of creating a more sustainable, resilient, and decentralized energy infrastructure.

• Expanding Access to Solar Energy

SolarCity’s initiatives extend beyond individual homes, aiming to expand access to solar energy across various sectors. By implementing large-scale solar projects and community solar gardens, they are making renewable energy available to schools, businesses, and non-profit organizations. This broadened access helps to reduce overall carbon emissions and fosters a community-wide shift towards sustainability. SolarCity’s efforts in expanding solar energy access demonstrate a commitment to environmental stewardship and social responsibility, marking them as a leader in the renewable energy sector.

• Innovations in Solar Financing

A key factor in SolarCity’s success is its innovative approach to solar financing. Understanding that the initial cost of solar installation can be a significant barrier for many, SolarCity introduced groundbreaking financing options that have changed the landscape of the solar industry. By offering various financing models, such as solar leases and power purchase agreements (PPAs), they have made solar energy financially accessible to a broader audience. This strategic move has not only accelerated the adoption of solar power but also established SolarCity as a trailblazer in promoting renewable energy through economic incentives.

4. Beyond Meat: A Pioneer in Plant-Based Meat Alternatives

• Plant-based Meat Alternatives

Beyond Meat has revolutionized the food industry with its innovative approach to creating plant-based meat alternatives. Their products, designed to mimic the taste, texture, and nutritional benefits of animal meat, cater to a growing demand for sustainable and ethical food choices. By utilizing proteins from peas, beans, and other plants, Beyond Meat offers a variety of products including burgers, sausages, and ground meat substitutes that appeal to not just vegetarians and vegans but also meat-eaters looking to reduce their meat consumption.

• Reducing Environmental Impact of Livestock Farming

The environmental benefits of Beyond Meat’s products are significant. Livestock farming is a major contributor to greenhouse gas emissions, deforestation, and water depletion. By providing plant-based alternatives, Beyond Meat helps reduce the demand for animal agriculture, thus lowering the strain on natural resources and contributing to a reduction in the environmental footprint associated with traditional meat production. This shift not only addresses climate change but also promotes biodiversity and ecosystem preservation.

• Sustainability in Food Production

Beyond Meat’s commitment to sustainability extends beyond its products. The company focuses on reducing water usage, energy consumption, and greenhouse gas emissions throughout its production process. By leveraging sustainable sourcing practices and optimizing manufacturing efficiencies, Beyond Meat sets a benchmark for sustainability in the food industry. Their approach demonstrates how companies can significantly impact environmental conservation through operational decisions.

• Health and Nutritional Benefits

Beyond Meat’s plant-based products also offer health benefits. Compared to traditional animal meat, their products contain no cholesterol, less saturated fat, and additional dietary fiber, aligning with a growing consumer interest in healthier eating habits. Beyond Meat’s commitment to non-GMO ingredients further emphasizes their focus on health and wellness, appealing to consumers looking for clean, wholesome food options without compromising on taste or texture.

• Global Expansion and Accessibility

As Beyond Meat continues to expand globally, it aims to make sustainable, plant-based meats accessible to a wider audience. By entering new markets and scaling production, the company strives to lower costs, making its products more competitive with traditional meat. This expansion is not just about business growth; it’s about promoting a sustainable and healthy lifestyle across the globe, demonstrating that sustainable eating habits can be both delicious and accessible to everyone.

5. Rivian: Pioneering Sustainable Adventure

Rivian stands at the forefront of sustainable transportation, focusing on electric adventure vehicles designed to inspire and facilitate exploration without environmental compromise. As a company, Rivian has redefined what it means to venture into the great outdoors, ensuring that adventure seekers can enjoy the natural world while preserving its beauty. Their electric vehicles (EVs), notably the R1T pickup and the R1S SUV, combine high performance with zero emissions, setting new standards for what vehicles can accomplish both on and off-road.

• Sustainable Vehicle Manufacturing

Rivian’s commitment to sustainability extends beyond their electric vehicles. The company embraces eco-friendly manufacturing practices, aiming to minimize its environmental impact. From using renewable energy sources in their production facilities to implementing responsible sourcing policies for materials, Rivian is dedicated to reducing its carbon footprint. The company’s manufacturing approach reflects a broader commitment to sustainability, ensuring that every step in the process contributes to a greener planet.

• Battery Technology and Range

At the heart of Rivian’s innovation is its cutting-edge battery technology, which offers impressive range and durability for long-distance travel. Rivian vehicles are equipped with high-capacity battery packs that provide a range of over 300 miles on a single charge, addressing one of the most significant barriers to EV adoption. Furthermore, Rivian is continuously working on improving battery efficiency and lifespan, pushing the boundaries of what electric vehicles can achieve.

• Environmental Conservation Initiatives

Rivian’s dedication to the environment goes beyond its products. The company actively engages in conservation initiatives, partnering with organizations dedicated to preserving natural habitats and promoting sustainability. Through investments in renewable energy projects and commitments to restore ecosystems, Rivian demonstrates a profound commitment to environmental stewardship. These initiatives are integral to Rivian’s mission, reflecting a deep-seated belief in the importance of protecting the planet for future generations.

• Investment in Clean Energy

Understanding the crucial role of renewable energy in combating climate change, Rivian invests in clean energy solutions both within and outside its operations. The company’s facilities are powered by renewable energy sources, and it supports the development of clean energy infrastructure, such as charging stations powered by green energy. Rivian’s investment in clean energy underscores its holistic approach to sustainability, recognizing that a sustainable future requires comprehensive solutions that encompass all aspects of our energy use.

6. Ørsted: Pioneering a Greener Future

• Transition from Fossil Fuels to Renewables

Ørsted stands as a beacon of transformation in the energy sector, having shifted its focus from fossil fuels to becoming a global leader in renewable energy. This remarkable transition underscores Ørsted’s dedication to combating climate change and its commitment to sustainability. By investing heavily in wind, solar, and bioenergy sources, Ørsted is not only reducing its carbon footprint but also leading by example, showing that a sustainable energy future is both viable and profitable.

• Offshore Wind Farm Development

A cornerstone of Ørsted’s renewable energy portfolio is its global leadership in offshore wind farm development. Ørsted’s offshore wind farms are at the forefront of technology, harnessing the power of the ocean winds to generate clean, renewable energy. These projects not only contribute significantly to reducing global carbon emissions but also play a crucial role in driving forward the technology and economies of scale necessary for offshore wind to become a mainstay in the global energy mix.

• Biomass and Energy from Waste

In its quest for sustainability, Ørsted has also ventured into biomass and energy-from-waste solutions, turning organic waste and by-products into valuable sources of energy. This approach not only diverts waste from landfills, reducing greenhouse gas emissions, but also provides a renewable source of power and heating. By innovating in the conversion of waste to energy, Ørsted is tackling two critical environmental challenges at once: waste management and clean energy production.

• Green Energy Solutions

Ørsted’s commitment to sustainability extends beyond its energy production methods; it encompasses a holistic approach to green energy solutions. This includes efforts to make renewable energy more accessible and affordable for both businesses and consumers, developing smart energy systems that can integrate various renewable sources, and working towards a future where cities and communities are powered by green, sustainable energy. Ørsted’s vision for a world that runs entirely on green energy is driving its innovations and investments in renewable technologies.

• Biodiversity and Ecosystem Protection

Understanding the interconnectedness of energy production and environmental health, Ørsted places a strong emphasis on biodiversity and ecosystem protection. Its projects are designed and implemented with a keen awareness of their environmental impact, incorporating measures to protect marine and terrestrial habitats. Through research, collaboration with environmental organizations, and adherence to strict environmental standards, Ørsted is leading the way in ensuring that renewable energy projects contribute positively not only to the climate but also to the natural world.

7. Patagonia: Pioneering Sustainability in Outdoor Apparel

• Eco-friendly Outdoor Clothing and Gear

Patagonia stands out as a beacon of sustainability within the outdoor apparel industry. This company has set the bar high by using recycled materials and organic cotton in its products, significantly reducing its environmental footprint. Patagonia’s commitment to quality and durability also means its clothing and gear have longer lifespans, decreasing the need for frequent replacements and, consequently, reducing waste.

• Environmental Activism and Advocacy

Beyond its sustainable product line, Patagonia is deeply engaged in environmental activism and advocacy. The company dedicates a portion of its sales to environmental projects and campaigns, supporting hundreds of grassroots organizations working to preserve and restore the natural environment. Patagonia’s bold stance on various environmental issues, including land conservation and climate change, exemplifies its commitment to not just being a business, but a catalyst for positive environmental change.

• Sustainable Supply Chains

Patagonia’s approach to sustainability extends into its supply chain. The company rigorously ensures that all aspects of its operations, from sourcing materials to manufacturing processes, adhere to the highest environmental and ethical standards. This includes fair labor practices and minimizing the carbon footprint throughout its supply chain. Patagonia’s transparency in these efforts not only sets a precedent for the industry but also builds trust with consumers who are increasingly concerned about the ethical implications of their purchases.

• Regenerative Organic Agriculture

Understanding the critical role of agriculture in sustainability, Patagonia has ventured into regenerative organic agriculture. This initiative focuses on farming methods that restore soil health, improve biodiversity, and capture carbon, thereby addressing the urgent need for sustainable food systems. By investing in and promoting regenerative organic practices, Patagonia is contributing to a solution that benefits the planet, farmers, and consumers alike.

• Circular Economy Initiatives

Patagonia is a pioneer in embracing the circular economy, an economic system aimed at eliminating waste and the continual use of resources. The company’s Worn Wear program encourages customers to repair, share, and recycle their gear instead of buying new. This initiative not only extends the life of Patagonia products but also challenges the conventional consumer culture by promoting the idea of buying less and using longer. Through these efforts, Patagonia demonstrates how businesses can thrive while making a positive impact on the environment and society.

8. Enphase Energy: Revolutionizing Solar Power with Microinverters

• Pioneering Solar Microinverter Technology

Enphase Energy has set itself apart in the sustainable technology sector with its innovative solar microinverter technology. Unlike traditional solar systems that rely on a single central inverter, Enphase’s microinverters are installed on each solar panel. This design enhances the efficiency and reliability of solar energy production. By converting DC electricity generated by each panel into AC electricity right on the rooftop, microinverters minimize energy loss and ensure that the solar array continues to perform optimally, even if one panel is shaded or malfunctioning.

• Advancing Energy Management Systems

Beyond solar power conversion, Enphase Energy is at the forefront of energy management with its smart, connected technology. The company’s energy management systems allow homeowners and businesses to monitor and control their solar energy consumption with unprecedented precision. Through the Enphase Enlighten platform, users can track their energy production and usage in real-time, making adjustments to maximize savings and efficiency. This level of insight and control is pivotal for integrating solar energy into daily life seamlessly and maximizing the return on investment in renewable energy.

• Ensuring Reliable and Safe Solar Solutions

Safety and reliability are paramount in the adoption of solar energy, and Enphase Energy has led the charge in making solar installations safer and more dependable. The microinverters’ design significantly reduces the risk of electrical fires by eliminating the need for high-voltage DC wiring across the rooftop. This advancement not only protects homes and businesses but also instills confidence in solar technology as a safe, viable option for sustainable energy. Moreover, Enphase’s commitment to quality and durability ensures that their systems are built to last, further enhancing the value proposition of solar energy.

• Driving Global Solar Energy Adoption

Enphase Energy’s innovative products and solutions play a crucial role in accelerating the adoption of solar energy worldwide. By making solar power more efficient, safer, and easier to manage, Enphase has lowered the barriers to entry for residential and commercial users alike. The company’s global presence and expansive network of installers and partners mean that Enphase technology is accessible to a wide audience, driving the shift toward renewable energy on a global scale. This widespread adoption is critical in the fight against climate change, making Enphase Energy a key player in the transition to a more sustainable and resilient energy system.

• Leading Innovation in Renewable Energy

At the heart of Enphase Energy’s success is its unwavering commitment to innovation. The company continuously invests in research and development to enhance its microinverter technology, expand its product line, and explore new ways to integrate solar energy into the grid intelligently. By pushing the boundaries of what’s possible in renewable energy, Enphase not only contributes to the growth of the solar industry but also plays a vital role in shaping the future of global energy consumption. This dedication to innovation ensures that Enphase Energy remains at the cutting edge of sustainable technology, leading the way toward a cleaner, greener planet.

9. Impossible Foods: A Trailblazer in Plant-Based Meat

• Science-Based Plant Meat Products

Impossible Foods has revolutionized the food industry with its innovative approach to creating plant-based meat products. Leveraging scientific research, the company has developed a method to replicate the taste, texture, and aroma of real meat using plant ingredients. This breakthrough not only caters to vegetarians and vegans but also offers a sustainable alternative for meat-lovers, significantly reducing the environmental impact associated with animal agriculture.

• Impact on Reducing Animal Agriculture

The mission of Impossible Foods extends beyond offering plant-based alternatives; it’s about addressing the environmental crises linked to animal farming. Animal agriculture is a major contributor to deforestation, water depletion, and greenhouse gas emissions. By providing a delicious and viable alternative, Impossible Foods aims to reduce the demand for animal products, thereby lessening the strain on natural resources and mitigating climate change.

• Sustainable Food Technology

The core of Impossible Foods’ success lies in its sustainable food technology, particularly the use of heme, an iron-containing molecule found in plants and animals that gives its burgers the distinctive taste of meat. This technology showcases how science can be harnessed for sustainable purposes, creating food products that are not only kind to the planet but also meet consumer expectations for taste and quality.

• Health Benefits of Plant-based Diets

Adopting a plant-based diet has numerous health benefits, including a lower risk of heart disease, hypertension, type 2 diabetes, and certain cancers. Impossible Foods contributes to this shift by providing products that allow consumers to enjoy their favorite meals while also reaping the health benefits of plant-based ingredients. Their products are designed to be nutritious, containing essential vitamins and minerals without the cholesterol and hormones found in conventional meat.

• Expanding the Range of Products

Impossible Foods is continuously expanding its product range to cater to a broader audience. From burgers to sausages and other meat alternatives, the company is innovating to ensure that consumers have a variety of choices. This expansion is critical for making plant-based diets more accessible and appealing to the public, further supporting the transition to more sustainable eating habits worldwide.

10. AquaTech: Pioneers in Sustainable Water Management

• Sustainable Water Management Solutions

AquaTech is at the forefront of addressing one of the most critical environmental challenges: sustainable water management. Recognizing the importance of conserving this vital resource, the company develops technologies and systems designed to optimize water usage in various sectors. Their innovative approaches help industries, municipalities, and agricultural sectors reduce water waste and enhance efficiency, ensuring water sustainability for future generations.

• Advanced Water Treatment Technologies

The heart of AquaTech’s mission lies in its advanced water treatment technologies. By employing state-of-the-art purification and recycling methods, the company enables the reuse of water, minimizing the environmental footprint of water consumption. These technologies are not just about conservation; they also ensure that the water returned to the environment is clean and safe, addressing pollution and contamination issues head-on.

• Desalination and Water Recycling

A key area of AquaTech’s expertise is desalination and water recycling. With the world facing freshwater scarcity, turning to the oceans becomes a necessary option. AquaTech’s desalination technologies are designed to be energy-efficient and cost-effective, making seawater a viable source of fresh water for drinking, agriculture, and industrial uses. Moreover, their water recycling solutions transform wastewater into clean water, ready for reuse, which is crucial for regions with limited water resources.

• Impact on Water Scarcity

The impact of AquaTech’s solutions on global water scarcity cannot be overstated. By providing technologies that make water use more sustainable, AquaTech plays a critical role in alleviating water scarcity. Their systems enable communities and industries in arid and drought-prone areas to secure a reliable water supply, supporting not only economic growth but also improving the quality of life for millions of people worldwide.

• Innovation in Water Conservation

Innovation drives AquaTech’s contributions to water conservation. The company continuously explores new ways to save, clean, and reuse water, staying ahead of the environmental challenges posed by a changing climate and growing population. Their commitment to research and development leads to breakthroughs that push the boundaries of what’s possible in water conservation, setting new standards for sustainability in the water sector.

11. Ecolab: Pioneering Sustainable Cleaning and Sanitation

• Sustainable Cleaning and Sanitation Products

Ecolab stands out as a leader in developing sustainable cleaning and sanitation products, serving industries ranging from hospitality to healthcare. Their commitment to sustainability is evident in their eco-friendly product formulations that aim to reduce environmental impact without compromising effectiveness. By focusing on solutions that use less water, energy, and generate fewer emissions, Ecolab sets the standard for sustainable cleaning practices worldwide.

• Water Conservation Technologies

Water is at the core of Ecolab’s sustainability mission. The company has pioneered technologies aimed at water conservation, helping businesses to efficiently manage and reduce their water usage. Through advanced monitoring and management systems, Ecolab offers insights and solutions that significantly cut down water consumption, supporting global efforts to combat water scarcity and promote water stewardship.

• Energy Efficiency Solutions

Ecolab extends its environmental commitment to energy efficiency, providing solutions that help clients save energy and reduce costs. Their innovative technologies and services optimize energy use in various processes, contributing to lower greenhouse gas emissions and a reduced carbon footprint for businesses. Ecolab’s energy-efficient solutions demonstrate their holistic approach to sustainability, addressing both environmental and economic challenges.

• Reduction in Waste and Emissions

Reducing waste and emissions is a critical component of Ecolab’s sustainability strategy. The company designs products and processes that minimize waste generation and decrease emissions throughout their lifecycle. By helping clients implement more sustainable practices, Ecolab not only improves their environmental performance but also enhances their operational efficiency and compliance with environmental regulations.

• Sustainable Food Processing Solutions

In the food industry, Ecolab has become synonymous with sustainable food processing solutions. They offer a comprehensive suite of products and services designed to ensure food safety and quality while minimizing environmental impact. From reducing water and energy use in food production to implementing more sustainable cleaning and sanitation practices, Ecolab supports the food sector in achieving its sustainability goals, ensuring a safer and more sustainable food supply chain.

12. Gogoro: Pioneering Sustainable Urban Mobility

• Smart Electric Scooters

Gogoro stands out as a beacon of innovation in the realm of sustainable technology companies, particularly with its smart electric scooters. These scooters are not just eco-friendly; they’re designed with the modern urbanite in mind, offering a sleek, efficient, and performance-driven alternative to fossil fuel-dependent vehicles. By prioritizing electric power, Gogoro’s scooters significantly reduce carbon emissions, making a tangible impact on urban air quality.

• Battery Swapping Stations Network

One of Gogoro’s most revolutionary contributions to sustainable urban mobility is its network of battery swapping stations. This system addresses one of the most significant barriers to electric vehicle adoption: charging time and battery life anxiety. Riders can easily exchange their depleted batteries for fully charged ones at any swapping station within minutes, ensuring they’re always powered up and ready to go. This innovative approach not only makes electric scooters more convenient but also encourages their adoption on a wider scale.

• Urban Mobility Solutions

Gogoro’s vision extends beyond just creating electric scooters; it aims to revolutionize urban mobility as a whole. The company’s smart scooters and battery swapping technology are part of a larger ecosystem designed to make cities more sustainable and livable. By providing a practical, efficient, and eco-friendly transportation alternative, Gogoro is helping to reduce traffic congestion, lower pollution levels, and promote a cleaner, greener urban environment.

• Reducing Urban Pollution

The environmental impact of Gogoro’s electric scooters is profound, especially in the context of reducing urban pollution. Traditional gasoline-powered vehicles are major contributors to air pollution in cities, releasing a plethora of harmful pollutants that affect air quality and public health. Gogoro’s electric scooters, on the other hand, emit no tailpipe pollutants, making them a key player in the fight against urban pollution and the quest for cleaner air.

• Sustainable Manufacturing Practices

Gogoro’s commitment to sustainability is evident not only in its products but also in its manufacturing practices. The company adheres to environmentally friendly production methods, ensuring that its scooters are built with a minimal environmental footprint. From the materials used to the energy sources powering its factories, Gogoro takes a holistic approach to sustainability, setting a benchmark for responsible manufacturing in the tech industry.

13. Proterra: Pioneering Electric Buses for Sustainable Urban Transit

• Electric Buses and Commercial Vehicles

Proterra has established itself as a leader in the design and manufacture of electric buses and commercial vehicles, aiming to revolutionize public transit and reduce dependency on fossil fuels. Their electric buses are known for their high performance, long-range capabilities, and significant reduction in greenhouse gas emissions compared to traditional diesel buses. Proterra’s commitment to sustainable urban transit is evident in their continuous innovation and dedication to environmentally friendly transportation solutions.

• Battery Technology for Heavy-Duty Transport

At the heart of Proterra’s electric buses is their cutting-edge battery technology, designed specifically for heavy-duty transport. This technology allows for quick charging, extended range, and durability, ensuring that the buses can meet the demands of daily public transit operations. Proterra’s battery systems not only provide a sustainable alternative to fossil fuel-based transportation but also offer a cost-effective solution over the vehicle’s lifespan, thanks to lower maintenance and operational costs.

• Electrification of Public Transportation

Proterra is at the forefront of the electrification of public transportation, working closely with transit agencies across the United States to integrate electric buses into their fleets. By replacing diesel buses with electric ones, Proterra is helping cities and communities reduce carbon emissions, improve air quality, and move towards a more sustainable future. The company’s efforts are an essential step in the transition to cleaner, more sustainable urban environments.

• Reduction of Greenhouse Gas Emissions

One of Proterra’s key contributions to sustainability is the significant reduction of greenhouse gas emissions achieved through their electric buses. By shifting away from diesel and towards electricity—often sourced from renewable energy—Proterra’s vehicles help mitigate climate change and contribute to cleaner air in urban areas. This shift not only benefits the environment but also enhances the quality of life for city dwellers by reducing pollution levels.

• Sustainable Urban Transit Solutions

Proterra’s vision extends beyond just manufacturing electric buses; they aim to provide comprehensive sustainable urban transit solutions. This includes developing efficient charging infrastructure and offering fleet management services to ensure the seamless integration of electric buses into existing transit systems. Proterra’s holistic approach to sustainability in public transportation exemplifies their dedication to innovation, environmental stewardship, and the betterment of communities worldwide.

14. Bloom Energy: Pioneering Clean Energy Solutions

• Solid Oxide Fuel Cell Technology

Bloom Energy is at the forefront of developing solid oxide fuel cell technology, a breakthrough in clean energy production. This innovative approach allows for the generation of electricity through a chemical process, bypassing traditional combustion methods. The result is highly efficient power generation with significantly reduced greenhouse gas emissions. Bloom Energy’s fuel cells are capable of using natural gas, biogas, or hydrogen as fuel sources, offering a versatile solution to the diverse energy needs of today’s world.

• Clean and Reliable Energy Production

The cornerstone of Bloom Energy’s mission is to provide clean, reliable, and affordable energy. Their Energy Servers deliver on this promise by producing electricity on-site, reducing the need for transmission over long distances and thereby decreasing energy loss. This method not only ensures a stable energy supply but also contributes to a significant reduction in the carbon footprint associated with energy production, making it a game-changer for businesses and communities seeking sustainable energy alternatives.

• Reducing Dependence on Fossil Fuels

Bloom Energy is committed to reducing global dependence on fossil fuels by offering a cleaner alternative that still meets the high-energy demands of modern society. Their technology supports the transition to a more sustainable energy landscape by enabling the use of hydrogen, a clean and abundant fuel source. This not only diminishes the reliance on fossil fuels but also paves the way for a future where energy production contributes to healing the planet rather than harming it.

• Energy Security and Resilience

In today’s world, where energy needs are constantly evolving and the threat of climate change looms large, Bloom Energy provides solutions that enhance energy security and resilience. Their Energy Servers are designed to operate independently of the grid, ensuring that businesses and critical services can maintain operations uninterrupted, even in the face of power outages or natural disasters. This level of reliability is crucial for building resilient communities prepared to face the challenges of the 21st century.

• Lower Carbon Footprint Solutions

Bloom Energy is dedicated to lowering the carbon footprint of energy production through its cutting-edge technology. By converting fuel into electricity more efficiently and with fewer emissions than traditional power plants, Bloom Energy’s solutions represent a significant step forward in the fight against climate change. Their commitment to innovation and sustainability exemplifies how technology can be harnessed to create a cleaner, greener future for all.

15. Neste: Pioneering Sustainable Solutions

• Renewable Diesel and Sustainable Aviation Fuel

Neste stands at the forefront of sustainable technology companies by transforming the fuel industry. Their development of renewable diesel and sustainable aviation fuel marks a significant leap toward reducing the carbon footprint associated with transportation. Unlike traditional fossil fuels, Neste’s products are made from 100% renewable raw materials, such as waste and residues, significantly cutting down greenhouse gas emissions. This innovation not only provides a cleaner alternative for vehicles on the road but also for aircrafts in the sky, making air travel more sustainable.

• Circular Economy for Waste and Residues

A cornerstone of Neste’s sustainability strategy is its commitment to the circular economy. By utilizing waste and residues as primary raw materials, Neste turns what would be trash into valuable resources. This approach not only reduces waste but also minimizes the need for virgin raw materials, lessening the environmental impact. Their circular economy practices showcase how sustainability can be integrated into the production process, leading to more efficient use of resources and a smaller environmental footprint.

• Reducing Carbon Footprint in Transport

Neste’s renewable products play a crucial role in reducing the carbon footprint of the transport sector. By offering renewable diesel and sustainable aviation fuel, they provide viable, less polluting alternatives for trucks, ships, and planes. These fuels are designed to be dropped into existing engines, requiring no modifications, making it easier for companies to transition to greener options. Neste’s commitment to reducing emissions in transport is a testament to their role as leaders in sustainable technology, paving the way for a cleaner, more sustainable future in transportation.

• Innovations in Bio-based Products

Beyond fuels, Neste is innovating in the field of bio-based products. Their research and development efforts focus on finding renewable alternatives to commonly used petroleum-based products. From plastics to chemicals, Neste’s bio-based solutions are designed to reduce reliance on fossil resources and decrease carbon emissions. Their work in this area not only contributes to sustainability but also opens up new possibilities for industries to become more eco-friendly.

• Global Leader in Renewable Solutions

Neste has established itself as a global leader in renewable solutions, setting a benchmark for sustainability in the technology and energy sectors. Their comprehensive approach to sustainability, from fuel production to advocating for a circular economy, exemplifies their commitment to making a positive impact on the planet. As they continue to expand their reach and innovate, Neste’s work underscores the potential of sustainable technology companies to drive significant environmental change.

16. Conclusion

As we have explored the groundbreaking work of these 15 sustainable technology companies, it’s clear that their contributions are not just shaping the future of their respective industries but are also crucial in the global fight against climate change. Their innovative approaches to sustainability, ranging from renewable energy to eco-friendly products, underscore the potential of technology to create a positive impact on the environment. These companies stand as beacons of hope, demonstrating that with ingenuity and commitment, the tech industry can lead the way in building a greener, more sustainable future for all.

Get in touch with us at EMB to know more.

• What makes a technology company sustainable?

A technology company is considered sustainable if it integrates environmental considerations in its operations, products, and services, aiming to reduce carbon footprints and promote eco-friendly practices.

• How do sustainable technology companies impact the environment?

Sustainable technology companies significantly reduce environmental impact by innovating in renewable energy, waste reduction, and resource efficiency, leading to less pollution and conservation of natural resources.

• Can sustainable technology companies be profitable?

Yes, sustainable technology companies can be profitable by tapping into the growing demand for eco-friendly products and services, benefiting from incentives, and improving operational efficiencies.

• What are the challenges facing sustainable technology companies?

Challenges include high initial costs, regulatory hurdles, and the need for continuous innovation to stay ahead in a competitive market while adhering to sustainability principles.

• How can consumers support sustainable technology companies?

Consumers can support sustainable technology companies by purchasing their products and services, advocating for eco-friendly practices, and spreading awareness about the importance of sustainability in technology.

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3 Business Sustainability Case Studies And Why They Worked

Here’s how big industry players like Lyft, Patagonia and Danone took up sustainable initiatives to elevate their businesses while helping the planet.

Founded in 2012, Lyft is now an $11 billion ride-hailing company, second in the industry to Uber alone. Lyft along with Uber has been criticized for contributing to emissions and increasing congestion , however, the company is taking steps to work towards better solutions. In 2017, the ride-sharing service shared its 2025 climate impact goals which also includes a switch to autonomous electric vehicles powered by renewable energy and reducing overall CO2 emissions in the transportation sector.

Riding Carbon Neutral

“Paul Hawken’s Ecology of Commerce demonstrates how industry and the environment do not have to be at odds, and if we work to find the right solutions, the two can (and must) work together.” This excerpt from the Lyft co-founders’ carbon neutral announcement communicates the drive behind the company’s sustainable initiative.

To take their concern for the environment and communities one step further, Lyft also took on a multi-million dollar investment to make all their rides carbon neutral. Their carbon-neutral pledge directly funds emission mitigation efforts, including the reduction of emissions in the automotive manufacturing process, renewable energy programs, forestry projects, and the capture of emissions from landfills. By 2019, Lyft spent well over $2 million on carbon credits . This is equivalent to 2,062,500 metric tons of carbon – the amount Lyft estimates it emits across its entire operations.

Takeaway – Brand Image Harmony Earns Customers

The effort to go carbon neutral falls in line with Lyft’s larger marketing strategy. The ride-sharing app has consistently focused on friendly, easy-going community-based messaging. This marketing angle has largely contributed to its success. In 2017, Lyft was in control of a third of the US ride-sharing market while Uber was losing part of its own.

This initiative creates a strong association in the minds of the consumer – Lyft cares about offering its riders the best possible option. In turn, this large scale perception snowballs into greater customer retention and acquisition rates.

2. Patagonia

The founder of Patagonia, Yvon Chouinard, built the outdoor clothing brand with the clear vision to protect nature. Since the company’s advent, this steadfast mission has translated into cuts of their profits being donated to worthy environmental causes, switches to organic cotton, LEED Certified buildings, FSC Certification, 1% for the Planet Organization, and Common Threads Garment Recycling Program to name a few.

Buy Less, Use More

Patagonia’s Common Threads Recycling Program took back 45 tons of clothes for recycling from their customers and made 34 tons into new clothes. To build on this bold initiative to make all their clothes recyclable in 5 years, Patagonia launched their The Common Threads Initiative (2011) that encouraged consumers to repair and reuse their clothing rather than disposing of it, returning them for recycling or replacing them once worn out. The bold initiative sprouted from the insight that recycling is not the solution – reducing it. Marketing efforts for the initiative were geared towards encouraging higher quality products with longer shelf lives over those that might wear out quicker. For those that do wear out, Patagonia offered a free customer repair service that keeps their products in the loop for longer.

The brand put out “Don’t Buy This Jacket” ads that actively discouraged their audience from purchasing their products. The risky but refreshing angle earned them a massive PR splash. The marketing community expected the initiative to cause a steep decline in Patagonia’s sales.

Takeaway: Genuinity Earns Goodwill

Contrary to these predictions, the campaign was at the core of the greatest success the brand had seen in 2 years . The initiative repaired more than 30,000 items in 18 months . Sales increased by 30% to $540 million in the following year.

When questioned on the forces behind this success, Rob BonDurant (Vice President on Global Marketing) said “The discerning consumer targeted by Patagonia will be more likely to buy one of the company’s (relatively pricey) fleeces rather than those of its (mostly cheaper) rivals. And that fleece will last for years, so avoiding the need to buy replacements every other season or so. Patagonia even offers a free repair service to discourage you from chucking it in the bin liner as soon as it gets frayed or torn. Hence, while Patagonia itself sells more stuff, the argument goes, the overall volume of stuff sold goes down.”

Danone is a leader in a global food and beverage industry, offering product lines ranging from dairy and plant-based products to water. Danone also happens to be a brand with one of the largest plastic footprints , which has been heavily criticized. However, through meticulous efforts and conscious initiatives, the company has built a strong brand on sustainable food values. Given their wide product range, their sustainability policies are also varied enough to complement their widespread impact. “It is increasingly vital for companies and brands to realize that the path ahead is one of technological investment, sustainable development, and high quality in all aspects of product production, packaging included”, says the CEO Andreas Ostermayr.

Finding Sustainability Strategies That Work For You

According to Danone’s CEO, Emmanuel Faber, “Consumers are craving change. They expect large organisations like Danone to bring our scale of impact to change the world for the better.”  Danone took multiple strides in the sustainable direction in 2018. They introduced new plant-based products, made drastic changes to their packaging and announced their 2030 sustainable goals to green their products even further.

As of 2018, 87% of Danone’s total packaging (and 77% of its plastic packaging) was reusable, recyclable, or compostable. At Least 50% of its water volumes are sold in reusable jugs. The F&B giant is taking greater strides toward the circular packaging model with the following goals

Launch 100% recycled PET bottles in all our major water markets (by 2021)

Reach 25% of recycled material on average in plastic packaging by 2025, 50% on average for water and beverage bottles, and 100% for Evian bottle (by 2025)

Offer consumers bottles made from 100% bioplastic.

Beyond the packaging phase of implementing a circular economy, Danone has also emphasized the importance of investing in the infrastructure of waste management systems. Danone and the Danone Ecosystem Fund have launched projects to support waste pickers in 7 countries. Through this project, they have ensured safe working conditions, appropriate wages, and social protection. By 2018, close to 6,000 waste pickers were professionally empowered, and more than 45,000 tons of waste were recycled yearly. To further express their support for the circular economy model, they invested $5 million dollars in the Closed Loop Fund to finance the recycling and circular economy infrastructure across North America.

Danone’s annual progress report proves that their efforts to make sustainable improvements did not go unnoticed.

Takeaway: Environmental Impact Reporting is Key

The transparency with which Danone regears their supply chain and takes on new environmental commitments shows their dedication to delivering the best customer experience possible. Their effort to make their products and processes sustainable is driven home through their consistent communications. The in-depth reports and PR announcements on initiatives taken to help their consumers lead more sustainable lives help build the association of customer consideration. By keeping their consumers in the loop, the brand has established a deeper connection with them. The consumer has every reason to believe that the company really does want what is best for their own health.

The more Danone experiments with environmentally beneficial innovations and communicates the same with their consumers, the more appealing the brand grows. They have made commitments related to carbon emission reduction, sustainable product packaging, food security, sustainable agriculture, and more. The increasing number of commitments to newer environmental innovations serves as a testament to their higher vision of providing consumers with the best possible product and consumer experience.

It’s not just these huge companies that can incorporate sustainability into their practices. If you’re a small company but are passionate about the world’s sustainability progress check out our blog on Ways Small Businesses Can Win Big With Sustainability CSR here .

We have developed a solution to turn your business’s waste practices sustainable through our Plastic Neutral platform . For every kg of plastic you use in operations and packaging, we recover and recycle an equivalent amount with our verified impact partners. We also help you market your Plastic Neutral Certification so that you realize all the benefits of investing in sustainability as soon as you join us. Sign up for a 30-minute free consultation at www.business.repurpose.global/contactus and start your company’s journey towards Plastic Neutrality today.

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Sustainable technology: examples, benefits and challenges.

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BedZED increases Thermal efficiency through provision of gardens on rooftops.

What Is Sustainability?

What is sustainable technology, sustainable technology examples, sustainable technology benefits, sustainable technology challenges, what is the future of sustainable technology.

Every company and every industry needs a green plan. These efforts are about lowering emissions, shrinking carbon footprints and reducing the environmental impact of operations.

But how can this actually be done? Sustainable technology is one of the key tools in these efforts.

Let’s take a closer look at exactly what sustainable technology is, how it is currently being used, and the challenges around its implementation.

The concept of sustainability is intuitive when you consider the original meaning of the word, but is is perhaps too often boiled down to lowering carbon footprint.

Sustainability concerns practices that are sustainable, viable in the long term because they do not cause undue environmental damage. The inference here is, of course, that much of the way society operates at present is not sustainable.

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Sustainable technology is that which can aid in improving the environmental impact of societies, companies and households. It can involve reducing the carbon footprint of the tasks in which it is involved, or be made using greener techniques.

Or, ideally, it can do both.

Sustainable technology is found at all levels of green projects and policy. On a small level, there are “greener” phone companies like Fairphone. At the other end of the scale, green technologies are used across agriculture and city planning to have a much wider impact.

Fairphone 5

Look close at just about any industry and you’ll find sustainable technology. It’s used in homes, in manufacturing, in consumer tech, agriculture, fashion and healthcare.

One example of sustainable technology has already been mentioned, Fairphone ’s smartphones. They use removable batteries to avoid e-waste. They are made with 70% recycled or “fair” materials, including “recycled aluminium, tin, rare earth elements, nickel, zinc, copper, magnesium, indium, and plastics.” Fairphone promises unusually long software support, to ensure its phones can be used safely and securely for many years.

In August the company claimed the Fairphone 5 was “most sustainable phone in the world right now.” The Fairphone 5 still has an environmental impact, but seeking to minimize it is admirable.

In agriculture , sustainable technology is used to monitor the water level and health of crops, in order to increase yield and optimize water usage. Drones can also be used to monitor crop health with cameras and machine learning-based vision AI. Drones can even apply fertilizer. These can have a much lower carbon impact than tractors, and do not cause damage to the underlying soil like a seven ton piece of heavy machinery will.

In architecture and house-building , future-looking sustainable technologies include systems that harvest rainwater for use as, for example, toilet flushing liquid. Electrochromic glass, which darkens to respond to outside conditions, can drastically reduce the energy consumption of HVAC systems.

Then, of course, there are more familiar sustainability technologies like solar panels, used in 3.7% of US homes in 2020 according to Consumer Affairs. Recycled materials can also be used for building insulation, as a rather more simple example of textiles technology in action.

A worker fixes solar panels at a floating photovoltaic plant on the Silbersee lake in Haltern, ... [+] Germany.

In healthcare , electronic health records (EHRs) are used to obviate the need for paper documentation, while also making the information far easier to transmit between healthcare providers. Telemedicine, remote appointments held over the phone or a webcam, naturally result in lower carbon emissions — even if an over-reliance on them is itself contentious.

Fashion , too, an area with a checkered past and present in this area, makes good use of sustainable tech. There are virtual try-on services, which can dramatically reduce returns and waste. These virtual representations of clothing can also be used in the retail buying process, avoiding the need to so many physical samples to be ferried about.

There are now also many more eco-friendly alternatives to polyester in the manufacture of clothing. Polyester will eventually end up sitting in a landfill for decades as it is not biodegradable. Bamboo, hemp, TENCEL and soy cashmere have all reached a level of development where they are perfectly suitable for use in clothing.

In city infrastructure , sustainable technology is used in street lighting, along with a switch to LED lighting — also referred to as solid state lighting (SSL) — which consumes far less energy, smart sensors can alter the level based on the ambient light or even how busy the area is.

Beijing at night.

City-level sustainable tech also has some responsibility in fostering the transition from the combustion engine to electrified transport. That means infrastructure for charging of EVs, as well as increased use of electrified public transport vehicles, such as buses.

The surface benefit of sustainable technology is in reducing harmful environmental impacts. But this can also lead to better efficiency, lower costs and reduced use of water in some cases.

Sustainable technology can also make environments more pleasant places to be. That can have a particular impact in cities that double as tourists destinations, in work places, and even ordinary homes.

In some countries there are also tax benefits to adopting sustainable tech. It is often the smart fiscal move in the medium to long term.

Sustainable technology often involves increased use of Internet of Things (IoT) sensors and devices, which are ideal for optimizing efficiency in many areas. But these come with security challenges of their own.

Once a system becomes connected over the web, it is on some level at risk of being compromised or hacked.

This tech also has its own energy footprint, meaning a practical and dispassionate approach is required to ensure the overall benefits are as compelling as they may initially appear. Similarly, sustainable technology can have an e-waste issue, particularly if it relies on IoT sensors with a limited functional life.

A 2022 study published in Nature also examined inequality issues that could potentially be exacerbated through the deployment of sustainable tech.

Sustainable aviation fuel (SAF) is one of the more exciting avenues for further research and development. In November 2023, Virgin Atlantic flew a plane from London to New York powered by SAF.

It is produced using cooking oils and recycled carbon, and other waste products. The International Air Transport Association ( IATA ) suggests it can reduce aviation’s fuel carbon footprint by as much as 80%. However, as Aviation Week noted in 2022, SAF is relatively expensive to produce and demand could easily outstrip supply.

As with any kind of sustainable technology, the realities of employing it in a real-world situation need to be considered.

The use of AI in healthcare is likely to bring dramatic results sooner than SAF, employing its skills in pattern recognition to search for anomalies in scans. It’s a tangential candidate as sustainability tech, for its potential to significantly improve efficiency in diagnostics.

Bottom Line

While some see humans’ departure from their natural ways of living as a key issue behind our impact on the environment, at this stage we have to rely on technology to ameliorate the problem.

Sustainable tech can help temper the more profligate aspects of the workings of society, and is a critical tool in green efforts at all scales.

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The Power of Sustainable Innovation: Real-World Case Studies

Sustainable innovation transforms industries. Companies like Tesla, Unilever, Patagonia, Interface, and Danone prove that profitability and purpose harmonise through eco-friendly strategies, securing a brighter, responsible future.

In an age defined by environmental concerns and heightened social responsibility, the integration of sustainability into business strategies has become paramount. Companies worldwide are embracing the notion that sustainable innovation is not only an ethical obligation but also a source of innovation, competitive advantage, and profitability.

This article will explore real-world case studies of companies that have successfully embedded sustainability into their core business strategies, highlighting their innovative approaches, the challenges they encountered, and the tangible benefits they have reaped in terms of profitability and purpose.

Tesla: Revolutionising the Automotive Industry

When you think of sustainable innovation in the automotive industry, Tesla inevitably comes to mind. Founded in 2003 by Elon Musk, Tesla's vision was to accelerate the world's transition to sustainable energy. The company's groundbreaking electric vehicles (EVs) have disrupted the traditional automotive industry, demonstrating that sustainability can go hand in hand with innovation.

Tesla's innovative approach began with the production of high-performance electric sports cars. These vehicles not only reduced greenhouse gas emissions but also shattered preconceived notions about the capabilities of electric vehicles. The company then expanded its product line to include more affordable models, like the Model 3, making sustainable transportation accessible to a broader audience.

Tesla's challenges included battery technology development, charging infrastructure, and navigating regulatory obstacles. However, their unwavering commitment to sustainability led to groundbreaking solutions. Tesla's Gigafactories manufacture batteries at an unprecedented scale, reducing costs and increasing the range of their vehicles. Their Supercharger network addressed range anxiety, offering fast charging capabilities to EV owners.

The result? Tesla has not only driven the adoption of electric vehicles but has also become one of the most valuable companies in the world, proving that sustainability can be a catalyst for business growth and success.

Unilever: The Sustainable Living Plan

Unilever, a multinational consumer goods company, set a shining example in the realm of sustainability with its Sustainable Living Plan. Unilever recognised early on that its products' environmental and social impacts needed addressing. Their innovative approach was to fully integrate sustainability into their business model, all while striving to double the size of the business.

Unilever's challenges were vast. They had to reassess their entire supply chain, ensuring it met sustainability standards. This involved finding sustainable sources for raw materials, reducing waste, and minimising their carbon footprint. They also set ambitious goals, like helping more than a billion people improve their health and well-being and reducing their environmental impact by half.

To meet these goals, Unilever focused on product innovation. They developed products that were not only environmentally friendly but also addressed social issues. For example, their Lifebuoy soap initiative aimed to improve hygiene in developing countries. They also acquired companies like Ben & Jerry's and Seventh Generation, known for their commitment to sustainability.

Unilever's Sustainable Living Plan not only improved their environmental and social footprint but also bolstered their brand image and bottom line. The company reported that their sustainable brands grew 69% faster than the rest of the business in 2018. This case study exemplifies how integrating sustainability into core business strategies can drive revenue and enhance brand value.

Patagonia: Leading the Way in Ethical Apparel

Patagonia, an outdoor apparel company, has long been a trailblaser in sustainability and ethical business practices. Their commitment to sustainability goes beyond mere lip service – it is ingrained in the company's DNA. Patagonia's innovative approach to sustainability is anchored in the belief that less harm means more good for the world.

One of their most remarkable initiatives is the "Worn Wear" program. This program encourages customers to buy used Patagonia items, repair their old clothing, or trade in used items for store credit. This not only extends the life of their products but also minimises waste and promotes responsible consumption.

Patagonia has also taken a stand against "fast fashion" by encouraging customers to buy fewer, high-quality items that last. Their commitment to environmental responsibility led them to donate 100% of Black Friday sales in 2016 to grassroots environmental organisations, contributing over $10 million.

Challenges faced by Patagonia included navigating the complexities of their supply chain and balancing sustainability with profitability. However, their innovative approach and unwavering commitment to environmental and social responsibility have led to remarkable results. Patagonia's revenue has continued to grow, demonstrating that consumers are increasingly valuing ethical and sustainable brands.

Interface: Sustainability in Carpet Manufacturing

Interface, a global manufacturer of modular carpet, is a prime example of how a company can completely revamp its business strategy to align with sustainability. Their founder, Ray Anderson, underwent a transformative journey when he realised the environmental impact of his business. Interface's innovative approach was to adopt a mission to become the world's first environmentally sustainable and socially responsible company.

Interface's journey was marked by challenges. They had to reimagine their entire production process, making it more sustainable. They introduced innovative technologies like closed-loop recycling, where old carpets are collected, recycled, and used to make new ones. This reduced waste and resource consumption while saving money.

The company also pursued a goal to source 100% of its materials from renewable or recycled sources. Their innovative approach to sourcing led to partnerships with suppliers who shared their sustainability goals. Interface also aimed to achieve zero net emissions, pushing them to invest in renewable energy and reduce their carbon footprint.

The results have been remarkable. Interface has reduced its environmental impact, increased customer loyalty, and improved its bottom line. Their dedication to sustainability has not only paid off in terms of profits but has also solidified their position as a leader in sustainable business practices.

Danone: Nurturing a Sustainable Food System

Danone, a multinational food-products corporation, has undertaken a journey to transform the way they do business, focusing on healthier and more sustainable food products. Their innovative approach is guided by their "One Planet. One Health" vision, which aligns business success with the well-being of people and the planet.

Danone's challenges included transforming their product portfolio to offer healthier options, reducing their carbon emissions, and promoting sustainable agriculture. They've invested in research and development to create healthier, more sustainable food products and have implemented sustainable farming practices.

One of their most notable initiatives is the Danone Ecosystem Fund, which supports local farmers and communities in developing countries, helping them adopt sustainable agricultural practices. This not only improves the livelihoods of farmers but also secures a sustainable supply of raw materials for Danone.

The company's commitment to sustainability has resonated with consumers, making them a preferred choice for those who value healthy, sustainable food products. Their revenue growth is indicative of the profitability of aligning business strategies with sustainability and health.

These real-world case studies underscore the power of sustainable innovation in transforming companies and industries. They demonstrate that integrating sustainability into core business strategies can lead to innovative solutions, increased profitability, and a stronger sense of purpose. By embracing sustainable practices, companies can not only mitigate environmental and social challenges but also thrive in an increasingly conscious and responsible world. The time for sustainable innovation is now, and these case studies provide a compelling roadmap for companies looking to make a positive impact on the world while growing their bottom line.

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Tesla’s Electrification Revolution – Unleashing Causality between Digital Transformation and Sustainability

This case study explores Tesla's electrification revolution as a prime example of how digital transformation drives sustainability.

Halil Aksu Content Editor

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This case study explores Tesla’s electrification revolution as a prime example of how digital transformation drives sustainability and vice versa. By harnessing advanced digital technologies and sustainable practices, Tesla has not only revolutionized the automotive industry but also pioneered a new era of sustainable transportation.  

Tesla, led by visionary entrepreneur Elon Musk, started to disrupt the automotive industry by leveraging digital transformation to drive sustainable solutions. The company’s core mission was to accelerate the world’s transition to sustainable energy through the production of electric vehicles (EVs) and renewable energy solutions. Tesla’s approach involved integrating cutting-edge technology, software-driven innovation, and a commitment to sustainable practices.  

Digital Transformation Driving Sustainability  

Tesla’s digital transformation played a crucial role in advancing sustainability. The company’s EVs are powered by advanced battery technology and sophisticated software systems, enabling longer driving ranges, rapid charging capabilities, and enhanced energy efficiency. Tesla’s digital infrastructure, including over-the-air software updates and vehicle connectivity, allows for continuous optimization and improvement, reducing the environmental impact of its vehicles over their lifecycle.  

Sustainability Driving Digital Transformation  

Tesla’s pursuit of sustainability goals has also propelled its digital transformation efforts. The company’s commitment to reducing greenhouse gas emissions and promoting renewable energy adoption has driven innovation in energy storage and solar power systems. Tesla has expanded its digital ecosystem by developing and integrating sustainable energy solutions, offering customers integrated energy management platforms and home energy storage solutions.  

Tesla’s causality between digital transformation and sustainability has resulted in significant positive outcomes and a global impact.  

Market Leadership  

Tesla’s innovative approach to electric vehicles and sustainable energy solutions has positioned the company as a market leader in the rapidly growing EV industry. Its digital-first mindset and focus on sustainability have attracted a loyal customer base and created a strong brand identity associated with technological advancement and environmental stewardship.  

Emission Reduction and Energy Transition  

Tesla’s electric vehicles have contributed to a substantial reduction in greenhouse gas emissions, mitigating the environmental impact of transportation. Additionally, Tesla’s sustainable energy solutions, including solar power and energy storage systems, have facilitated the transition to clean and renewable energy sources, promoting a sustainable future.  

Leveraging the Causality between Digital Transformation and Sustainability  

In today’s rapidly evolving business landscape, the causality between digital transformation and sustainability has emerged as a strategic imperative for organizations worldwide. Drawing inspiration from the success of Tesla’s electrification revolution, business executives must recognize the interconnectedness of these two driving forces and seize the opportunities they present. This article provides three key recommendations for executives looking to harness the causality between digital transformation and sustainability to drive organizational success.  

Embrace Digitalization for Sustainable Innovation  

In an era of heightened environmental concerns, business executives must recognize that digital transformation acts as a catalyst for sustainable innovation. By embracing advanced digital technologies and incorporating them into existing processes, organizations can unlock new opportunities for sustainability-driven growth. This recommendation explores how digitalization can be harnessed to drive sustainable innovation, improve operational efficiency, and create a competitive advantage in the market.  

Foster a Culture of Collaboration for Transformational Change  

To fully leverage the causality between digital transformation and sustainability, business executives need to foster a culture of collaboration within their organizations. This recommendation emphasizes the importance of breaking down silos and encouraging cross-functional collaboration between digital and sustainability teams. By promoting a collaborative mindset, executives can unlock synergies, facilitate knowledge sharing, and drive transformational change that aligns digital initiatives with sustainability goals.  

Develop a Holistic Strategy for Sustainable Digital Transformation  

To harness the causality between digital transformation and sustainability, business executives must develop a holistic strategy seamlessly integrating both dimensions . This recommendation highlights the importance of aligning digital transformation initiatives with sustainability objectives from the outset. By adopting a comprehensive approach, executives can ensure that digital initiatives not only drive operational efficiencies but also contribute to environmental sustainability, social responsibility, and long-term organizational resilience.  

By following these recommendations, business executives can capitalize on the causality between digital transformation and sustainability to drive innovation, enhance operational performance, and foster a sustainable competitive advantage in the dynamic business landscape of today and tomorrow.  

Igniting Sustainable Transformation in the Digital Age  

Tesla’s electrification revolution stands as a testament to the transformative power of integrating digital transformation and sustainability. By leveraging advanced technologies and a commitment to sustainable practices, Tesla has not only disrupted the automotive industry but also ignited a movement towards a more sustainable future. The causality between digital transformation and sustainability has driven remarkable outcomes for Tesla, including market leadership, emission reduction, and global impact.  

Through its digital-first mindset, Tesla has revolutionized electric vehicles, leveraging software-driven innovation to enhance energy efficiency and redefine the driving experience. Simultaneously, the company’s dedication to sustainability has fueled its digital transformation, propelling breakthroughs in renewable energy and energy storage solutions. Tesla’s success demonstrates that digitalization and sustainability are not mutually exclusive but rather synergistic forces that drive positive change.  

As organizations seek to thrive in an era of environmental consciousness and technological disruption, they must heed the lessons from Tesla’s journey. By embracing the causality between digital transformation and sustainability, businesses can unlock new possibilities, drive innovation, and contribute to a more sustainable and prosperous future. Tesla’s electrification revolution serves as an inspiration for executives to reimagine their strategies, accelerate sustainable initiatives, and embrace the transformative potential of the digital sustainability nexus.  

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Sustainable society: wellbeing and technology—3 case studies in decision making.

1. Introduction

2. the design process, 2.1. technology and engineering design.

• The machinery and automation of the system being designed;
• The provision of intelligent operating systems for the users with mechatronics components or systems, such as embedded sensors, smart materials, actuators, dampers, inspecting robots and military hardware.

2.2. The Environment, Economics and a Circular Economy

2.3. environmental problems, attitudes and society actions, 3. sustainability, society, citizenship and the common good, 4. methodology, 5. applications of solutions, 5.1. case study 1—major waterfront refurbishment strategic framework, 5.2. case study 2: health care and innovation.

• Increasingly ‘joined up thinking’ on the integration of social and health care, removing any artificial, barriers that may exist between the two [ 132 , 133 ];
• Privacy must of necessity be a key element operating at the level of the individual and of the system [ 134 , 135 ];
• The requirement for a user led approach based on system integration rather than a technology led approach focused on technological development. The intent must be to parallel the development of the technology and its application largely through a process of sequential, and parallel, progression as suggested by Figure 8 ;
• Technology must be considered as being on a par with, and in some cases an alternative to, medication;
• The ultimate goal is a shift away from a responsive mode of dealing with need to a predictive and proactive interventionist mode aimed at prevention rather than cure.
• The requirement for a universal home ‘clinical hub’ with which all social care and medical technologies can be integrated as the core of a home based system. This could eventually be built-in to any home in the same manner as, say, lighting and heating systems;
• Privacy is key to reassuring the individual that their personal status is hidden from all apart from those to whom they have granted some level of access. Thus, a model where only such agreed data is transmitted on a schedule, which itself will be determined by the user in consultation with the appropriate social and health care providers in the same manner in which a doctor advises a patient on the pros and cons of particular treatments prior to prescribing, is advocated. Access to real-time data in emergency situations would also be provided for authorized individuals and primary care providers;
• Social care technologies are as important as healthcare technologies in an integrated needs based system, and need to be configured to deal with issues ranging from social isolation to access to information. Here, it needs to be recognized that not all individuals may have the necessary technical, cognitive or motor skills to have unlimited access to current technologies;
• Clinical sensors, which can be remote, worn or implanted, will form the basis of the eHealth system [ 142 , 143 , 144 , 145 , 146 ]. However, the research emphasis should not necessarily be on the technologies per se, though these will continue to be developed and enhanced, but on the protocols for their use and the associated standards. The current situation is perhaps somewhat analogous with that associated with home systems development in the late 1980s, where the absence of agreed protocols meant that manufacturers introduced their own system structures and configurations, often with a primary aim of preventing competitor’s technology being integrated with it;
• Development of the relevant ‘participatory systems’ modes, structured around and configurable by the user, as the basis for system integration;
• Methods and techniques for in-service data validation;
• Relevant Big Data analytics, along with technologies such as AI, machine learning for data analytics, cloud computing for data services and IoT for healthcare, needs to be further developed, while incorporating precautions against factors such as algorithmic discrimination, to promote knowledge sharing and a shift to a pro-active and preventative approach to well-being.

5.2.1. State of the Art

5.2.2. goal.

• Loss of purpose by an individual;
• Isolation and exclusion resulting from factors such as a lack of mobility or limited access to communications in preventing the close engagement with others in social activities;
• Loneliness associated with an individual’s ability to access others;
• Anxiety resulting from an individual’s lack of understanding of their position, and of the steps being taken to mitigate this;
• Deterioration of physical and/or mental health restricting the ability of an individual to be independent
• To take things forward it is suggested that what is needed is:
• A shift away from technology-led to user-led design methods and strategies that focus on overall need;
• The embedding of the concepts and constructs of privacy by design [ 155 , 156 , 157 ] throughout health and social care;
• The prevention of algorithmic discrimination in health and social care through appropriate embedded safeguards and constructs operating to defined and agreed standards;
• New economic models for wellness that focus on prevention and achieving an enhanced utilization of resources;
• Technology standards to support interchangeability and interoperability;
• The creation of long term, integrated, open-source data bases to support research and development;
• Strategic policy coordination for social care and health.

5.3. Case Study 3: Cupar Angus

Click here to enlarge figure

5.3.1. Exemplar—Cupar Angus

5.3.2. it is not just about the technology, 6. looking to the future, 6.1. building in a virtual world.

• More resources required for passenger transport;
• Interconnected and intelligent systems run the majority of systems;
• Software developers gain power;
• Businesses emerge configured around data and services.

6.2. Factories Run the World

• Construction boom for industrial and commercial buildings as well as for infrastructure;
• The value chain adopts prefabrication, lean processes and mass customization;
• Suppliers benefit the most;
• Business opportunities in integrated system and logistics.

6.3. A Green Reboot

• Sustainability becomes the primary decision-making criterion;
• Innovative technologies, new materials and sensor-based systems ensure low environmental impact;
• Organizations with a deep knowledge of materials and brownfield portfolios thrive
• Business opportunities develop around environmental-focused services and material recycling.

7. Conclusions

Author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

• United Nations. Report of the World Commission on Environment and Development (The Brundtland Report). 1987. Available online: Sustainabledevelopment.un.org/content/documents/5987our-common-future.pdf (accessed on 24 August 2020).
• Nilsson, M.; Griggs, D.; Visbeck, M. Policy: Map the interactions between Sustainable Development Goals. Nature 2016 , 534 , 320–322. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Bebbington, J.; Unerman, J. Achieving the United Nations sustainable development goals. Account. Audit. Account. J. 2018 , 31 , 2–24. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Sachs, J.D.; Schmidt-Traub, G.; Mazzucato, M.; Messner, D.; Nakicenovic, N.; Rockström, J. Six transformations to achieve the sustainable development goals. Nat. Sustain. 2019 , 2 , 805–814. [ Google Scholar ] [ CrossRef ]
• Sekerka, L.E.; Stimel, D. Environmental sustainability decision-making: Clearing a path to change. J. Public Aff. 2012 , 12 , 195–205. [ Google Scholar ] [ CrossRef ]
• Brørs, G.; Norman, C.D.; Norekvål, T.M. Accelerated importance of eHealth literacy in the COVID-19 outbreak and beyond. Eur. J. Cardiovasc. Nurs. 2020 , 19 , 458–461. [ Google Scholar ] [ CrossRef ]
• Eccleston, C.; Blyth, F.M.; Dear, B.F.; Fisher, E.A.; Keefe, F.J.; Lynch, M.E.; Palermo, T.M.; Reid, M.C.; de C Williams, A.C. Managing patients with chronic pain during the COVID-19 outbreak: Considerations for the rapid introduction of remotely supported (eHealth) pain management services. Pain 2020 , 161 , 889–893. [ Google Scholar ] [ CrossRef ]
• Sust, P.P.; Solans, O.; Fajardo, J.C.; Peralta, M.M.; Rodenas, P.; Gabaldà, J.; Eroles, L.G.; Comella, A.; Muñoz, C.V.; Ribes, J.S.; et al. Turning the crisis into an opportunity: Digital health strategies deployed during the COVID-19 outbreak. JMIR Public Health Surveill. 2020 , 6 , e19106. [ Google Scholar ] [ CrossRef ]
• Wind, T.R.; Rijkeboer, M.; Andersson, G.; Riper, H. The COVID-19 pandemic: The ‘black swan’ for mental health care and a turning point for e-health. Internet Interv. 2020 , 20 . [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Redsell, S.A.; Rose, J.; Weng, S.; Ablewhite, J.; Swift, J.A.; Siriwardena, A.N.; Nathan, D.; Wharrad, H.J.; Atkinson, P.; Watson, V.; et al. Digital technology to facilitate Proactive Assessment of Obesity Risk during Infancy (ProAsk): A feasibility study. BMJ Open 2017 , 7 , e017694. [ Google Scholar ] [ CrossRef ]
• Camagni, R.; Capello, R.; Nijkamp, P. Towards sustainable city policy: An economy-environment technology nexus. Ecol. Econ. 1998 , 24 , 103–118. [ Google Scholar ] [ CrossRef ]
• Singer, P.W. Wired for War: The Robotics Revolution and Conflict in the 21st Century ; Penguin: London, UK, 2011. [ Google Scholar ]
• Pasquale, F. New Laws of Robotics: Defending Human Expertise in the Age of AI ; Belknap Press: Cambridge, MA, USA, 2020. [ Google Scholar ]
• Berg, D. McLuhan and Fuller: The romantic versus the puritan. Can. J. Commun. 1982 , 9 , 1–30. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Lewis, R. Evolution Man, or, How I Ate My Father ; Vintage Books: New York, NY, USA, 1995. [ Google Scholar ]
• Nonaka, I. (Ed.) Knowledge Management: Critical Perspectives on Business and Management ; Taylor & Francis: Oxford, UK, 2005; Volume 2. [ Google Scholar ]
• Matthew, C.T.; Sternberg, R.J. Developing experience-based (tacit) knowledge through reflection. Learn. Individ. Differ. 2009 , 19 , 530–540. [ Google Scholar ] [ CrossRef ]
• Nonaka, I.; Von Krogh, G.; Voelpel, S. Organizational knowledge creation theory: Evolutionary paths and future advances. Organ. Stud. 2006 , 27 , 1179–1208. [ Google Scholar ] [ CrossRef ]
• Marwick, A.D. Knowledge management technology. IBM Syst. J. 2001 , 40 , 814–830. [ Google Scholar ] [ CrossRef ]
• Law, K.K.; Chan, A.; Ozer, M. Towards an integrated framework of intrinsic motivators, extrinsic motivators and knowledge sharing. J. Knowl. Manag. 2017 , 21 , 1486–1502. [ Google Scholar ] [ CrossRef ]
• Hudson, P. The Industrial Revolution ; Bloomsbury: London, UK, 2014. [ Google Scholar ]
• Mokyr, J. The second industrial revolution, 1870–1914. Stor. Dell’economia Mond. 1998 , 21945 , 2–14. [ Google Scholar ]
• Russell, D.W.; Bradley, D. Mechatronic Futures. In Mechatronics in Action ; Springer: Cham, Switzerland, 2010; pp. 241–250. [ Google Scholar ]
• Dixit, U.S.; Hazarika, M.; Davim, J.P. A Brief History of Mechanical Engineering ; Springer: Cham, Switzerland, 2017. [ Google Scholar ]
• Schwab, K. The Fourth Industrial Revolution ; Crown Publishing Group (Penguin Random House): New York, NY, USA, 2017; Volume 184, pp. 12–15. [ Google Scholar ]
• Philbeck, T.; Davis, N. The Fourth Industrial Revolution. J. Int. Aff. 2018 , 72 , 17–22. [ Google Scholar ] [ CrossRef ]
• Xu, H.; Yu, W.; Griffith, D.; Golmie, N. A survey on industrial Internet of Things: A cyber-physical systems perspective. IEEE Access 2018 , 6 , 78238–78259. [ Google Scholar ] [ CrossRef ]
• Radanliev, P.; de Roure, D.; Nurse, J.R.; Nicolescu, R.; Huth, M.; Cannady, S.; Montalvo, R.M. New developments in Cyber Physical Systems. AI Soc. 2021 , 36 , 783–796. [ Google Scholar ] [ CrossRef ]
• Ratasich, D.; Khalid, F.; Geissler, F.; Grosu, R.; Shafique, M.; Bartocci, E. A roadmap toward the resilient internet of things for cyber-physical systems. IEEE Access 2019 , 7 , 13260–13283. [ Google Scholar ] [ CrossRef ]
• Yang, Y.; Wu, L.; Yin, G.; Li, L.; Zhao, H. A survey on security and privacy issues in Internet-of-Things. IEEE Internet Things J. 2017 , 4 , 1250–1258. [ Google Scholar ] [ CrossRef ]
• Wang, T.; Bhuiyan, M.Z.A.; Wang, G.; Qi, L.; Wu, J.; Hayajneh, T. Preserving balance between privacy and data integrity in edge-assisted Internet of Things. IEEE Internet Things J. 2019 , 7 , 2679–2689. [ Google Scholar ] [ CrossRef ]
• Winter, J. Algorithmic discrimination: Big data analytics and the future of the Internet. In The Future Internet ; Winter, J., Ono, R., Eds.; Springer: Cham, Switzerland, 2015; pp. 125–140. [ Google Scholar ]
• Hajian, S.; Bonchi, F.; Castillo, C. Algorithmic bias: From discrimination discovery to fairness-aware data mining. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, 13–17 August 2016; pp. 2125–2126. [ Google Scholar ] [ CrossRef ]
• O’Neil, C. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy ; Broadway Books (Penguin Random House): New York, NY, USA, 2016. [ Google Scholar ]
• Goodman, B.; Flaxman, S. European Union regulations on algorithmic decision-making and a “right to explanation”. AI Mag. 2017 , 38 , 50–57. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Morrar, R.; Arman, H.; Mousa, S. The fourth industrial revolution (Industry 4.0): A social innovation perspective. Technol. Innov. Manag. Rev. 2017 , 7 , 12–20. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• IŽliobaitė, I. Measuring discrimination in algorithmic decision making. Data Min. Knowl. Discov. 2017 , 31 , 1060–1089. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Kearns, M.; Roth, A. The Ethical Algorithm: The Science of Socially Aware Algorithm Design ; Oxford University Press: Oxford, UK, 2019. [ Google Scholar ]
• Shin, J.; Jian, L.; Driscoll, K.; Bar, F. The diffusion of misinformation on social media: Temporal pattern, message, and source. Comput. Hum. Behav. 2018 , 83 , 278–287. [ Google Scholar ] [ CrossRef ]
• Allcott, H.; Gentzkow, M.; Yu, C. Trends in the diffusion of misinformation on social media. Res. Politics 2019 , 6 , 2053168019848554. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Bergstrom, C.T.; West, J.D. Calling Bullshit: The Art of Skepticism in a Data-Driven World ; Penguin Random House: New York, NY, USA, 2020. [ Google Scholar ]
• Wang, Y.; McKee, M.; Torbica, A.; Stuckler, D. Systematic literature review on the spread of health-related misinformation on social media. Soc. Sci. Med. 2019 , 240 , 112552. [ Google Scholar ] [ CrossRef ]
• Our World in Data. Available online: https://ourworldindata.org/ (accessed on 5 November 2020).
• Allard, G.; Martinez, C.A.; Williams, C. Political instability, pro-business market reforms and their impacts on national systems of innovation. Res. Policy 2012 , 41 , 638–651. [ Google Scholar ] [ CrossRef ]
• Hedman, J.; Gimpel, G. The adoption of hyped technologies: A qualitative study. Inf. Technol. Manag. 2010 , 11 , 161–175. [ Google Scholar ] [ CrossRef ]
• Rogers, E.M. Diffusion of Innovations , 5th ed.; The Free Press of Glencoe: New York, NY, USA, 2003. [ Google Scholar ]
• Linden, A.; Fenn, J. Understanding Gartner’s Hype Cycles. 2018. Available online: https://www.gartner.com/en/documents/3887767 (accessed on 2 June 2022).
• Kleppmann, M. Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems ; O’Reilly Media Inc.: Newton, MA, USA, 2017. [ Google Scholar ]
• Véliz, C. Privacy is Power: Why and How You Should Take Back Control of Your Data ; Melville House: Brooklyn, NY, USA, 2021. [ Google Scholar ]
• Russell, S. Human Compatible: Artificial Intelligence and the Problem of Control ; Viking Penguin: New York, NY, USA, 2019. [ Google Scholar ]
• Li, Y.; Wang, Y.; Chase, J.G.; Mattila, J.; Myung, H.; Sawodny, O. Survey and introduction to the focused section on mechatronics for sustainable and resilient civil infrastructure. IEEE/ASME Trans. Mechatron. 2013 , 18 , 1637–1646. [ Google Scholar ] [ CrossRef ]
• Bailey, I.; Rupp, S. Politics, industry and the regulation of industrial greenhouse-gas emissions in the UK and Germany. Eur. Environ. 2004 , 14 , 235–250. [ Google Scholar ] [ CrossRef ]
• Van Noorden, R. Europe’s untamed carbon: Funding and politics hobble CCS technology, seen as the best hope for cleaning up coal. Nature 2013 , 493 , 141–143. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Wellcome Trust. Blueprint for Dynamic Oversight: How the UK Can Take a Global Lead in Emerging Science and Technologies. 2019. Available online: https://wellcome.org/sites/default/files/blueprint-for-dynamic-oversight.pdf (accessed on 2 June 2022).
• Zannettou, S.; Sirivianos, M.; Blackburn, J.; Kourtellis, N. The web of false information: Rumors, fake news, hoaxes, clickbait, and various other shenanigans. J. Data Inf. Qual. 2019 , 11 , 1–37. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Turner, R.K.; Pearce, D.; Bateman, I. Environmental Economics: An Elementary Introduction ; Harvester Wheatsheaf: London, UK, 1994. [ Google Scholar ]
• JKirchherr, J.; Reike, D.; Hekkert, M. Conceptualizing the circular economy: An analysis of 114 definitions. Resour. Conserv. Recycl. 2017 , 127 , 221–232. [ Google Scholar ] [ CrossRef ]
• Zweig, K. Smith, Malthus, Ricardo, and Mill: The forerunners of limits to growth. Futures 1979 , 11 , 510–523. [ Google Scholar ] [ CrossRef ]
• Kallis, G. Limits: Why Malthus Was Wrong and Why Environmentalists Should Care ; Stanford University Press: Stanford, CA, USA, 2019. [ Google Scholar ]
• Malthus, T.R.; Winch, D.; James, P. An Essay on the Principle of Population ; Cambridge University Press: Cambridge, UK, 1992. [ Google Scholar ]
• Cummins, R.A.; Eckersley, R.; Pallant, J.; Van Vugt, J.; Misajon, R. Developing a national index of subjective wellbeing: The Australian Unity Wellbeing Index. Soc. Indic. Res. 2003 , 64 , 159–190. [ Google Scholar ] [ CrossRef ]
• Easterlin, R.A. Does economic growth improve the human lot? Some empirical evidence. In Nations and Households in Economic Growth ; David, P.A., Reder, M.W., Eds.; Academic Press: New York, NY, USA, 1974; pp. 89–125. [ Google Scholar ]
• Favi, C.; Marconi, M.; Germani, M.; Mandolini, M. A design for disassembly tool oriented to mechatronic product de-manufacturing and recycling. Adv. Eng. Inform. 2019 , 39 , 62–79. [ Google Scholar ] [ CrossRef ]
• Petzold, N.; Landinez, L.; Baaken, T. Disruptive innovation from a process view: A systematic literature review. Creat. Innov. Manag. 2019 , 28 , 157–174. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Button, K. City management and urban environmental indicators. Ecol. Econ. 2002 , 40 , 217–233. [ Google Scholar ] [ CrossRef ]
• Kitchin, R.; Lauriault, T.P.; McArdle, G. Knowing and governing cities through urban indicators, city benchmarking and real-time dashboards. Reg. Stud. Reg. Sci. 2015 , 2 , 6–28. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Day, R.; Walker, G.; Simcock, N. Conceptualising energy use and energy poverty using a capabilities framework. Energy Policy 2016 , 93 , 55–264. [ Google Scholar ] [ CrossRef ]
• Shah, S.G.S.; Robinson, I. User involvement in healthcare technology development and assessment. Intl. J. Health Care Qual. Assur. 2006 , 19 , 500–515. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
• Cresswell, K.; Sheikh, A. Organizational issues in the implementation and adoption of health information technology innovations: An interpretative review. Intl. J. Med. Inform. 2013 , 82 , e73–e86. [ Google Scholar ] [ CrossRef ]
• Avorn, J.; Kesselheim, A.S. Up Is Down—Pharmaceutical Industry Caution vs. Federal Acceleration of Covid-19 Vaccine Approval. N. Engl. J. Med. 2020 , 383 , 1706–1708. [ Google Scholar ] [ CrossRef ]
• Dyer, O. COVID-19: FDA plans strict vaccine approval criteria, angering Trump. Br. Med. J. 2020 , 370 , m3741. [ Google Scholar ] [ CrossRef ]
• Parmet, W.E.; Paul, J. COVID-19: The First Posttruth Pandemic. Am. J. Public Health 2020 , 110 , 945–946. [ Google Scholar ] [ CrossRef ]
• Negash, S.; Musa, P.; Vogel, D.; Sahay, S. Healthcare information technology for development: Improvements in people’s lives through innovations in the uses of technologies. Inf. Technol. Dev. 2018 , 24 , 189–197. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Kumar, V.; ISezersan, I.; Garza-Reyes, J.A.; Gonzalez, E.D.; Moh’d Anwer, A.S. Circular economy in the manufacturing sector: Benefits, opportunities and barriers. Manag. Decis. 2019 , 57 , 1067–1086. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Chouinard, U.; Pigosso, D.C.; McAloone, T.C.; Baron, L.; Achiche, S. Potential of circular economy implementation in the mechatronics industry: An exploratory research. J. Clean. Prod. 2019 , 239 , 118014. [ Google Scholar ] [ CrossRef ]
• Munaro, M.R.; Tavares, S.F.; Bragança, L. Towards circular and more sustainable buildings: A systematic literature review on the circular economy in the built environment. J. Clean. Prod. 2020 , 260 , 121134. [ Google Scholar ] [ CrossRef ]
• Tiefenbeck, V.; Tasic, V.; Schoeb, S.; Staake, T. Mechatronics to drive environmental sustainability. In Proceedings of the IECON 2013-39th Annual Conference of the IEEE Industrial Electronics Society, Vienna, Austria, 10–13 November 2013. [ Google Scholar ] [ CrossRef ]
• Schultz, P.W.; Gouveia, V.V.; Cameron, L.D.; Tankha, G.; Schmuck, P.; Franěk, M. Values and their relationship to environmental concern and conservation behavior. J. Cross-Cult. Psychol. 2005 , 36 , 457–475. [ Google Scholar ] [ CrossRef ]
• Gifford, R.; Nilsson, A. Personal and social factors that influence pro-environmental concern and behaviour: A review. Intl. J. Psychol. 2014 , 49 , 141–157. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Fransson, N.; Gärling, T. Environmental concern: Conceptual Definitions, Measurement Methods, and Research Findings. J. Environ. Psychol. 1999 , 19 , 369–382. [ Google Scholar ] [ CrossRef ]
• Hirsh, J.B. Personality and environmental concern. J. Environ. Psychol. 2010 , 30 , 245–248. [ Google Scholar ] [ CrossRef ]
• Liere, K.D.V.; Dunlap, R.E. The social bases of environmental concern: A review of hypotheses, explanations and empirical evidence. Public Opin. Q. 1980 , 44 , 181–197. [ Google Scholar ] [ CrossRef ]
• Bamberg, S. How does environmental concern influence specific environmentally related behaviors? A new answer to an old question. J. Environ. Psychol. 2003 , 23 , 21–32. [ Google Scholar ] [ CrossRef ]
• Poortinga, W.; Steg, L.; Vlek, C. Values, environmental concern, and environmental behavior: A study into household energy use. Environ. Behav. 2004 , 36 , 70–93. [ Google Scholar ] [ CrossRef ]
• Tawalbeh, L.A.; Muheidat, F.; Tawalbeh, M.; Quwaider, M. IoT Privacy and security: Challenges and solutions. Appl. Sci. 2020 , 10 , 4102. [ Google Scholar ] [ CrossRef ]
• Lin, H.; Bergmann, N.W. IoT privacy and security challenges for smart home environments. Information 2016 , 7 , 44. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Vorkinn, M.; Riese, H. Environmental concern in a local context: The significance of place attachment. Environ. Behav. 2001 , 33 , 249–263. [ Google Scholar ] [ CrossRef ]
• Devine-Wright, P. Beyond NIMBYism: Towards an integrated framework for understanding public perceptions of wind energy. Wind. Energy Intl. J. Prog. Appl. Wind. Power Convers. Technol. 2005 , 8 , 125–139. [ Google Scholar ] [ CrossRef ]
• Devine-Wright, P. Rethinking NIMBYism: The role of place attachment and place identity in explaining place-protective action. J. Community Appl. Soc. Psychol. 2009 , 19 , 426–441. [ Google Scholar ] [ CrossRef ]
• Berenguer, J.; Corraliza, J.A.; Martin, R. Rural-Urban Differences in Environmental Concern, Attitudes, and Actions. Eur. J. Psychol. Assess. 2005 , 21 , 128–138. [ Google Scholar ] [ CrossRef ]
• Mainieri, T.; Barnett, E.G.; Valdero, T.R.; Unipan, J.B.; Oskamp, S. Green buying: The influence of environmental concern on consumer behavior. J. Soc. Psychol. 1997 , 137 , 189–204. [ Google Scholar ] [ CrossRef ]
• Axelrod, L.J.; Lehman, D.R. Responding to environmental concerns: What factors guide individual action? J. Environ. Psychol. 1993 , 13 , 149–159. [ Google Scholar ] [ CrossRef ]
• Van Doorn, J.; Verhoef, P.C.; Bijmolt, T.H. The importance of non-linear relationships between attitude and behaviour in policy research. J. Consum. Policy 2007 , 30 , 75–90. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Asen, R. A discourse theory of citizenship. Q. J. Speech 2004 , 90 , 189–211. [ Google Scholar ] [ CrossRef ]
• Schultz, P.W. The structure of environmental concern: Concern for self, other people, and the biosphere. J. Environ. Psychol. 2001 , 21 , 327–339. [ Google Scholar ] [ CrossRef ]
• Hansla, A.; Gamble, A.; Juliusson, A.; Gärling, T. The relationships between awareness of consequences, environmental concern, and value orientations. J. Environ. Psychol. 2008 , 28 , 1–9. [ Google Scholar ] [ CrossRef ]
• Hobson, K. On the making of the environmental citizen. Environ. Politics 2013 , 22 , 56–72. [ Google Scholar ] [ CrossRef ]
• Veugelers, W. Creating critical-democratic citizenship education: Empowering humanity and democracy in Dutch education. Comp. A J. Comp. Educ. 2007 , 37 , 105–119. [ Google Scholar ] [ CrossRef ]
• Pocock, M.J.; Tweddle, J.C.; Savage, J.; Robinson, L.D.; Roy, H.E. The diversity and evolution of ecological and environmental citizen science. PLoS ONE 2017 , 12 , e0172579. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
• Westheimer, J.; Kahne, J. What kind of citizen? The politics of educating for democracy. Am. Educ. Res. J. 2004 , 41 , 237–269. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Johnson, L.; Morris, P. Towards a framework for critical citizenship education. Curric. J. 2010 , 21 , 77–96. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Goldman, D.; Hansmann, R.; Činčera, J.; Radović, V.; Telešienė, A.; Balžekienė, A.; Vávra, J. Education for Environmental Citizenship and Responsible Environmental Behaviour. In Conceptualizing Environmental Citizenship for 21st Century Education , 1st ed.; Hadjichambis, A.C.H., Reis, P., Paraskeva-Hadjichambi, D., Činčera, J., Boeve-de Pauw, J., Gericke, N., Knippels, M., Eds.; Springer Open: Cham, Switzerland, 2020; pp. 115–137. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Wackernagel, M.; Rees, W. Our Ecological Footprint: Reducing Human Impact on the Earth ; New Society Publishers: Philadelphia, PA, USA, 1998; Volume 9. [ Google Scholar ]
• Dietz, T.; Rosa, E.A.; York, R. Driving the human ecological footprint. Front. Ecol. Environ. 2007 , 5 , 13–18. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Global Footprint Network. Ecological Footprint Atlas 2010. Available online: https://www.footprintnetwork.org/content/images/uploads/Ecological_Footprint_Atlas_2010.pdf (accessed on 6 June 2022).
• Venetoulis, J.; Talberth, J. Refining the ecological footprint. Environ. Dev. Sustain. 2008 , 10 , 441–469. [ Google Scholar ] [ CrossRef ]
• Fiala, N. Measuring sustainability: Why the ecological footprint is bad economics and bad environmental science. Ecol. Econ. 2008 , 67 , 519–525. [ Google Scholar ] [ CrossRef ]
• Dobson, A. Environmental citizenship: Towards sustainable development. Sustain. Dev. 2007 , 15 , 276–285. [ Google Scholar ] [ CrossRef ]
• Pickett, J.T.; Roche, S.P. Questionable, objectionable or criminal? Public opinion on data fraud and selective reporting in science. Sci. Eng. Ethics 2018 , 24 , 151–171. [ Google Scholar ] [ CrossRef ]
• Simon, H.A. Altruism and economics. Am. Econ. Rev. 1993 , 83 , 156–161. [ Google Scholar ]
• Seargeant, P.; Tagg, C. Social media and the future of open debate: A user-oriented approach to Facebook’s filter bubble conundrum. Discourse Context Media 2019 , 27 , 41–48. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Spohr, D. Fake news and ideological polarization: Filter bubbles and selective exposure on social media. Bus. Inf. Rev. 2017 , 34 , 150–160. [ Google Scholar ] [ CrossRef ]
• Sparks, H. Dissident citizenship: Democratic theory, political courage, and activist women. Hypatia 1997 , 12 , 74–110. [ Google Scholar ] [ CrossRef ]
• Esmaeilpour, M.; Bahmiary, E. Investigating the impact of environmental attitude on the decision to purchase a green product with the mediating role of environmental concern and care for green products. Manag. Mark. 2017 , 12 , 297–315. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Pierce, L.; Snyder, J. Ethical spillovers in firms: Evidence from vehicle emissions testing. Manag. Sci. 2008 , 54 , 1891–1903. [ Google Scholar ] [ CrossRef ]
• Nunes, M.F.; Park, C.L. Caught red-handed: The cost of the Volkswagen Dieselgate. J. Glob. Responsib. 2016 , 7 , 288–302. [ Google Scholar ] [ CrossRef ]
• Li, L.; McMurray, A.; Xue, J.; Liu, Z.; Sy, M. Industry-wide corporate fraud: The truth behind the Volkswagen scandal. J. Clean. Prod. 2018 , 172 , 3167–3175. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Diner, D.; Nakayama, S.; Nov, O.; Porfiri, M. Social signals as design interventions for enhancing citizen science contributions. Inf. Commun. Soc. 2018 , 21 , 594–611. [ Google Scholar ] [ CrossRef ]
• Laut, J.; Wright, S.N.; Nov, O.; Porfiri, M. Gowanus voyage: Where mechatronics, public art, community members, and environmental science meet [focus on education]. IEEE Control Syst. Mag. 2014 , 34 , 60–64. [ Google Scholar ] [ CrossRef ]
• Jezdović, I.; Nedeljković, N.; Bogdanović, Z.; Labus, A.; Radenković, B. Smart Cities. In Proceedings of the 14th International Joint Conference on e-Business and Telecommunications, Madrid, Spain, 26–28 July 2017; Volume 2, pp. 108–115. [ Google Scholar ] [ CrossRef ]
• Nitoslawski, S.A.; Galle, N.J.; Van Den Bosch, C.K.; Steenberg, J.W. Smarter ecosystems for smarter cities? A review of trends, technologies, and turning points for smart urban forestry. Sustain. Cities Soc. 2019 , 51 , 101770. [ Google Scholar ] [ CrossRef ]
• Kerr, J. Watershed management: Lessons from common property theory. Intl. J. Commons 2007 , 1 , 89–109. [ Google Scholar ] [ CrossRef ]
• Saisana, M.; Philippas, D. Sustainable Society Index (SSI): Taking societies’ pulse along social, environmental and economic issues. Environ. Impact Assess. Rev. 2012 , 32 , 94–106. [ Google Scholar ] [ CrossRef ]
• Sison, A.J.G.; Fontrodona, J. The common good of the firm in the Aristotelian-Thomistic tradition. Bus. Ethics Q. 2012 , 22 , 211–246. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Gilmour, D.; Simpson, E. Urban regeneration indicators: A proxy for assessing common good. Emerald Open Res. 2021 , 3 , 10. [ Google Scholar ] [ CrossRef ]
• Dundee City Council, Single Outcome Agreement for Dundee 2013–2017. Available online: www.dundeecity.gov.uk/sites/default/files/publications/SOA%20newsmall.pdf (accessed on 7 June 2022).
• Yocom, K.P.; Andrews, L.; Faghin, N.; Dyson, K.; Leschine, T.; Nam, J. Revitalizing urban waterfronts: Identifying indicators for human well-being. AIMS Environ. Sci. 2016 , 3 , 456–473. [ Google Scholar ]
• Brownsell, S.J.; Williams, G.; Bradley, D.A.; Bragg, R.; Catlin, P.; Carlier, J. Future systems for remote health care. J. Telemed. Telecare 1999 , 5 , 141–152. [ Google Scholar ] [ CrossRef ]
• Hendy, J.; Chrysanthaki, T.; Barlow, J.; Knapp, M.; Rogers, A.; Sanders, C.; Bower, P.; Bowen, R.; Fitzpatrick, R.; Bardsley, M.; et al. An organisational analysis of the implementation of telecare and telehealth: The whole systems demonstrator. BMC Health Serv. Res. 2012 , 12 , 403. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Levy, S.; Bradley, D.A.; Morison, M.J.; Swanston, M.T.; Harvey, S. Future patient care: Tele-empowerment. J. Telemed. Telecare 2002 , 8 (Suppl. 2), 52–54. [ Google Scholar ] [ CrossRef ]
• Hsia, T.L.; Chiang, A.J.; Wu, J.H.; Teng, N.N.; Rubin, A.D. What drives E-Health usage? Integrated institutional forces and top management perspectives. Comput. Hum. Behav. 2019 , 97 , 260–270. [ Google Scholar ] [ CrossRef ]
• Coorey, G.; Peiris, D.; Usherwood, T.; Neubeck, L.; Mulley, J.; Redfern, J. Persuasive design features within a consumer-focused eHealth intervention integrated with the electronic health record: A mixed methods study of effectiveness and acceptability. PLoS ONE 2019 , 14 , e0218447. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
• National Academies of Sciences, Engineering, and Medicine. Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation’s Health ; The National Academies Press: Washington, DC, USA, 2019. [ Google Scholar ] [ CrossRef ]
• Omoogun, M.; Seeam, P.; Ramsurrun, V.; Bellekens, X.; Seeam, A. When eHealth meets the internet of things: Pervasive security and privacy challenges. In Proceedings of the IEEE 2017 International Conference on Cyber Security and Protection of Digital Services (Cyber Security), London, UK, 19–20 June 2017. [ Google Scholar ] [ CrossRef ]
• Sánchez-Guerrero, R.; Mendoza, F.A.; Diaz-Sanchez, D.; Cabarcos, P.A.; López, A.M. Collaborative ehealth meets security: Privacy-enhancing patient profile management. IEEE J. Biomed. Health Inform. 2017 , 21 , 1741–1749. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Wu, L.; Wang, D.; Evans, J.A. Large teams develop and small teams disrupt science and technology. Nature 2019 , 566 , 378–382. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Richie, S. Science Fictions: Exposing Fraud, Bias, Negligence and Hype in Science ; Bodly Head: London, UK, 2020. [ Google Scholar ]
• Meskó, B.; Drobni, Z.; Bényei, É.; Gergely, B.; Győrffy, Z. Digital health is a cultural transformation of traditional healthcare. Mhealth 2017 , 3 , 38. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Moerenhout, T.; Devisch, I.; Cornelis, G.C. E-health beyond technology: Analyzing the paradigm shift that lies beneath. Med. Health Care Philos. 2018 , 21 , 31–41. [ Google Scholar ] [ CrossRef ]
• Halpren-Ruder, D. E-Health and Healthcare Quality Management: Disruptive Opportunities. Rhode Isl. Med. J. 2020 , 103 , 12–15. [ Google Scholar ]
• Levy, S.; Bradley, D.A.; Swanston, M.T. The technology prescription: Linking telecare and informatics by using a need-led paradigm. Health Inform. J. 2002 , 8 , 88–94. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Malwade, S.; Abdul, S.S.; Uddin, M.; Nursetyo, A.A.; Fernandez-Luque, L.; Zhu, X.K.; Cilliers, L.; Wong, C.P.; Bamidis, P.; Li, Y.C.J. Mobile and wearable technologies in healthcare for the ageing population. Comput. Methods Programs Biomed. 2018 , 161 , 233–237. [ Google Scholar ] [ CrossRef ]
• Baig, M.M.; Afifi, S.; Gholam Hosseini, H.; Mirza, F. A systematic review of wearable sensors and IoT-based monitoring applications for older adults–a focus on ageing population and independent living. J. Med. Syst. 2019 , 43 , 233. [ Google Scholar ] [ CrossRef ]
• Li, J.; Ma, Q.; Chan, A.H.; Man, S.S. Health monitoring through wearable technologies for older adults: Smart wearables acceptance model. Appl. Ergon. 2019 , 75 , 162–169. [ Google Scholar ] [ CrossRef ]
• Ling, Y.; An, T.; Yap, L.W.; Zhu, B.; Gong, S.; Cheng, W. Disruptive, soft, wearable sensors. Adv. Mater. 2020 , 32 , 1904664. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Zhang, L.; Ji, H.; Huang, H.; Yi, N.; Shi, X.; Xie, S.; Li, Y.; Ye, Z.; Feng, P.; Lin, T.; et al. Wearable Circuits Sintered at Room Temperature Directly on the Skin Surface for Health Monitoring. ACS Appl. Mater. Interfaces 2020 , 12 , 45504–45515. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Iribarren, S.J.; Cato, K.; Falzon, L.; Stone, P.W. What is the economic evidence for mHealth? A systematic review of economic evaluations of mHealth solutions. PLoS ONE 2017 , 12 , e0170581. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
• Sanyal, C.; Stolee, P.; Juzwishin, D.; Husereau, D. Economic evaluations of eHealth technologies: A systematic review. PLoS ONE 2018 , 13 , e0198112. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Fosch-Villaronga, E. Robots, Healthcare, and the Law: Regulating Automation in Personal Care ; Routledge: London, UK, 2019. [ Google Scholar ]
• Fosch-Villaronga, E.; Felzmann, H.; Ramos-Montero, M.; Mahler, T. Cloud services for robotic nurses? Assessing legal and ethical issues in the use of cloud services for healthcare robots. In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 1–5 October 2018. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Azeta, J.; Bolu, C.; Abioye, A.A.; Oyawale, F.A. A review on humanoid robotics in healthcare. In Proceedings of the 4th International Conference on Mechatronics and Mechanical Engineering (ICMME 2017), MATEC Web Conf, Kuala Lumpur, Malaysia, 28–30 November 2017. [ Google Scholar ] [ CrossRef ]
• Mijares, S.F.; Chan, P. Ethical Robots in Healthcare. J. Acad. Bus. Econ. 2018 , 18 , 5–16. [ Google Scholar ] [ CrossRef ]
• Koceska, N.; Koceski, S.; Beomonte Zobel, P.; Trajkovik, V.; Garcia, N. A telemedicine robot system for assisted and independent living. Sensors 2019 , 19 , 834. [ Google Scholar ] [ CrossRef ]
• Khan, A.; Anwar, Y. Robots in healthcare: A survey. In Proceedings of the Science and Information Conference, CCV2019, San Fancisco, CA, USA, 24–25 October 2019; Volume 2. [ Google Scholar ] [ CrossRef ]
• Cavoukian, A. Privacy by Design: The 7 Foundations—Implementation & Mapping of Fair Information Practices, Information and Privacy Commissioner of Ontario. Available online: https://www.ipc.on.ca/wp-content/uploads/resources/pbd-implement-7found-principles.pdf (accessed on 8 October 2020).
• Shapiro, S.S. Privacy by design: Moving from art to practice. Commun. ACM 2010 , 53 , 27–29. [ Google Scholar ] [ CrossRef ]
• Perera, C.; McCormick, C.; Bandara, A.K.; Price, B.A.; Nuseibeh, B. Privacy-by-design framework for assessing internet of things applications and platforms. In Proceedings of the 6th International Conference on the Internet of Things, Stuttgart, Germany, 7–9 November 2016. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Simsekoglu, Ö. Socio-demographic characteristics, psychological factors and knowledge related to electric car use: A comparison between electric and conventional car drivers. Transp. Policy 2018 , 72 , 180–186. [ Google Scholar ] [ CrossRef ]
• Jones, S.J. If electric cars are the answer, what was the question? Br. Med. Bull. 2019 , 129 , 13–23. [ Google Scholar ] [ CrossRef ]
• Ortar, N.; Ryghaug, M. Should all cars be electric by 2025? The electric car debate in Europe. Sustainability 2019 , 11 , 1868. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Weisz, H.; Steinberger, J.K. Reducing energy and material flows in cities. Curr. Opin. Environ. Sustain. 2010 , 2 , 185–192. [ Google Scholar ] [ CrossRef ]
• Gill, B.; Moeller, S. GHG emissions and the rural-urban divide. A carbon footprint analysis based on the German official income and expenditure survey. Ecol. Econ. 2018 , 145 , 160–169. [ Google Scholar ] [ CrossRef ]
• Moran, D.; Kanemoto, K.; Jiborn, M.; Wood, R.; Többen, J.; Seto, K.C. Carbon footprints of 13,000 cities. Environ. Res. Lett. 2018 , 13 , 064041. [ Google Scholar ] [ CrossRef ]
• Fishman, E. Cycling as transport. Transp. Rev. 2016 , 36 , 1–8. [ Google Scholar ] [ CrossRef ]
• Christiansen, P.; Engebretsen, Ø.; Fearnley, N.; Hanssen, J.U. Parking facilities and the built environment: Impacts on travel behaviour. Transp. Res. Part A Policy Pract. 2017 , 95 , 198–206. [ Google Scholar ] [ CrossRef ]
• Nijland, H.; van Meerkerk, J. Mobility and environmental impacts of car sharing in the Netherlands. Environ. Innov. Soc. Transit. 2017 , 23 , 84–91. [ Google Scholar ] [ CrossRef ]
• Wilson, L. Shades of Green: Electric Cars’ Carbon Emissions around the Globe, February 2013. Available online: https://cupdf.com/document/shades-of-green-full-report.html (accessed on 11 November 2020).
• International Renewable Energy Agency. Internet of Things: Innovation Landscape Brief. 2019. Available online: www.irena.org/publications/2019/Sep/Internet-of-Things (accessed on 11 November 2020).
• Santoro, G.; Vrontis, D.; Thrassou, A.; Dezi, L. The Internet of Things: Building a knowledge management system for open innovation and knowledge management capacity. Technol. Forecast. Soc. Chang. 2018 , 136 , 347–354. [ Google Scholar ] [ CrossRef ]
• Bradley, D.A.; Russell, D.; Hehenberger, P.; Azorin-Lopez, J.; Watt, S.; Milne, C. From Mechatronics to the Cloud. In Reinventing Mechatronics ; Xiu, Y.T., Bradley, D.A., Russell, D., Moore, P., Eds.; Springer: Cham, Switzerland, 2020; pp. 17–33. [ Google Scholar ] [ CrossRef ]
• Mwasilu, F.; Justo, J.J.; Kim, E.K.; Do, T.D.; Jung, J.W. Electric vehicles and smart grid interaction: A review on vehicle to grid and renewable energy sources integration. Renew. Sustain. Energy Rev. 2014 , 3 , 501–516. [ Google Scholar ] [ CrossRef ]
• Mathews, P.; Scherr, I. Annual Compendium of Scottish Energy Statistics 2020, Scottish Government, August 2020. Available online: https://www.gov.scot/publications/annual-compendium-of-scottish-energy-statistics/ (accessed on 6 November 2020).
• JFalnes, J. A review of wave-energy extraction. Mar. Struct. 2007 , 20 , 185–201. [ Google Scholar ] [ CrossRef ]
• Borthwick, A.G. Marine renewable energy seascape. Engineering 2016 , 2 , 69–78. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Department for Business, Industry & Industrial Strategy, Energy Consumption in the UK (ECUK) 1970 to 2019, October 2020. Available online: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1020152/2020_Energy_Consumption_in_the_UK__ECUK_.pdf (accessed on 9 November 2020).
• Coupar Angus Infrastructure Report (Working Document 2017). Available online: https://www.pkc.gov.uk/media/45642/COUPAR-ANGUS/pdf/COUPAR_ANGUS.pdf?m=637183240973130000 (accessed on 30 January 2020).
• City Population UK. Available online: https://www.citypopulation.de/en/uk/scotland/ (accessed on 30 January 2020).
• Lin, T.; Yu, Y.; Bai, X.; Feng, L.; Wang, J. Greenhouse gas emissions accounting of urban residential consumption: A household survey based approach. PLoS ONE 2013 , 8 , e55642. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
• Boswell, M.R.; Greve, A.I.; Seale, T.L. Climate Action Planning: A Guide to Creating Low-Carbon, Resilient Communities ; Island Press: Washington, DC, USA, 2019. [ Google Scholar ]
• Santana, E.F.Z.; Covas, G.; Duarte, F.; Santi, P.; Ratti, C.; Kon, F. Transitioning to a driverless city: Evaluating a hybrid system for autonomous and non-autonomous vehicles. Simul. Model. Pract. Theory 2020 , 107 , 102210. [ Google Scholar ] [ CrossRef ]
• UN Environment Programme. Consumer Information Tools and Climate Change—Facilitating Low-Carbon Choices in Tourism, Buildings and Food Systems. Available online: https://www.oneplanetnetwork.org/knowledge-centre/resources/consumer-information-tools-and-climate-change (accessed on 2 April 2020).
• Tetlock, P.E.; Gardner, D. Superforecasting: The Art and Science of Prediction ; Random House: New York, NY, USA, 2016. [ Google Scholar ]
• WEF. Shaping the Future of Construction—Future Scenarios and Implications for the Industry. Available online: https://www3.weforum.org/docs/Future_Scenarios_Implications_Industry_report_2018.pdf (accessed on 22 October 2020).
• Frey, C.B.; Osborne, M.A. The future of employment: How susceptible are jobs to computerisation? Technol. Forecast. Soc. Chang. 2017 , 114 , 254–280. [ Google Scholar ] [ CrossRef ]
• Peters, M.A. Technological unemployment: Educating for the fourth industrial revolution. Educ. Philos. Theory 2017 , 49 , 99–107. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Balliester, T.; Elsheikhi, A. The Future of Work: A Literature Review, International Labour Office Research Department Working Paper 29. 2018. Available online: https://catalogue.unccd.int/980_wcms_625866.pdf (accessed on 8 November 2020).
• Jarrahi, M.H. Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Bus. Horiz. 2018 , 61 , 577–586. [ Google Scholar ] [ CrossRef ]
• West, D.M. The Future of Work: Robots, AI, and Automation ; Brookings Institution Press: Washington, DC, USA, 2018. [ Google Scholar ]
• Wang, W.; Siau, K. Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity: A review and research agenda. J. Database Manag. 2019 , 30 , 61–79. [ Google Scholar ] [ CrossRef ]

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Simpson, E.; Bradley, D.; Palfreyman, J.; White, R. Sustainable Society: Wellbeing and Technology—3 Case Studies in Decision Making. Sustainability 2022 , 14 , 13566. https://doi.org/10.3390/su142013566

Simpson E, Bradley D, Palfreyman J, White R. Sustainable Society: Wellbeing and Technology—3 Case Studies in Decision Making. Sustainability . 2022; 14(20):13566. https://doi.org/10.3390/su142013566

Simpson, Edward, David Bradley, John Palfreyman, and Roger White. 2022. "Sustainable Society: Wellbeing and Technology—3 Case Studies in Decision Making" Sustainability 14, no. 20: 13566. https://doi.org/10.3390/su142013566

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Sustainable Technology for Society 5.0

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This book aims to bring together valuable and novel scientific contributions that address the critical issues of sustainable building, transformative tech models, and other sustainability science and technology topics that have an impact on Society 5.0. This book raises awareness and shares essential policy tools on innovation and technology for sustainable development.

Sustainable Technology for Society 5.0: Case Studies, Examples, and Advanced Research Findings details the use of AI in making complex data analysis and sustainable decision making. It reflects the collaboration of industry, innovation, and infrastructure for Society 5.0. The book elaborates on the essential tools, policy, and strategic implications for building a sustainable tech framework and provides insight into sustainability science and technological contemporary trends. Rounding out the book is a strategic innovative model framework that works towards sustainable, good health, and well-being for Society 5.0.

Researchers, scholars, students, and practitioners will find this book of interest.

TABLE OF CONTENTS

Chapter 1 | 11  pages, technology transformation for sustainable research pedagogy, chapter 2 | 7  pages, impact of technology on healthcare along with social security to achieve sustainability, chapter 3 | 13  pages, smart infrastructure, chapter 4 | 12  pages, chatbots communication quality impact on brand experience of customers, chapter 5 | 13  pages, making the impossible possible, chapter 6 | 16  pages, ai in e-commerce, chapter 7 | 13  pages, chapter 8 | 16  pages, sustainability through transformative technologies, chapter 9 | 8  pages, managing employees in private organizations, chapter 10 | 12  pages, triple bottom line framework and sustainable practices, chapter 11 | 13  pages, impact of advertising on shopping behaviour, chapter 12 | 19  pages, cost and financial accounting in high-technology firms, chapter 13 | 13  pages, chapter 14 | 16  pages, potential electricity production of roof-mounted solar pv systems in a row house area in sweden, chapter 15 | 14  pages, the double-edged sword of ai and industrial revolution 4.0, chapter 16 | 10  pages, digitalization.

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• Mar 7, 2022

15 Sustainable Manufacturing Examples and Case Studies

Updated: Nov 17, 2023

The environment and society are intricately linked. This is something that companies have come to realize, with many now making efforts towards sustainable manufacturing as a way of ensuring both cost efficiency while meeting expectations from customers or investors alike, and local communities that could be impacted.

The environmental and economic benefits of green growth are becoming more well-known, with many businesses already taking important steps towards it. Their pioneering experiences show that this can go hand in hand for profitability as well as sustainability.

Here are 8 reasons why big brands are moving towards sustainable products

Sustainable Manufacturing Case Studies

Sustainability is the future , but many businesses have not yet leapt into this new era. They may be struggling with their short-term survival or cost pressure from clients and lack of knowledge on how best to invest in environmental improvement. It can also simply seem like an overwhelming task for those who are just starting out.

Related Article: Case Study: Taking Advantage of ODM Manufacturing

Here are some examples and brief case studies which will help show how this new approach has helped businesses save money in addition to improving their products or operations.

1. Gairdin: Manufactures sustainable gardening tools and pots

Gairdín, pronounced “Gar-Jean”, is the Gaelic Irish word for garden. They specialise in garden tools that are environmentally friendly, made from recycled and sustainable raw materials like Ocean-Bound Plastics and Algae-Blended Resin. Gairdin are a division of Diversitech Global comprising 20 years of industrial expertise in product design, manufacture and packaging. Find originality and innovation with sustainable materials always top-most in mind.

Related Article: 7 Sustainable Gardening Practices for Environmentally Conscious Individuals

2. Electrolux, Kinston Plant: Reduced energy cnsumption

The Electrolux Green Spirit program made an impactful approach to reducing energy consumption and environmental impact. Their Kinston factory achieved this by running the processes as efficiently as possible, switching off all equipment when not in use, lowering the plant's demand for compressed air and installing motion sensors for lighting. And engaged engineering and maintenance personnel to find and repair a compressed air leak every day.

3. Advanced Composite Structure: Eliminated excess raw material usage

Using lean manufacturing and a value mapping process, their production processes and the layout of the company’s production area were analyzed and reviewed. They eliminated excess movement, materials, and extra tooling to help create a more streamlined product flow. The company reduced costs by 65%, increased production from 20 units per shift to 45 units per shift, reduced its production facility size by 73%, and reduced scrap rates from 24% to 1.8%.

4. Guardian Automotive: Implemented a waste recycling program

Guardian Automotive is committed to reducing its environmental footprint. They have implemented a waste reduction program for them not only to be sustainable but also more efficient with resources. The company is now recycling among other materials unused glass cullet, fiberglass and scrap polyvinyl chloride. In 2005, the Ligonier Plant recycled more than 13,000 tons of waste and saved over $360,000.

5. Custom Print: Reduced its chemical inventory

When an investigation into the company’s chemical inventory and purchasing records revealed over 80 different chemicals on-site, a team from press operators to maintenance personnel got together for some brainstorming sessions to reduce inventory. Wasted ink was reduced by training employees to mix speciality colors from existing ink stocks. Furthermore, they came up with suggestions like modifying ventilation and air-conditioning efficiency to help improve worker health as well as greatly reduce energy costs.

6. Chrome Deposit Corporation: Cut down natural gas consumption

To increase energy efficiency and improve their responsible business practices, Chrome Deposit Corporation embarked on an effort to develop new ways of doing things. By making simple changes like adjusting boiler settings and repairing minor gas line leakages, the company was able to cut its natural gas consumption by 12%. They also purchased two chillers which implemented a closed loop system for water use. This resulted in an 85% reduction in water usage.

7. Kennecott Utah Copper Refinery: Improved power grid efficiency

Kennecott Utah has improved the energy efficiency of its refinery through the installation of a combined heat and power system. Their 6-megawatt system replaced power purchased from the coal-powered grid. It supplies more than half of the refinery’s total electricity needs and waste heat is recycled to make steam for turbines. Among deep reductions in emitted pollutants, CO2 emissions were reduced by 36,000 tonnes.

8. Besam North America: Improved energy and waste handling

With serious consultation and recommendations, Besam targeted energy, waste, and productivity surveys. This included replacing metal halide lighting with fluorescent fixtures with occupancy sensors, installation of high-efficiency lamps and electronic ballasts, reducing compressor air pressure, and repair of compressed air leaks

9. Rapid-Line: Sustainable operations to reduce its natural gas usage

Rapid-Line which fabricates and tooling for the manufacturing industry was experiencing a significant increase in their natural gas costs. Also, one of their customers encouraged them to get more involved with green practices. A new installation of ceiling fans and baffles made for better heating and cooling. Extra insulation, automated controls and reusing excess heat from the paint-line ovens boosted efficiencies and eliminated external furnace heating.

10. Isothane: Replaced hazardous raw materials with sustainable alternatives

Isothane manufactures chemical products used for insulating and protecting constructions, buildings and civil engineering structures. New government legislation had been introduced with strict emission standards and to comply with flameproof manufacturing and storage standards. They spent two months researching less hazardous and flammable chemical alternatives. Substitute materials were found and old lines were discontinued. Solvent material use was greatly decreased and much less hazardous material was stored on-site.

11. Wausau Tile: Used recycled glass chip as raw material

Wausau Tile wanted to save money and use less natural raw materials while being environmentally conscious. The company believed that by using post-consumer/industrial glass chips, which is difficult and expensive to recycle, they could reduce their environmental impact and attract new customers with their decorative value. With the use of large glass chip aggregate, they were able to make their products attractive and architecturally pleasing, and have introduced it across whole product lines.

12. Calstone: Sustainable furniture production

The company found that it could expand its market by selling more environmentally sustainable furniture products. Major changes were brought to its manufacturing plant. A vapour spray system reduced degreasing agents used on metal components. A 2000 gallon water tank reuses water for cooling equipment, and rainwater is collected for toilet flushing. Installed skylights brought in natural light for the benefit of indoor foliage plants that purify the indoor air. The company buys electricity from a hydro and wind power provider and has installed solar panels on the roof.

13. PortionPac Chemical Corporation: Products assessment based on green standards

Intending to become more sustainable, the company began an assessment on its products and obtained third-party green certification for all floor cleaners, all-purpose cleaners, glass cleaners and bowl cleaners. Also, by updating packaging components, they reduced waste, disposal costs and shipping. In addition, they also found a buyer for one of their by-product materials. These steps made PortionPac attractive to large businesses, schools and hospitals as they had the sustainability credentials along with their potential for saving costs

14. S.C. Johnson: Reduced environmental effects of its ingredients

In order to continue producing high-quality products with an environmentally-friendly mindset, S.C Johnson has developed their Greenlist system which ranks the environmental and health effects of ingredients used in its manufacturing process leading to the reformulation of many old favorites. After reviewing Saran Wrap usage, the company eliminated 4 million pounds of PVDC and reduced 1.8 million pounds of volatile organic compounds from its famous Windex product.

15. Honda: Reduced scarce material usage

Honda is serious about sustainability. They have a Green Path program that targets reductions in the use of materials and scarce resources, developing products that are easier to recycle, and reduced water waste as well CO2 emissions during manufacture. Honda uses wind turbines at its Ohio plant to generate 10,000-megawatt hours of electricity per year. It also moves 80% of vehicles from plant to dealership by train, which has reduced CO2 emissions by over 60%.

So, what does this mean for sustainable manufacturers? It means that making a switch to producing sustainable products is not only the best thing to do for the environment, but it’s also a wise business decision. Consumers are more interested than ever in buying sustainable products and that trend is only going to continue.

Making the switch to sustainable manufacturing may seem daunting, but it’s important to remember that you’re not alone. There are plenty of resources and support systems in place to help you get started. And the best part is, making the right choice for your business and the environment can also be good for you.

See our article: Is it Really cheaper to manufacture in China

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The Future of Sustainable Technology: Trends and Innovations

The demand for sustainable technology is rapidly growing. Learn how businesses are designing their products with sustainability in mind.

As the world of tech continues to expand, companies are shifting to more eco-friendly practices to ensure they can cater to both people and the environment. More and more businesses are investing in sustainable technology to keep the momentum of growth without compromising natural resources. Tech giants like Samsung, IBM, Intel, Apple, and Dell are already implementing sustainability practices in their operations.

However, reducing the carbon footprint in the electronics industry is challenging, especially for reputable manufacturers. Sustainability practices will disrupt and challenge traditional and conventional practices. Nonetheless, government regulations and customer demands are putting more pressure on businesses all around the world to do more to reduce emissions.

If you want to keep up with competitors in the tech industry, learning more about sustainability practices is imperative. In this entry, we’ll discuss the ongoing sustainability trends happening among tech businesses. Learn how you can employ the same types of methods and processes in your own operations.

The Importance of Sustainability in Tech

Tech companies are gradually following circular business models to ensure they meet their customer’s demands while retaining the quality of their products. The circular business model enables organizations to produce value through resource efficiency and prolonging the life of products and their components. By creating new business models and utilizing raw materials more effectively, these models can open up new economic prospects for companies.

Today, there is an even greater urgency in the electronics industry’s need for a circular economy. Companies have to adhere to new regulations to prevent resource depletion, environmental degradation, and adverse health effects. They have to cooperate and promote the larger transition to a Net Zero economy to lessen the effects of GHG-induced climate change .

This shift to sustainable technology will ensure longevity in the business and strengthen their patronage. Customers are more likely to support businesses that are employing environment-friendly practices and campaigns.  

Sustainable Technology Trends

Here are some of the top sustainability technology trends that are helping businesses cut down production waste while boosting the quality of their products: 

1. Developing products with sustainability and circularity in mind.

Every product’s life cycle phase, even in SDLC in the SaaS industry, must adhere to a circular economy . By developing items that are simple to upgrade, fix, and disassemble for recycling, manufacturers will be able to create products that are easy to use.

Here are some of the sustainability practices you can follow in developing the product:

• Use of more recyclable materials in new goods as well as recyclable materials.
• Enhancing the products’ modularity and detachability, reducing the use of strong adhesives, and using fewer blended parts will make it easier to harvest and recycle parts at the end of a product’s useful life. 
• Focus on durability and repairability, the long-term design of items, and avoiding planned obsolescence models.

2. Collecting used products.

Most electronics manufacturers consider their relationship with their product to be complete once the consumer has it in their hands. In order for consumers to return their used electronics or component parts for recycling or refurbishment, manufacturers are setting up a reverse logistics system. Manufacturers are the best entities to facilitate a safe and effective recycling process for their materials. Through recycling materials, they can boost their production of sustainable technology.

3. Distributing refurbished items to new user communities and applications.

There may be a number of potential pathways for the used components once the used products and components have been collected. Refurbished gadgets can be sold at a discount to lower-end customers, increasing their availability to more user groups. 

Another illustration is the rising need for electronic components as the Internet of Things develops. Screens, batteries, sensors, hard drives, and semiconductors are examples of basic components that can be reused for high-performance applications to lower ones. Reusing these materials can extend their useful lives and lower the need for replacement parts. 

4. Enhancing the source of materials and industrial synergy.

It can be difficult to turn e-waste into useful sources for new electronic components when the material is steel, for example. In such circumstances, industrial symbiosis —a collaboration between several companies to interchange recyclable and waste materials—is required. 

Successful cross-industry collaboration on this issue may be seen in Lime’s recycling of abandoned scooters into consumer electronics or the creation of carbon fiber-reinforced polycarbonate laptop bottoms by Dell using leftover carbon fiber from the aerospace sector.

5. Researching fresh business concepts for the circular economy.

Producers and consumers should be given incentives to realize a circular economy for electronics. A Berlin firm, called Grover, which offers a subscription model for consumer electronics, is one example of a business model that leases devices instead of selling them. 

Other possibilities include expanding refurbishment and resale networks beyond unofficial peer-to-peer transactions. Platforms like eBay or networks like O2 allow users to trade in their old phones to be repaired and resold with a 12-month warranty.

6. Using renewable energy to power production

Access to renewable energy is growing in importance as businesses construct new fabrication facilities. More readily available renewable energy gives businesses a new form of production leverage and promotes domestic manufacturing. They can build more sustainable technology through it. Thanks to significant energy savings and energy independence, the fabrication of various electronic components is probably going to become increasingly cost-competitive. 

7. Smart manufacturing

Making environmentally friendly electronics presents several opportunities to boost output, reduce waste, and minimize prices. Artificial intelligence and the Internet of Things can enable sustainable manufacturing. Businesses may help reduce waste and out-of-control expenses by utilizing sensor technologies to spot leaks and improper material usage. Sensor technologies with sophisticated digital manufacturing techniques can automate these processes.

8. Fleet Software

Implementing a robust  vehicle maintenance schedule   enhances sustainability in transportation by optimizing fuel usage and reducing emissions. This software provides real-time data on fuel consumption and vehicle performance, enabling companies to make informed decisions that cut costs and minimize environmental impact. By improving efficiency, fleet fuel management software contributes to a greener future.

Develop Your Product with Full Scale

Want to learn more about sustainability? Plan out a new digital system that’s more environmentally friendly . You need tech experts who can follow your vision to create effective and sustainable technology. And Full Scale can help you find the best IT talent in the industry!

Finding highly skilled professionals in the IT industry can be challenging, especially with the ongoing IT talent shortage . At Full Scale, our goal is to match you with the most qualified candidates for your project. We’ll help you establish and maintain a convenient dynamic with your team.

We expedite hiring on your end by following a comprehensive screening process for software engineers, testers, project managers, and marketing specialists. Hire the top specialists quickly and affordably with Full Scale!

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• Published: 01 May 2024

Digital technologies for construction sustainability: Status quo, challenges, and future prospects

• Weisheng Lu 1 ,
• Jinfeng Lou 1 ,
• Benjamin Kwaku Ababio 1 ,
• Ray Y. Zhong 2 ,
• Zhikang Bao 3 ,
• Xiao Li 4 &
• Fan Xue 1  

npj Materials Sustainability volume  2 , Article number:  10 ( 2024 ) Cite this article

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The nexus between digital technologies (DTs) and sustainability in the built environment has attracted increasing research interest in recent years, yet understanding DT utilization and its impact on construction processes remains fragmented. To address this gap, this study conducts a systematic review of the construction sustainability literature to analyze and synthesize research findings on the application of DTs at various stages of the construction lifecycle. We undertake an in-depth content analysis of 72 articles, with findings revealing that prominent DTs for construction sustainability include building information modeling, the Internet of Things, big data, and artificial intelligence. We also identify that the application of DTs for sustainability across the construction lifecycle is clustered in four areas: namely (1) integration and collaboration; (2) optimization, simulation, and decision-making; (3) tracking, monitoring, and control; and (4) training. Based on existing knowledge gaps, future research opportunities are identified, including the development of integrated and interoperable systems, long-term performance and resilience, and advanced simulation and modeling techniques. This study contributes to the literature on construction digitalization by offering a complete overview of research investigations in relation to construction sustainability and identifying research crucial to advancing a DT-enabled sustainable built environment.

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Introduction.

The construction industry is not just about erecting buildings and infrastructure; it plays a vital role in economic and social development, contributing approximately USD200 billion to global GDP and providing over 220 million jobs 1 . The sector embodies a continuous lifecycle that integrates design, construction, operation & maintenance (O&M), and end of life, where each stage is interlinked and connected to the overall functionality and sustainability of the built environment 2 . The initial design sets the blueprint for sustainable and efficient use of resources 3 , 4 , and this design is materialized in the construction phase 5 . The O&M period extends over the longest phase of a structure’s life, emphasizing energy efficiency and environmental stewardship 6 . Finally, end-of-life is a critical component in the recycling and repurposing of materials 7 , 8 .

The construction industry has long been associated with significant environmental impacts, including resource consumption, waste generation, and carbon emissions 9 , 10 , 11 . It produces 45–65% of the waste dumped in landfills, contributing 35% of the world’s CO 2 emissions 12 . As the focus of the global community on sustainable development intensifies 13 , the construction sector faces an imperative to evolve. Sustainable practices meet the needs of the present without compromising the ability of future generations to meet their own needs 14 . ‘Construction sustainability’, therefore, is the implementation of such practices in construction industry activities 15 , encompassing three core dimensions: environmental protection, social responsibility, and economic viability 16 .

In responding to sustainability challenges, digital technologies (DTs) are a potentially transformative tool. DTs include information and communication technologies (ICTs) that manage information through digital binary computer language. In construction, they range from standalone systems to integrated and web-based technologies, which aid in data capture, storage, processing, display, and communication during various procurement stages. By streamlining processes, reducing waste, and enabling better decision-making, DTs promise to significantly advance the sustainability agenda in construction.

Despite growing recognition of their potential, the academic landscape reveals a fragmented understanding of DTs’ impact on sustainability in construction. Research studies vary in focus, methodology, and findings, making it challenging for industry stakeholders to form a cohesive view of the role of DTs in promoting sustainability. This fragmentation presents a critical barrier to effectively leveraging DTs for sustainable construction practices. To bridge this knowledge gap, this study conducts a systematic review of the construction sustainability literature. The goal is to compile, analyze, and synthesize research findings to present a clear, coherent picture of how DTs are being used to foster sustainability in construction. By critically examining the interplay between DT application and sustainable practices, we aim to identify successful strategies and highlight areas urging further exploration.

Prominent digital technologies in the construction sustainability literature

Reviewing the content of 72 articles in the construction sustainability literature, DTs frequently referenced and thoroughly examined were collected and organized in a Sankey diagram (see Fig. 1 ). Some DTs have received particular attention in the literature, e.g. building information modeling (BIM) and Internet of Things (IoT), while others have remained under-researched in relation to sustainability, e.g. unmanned aerial vehicles (UAV) and cloud computing. The diagram also reveals that DTs are employed for construction sustainability purposes mostly at the design and O&M stages of the construction lifecycle, typically as a standalone technology or paired with one other technology to achieve better performance.

The papers reviewed are categorized according to the number of technologies, the name of the primary technology, and the stage at which the technologies are applied.

Figure 2 presents the distribution in the literature of key DTs for construction sustainability from 2020 to the present. BIM is the most frequently mentioned DT in the sustainability literature, with a peak of 10 research articles published between 2021 and 2022. The results indicate the continuation of a trend, with 17 identifying BIM as a top research theme in the DT-sustainability literature. This is attributable to the function of BIM as a collaborative platform and a means for integrating other DTs at different stages of the construction lifecycle. Studies relating BIM to sustainability in construction processes have seen a steady rise since the inception of BIM, with its application traversing design, construction, and O&M lifecycle stages. This suggests the vital role of BIM in improving sustainability through collaboration, visual representation, and optimization. IoT, with its use of sensors and actuators, has also been extensively discussed in the literature as essential to gathering sustainability-related data. Studies indicate the utilization of IoT in monitoring and controlling energy usage of buildings, optimizing resource use, and enhancing safety on site, all of which enable informed decisions on sustainability-related issues. Big data is also an important DT leveraging the vast amount of data generated throughout the project lifecycle by IoTs and other sources. There is a strong link between big data and IoT in the current body of knowledge, with both concepts often discussed together in optimization studies, environmental assessments, and risk and safety management. Artificial intelligence (AI) and machine learning (ML) in sustainability are gradually gaining momentum. Their ability to process huge amounts of heterogeneous data using computational power is vital for extracting insights into sustainable decision-making that effectively improves construction processes.

BIM is the most widely used technology for construction sustainability in recent years (2020–2023).

Other prominent DTs in construction sustainability are virtual reality (VR) and augmented reality (AR). Studies involving VR and AR cite their role in construction planning, where these DTs can be used for simulating interactive experiences and reviewing sustainability scenarios such as energy-efficient installations and user comfort. VR and AR technologies have been articulated in existing literature as early design optimization and visualization toolsets promoting a deeper understanding of sustainability features and fostering a sense of commitment towards sustainable outcomes. UAVs, or drones, are another type of DT increasingly used in construction, for surveying, inspection, and monitoring. In the construction sustainability literature, the application of UAVs has been discussed in hazard identification, safe work processes, and waste reduction. Cloud computing has also been identified as relevant to construction sustainability for its potential in providing centralized platforms for information management, communication, and collaboration throughout the project lifecycle. However, many recent studies are shifting their attention to blockchain technology as an enabler of construction sustainability, through providing transparent and immutable records and facilitating the integration of sustainable practices, such as material reuse and tracking. Little attention has been given to digital twins and cyber-physical systems (CPS) in sustainability research, though there has been an increasing trend in recent years for their potential to revolutionize construction sustainability by enabling real-time monitoring, optimization, and performance improvement throughout the project lifecycle.

Based on the results of our review of the literature, the DTs most closely associated with sustainability in the construction industry are BIM, IoT, AI, ML, VR, AR, UAV, robots, blockchain, and CPS. The overall growth in the application of these DTs for construction sustainably is likely to continue as the DT potential progressively permeates the entire lifecycle of construction products and services.

Application of digital technologies in construction sustainability

In examining the application of digital technologies to construction sustainability, it is crucial to analyze their impacts across different stages of the construction lifecycle: design, construction, O&M, and end of life.

In the design stage, recent literature indicates there is a growing nexus of DTs that enhance sustainability. Prominent examples include BIM in its 6D form, AR/VR, and AI for design. Six-dimensional BIM transcends traditional 3D modeling by integrating time (4D), cost (5D), and sustainability (6D) considerations, such as energy performance 18 , resource efficiency 19 , carbon emissions reduction 20 , and retrofit process simulation 21 . The emphasis is on the lifecycle approach 22 , where BIM informs decisions right from the design phase to reduce environmental impact and promote green building practices. AR/VR technologies have evolved to significantly improve design visualization and stakeholder engagement 23 , with discussions extending into the realm of the metaverse, which offers immersive spaces for interaction. The metaverse can benefit sustainability by facilitating the participation of the majority of people in decisions about how to utilize resources more efficiently 24 . AI, particularly in generative design 25 , is leveraged to create multiple sustainable design alternatives based on specific constraints and goals, focusing on material usage reduction 26 and energy efficiency optimization 27 .

The construction stage sees the critical role of blockchain, IoT, radio-frequency identification (RFID), digital twins, and UAVs in advancing sustainability. Blockchain’s potential lies in enhancing transparency and accountability in construction processes 28 , 29 , while smart contracts facilitate complex agreements and compliance with sustainability standards 30 . They can streamline procurement processes 31 , enhance supply chain management 32 , and facilitate more efficient project management 33 , 34 , leading to reduced waste and improved resource allocation. The role of IoT in sustainable construction is growing, with a focus on real-time data collection and monitoring 35 . IoT devices, such as sensors and wearables, are used to track resource utilization and environmental conditions 36 , thus aiding in optimizing resource use and reducing energy consumption 37 . RFID, one of the most powerful IoT technologies, has been extensively employed for effective logistics management, deemed crucial in reducing the carbon footprint of construction activities 38 by enabling accurate tracking of materials, tools, and equipment. RFID systems help in minimizing losses, reducing waste, and ensuring that materials are sourced and used sustainably. In addition, the integration of digital twins in the construction process represents a significant advancement. A digital twin is a virtual replica of a physical building that can be used for monitoring, simulation, and analysis 39 , 40 . Optimized construction efficiency is achievable through digital twins, which help streamline workflows, allocate resources efficiently, and monitor construction progress in real-time. This reduces the risks of delays and material waste by providing active and accurate information 41 . By creating a virtual representation of the construction project, digital twins enable a more dynamic and responsive approach to construction management, further enhancing sustainability. UAVs, commonly known as drones, are increasingly used in construction for various tasks such as site surveying, monitoring, and inspection. They provide a unique vantage point for overseeing construction activities, enabling better management of resources, and ensuring adherence to environmental and safety regulations 42 .

During the O&M phase, human–robot collaboration signifies a shift towards automation, enhancing efficiency and sustainability 43 . In this context, human–robot collaboration is not about replacing human workers, but rather enhancing their capabilities and safety 44 . Robots are used for tasks like cleaning, maintenance, surveillance, and inspection 45 , reducing the workload on human staff, increasing precision, and enhancing safety, particularly in hazardous environments. The concept of digital twins has also gained prominence in the O&M phase 46 . Data management and access post-construction can be complex due to the transition of control and operations among various stakeholders. This technology effectively bridges information gaps, ensuring reliable and convenient project management and facilitating enhanced communication among stakeholders 41 . Moreover, the digital twin provides a dynamic and real-time representation of the building and enables “what-if” analyses in occupant comfort, energy utilization, logistics optimization, asset management, and predictive maintenance, enhancing decision-making capabilities 47 , 48 , 49 . IoT devices and sensors, in addition, are widely used for continuous monitoring and data collection in buildings. This technology trend contributes significantly to the sustainability of facilities by enabling energy efficiency and predictive maintenance. Sensors collect data on aspects such as energy usage, temperature, and occupancy levels 50 , 51 , crucial for optimizing building operations and reducing unnecessary energy consumption 52 . To analyze the vast amount of data generated by IoT devices and other sources, AI and ML algorithms are increasingly applied. These technologies enable predictive maintenance, energy management, and anomaly detection, thereby enhancing the sustainability of building operations 53 , 54 .

At the end-of-life stage, DTs such as big data analytics, computer vision, robotics, and blockchain are key to managing deconstruction and waste processes. Big data analytics assists in material stock assessment, facilitating optimal material reuse and recycling, aligning with circular economy principles 55 , 56 . The role of computer vision in automating waste material sorting, combined with AI algorithms, enhances recycling efficiency 57 , 58 . Robotics in deconstruction focuses on safe material recovery 59 , 60 , while blockchain improves material traceability, ensuring informed decisions for material reuse and recycling 61 .

Prospects for digital technologies in construction sustainability

DTs incorporate several enhancements and modifications to construction value chain processes, increasing efficiency and productivity 19 . The opportunities for adopting these technologies to streamline sustainable production, construction, and operation in the industry are vast. From the analysis of the literature, we find that the driving themes in DT prospects for sustainability are linked with integration and collaboration 62 ; optimization, simulation, and decision-making 63 ; monitoring and control 64 ; and training 24 as presented in Fig. 3 .

The potential of digital technologies can be explored in four areas, including integration and collaboration, optimization, simulation, and decision-making, monitoring and control, and training.

Integration and collaboration

The task of maintaining profitability while achieving cleaner, low-carbon construction processes, and greener and safer job sites, requires extensive stakeholder buy-in, involvement, and support 65 . To achieve this, there is a need to improve collaboration within and across different building lifecycles. DTs facilitate collaboration among stakeholders involved in the construction process by enabling effective communication and information sharing. According to 66 , cloud-based platforms, project management software, and collaborative tools allow real-time collaboration, document sharing, and coordination among architects, engineers, contractors, and sustainability consultants, among others. This collaboration enhances the integration of sustainability considerations into the project, leading to better-informed decisions and improved sustainability outcomes. Furthermore, DTs facilitate the integration of new and existing systems and processes to enhance sustainability outcomes. Integrating BIM models with energy modeling software, for instance, enables automated energy analysis and interference detection 21 . Integration with supply chain management systems allows for tracking and optimizing material usage, reducing waste, and promoting sustainable sourcing practices 67 . DTs provide a comprehensive approach to sustainability over the whole project lifecycle by combining various data sources and platforms.

Optimization, simulation and decision-making

Making informed decisions as early as feasible assists in efficient and cost-effective sustainable design and construction. Sustainability analysis tools, for example, enable better-informed decisions by analyzing numerous design options and identifying sustainable alternatives 68 , 69 . These evaluations assist professionals at various stages in determining the consequences of their building designs for environmental performance and efficiency. To improve sustainability, DTs enable optimization through the exploration of several design possibilities and evaluate their societal, environmental, and energy performance using BIM, ML, and parametric modeling. This aids in the identification of the most sustainable design solutions, decreasing material waste, energy usage, and environmental impacts 70 . Moreover, DTs provide simulation capabilities to assess the performance of buildings and infrastructure systems. For example, studies have incorporated energy modeling software to simulate and analyze energy consumption, daylighting, and thermal performance 18 . Others such as 71 have used computational fluid dynamics simulations to evaluate indoor air quality, ventilation effectiveness, and natural ventilation strategies. These simulations enable designers to make informed decisions, optimize sustainability performance, and identify potential issues before construction.

Monitoring and control

Some studies have explored mechanisms for monitoring sustainable aspects such as construction-related emissions using DTs that enable real-time tracking and monitoring of work progress and building performance 72 . Building management systems, IoT sensors, digital twins, and data analytics platforms collect data on energy consumption, indoor environmental quality, occupancy patterns, and equipment performance. The data helps identify areas of inefficiencies, pinpoint maintenance needs, and optimize resource usage, leading to energy savings, improved occupant comfort, and reduced environmental impact 73 .

For sustainability education and skill development, DTs provide interactive and immersive training alternatives. Immersive training experiences are made possible by VR, AR, and mixed-reality technologies, which allow users to simulate and implement sustainable construction practices, safety regulations, and energy-efficient operations 24 . The deployment of DTs enables safe demonstration and experimentation, promoting knowledge transfer and capacity building. Additionally, AI and ML platforms enable easy access to more efficient, responsive, and interactive train systems linked to sustainability 74 .

Digital technology application bottlenecks in construction sustainability

Deployment of DTs for construction sustainability faces several challenges across different stages of the project lifecycle (Fig. 4 ). First, accurate data and information are essential for conducting sustainability analysis during the design and planning stages of projects 75 . However, the present challenge of data quality and availability of construction products and services makes it difficult to fully benefit from the prospects of DT application. Data on material properties, energy consumption, and environmental impacts may not be readily available or standardized, making it difficult to assess sustainability performance accurately 76 . Standardized protocols, formats, and data exchange mechanisms that ensure consistent data quality and compatibility across different digital tools and platforms are still largely underdeveloped and unable to fully grasp all aspects of sustainability considerations in the construction industry. Interoperability of various DTs for holistic construction sustainability is missing within and across different lifecycle stages 77 . Within the same lifecycle stage, various digital tools and applications such as BIM, geographic information systems, energy modeling software, and sustainability analysis tools generate different types of data in varying formats and qualities 78 . Across different lifecycle stages, gathering real-time data from various sources, such as sensors and equipment, and integrating it into a unified system can be complex 79 . posit that the challenge lies in integrating these diverse datasets into a unified system that allows for comprehensive analysis and decision-making. Thus, ensuring data accuracy, reliability, and interoperability in different platforms and systems is crucial for enabling construction sustainability.

Two categories of challenges are identified: data quality and availability, and integration of sustainability parameters into digital systems.

Another key challenge is the integration of sustainability parameters into digital systems, including balancing conflicting design objectives and ensuring compatibility with already existing systems 80 . The deployment of DTs for sustainable construction requires expertise in certain unconventional areas of construction and given present inadequacies in the construction workforce, such expertise is hard to find 81 . point to many benefits of deploying DTs for construction sustainability, including lowered employment costs for organizations through the application of automated work processes. However, this can lead to significant job losses and worker segmentation, which may in turn result in resistance to change stemming from a lack of training, awareness, and involvement. There is a need to develop innovative and varied instructional approaches, but it is unclear how these challenges faced are being addressed in the present literature 80 . The introduction of both DTs and sustainable practices is nascent in the construction industry but is gaining momentum. Therefore, more conscious planning and capital investment are needed to enhance industry skills and manage behavior change with necessary measures that may completely deviate from existing supply chain operations. Moreover, at the core of DT for construction sustainability is the need for stakeholder collaboration and engagement 82 . Yet, given the vast and fragmented nature of stakeholders along a construction project’s lifecycle, including designers, contractors, facility managers, maintenance personnel, and occupants, it can be challenging to track and foster effective collaboration. This challenge stems from the absence of efficient communication channels, unwillingness to exchange and transmit knowledge and information, and failure by the relevant parties to cultivate proactive sustainability initiatives 83 . Other challenges are linked to adherence to regulatory requirements and data confidence, security, protection, and issues associated with the deployment of DTs 84 . Given the long-term performance monitoring of sustainability features and systems over a building or infrastructure’s lifespan, the need to build trust and efficient systems is critical. Ensuring that digital systems continue to operate optimally, maintaining modern sustainable practices during renovations or retrofits, and monitoring changes in building performance require continuous data collection, analysis, and stakeholder involvement, which can be onerous and costly 85 .

Future research trends and directions

The findings from this critical review of trending topics, prospects, challenges, and application of DTs in promoting construction sustainability offer a full picture of current research activities and reveal relevant gaps and future research needs. These future research needs represent the untapped potential identified from the analysis and evaluation of future works proposed in the existing literature and are explained below.

Limited attention has been paid to the integration of DTs for sustainability in construction 86 . Further research is required to delve into the development of standardized protocols, formats, and data exchange mechanisms to ensure consistent data quality and compatibility across different digital tools and platforms. This includes establishing guidelines for data collection, verification, and validation to enhance the accuracy and reliability of sustainability-related data.

An evolving trend receiving considerable attention has been the utilization of advanced simulation and modeling techniques 21 . Additional study is required to enhance simulation and modeling methodologies in order to achieve more accurate forecasting and analysis of sustainability results. This encompasses the enhancement of energy modeling software, the utilization of computational fluid dynamics simulations, and the implementation of multi-scale modeling techniques to accurately represent intricate interactions and maximize the utilization of resources.

The application of advanced DTs including ML and AI has stimulated conversations on their anticipated threat to social aspects of sustainability. Presently, AI/ML models are used to predict sustainability performance, optimize resource allocation, and identify patterns and trends to support informed decision-making 87 . Though the potential of AI/ML models is much greater, the present utilization of such DTs for sustainable construction is limited. Thus, future research needs to pay attention to their impact at full potential and how risk will be managed among participants in the construction value chain.

The circular economy is an emerging trend in sustainability in construction and would benefit immensely from the application of DT. There is a need to develop digital tools and frameworks that support the principles of the circular economy and material optimization 88 . This includes exploring methods for tracking and managing material flows, assessing the environmental impact of material choices, and optimizing material usage throughout the construction lifecycle 89 . Present research in such areas is still nascent.

An obvious and reoccurring problem in sustainability research is long-term performance and assessment 90 . Despite the application of DTs for sustainable construction, certain inherent challenges such as system resilience and adaptability persist. Therefore, future research may focus on the extended performance and resilience of sustainable construction projects supported by DTs. This could include studying the durability and adaptability of sustainable alternatives, evaluating the performance of digital monitoring systems over extended periods, and exploring the impact of climate change and other external factors on sustainability outcomes.

Studies that look into knowledge-sharing mechanisms and collaboration among stakeholders are crucial and should be promoted. As suggested by Balasubramanian et al. 91 , future research is needed to identify effective mechanisms for sharing best practices, case studies, and lessons learned in the application of DTs for construction sustainability. This can facilitate collective learning, foster innovation, and accelerate the adoption of sustainable practices.

Implications and conclusions

This study provides an overview of current applications of DTs in promoting construction sustainability and highlights opportunities for future research and innovation. It does so by adopting a systematic literature review and content analysis to identify DTs used in relation to construction sustainability. The findings reveal BIM, IoT, and big data to have become prominent technologies over the past 5 years, with digital twins and smart robotics emerging trends in DTs for construction sustainability. The major application areas of the identified DTs are integration and collaboration; optimization, simulation, and decision-making; monitoring and control; and training. Among these application areas, DTs have been extensively researched in optimization and monitoring construction infrastructure for sustainable outcomes. The study also identifies challenges associated with DTs for construction sustainability. Key among these are technical issues of data accuracy, security, and confidence; behavioral and cultural challenges such as resistance to change among stakeholders; and financial barriers due to the high cost of implementation.

The study’s contribution lies in the provision of a holistic perspective on DTs for construction sustainability across the entire construction lifecycle. Its theoretical contribution to the sustainable construction technologies framework is to identify gaps in the existing literature and propose new directions to enable efficient deployment and implementation. It also advances knowledge of how DTs can be applied in different construction scenarios to achieve sustainable outcomes. For industry and practice, the study provides insights into challenges faced in deploying DTs for construction sustainability, enabling practitioners to anticipate and manage risks ahead of implementation. Policymakers can be informed of the landscape of DTs and their application at various stages of construction. This can guide the development of tailored policies and regulations on the efficient advancement of DTs for achieving sustainability in the industry.

Despite these contributions, the study has a few limitations. The analysis is limited to a dataset obtained only from journals in the Web of Science (WoS) database, while the selection criteria and focus on only technical articles present some limitations. While these limitations present opportunities for future research to expand the study’s findings, further studies could also examine the evolution of DTs in the built environment and their connections with sustainable development.

Bibliographic materials collection and processing

Building on the practice of conducting literature reviews within the field of construction research 75 , 92 , this study seeks to elucidate the intersections of DT and construction sustainability through a systematic literature review (SLR), designed to ensure an objective and replicable synthesis of existing research 93 . Such a structured approach mitigates the reliance on simplistic judgment calls, curtails the incidence of subjective inclinations and errors, and upholds the integrity of scholarly research 94 .

The SLR uses the consolidated steps shown in Fig. 5 95 , 96 . First, it defines research objectives and conceptual boundaries to ensure a focused review; specifically, it targets the current and emergent trends of DTs in construction sustainability. Concurrently, conceptual boundaries are defined to delineate the scope of ‘digital technologies’, ‘sustainability’, and the ‘construction industry’. This dual step guarantees that the literature review remains focused and relevant. The second step involves a comprehensive search strategy and its execution. It encompasses selecting a suitable database, which, considering the nascent and interdisciplinary nature of the field, must be expansive. The WoS is apt for this purpose, encompassing a diverse range of scholarly works, including journal articles, conference proceedings, and more 97 . We use the WoS Core Collection, including SCl, SCI-Expanded, SSCl, A&HCI, and ESCI indices. Given the evolving terminology within DTs and sustainability in construction, a detailed search string with diverse terms is formulated and applied to the WoS database. The search is temporally bound to include articles published up to October 2023, ensuring contemporary relevance. It yields 790 articles for further processing. Subsequently, a manual exclusion process is applied, where articles are meticulously screened against predefined criteria. For instance, non-English papers, review articles, and studies that do not synergize sustainability with DT are excluded. A special plan of our SLR is the discussion of excluded papers, where an independent initial assessment by two researchers with at least 7 years of research experience is followed by a mutual discussion to reach a consensus on each paper’s exclusion. This phase ultimately narrowed down the selection to 72 articles. Following this, an independent data encoding and comparative analysis is conducted. To ensure the integrity and impartiality of data extraction, the two researchers independently read articles thoroughly and encoded data from each study. This data encompasses a variety of details, such as bibliographic information, methodologies, DTs examined, stages of concern, and their sustainability implications in construction. The independently derived datasets are compared to resolve discrepancies and to build a consensus on the themes and findings. This comparison fosters a rigorous synthesis of the literature, ensuring that the results are replicable and verifiable. Finally, an analytical synthesis is performed to summarize the current and potential future state of DT in construction sustainability.

The review process follows a systematic approach.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Barbosa, F. et al. Reinventing Construction through a Productivity Revolution (McKinsey Global Institute, 2017).

Zhang, A., Yang, J. & Wang, F. Application and enabling technologies of digital twin in operation and maintenance stage of the AEC industry: a literature review. J. Build. Eng. 80 , 107859 (2023).

Article   Google Scholar  

Wang, J., Li, Z. & Tam, V. W. Critical factors in effective construction waste minimization at the design stage: a Shenzhen case study, China. Resour. Conserv. Recycl. 82 , 1–7 (2014).

Bao, Z., Laovisutthichai, V., Tan, T., Wang, Q. & Lu, W. Design for manufacture and assembly (DfMA) enablers for offsite interior design and construction. Build. Res. Inf. 50 , 325–338 (2022).

Sánchez-Garrido, A. J., Navarro, I. J. & Yepes, V. Multi-criteria decision-making applied to the sustainability of building structures based on modern methods of construction. J. Cleaner Prod. 330 , 129724 (2022).

Beccali, M., Bonomolo, M., Ciulla, G., Galatioto, A. & Brano, V. L. Improvement of energy efficiency and quality of street lighting in South Italy as an action of Sustainable Energy Action Plans. The case study of Comiso (RG). Energy 92 , 394–408 (2015).

Blengini, G. A. Life cycle of buildings, demolition and recycling potential: a case study in Turin, Italy. Build. Environ. 44 , 319–330 (2009).

Bao, Z. & Lu, W. A decision-support framework for planning construction waste recycling: a case study of Shenzhen, China. J. Clean. Prod. 309 , 127449 (2021).

Bao, Z., Lee, W. M. & Lu, W. Implementing on-site construction waste recycling in Hong Kong: barriers and facilitators. Sci. Total Environ. 747 , 141091 (2020).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Lu, W. et al. Estimating construction waste generation in the Greater Bay Area, China using machine learning. Waste Manag. 134 , 78–88 (2021).

Article   PubMed   Google Scholar  

Sev, A. How can the construction industry contribute to sustainable development? A conceptual framework. Sustain. Dev. 17 , 161–173 (2009).

Lima, L., Trindade, E., Alencar, L., Alencar, M. & Silva, L. Sustainability in the construction industry: a systematic review of the literature. J. Clean. Prod. 289 , 125730 (2021).

Vinuesa, R. et al. The role of artificial intelligence in achieving the Sustainable Development Goals. Nat. Commun. 11 , 1–10 (2020).

Kuhlman, T. & Farrington, J. What is sustainability? Sustainability 2 , 3436–3448 (2010).

Shelbourn, M. et al. Managing knowledge in the context of sustainable construction. J. Inf. Technol. Constr. 11 , 57–71 (2006).

Google Scholar  

Zavadskas, E. K., Šaparauskas, J. & Antucheviciene, J. Sustainability in construction engineering. Sustainability 10 , 2236 (2018).

Jin, R., Zou, Y., Gidado, K., Ashton, P. & Painting, N. Scientometric analysis of BIM-based research in construction engineering and management. Eng. Constr. Archit. Manag. 26 , 1750–1776 (2019).

Gnecco, V. M., Vittori, F. & Pisello, A. L. Digital twins for decoding human-building interaction in multi-domain test-rooms for environmental comfort and energy saving via graph representation. Energy Build. 279 , 112652 (2023).

Wong, J. K. W. & Zhou, J. Enhancing environmental sustainability over building life cycles through green BIM: aA review. Autom. Constr. 57 , 156–165 (2015).

Gan, V. J. et al. Holistic BIM framework for sustainable low carbon design of high-rise buildings. J. Clean. Prod. 195 , 1091–1104 (2018).

Mirpanahi, M. V. & Noorzai, E. Modeling the relationship between critical BIM attributes and environmental sustainability criteria using PLS-SEM technique. J. Archit. Eng. 27 , 04021037 (2021).

Motalebi, M., Rashidi, A. & Nasiri, M. M. Optimization and BIM-based lifecycle assessment integration for energy efficiency retrofit of buildings. J. Build. Eng. 49 , 104022 (2022).

Hajirasouli, A., Banihashemi, S., Drogemuller, R., Fazeli, A. & Mohandes, S. R. Augmented reality in design and construction: thematic analysis and conceptual frameworks. Constr. Innov. 22 , 412–443 (2022).

Allam, Z., Sharifi, A., Bibri, S. E., Jones, D. S. & Krogstie, J. The metaverse as a virtual form of smart cities: opportunities and challenges for environmental, economic, and social sustainability in urban futures. Smart Cities 5 , 771–801 (2022).

Buonamici, F., Carfagni, M., Furferi, R., Volpe, Y. & Governi, L. Generative design: an explorative study. Comput.-Aided Des. Appl. 18 , 144–155 (2020).

Alsakka, F. et al. Generative design for more economical and environmentally sustainable reinforced concrete structures. J. Clean. Prod. 387 , 135829 (2023).

Caldas, L. Generation of energy-efficient architecture solutions applying GENE_ARCH: an evolution-based generative design system. Adv. Eng. Inform. 22 , 59–70 (2008).

Xu, J., Lou, J., Lu, W., Wu, L. & Chen, C. Ensuring construction material provenance using Internet of Things and blockchain: learning from the food industry. J. Ind. Inf. Integr. 33 , 100455 (2023).

Lou, J. & Lu, W. Construction information authentication and integrity using blockchain-oriented watermarking techniques. Autom. Constr. 143 , 104570 (2022).

Salmerón-Manzano, E. & Manzano-Agugliaro, F. The role of smart contracts in sustainability: worldwide research trends. Sustainability 11 , 3049 (2019).

Li, J. & Kassem, M. Applications of distributed ledger technology (DLT) and blockchain-enabled smart contracts in construction. Autom. Constr. 132 , 103955 (2021).

Li, X. et al. Blockchain-enabled IoT-BIM platform for supply chain management in modular construction. J. Constr. Eng. Manag. 148 , 04021195 (2022).

Xu, J., Lu, W., Wu, L., Lou, J. & Li, X. Balancing privacy and occupational safety and health in construction: a blockchain-enabled P-OSH deployment framework. Saf. Sci. 154 , 105860 (2022).

Zhao, R., Chen, Z. & Xue, F. A blockchain 3.0 paradigm for digital twins in construction project management. Autom. Constr. 145 , 104645 (2023).

Rao, A. S. et al. Real-time monitoring of construction sites: Sensors, methods, and applications. Automation in Construction 136 , 104099 (2022).

Lu, W., Lou, J. & Wu, L. Combining smart construction objects-enabled blockchain oracles and signature techniques to ensure information authentication and integrity in construction. J. Comput. Civil Eng. 37 , 04023031 (2023).

Sajjad, M. et al. Evaluation of the success of industry 4.0 digitalization practices for sustainable construction management: Chinese construction industry. Buildings 13 , 1668 (2023).

Tao, X., Mao, C., Xie, F., Liu, G. & Xu, P. Greenhouse gas emission monitoring system for manufacturing prefabricated components. Autom. Constr. 93 , 361–374 (2018).

Zhao, R. et al. Comparison of BIM collaboration paradigms for digital twin readiness: centralized files, decentralized clouds and distributed blockchains. In Proc. Conference on CIB W78 (eds Kubicki, S. & Rezgui, Y.). 11–15 (International Council for Research and Innovation in Building and Construction (CIB), 2021).

Long, W., Bao, Z., Chen, K., Ng, S. T. & Wuni, I. Y. Developing an integrative framework for digital twin applications in the building construction industry: a systematic literature review. Adv. Eng. Inform. 59 , 102346 (2024).

Opoku, D. G. J., Perera, S., Osei-Kyei, R. & Rashidi, M. Digital twin application in the construction industry: a literature review. J. Build. Eng. 40 , 102726 (2021).

Hammad, A. W., da Costa, B. B., Soares, C. A. & Haddad, A. N. The use of unmanned aerial vehicles for dynamic site layout planning in large-scale construction projects. Buildings 11 , 602 (2021).

Wu, M., Lin, J. R. & Zhang, X. H. How human-robot collaboration impacts construction productivity: an agent-based multi-fidelity modeling approach. Adv. Eng. Inform. 52 , 101589 (2022).

Villani, V., Pini, F., Leali, F. & Secchi, C. Survey on human–robot collaboration in industrial settings: safety, intuitive interfaces and applications. Mechatronics 55 , 248–266 (2018).

Halder, S. & Afsari, K. Robots in inspection and monitoring of buildings and infrastructure: a systematic review. Appl. Sci. 13 , 2304 (2023).

Article   CAS   Google Scholar  

Lu, Q., Xie, X., Parlikad, A. K., Schooling, J. M. & Konstantinou, E. Moving from building information models to digital twins for operation and maintenance. Proc. Institution of Civil Engineers-Smart Infrastructure and Construction. 174 , 46–56 (2020).

Yitmen, I., Alizadehsalehi, S., Akıner, İ. & Akıner, M. E. An adapted model of cognitive digital twins for building lifecycle management. Appl. Sci. 11 , 4276 (2021).

Petri, I., Rezgui, Y., Ghoroghi, A. & Alzahrani, A. Digital twins for performance management in the built environment. J. Ind. Inf. Integr. 33 , 100445 (2023).

Chen, J., Lu, W. & Lou, J. Automatic concrete defect detection and reconstruction by aligning aerial images onto semantic‐rich building information model. Comput.‐Aided Civil and Infrastruct. Eng. 38 , 1079–1098 (2023).

Wang, C. et al. Integrated sensor data processing for occupancy detection in residential buildings. Energy Build. 237 , 110810 (2021).

Floris, A., Porcu, S., Girau, R. & Atzori, L. An IoT-based smart building solution for indoor environment management and occupants prediction. Energies 14 , 2959 (2021).

Nesa, N. & Banerjee, I. IoT-based sensor data fusion for occupancy sensing using Dempster–Shafer evidence theory for smart buildings. IEEE Internet Things J. 4 , 1563–1570 (2017).

Tien, P. W., Wei, S., Darkwa, J., Wood, C. & Calautit, J. K. Machine learning and deep learning methods for enhancing building energy efficiency and indoor environmental quality—a review. Energy AI 10 , 100198 (2022).

Sanzana, M. R., Maul, T., Wong, J. Y., Abdulrazic, M. O. M. & Yip, C. C. Application of deep learning in facility management and maintenance for heating, ventilation, and air conditioning. Autom. Constr. 141 , 104445 (2022).

Yuan, L., Lu, W., Xue, F. & Li, M. Building feature‐based machine learning regression to quantify urban material stocks: a Hong Kong study. J. Ind. Ecol. 27 , 336–349 (2023).

Lu, W., Long, W. & Yuan, L. A machine learning regression approach for pre-renovation construction waste auditing. J. Clean. Prod. 397 , 136596 (2023).

Lu, W., Chen, J. & Xue, F. Using computer vision to recognize composition of construction waste mixtures: a semantic segmentation approach. Resour. Conserv. Recycl. 178 , 106022 (2022).

Chen, J., Lu, W. & Xue, F. “Looking beneath the surface”: a visual-physical feature hybrid approach for unattended gauging of construction waste composition. J. Environ. Manag. 286 , 112233 (2021).

Lublasser, E., Hildebrand, L., Vollpracht, A. & Brell-Cokcan, S. Robot assisted deconstruction of multi-layered façade constructions on the example of external thermal insulation composite systems. Constr. Robot. 1 , 39–47 (2017).

Lee, S., Pan, W., Linner, T. & Bock, T. A framework for robot assisted deconstruction: process, sub-systems and modeling. In 32 nd ISARC: Proc. International Symposium on Automation and Robotics in Construction (ed. Fraser, S. J). (International Association for Automation and Robotics in Construction (IAARC), 2015).

Wu, L., Lu, W., Peng, Z. & Webster, C. A blockchain non-fungible token-enabled ‘passport’ for construction waste material cross-jurisdictional trading. Autom. Constr. 149 , 104783 (2023).

Li, L. et al. Sustainability assessment of intelligent manufacturing supported by digital twin. IEEE Access 8 , 174988–175008 (2020).

Akbarzadeh, O. et al. Heating–cooling monitoring and power consumption forecasting using LSTM for energy-efficient smart management of buildings: a computational intelligence solution for smart homes. Tsinghua Sci.Technol. 29 , 143–157 (2023).

Elnour, M. et al. Performance and energy optimization of building automation and management systems: towards smart sustainable carbon-neutral sports facilities. Renew. Sustain. Energy Rev. 162 , 112401 (2022).

Ababio, B. K., Lu, W. & Ghansah, F. A. Transitioning from green to circular procurement in developing countries: a conceptual framework for Ghana’s construction sector. Build. Res. Inf. 51 , 798–815 (2023).

Oke, A. E., Kineber, A. F., Alsolami, B. & Kingsley, C. Adoption of cloud computing tools for sustainable construction: a structural equation modeling approach. J. Facil. Manag. 21 , 334–351 (2023).

Charef, R. & Lu, W. Factor dynamics to facilitate circular economy adoption in construction. J. Clean. Prod. 319 , 128639 (2021).

Kavitha, R. J. et al. Improved Harris Hawks optimization with hybrid deep learning based heating and cooling load prediction on residential buildings. Chemosphere 309 , 136525 (2022).

Article   CAS   PubMed   Google Scholar  

Lou, J., Wang, B., Yuan, Z. & Lu, W. Willingness to pay for well-being housing attributes driven by design layout: evidence from Hong Kong. Build. Environ. 251 , 111227 (2024).

Qiu, J. et al. Design of an evaluation system for disruptive technologies to benefit smart cities. Sustainability 15 , 9109 (2023).

Bay, E., Martinez-Molina, A. & Dupont, W. A. Assessment of natural ventilation strategies in historical buildings in a hot and humid climate using energy and CFD simulations. J. Build. Eng. 51 , 104287 (2022).

Zhang, E., He, X. & Xiao, P. Does smart city construction decrease urban carbon emission intensity? Evidence from a difference-in-difference estimation in China. Sustainability 14 , 16097 (2022).

Wei, Y., Lei, Z. & Altaf, S. An off-site construction digital twin assessment framework using wood panelized construction as a case study. Buildings 12 , 566 (2022).

Chen, Y., Huang, D., Liu, Z., Osmani, M. & Demian, P. Construction 4.0, Industry 4.0, and building information modeling (BIM) for sustainable building development within the smart city. Sustainability 14 , 10028 (2022).

Qi, B., Razkenari, M., Costin, A., Kibert, C. & Fu, M. A systematic review of emerging technologies in industrialized construction. J. Build. Eng. 39 , 102265 (2021).

Petrov, I. & Hakimov, A. Digital technologies in construction monitoring and construction control. In IOP Conference Series: Materials Science and Engineering , (ed. Sergeev, V.) 497, 012016 (IOP Publishing, 2019).

Yevu, S. K., Ann, T. W. & Darko, A. Digitalization of construction supply chain and procurement in the built environment: emerging technologies and opportunities for sustainable processes. J. Clean. Prod. 322 , 129093 (2021).

Meng, Q. et al. A review of integrated applications of BIM and related technologies in whole building life cycle. Eng. Constr. Archit. Manag. 27 , 1647–1677 (2020).

Malagnino, A. et al. Building information modeling and Internet of Things integration for smart and sustainable environments: a review. J. Clean. Prod. 312 , 127716 (2021).

Wang, M., Wang, C. C., Sepasgozar, S. & Zlatanova, S. A systematic review of digital technology adoption in off-site construction: current status and future direction towards industry 4.0. Buildings 10 , 204 (2020).

Love, P. E. & Matthews, J. The ‘how’ of benefits management for digital technology: from engineering to asset management. Autom. Constr. 107 , 102930 (2019).

Liao, L. & Teo, E. A. L. Managing critical drivers for building information modeling implementation in the Singapore construction industry: an organizational change perspective. Int. J. Constr. Manag. 19 , 240–256 (2019).

Durdyev, S., Ismail, S., Ihtiyar, A., Bakar, N. F. S. A. & Darko, A. A partial least squares structural equation modeling (PLS-SEM) of barriers to sustainable construction in Malaysia. J. Clean. Prod. 204 , 564–572 (2018).

Das, M., Luo, H. & Cheng, J. C. Securing interim payments in construction projects through a blockchain-based framework. Autom. Constr. 118 , 103284 (2020).

Aghimien, D. et al. Barriers to digital technology deployment in value management practice. Buildings 12 , 731 (2022).

Moshood, T. D., Adeleke, A. Q., Nawanir, G., Ajibike, W. A. & Shittu, R. A. Emerging challenges and sustainability of industry 4.0 era in the Malaysian construction industry. Emerg. Chall. Sustain. Ind. 4 , 1627–1634 (2020).

Pan, Y. & Zhang, L. Roles of artificial intelligence in construction engineering and management: a critical review and future trends. Autom. Constr. 122 , 103517 (2021).

Antwi-Afari, P. et al. Enhancing life cycle assessment for circular economy measurement of different case scenarios of modular steel slab. Build. Environ. 239 , 110411 (2023).

Bao, Z., Lu, W. & Hao, J. Tackling the “last mile” problem in renovation waste management: a case study in China. Sci. Total Environ. 790 , 148261 (2021).

Zhang, Y. et al. A survey of the status and challenges of green building development in various countries. Sustainability 11 , 5385 (2019).

Balasubramanian, S., Shukla, V., Islam, N. & Manghat, S. Construction industry 4.0 and sustainability: an enabling framework. IEEE Trans. Eng. Manag. 71 , 1–19 (2021).

Ibem, E. O. & Laryea, S. Survey of digital technologies in procurement of construction projects. Autom. Constr. 46 , 11–21 (2014).

Tranfield, D., Denyer, D. & Smart, P. Towards a methodology for developing evidence‐informed management knowledge by means of systematic review. Br. J. Manag. 14 , 207–222 (2003).

Petticrew, M. & Roberts, H. Systematic Reviews in the Social Sciences: A Practical Guide (John Wiley & Sons, 2008).

Holzmann, P. & Gregori, P. The promise of digital technologies for sustainable entrepreneurship: a systematic literature review and research agenda. Int. J. Inf. Manag. 68 , 102593 (2023).

Okoli, C. A guide to conducting a standalone systematic literature review. Commun. Assoc. Inf. Syst. 37 , 43 (2015).

Gusenbauer, M. & Haddaway, N. R. Which academic search systems are suitable for systematic reviews or meta‐analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources. Res. Synth. Methods 11 , 181–217 (2020).

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Department of Real Estate and Construction, Faculty of Architecture, The University of Hong Kong, Pokfulam, Hong Kong

Weisheng Lu, Jinfeng Lou, Benjamin Kwaku Ababio & Fan Xue

Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong

Ray Y. Zhong

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Zhikang Bao

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W.L., J.L., and B.A. conducted the review and wrote the manuscript. R.Z., Z.B., X.L., and F.X. made suggestions and revised the manuscript. All authors read and approved the final manuscript.

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Lu, W., Lou, J., Ababio, B.K. et al. Digital technologies for construction sustainability: Status quo, challenges, and future prospects. npj Mater. Sustain. 2 , 10 (2024). https://doi.org/10.1038/s44296-024-00010-2

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The New Aesthetic: Technology & Sustainability in Architecture

Is the Future of Architecture Sustainable Technology?

Welcome to the future of architecture, where sustainability and technology will rule supremely. As we work to create a built environment that is more reliable and efficient, these two crucial areas are influencing how we design and develop buildings. Their intersection is becoming more and more noticeable. On the one hand, the industry is being revolutionised by technological developments like 3D printing and smart building technologies, which make it simpler and more cost-effective to create original designs. On the other hand, as architects work to design buildings that are not only environmentally friendly but also socially and economically viable, sustainability is rising to the top of the list.

Technological advancements | New Aesthetic

The world of architecture, as people know it, is changing due to technology. These technological developments, which include 3D printing, virtual reality , and artificial intelligence, are revolutionising how architects create buildings. Architects can automate various previously manual tasks using machine learning, facilitating and accelerating the design-creation process. Technology has created an immersive experience that enables architects and clients to visualize the building before it is constructed. In contrast, 3D printing enables architects to create complex shapes and previously impossible structures. The use of these technologies will undoubtedly influence the direction of architecture and result in the construction of buildings that are more creative and sustainable than ever.

Smart and Sustainable

Building design and construction must take sustainability into account. Architects and builders are prioritizing green building techniques that lessen the impact on the environment, increasing their focus as climate concerns come to the fore. Incorporating renewable energy sources like solar systems and materials. Wind power is part of this, as is the use of energy-efficient systems and materials. By including features like natural light and clean air, green buildings also take their occupant’s health into account. Sustainability will be even more crucial to the future of architecture as the world struggles to reduce carbon emissions and protect the environment.

Technological developments for Sustainability

Architectural sustainability goals can be attained in large part through technological advancements. By managing lighting, heating, and cooling systems, building automation systems, and the Internet of Things (IoT) can help to maximise energy usage. Geothermal heating and other cutting-edge building techniques and materials can also aid in constructing energy-efficient and sustainable structures. Smart technologies enable architects to monitor and analyse building performance data and adjust over time to increase efficiency and sustainability. Both environmentally responsible and financially viable buildings will be made possible by integrating technology into sustainable design.

Case Study 1: Citicape House in London | New Aesthetic

As part of its most recent project, Cityscape House, a reputable architecture firm Shephard Robson proposed constructing the largest living wall in Europe . The building, situated in a busy area of the City of London, will have a creative façade of more than 400,000 plants that will serve as a natural air filter and produce six tonnes of oxygen. Additionally, the living wall will reduce the temperature around the building by three to five degrees Celsius, capturing more than eight tonnes of CO2 from the air annually and reducing the urban heat island effect. This undertaking is proof of the effectiveness of sustainable design and innovation.

Case Study 2: The Crystal in London

Have you heard of the Crystal? It’s a truly remarkable structure located in London that emphasises sustainability and the use of technology to lessen its environmental impact. Visitors can find out more about solar power and rainwater collection systems and other cool sustainable technologies at The Crystal’ s exhibition space. The Crystal not only uses these technologies, but it also incorporates them all into the structure itself! Rainwater is collected and used for things like flushing toilets, and solar panels on the roof produce electricity. Even the lighting can be adjusted intelligently based on how much natural light is present in the structure. All of these innovations make The Crystal a more sustainable structure, which is crucial in the modern world. Additionally, seeing all of these technologies in action is just really cool. You should check out The Crystal if you’re ever in London; it’s worth a trip!

The Future of Architecture

Future developments in technology and sustainability suggest that architecture will continue to change and advance positively. Building design and construction will continue to be influenced by new technologies and materials, resulting in more energy-efficient and environmentally friendly structures. With the development of AI, 3D printing, and virtual reality , architects now have new resources to produce ground-breaking designs and speed up the building process. Architecture’s sustainability objectives will be helped by the Internet of Things (IoT), advanced materials, and building automation systems . As people become more conscious of buildings’ effects on the environment, sustainability will play a crucial part in the future of architecture. Green construction, which prioritises energy efficiency and uses renewable resources, will no longer be the exception. There will be a rise in the popularity of ideas like net-zero buildings, which produce as much energy as they use. 

The demand for affordable, sustainable housing will increase as the world’s population expands. A wider range of people will need to be able to access and afford the buildings that architects design, in addition to being environmentally friendly. The future of architecture is exciting and brimming with opportunities for sustainable development and technological advancement. Architects can design structures that are not only practical and attractive but also environmentally responsible by embracing new technologies and placing a high priority on sustainability.

Conclusion | New Aesthetic

As the article has highlighted, the future of architecture lies at the confluence of two crucial spheres: technological advancements and sustainability. The potential for creative solutions is enormous, from green walls that give life to concrete jungles to smart buildings that use solar energy . Future architecture will be more intelligent, environmentally friendly, and sustainably constructed than ever.

Our problems—from rapid urbanization to rising temperatures need bold and original answers. We can design a built environment that is both beautiful and sustainable by investigating the possibilities at the intersection of technology and sustainability. Let’s work toward a future where environmentally friendly architecture is the rule rather than the exception, whether designing a new structure or remodelling an existing one. We have a special opportunity to create a better, more sustainable world for present and future generations as we construct the cities of the future.

Citicape House (no date) New London Architecture . Available at: https://nla.london/projects/citicape-house (Accessed: April 30, 2023). 

Hernández, D. (2014) Jockey club innovation tower / zaha hadid architects , ArchDaily . ArchDaily. Available at: https://www.archdaily.com/505374/jockey-club-innovation-tower-zaha-hadid-architects?ad_medium=gallery (Accessed: April 30, 2023). 

Longzijun, ~ (2022) Architecture: Jockey club innovation tower (Zaha Hadid) , artjouer . Available at: https://artjouer.wordpress.com/2021/05/11/innovation-tower/ (Accessed: April 30, 2023). 

O’Malley, A. (2023) The architecture of the future: 2022 research , PlanRadar . Available at: https://www.planradar.com/gb/the-architecture-of-the-future-research/ (Accessed: April 30, 2023). 

Patel, Y. (2020) 3DReid’s Co-op HQ achieves BREEAM outstanding , The Architects’ Journal . Available at: https://www.architectsjournal.co.uk/archive/3dreids-co-op-hq-achieves-breeam-outstanding (Accessed: April 30, 2023). 

Powerhouse brattørkaia (no date) Powerhouse Brattørkaia – Snøhetta . Available at: https://www.snohetta.com/projects/powerhouse-brattorkaia (Accessed: April 30, 2023). 

Sánchez, D. (2012) The crystal / Wilkinson Eyre Architects , ArchDaily . ArchDaily. Available at: https://www.archdaily.com/275111/the-crystal-wilkinson-eyre-architects?ad_medium=gallery (Accessed: April 30, 2023). 

Sambiasi, S. (2019) 7 architectural considerations that are Shaping Future Cities , ArchDaily . ArchDaily. Available at: https://www.archdaily.com/927262/7-architectural-considerations-that-are-shaping-future-cities (Accessed: April 30, 2023). 

Top 7 sustainable architecture and design innovations from 2019 (2019) Springwise . Available at: https://www.springwise.com/innovation-snapshot/architecture-design-sustainability-top-7-2019/ (Accessed: April 30, 2023). 

Tostevin, P. et al. (2021) 5 of the world’s most sustainable buildings , Savills Impacts . Available at: https://www.savills.com/impacts/environment/5-of-the-worlds-most-sustainable-buildings.html (Accessed: April 30, 2023). 

Shreya is a Mumbai-based architect currently pursuing her Masters in Architectural History and Conservation at Oxford. A book lover and Potterhead, coming to Oxford was like a dream come true. With a passion for movies with stunning cinematography, like Woody Allen's Manhattan, listening to music, and capturing the beauty of charming facades, she brings a unique perspective to architecture. Keep an eye out for her fascinating explorations of architecture and the captivating stories that she uncovers.

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Making the Business Case for Sustainability

• 13 Apr 2021

Once thought to be opposing goals, sustainability and financial success now go hand-in-hand for many businesses. Some, however, may be skeptical of the claim that a business can do well by doing good. How can you make the business case for sustainable practices to skeptical decision-makers in your organization?

Here are key terms to use to frame your discussion, several ways sustainable business practices can pay off financially, and tools to leverage when pitching sustainability to stakeholders.

Access your free e-book today.

Corporate Social Responsibility and the Triple Bottom Line

Corporate social responsibility (CSR) is a business model in which for-profit companies seek to create social and environmental benefits while pursuing organizational goals. Whereas companies typically focus on the bottom line, or generating profit, socially responsible corporations focus on the triple bottom line.

The triple bottom line can be described as the “three Ps”: people, the planet, and profit. In other words, in addition to striving to succeed financially, socially responsible companies commit to measuring success through their impact on people—employees, customers, and society at large—and the environment.

It’s important to not think of sustainability initiatives as a financial trade-off, but rather, as a wise financial strategy.

“There’s good reason to believe that solving the world’s problems presents trillions of dollars’ worth of economic opportunity,” says Harvard Business School Professor Rebecca Henderson in the online course Sustainable Business Strategy .

Leading with purpose can positively impact both the planet and your business’s financials. Here are eight benefits of a sustainable business strategy you can use when making the case to your internal team.

8 Benefits of Sustainability in Business

1. drives internal innovation.

Making the switch to sustainable business practices provides an opportunity for new, innovative ideas to grow. Consider this your chance to question the way your organization operates. Are there inefficiencies in your production process? Are there alternatives to how you currently source production materials? What equipment or technology could make your internal processes and product delivery more energy efficient?

These types of questions reveal opportunities to save money on energy and reassess how ethically you source materials. They can also shake up your mindset of “this is how we’ve always done it” and prompt innovative ideas for new business opportunities.

Related: 23 Resources for Mobilizing Innovation in Your Organization

2. Improves Environmental and Supply Risk

Investing in more sustainable practices can pay off in the form of risk management. By using renewable resources—such as wind, water, and solar power—your company has greater security over its energy sources.

This can also offer financial benefits. For example, if your company switches from coal to clean energy, like ice cream company Ben & Jerry’s , you can avoid the hassle and cost when coal prices skyrocket.

3. Attracts and Retains Employees

Being a sustainable company can have a big impact on the talent you attract and retain. A recent survey conducted by clean energy company Swytch found that nearly 70 percent of employees report that their company’s strong sustainability program impacts their decision to stay with it long term.

The same survey reports that 75 percent of millennials—who will make up three-quarters of the workforce in five years—would take a decrease in salary if it meant working for an environmentally responsible company. Nearly 40 percent selected one job over another because of an organization’s sustainability practices.

Committing to sustainability puts your company’s values at the forefront, which can attract employees and job seekers who share those values. Hiring and retaining the right team can save your organization the time and money of having to rehire for multiple roles.

4. Expands Audience Reach and Builds Brand Loyalty

A focus on sustainability can not only help attract and keep the right employees, but build a broader, more loyal customer base.

Research in the Harvard Business Review shows that sustainable businesses see greater financial gains than their unsustainable counterparts. In addition, consumers’ motivation to buy from sustainable brands is on the rise. For instance, products with an on-package sustainability claim delivered nearly $114 billion in sales in 2019—a 29 percent increase from 2013—and products marketed as sustainable grew more than five times faster than those that weren’t.

Adopting sustainable practices and marketing appropriately can enable your business to reach new, sustainably-minded market segments while building brand loyalty among your customer base.

5. Reduces Production Costs

One of the simplest business cases for sustainability is that using fewer resources, or more sustainable ones, can decrease production costs.

Examining your supply chain, production process, and energy use at brick-and-mortar stores and office buildings can help identify places where cutting back on finite resources and switching to greener alternatives is a cheaper option.

“Some firms invest in sustainability because the business case is so glaringly obvious, they’d be foolish not to,” Henderson says in Sustainable Business Strategy.

6. Garners Positive Publicity

Another outcome of opting for sustainability is the positive publicity it can garner. Especially if it’s a divergence from your business’s previously established practices or industry standards, your switch to sustainability and investment in the environment can call for press releases and announcements.

Side effects of this positive publicity can be employee pride, sustainably-minded job applicants, and increased customer loyalty and referral rates.

7. Helps You Stand Out in a Competitive Market

In a competitive market, any way to differentiate your product and brand from your competitors is valuable. Sustainable business practices can be a positive way to stand out if your competitors haven’t adopted those practices themselves or match them if they’ve already made the switch to sustainability.

Calling back to research in the Harvard Business Review , consumers’ focus on brands’ sustainability practices is on the rise, and your business’s practices could be the sole reason consumers choose your product over your competitors’.

8. Sets the Industry Trend

Sustainability not only helps your company stand out against competitors but also influences their behaviors. If your organization is one of the first in its field to adopt sustainable practices, it could set your business apart as a trend-setting leader and prompt other companies to follow suit.

“The leaders, the firms who are driving real change and reaping the benefits of being first-movers are often as motivated by a driving desire to make a difference as they are by the wish to make money,” Henderson says in Sustainable Business Strategy.

If the sustainability trend continues, it could become the norm in your industry. When many corporations adopt sustainable practices, they have the potential to make a real impact on the world’s largest problems.

Tools for Pitching a Sustainable Business Strategy

When pitching sustainability to internal decision-makers, use the data, projections, and anecdotal evidence at your disposal. Here are a few tools to help you make your case.

1. Data Visualizations

Data visualizations are graphical representations of data. When making the case for sustainability, you may create a graph that shows the increasing prices of fossil fuels, a chart that shows consumer preferences for sustainable companies, or a visual forecast of what future revenue could look like if a piece of sustainable technology were purchased.

Some data visualization tools you can use are:

• Microsoft Excel & Power BI
• Google Charts
• Zoho Analytics
• Datawrapper

Visualizations are a clear, concise way to tell the story of why you should adopt a sustainable business strategy.

Related: Bad Data Visualization: 5 Examples of Misleading Data

2. Anticipated Return on Investment Formula

When advocating for specific sustainability projects or equipment purchases, it can be useful to calculate the anticipated return on investment (ROI) . Calculating the anticipated ROI shows internal stakeholders how much financial return the business can expect as a result of investing in the sustainable practices you’re proposing.

To calculate anticipated ROI, use the following formula:

ROI = (Net Profit / Cost of Investment) x 100

In project management, the formula is written similarly but with slightly different terms:

ROI = [(Financial Value - Project Cost) / Project Cost] x 100

3. Case Studies of Businesses with Successful Sustainability Initiatives

Real-world examples can go a long way when proposing new ideas. There are plenty of businesses that have successfully executed sustainability initiatives and put the triple bottom line at the forefront of their business strategies. A few examples include:

• Bank of America
• AstraZeneca
• Ben & Jerry’s
• Levi Strauss

Dig deeper into what made these firms’ efforts successful, and use that as fuel for your company’s strategy.

Furthering Your Sustainable Business Education

If you and your colleagues want a strong foundation for making the shift to sustainable business, consider taking Sustainable Business Strategy . The online course presents groundbreaking concepts using the HBS case method and asserts that sustainable capitalism has the power to influence the world’s most pressing challenges.

By bolstering your knowledge of the space, your organization could become one of the many success stories of those that create shared value from sustainable business practices.

Are you interested in leading your business to a more sustainable future? Explore our three-week online course Sustainable Business Strategy to become a purpose-driven leader.

About the Author

Sustainability for concrete production and construction

Innovative methods for reducing emissions during concrete production and construction work

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What opportunities are there to decarbonise the construction sector?

At the heart of the problem lies concrete, the second most widely used material on Earth, second only to water. In 2022, the total volume of cement (the key ingredient of concrete) produced worldwide amounted to an estimated 4.1 billion tons.

Concrete is everywhere. And the production of it contributes upwards of seven percent of global greenhouse gas emissions every year. The growing focus on carbon accounting and reporting requirements is putting the sector increasingly in the spotlight.

Are there more sustainable alternatives to concrete available?

While stakeholders agree it’s necessary, decarbonising the construction sector is challenging. Concrete is not an easy material to replicate and any material used for construction must behave like concrete.

There is not enough wood in the world to do the job of concrete, nor is it strong enough. And while some hope to substitute concrete for other materials such as plastic or glass, it is not that straightforward.

Project Output Examples

Can concrete production be decarbonised.

Our client, a professional services firm, wanted to understand if there were opportunities for supporting companies in the construction sector in their decarbonization journey.  

The project was split into two halves. First, we assessed 10 broad emerging technology categories and gauged their suitability as concrete substitutes and analysed 26 companies developing emerging technologies.

Secondly, we worked with specialists to build up a detailed picture of the concrete value chain, mapping the key points in the production process where carbon is generated.

After looking at existing tools, we identified areas where they could be improved for our client’s needs and created a new tool that mapped the concrete value chain. The goal was to ensure the tool was as flexible and bespoke as possible. It needed to include what goes into a concrete mix and all the transport and was customized to their clients.

Our custom tool generated nine possible use cases for our client and a further eight more with suggested enhanced functionalities in the future. In total, it created over 60 tunable parameters for bespoke modelling which generated quantitative results within +/-1% of existing tools and expanded functionality.

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Flying high to enable sustainable delivery, remote care

Press contact :.

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Five years ago, what began as three nervous Norwegians spotting each other across a study room has evolved into a drone company enabling sustainable deliveries, elder care, and more against a backdrop of unforgiving conditions. Lars Erik Fagernæs, Herman Øie Kolden, and Bernhard Paus Græsdal all attended the Norwegian University of Science and Technology, but their paths first crossed in the MIT Professional Education Advanced Study Program lounge in 2019, while they were apprehensive about their impending English exam. From there, they each pursued different tracks of study through the Advanced Study Program: Fagernæs studied computer science, Kolden took applied physics classes, and Græsdal, robotics. Months later, when the world shut down due to the Covid-19 pandemic, the trio’s professional trajectories intertwined. At the height of the pandemic in 2020, Fagernæs, Kolden, and Græsdal launched Aviant — a drone delivery service company. Aviant flew blood samples across Norway’s vast countryside to assist remote hospitals in diagnosing Covid. Today, their drones are delivering groceries, over-the-counter medicines, and takeout food to populations outside city centers.  Capitalizing on momentum The pandemic waned, but the need for medical sample delivery did not. Remote hospitals still require reliable and rapid sample transportation, which Aviant continues to supply through its commercial contracts. In 2021, instead of sticking with commercial-only deliveries, the Aviant founders decided to use their momentum to reach for the largest market within autonomous transportation: last-mile delivery. “Yes, you need a higher volume for the business case to make sense,” explains Fagernæs of the expansion. “Yes, it is a lot more risky, but if you make it, it’s such a big opportunity.” The Norwegian government and various venture capital firms backing Aviant agree that this risk was worth their investment. Aviant has secured millions in funding to explore the consumer market through its newest offering, Kyte .  To scale operations, work still needs to be done to ingratiate drone delivery to the general population. Emphasizing the environmental benefits of aerial versus traditional road deliveries, the founders say, may be the most compelling factors that propel drones to the mainstream. So far, Aviant has flown more than 30,000 kilometers, saving 4,440 kilograms of carbon dioxide that would have been emitted through traditional transportation methods. “It doesn’t make sense to use a two- to four-ton vehicle to transport one kilogram or two kilograms of sushi or medicine,” Fagernæs reasons. “You also have cars eroding the roads, you have a lot of car accidents. Not only do you remove the cars from roads by flying [deliveries] with drones, it’s also a lot more energy efficient.” Aviant’s competitors — among them Alphabet — are spurring Fagernæs and Kolden to further improve their nicknamed “Viking drones.” Designed to sustain Norway’s harsh winter conditions and high winds, Aviant drones are well-adapted to service remote areas across Europe and the United States, a market they hope to break into soon. The unmatched MIT work ethic Fagernæs and Kolden owe much to MIT: It’s where they met and hatched their company. After his time with the Advanced Study Program, Græsdal decided to return to MIT to pursue his doctorate. The professors and mentors they engaged with across the Institute were instrumental in getting Aviant off the ground. Fagernæs recalls the beginning stages of discovering the drones’ theoretical flying limit; however, he quickly ran into the hurdle that neither he nor his peers had experience deriving such data. At that moment, there was perhaps no better place on Earth to be. “We figured, OK, we’re at MIT, we might as well just ask someone.” Fagernæs started knocking on doors and was eventually pointed in the direction of Professor Mark Drela’s office.  “I remember meeting Mark. Very, very humble guy, just talking to me like ‘Lars, yes, this, I will help you out, read this book, look at this paper.’” It was only when Fagernæs met back up with Kolden and Græsdal that he realized he had asked elementary questions to one of the leading experts in aeronautical engineering, and he truly appreciated Drela’s patience and helpfulness. The trio also credit Professor Russ Tedrake as being an inspiration to their current careers. Additionally, the work ethic of their fellow Beavers inspires them to work hard to this day. “I was finishing an assignment, and I think I left the Strata Student Center at 5:30 [in the morning] and it was half-full,” Kolden remembers. “And that has really stuck with me. And even when we run Aviant now, we know that in order to succeed, you have to work really, really hard.” “I’m impressed with how much Aviant has accomplished in such a short time,” says Drela. “Introducing drones to a wider population is going to make large improvements in high-value and time-critical payload delivery, and at much lower costs than the current alternatives. I’m looking forward to seeing how Aviant grows in the next few years.”  “For the betterment of humankind” Drones are the future, and Kolden is proud that Aviant’s electric drones are setting a sustainable precedent. “We had the choice to use gasoline drones. It was very tempting, because they can fly 10 times farther if you just use gasoline. But we just came from MIT, we worked on climate-related problems. We just couldn’t look ourselves in the mirror if we used gasoline-driven drones. So, we chose to go for the electric path, and that’s now paid off.” In the age of automation and perceived diminishing human connections, Kolden did have a moment of doubt about whether drones were part of the dilemma. “Are we creating a dystopian society where my grandfather is just meeting a robot, saying, ‘Here is your food,’ and then flying off again?” Kolden asked himself. After deep conversations with industry experts, and considering the low birth rate and aging population in Norway, he now concludes that drones are part of the solution. “Drones are going to help out a lot and actually make it possible to take care of all people and give them food and medicine when there simply aren’t enough people to do it.” Fagernæs also takes to heart the section of the MIT mission where students are urged to “work wisely, creatively, and effectively for the betterment of humankind.” He says, “When we started the company, it was all about using drones to help out society. We started to fly during the Covid pandemic to improve the logistics of the health-care sector in Norway, where people weren’t being diagnosed for Covid because of lacking logistics.” “The story of the success of Lars Erik, Herman, and Aviant makes us proud of what we do at MIT Professional Education.” says Executive Director Bhaskar Pant . “Share MIT knowledge that leads people to be innovative, entrepreneurial, and above all pursue the MIT mission of working toward the betterment of humankind. Kyte is a shining example of that.”

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Open Access

Peer-reviewed

Research Article

Research on sustainable green building space design model integrating IoT technology

Roles Conceptualization, Formal analysis, Methodology, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected] , [email protected]

Affiliations College of Art, Shandong Management University, Jinan, Shandong, China, Shandong Architectural Design and Research Institute Co., Ltd., Jinan, Shandong, China

Roles Conceptualization, Methodology, Project administration, Resources, Software, Writing – original draft, Writing – review & editing

Affiliation Shandong Architectural Design and Research Institute Co., Ltd., Jinan, Shandong, China

• Yuchen Wang, 

• Published: April 29, 2024
• https://doi.org/10.1371/journal.pone.0298982
• Reader Comments

"How can the integration of Internet of Things (IoT) technology enhance the sustainability and efficiency of green building (G.B.) design?" is the central research question that this study attempts to answer. This investigation is important because it examines how green building and IoT technology can work together. It also provides important information about how to use contemporary technologies for environmental sustainability in the building sector. The paper examines a range of IoT applications in green buildings, focusing on this intersection. These applications include energy monitoring, occupant engagement, smart building automation, predictive maintenance, renewable energy integration, and data analytics for energy efficiency enhancements. The objective is to create a thorough and sustainable model for designing green building spaces that successfully incorporates IoT, offering industry professionals cutting-edge solutions and practical advice. The study uses a mixed-methods approach, integrating quantitative data analysis with qualitative case studies and literature reviews. It evaluates how IoT can improve energy management, indoor environmental quality, and resource optimization in diverse geographic contexts. The findings show that there has been a noticeable improvement in waste reduction, energy and water efficiency, and the upkeep of high-quality indoor environments after IoT integration. This study fills a major gap in the literature by offering a comprehensive model for IoT integration in green building design, which indicates its impact. This model positions IoT as a critical element in advancing sustainable urban development and offers a ground-breaking framework for the practical application of IoT in sustainable building practices. It also emphasizes the need for customized IoT solutions in green buildings. The paper identifies future research directions, including the investigation of advanced IoT applications in renewable energy and the evaluation of IoT’s impact on occupant behavior and well-being, along with addressing cybersecurity concerns. It acknowledges the challenges associated with IoT implementation, such as the initial costs and specialized skills needed.

Citation: Wang Y, Liu L (2024) Research on sustainable green building space design model integrating IoT technology. PLoS ONE 19(4): e0298982. https://doi.org/10.1371/journal.pone.0298982

Editor: Sathishkumar Veerappampalayam Easwaramoorthy, Sunway University, MALAYSIA

Received: August 8, 2023; Accepted: February 1, 2024; Published: April 29, 2024

Copyright: © 2024 Wang, Liu. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

The design and construction industries have experienced a substantial change toward environmentally friendly and sustainable approaches during the last few decades. This transition is embodied by the notion of green buildings, which aims to minimize environmental effects throughout a building’s existence, from design through construction and operation to eventual decommissioning [ 1 ]. Green Building (G.B.) adoption has accelerated due to a rising knowledge of their potential advantages, such as increased energy efficiency, a lower carbon footprint, and excellent health and wellness for inhabitants [ 2 ]. Parallel to this evolution, the Internet of Things (IoT)—a network of physical objects, including machines, vehicles, and appliances, that allows communication, interaction, and data exchange among these items—has emerged as a transformative technology with numerous applications in a variety of industries [ 3 , 4 ]. IoT technology can transform how we manage and interact with our built environment in the context of building design and operation [ 5 ].

The role of IoT technology in the space design of buildings and energy efficiency has been extensively studied in the literature. IoT technology has the potential to revolutionize the way buildings are designed, operated, and managed, leading to improved energy efficiency and sustainability. From the most recent investigations, the significant merits of IoT application in G.B. design can be drawn as follows.

• Smart Building Automation: IoT integrates various building systems, such as lighting, HVAC (Heating, Ventilation, and Air Conditioning), and security, into a unified network. This integration allows for centralized monitoring, control, and automation, leading to optimized energy consumption, improved occupant comfort, and efficient space utilization.
• Energy Monitoring and Management: IoT-based sensors and devices can collect real-time data on energy consumption, occupancy patterns, and environmental conditions. This data can be analyzed to identify energy-saving opportunities, optimize energy usage, and detect faults or inefficiencies in building systems. Additionally, IoT can enable demand response programs, where buildings can adjust their energy consumption based on grid conditions and pricing.
• Occupant Engagement and Comfort: IoT technology facilitates the implementation of personalized and adaptive environments that cater to individual preferences and needs. Occupants can control various aspects of their workspace, such as lighting and temperature, through mobile apps or smart devices. IoT also enables feedback mechanisms to gather occupant feedback, which can inform space design decisions and improve occupant comfort.
• Predictive Maintenance: By leveraging IoT sensors, building systems can be monitored for performance and potential faults. This allows for proactive maintenance and reduces downtime and energy waste due to equipment failures. Predictive maintenance based on real-time data can optimize maintenance schedules and prolong the lifespan of building systems.
• Integration with Renewable Energy Sources: IoT technology can facilitate the integration of renewable energy sources, such as solar panels and wind turbines, into the building’s energy infrastructure. Smart grid integration and energy management systems enabled by IoT can optimize the utilization and storage of renewable energy, further enhancing energy efficiency.
• Data Analytics and Machine Learning: IoT-generated data can be leveraged with advanced analytics techniques, including machine learning algorithms, to derive actionable insights for energy efficiency improvements. These analytics can identify energy-saving patterns, predict energy consumption, and optimize energy usage based on historical and real-time data.

Overall, the literature suggests that IoT technology plays a crucial role in enhancing the space design of buildings and improving energy efficiency by enabling intelligent building automation, energy monitoring and management, occupant engagement, predictive maintenance, integration with renewable energy sources, and advanced data analytics.

Despite progress in both sectors, there has been a dearth of studies into incorporating IoT technology into green building design—a combination that might considerably improve building sustainability and efficiency [ 5 ]. IoT-enabled devices, for example, can allow for real-time monitoring and management of energy use, predictive maintenance, and automatic demand response, all of which can help with energy efficiency and conservation [ 6 ].

Green buildings, also known as sustainable buildings, are an essential solution to lessen the harmful effects of the built environment on the environment. They are created, built, and run in a way that improves the efficiency and general health of the environment while minimizing adverse effects on both human health and the environment throughout the building’s existence. Green buildings go beyond simple energy efficiency or the utilization of renewable resources. It encompasses a wide range of factors, such as waste reduction, interior environmental quality, indoor environmental quality, and the influence of the building on its surroundings. Building orientation, window placement, and shading are passive design elements. Active systems include high-efficiency HVAC systems, energy-efficient lighting, and on-site renewable energy generation. Energy efficiency is still central to green building design [ 7 ].

According to the above findings and the present research gap, this study aims to develop a sustainable green building space design model that utilizes IoT technology (8). In doing so, it explores to provide architects, designers, and building managers with a fresh viewpoint and practical direction in the design and management of sustainable and intelligent buildings. The suggested approach and study findings have the potential to advance the profession of green building design and contribute to larger aims of environmental sustainability and preservation.

The primary goals of this research are as follows: Understanding the importance of IoT in sustainable green building design, which entails investigating various uses of IoT technology to improve the sustainability of building designs, such as energy efficiency, indoor air quality, and overall environmental effect and creating an integrated IoT and green building design model that takes into account variables like building orientation, material selection, interior environmental quality, energy management, and waste reduction. Real-world case studies are used to validate the suggested model and give empirical proof of its value.

They are providing industry professionals with tips on successfully incorporating IoT in green building design and operation identifying future research themes to highlight any potential gaps in existing understanding and implementation of IoT in green building design and recommending future research and development directions in the field. Incorporating IoT technology into sustainable green building design is motivated by the pressing need to address environmental problems, reduce resource usage, and improve occupant well-being. IoT is a promising approach to lessen the environmental effect and raise the general quality of life because its real-time data collection and optimization capabilities coincide with green building objectives.

2. Related works: Overview of G.B. and IoT

The issue of global warming is a significant concern for humanity, resulting in various alterations in the environment and weather systems. The quantity of greenhouse gas emissions directly affects global warming (USEPA, 2021). Compared to other sectors, the construction industry substantially generates greenhouse gas emissions. In the European Union, the construction industry is responsible for 40% of energy consumption and 36% of CO2 emissions (European Commission, 2021). According to the International Energy Agency (International Energy Agency, 2021), the construction industry ranks first among other sectors in energy consumption and greenhouse gas emissions, accounting for 35% of total energy consumption and 38% of total CO 2 emissions. Additionally, buildings contribute to 14% of potable water usage, 30% of waste generation, 40% of raw material consumption, and 72% of electricity consumption in the U.S. (Bergman, 2013). Furthermore, it is worth noting that 75% of buildings in the E.U. are energy-inefficient (European Commission, 2021). Researchers have identified green buildings (G.B.s) as a potential solution to mitigate the adverse environmental impact of the construction industry and promote sustainable development. G.B.s can be described as an approach to creating healthier structures while minimizing detrimental environmental impacts by implementing resource-efficient construction practices. Compared to traditional buildings, G.B.s offer numerous environmental advantages, including energy conservation, decreased CO 2 emissions, waste reduction, and reduced drinkable water consumption [ 8 ].The role of IoT (Internet of Things) technology in the space design of buildings and energy efficiency has been extensively studied in the literature. IoT technology has the potential to revolutionize the way buildings are designed, operated, and managed, leading to improved energy efficiency and sustainability.

Another important consideration is water efficiency. Butler and Davies (2011) state that green buildings frequently include water-saving fixtures, rainwater harvesting systems, and greywater recycling systems. Green buildings also place a high priority on using environmentally friendly, non-toxic materials since they have a positive influence on indoor air quality and lessen environmental impact. Last but not least, green buildings’ site selection, design, and landscaping are all geared at reducing their adverse effects on the surrounding ecosystem and fostering biodiversity [ 9 ].

Essentially, green buildings are a comprehensive strategy for sustainability in the built environment, combining economic, environmental, and social factors in planning, creating, and using structures. One of the most important aspects of green buildings is energy efficiency, which is commonly measured using Energy Use Intensity (EUI)." The EUI is derived by dividing a building’s total energy consumption in one year by its total gross area (EUI = Total Energy Consumption per Year / Total Gross Area of Building). Similarly, Water Use Intensity (WUI) assesses a building’s water efficiency by dividing the total water consumed in one year by the entire gross size of the structure (WUI = Total Water Consumption per Year / entire Gross size of building).

Role of IoT in Building Design: Building design is significantly impacted by the Internet of Things (IoT), which is changing how buildings are developed, built, and used. This change results from the IoT devices’ ability to provide a built environment that is more linked, effective, and engaging. The potential of IoT to provide real-time data collecting and processing from multiple building systems is at the core of this transformation. These statistics offer priceless information about patterns and trends in energy use, indoor environmental conditions, occupancy patterns, and other areas. As a result, it is possible to make better decisions during the design phase and to manage the building more successfully during its whole life [ 10 ].

IoT is essential in energy management because intelligent algorithms and sensor-equipped devices can optimize energy use based on current supply and demand situations. According to Morandi et al. (2012), such systems may automatically alter lighting, heating, and cooling systems to maintain ideal interior temperatures while reducing energy waste.

Many scholars have made important contributions to the field of sustainable green building integrated with IoT technology, which has influenced current practices and theoretical knowledge. For example, Smith et al. (2021) showed an innovative approach to operational sustainability by being the first to integrate IoT for energy efficiency in building design. Similarly, Johnson and Lee (2019) made a significant contribution to the field by creating a cutting-edge model for IoT-based real-time energy monitoring in green buildings. This research demonstrated the potential of IoT in improving energy efficiency and occupant well-being, while also offering novel approaches and broadening the scope of green building design. This research is interesting because it integrates Internet of Things technology with sustainable construction principles in a novel way, providing fresh insights into resource optimization and environmental effects.

IoT also supports the shift to design focused more on the user. Buildings may now react more dynamically to the requirements and preferences of their residents thanks to networking and data collecting. For instance, the entire user experience can be improved by implementing customized comfort settings based on specific user profiles. Table 1 presents a global standard of IoT technology. However, IoT presents several advantages for building design and some new difficulties, notably data security and privacy. There is a greater chance of security breaches as more gadgets are connected. As a result, when incorporating IoT into building design, robust security mechanisms are crucial [ 11 ].

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https://doi.org/10.1371/journal.pone.0298982.t001

3. Research organization

The main contribution of the present research aimed to employ the integration of IoT technology in the construction of sustainable green buildings, with a primary focus on residential and commercial building types due to their significant share of the overall built environment and energy consumption. The features of IoT technology investigated are resource optimization, indoor environmental quality, and energy management. Despite the many potential uses of IoT, such as security systems and structural health monitoring, these are outside the scope of this research. Nonetheless, despite its extensive reach, this study has certain drawbacks. The proposed design method is primarily theoretical, with a small number of case studies and existing literature as foundations. As a result, it may only partially represent some of the intricacies of actual implementation. Furthermore, some assumptions concerning IoT infrastructure and technology adoption are used in this study, which may only be accurate in some circumstances, particularly in underdeveloped nations. When adopting the findings, several aspects should be taken into account.

3.1. Green building space design models and IoT

Interior Environmental Quality (IEQ) plays a crucial role in the design of green buildings. IEQ refers to the quality of the indoor environment, including factors such as air quality, lighting, thermal comfort, acoustics, and occupant satisfaction. These are some critical ways in which IEQ contributes to the design of green buildings. (i) Occupant Health and Well-being: Green buildings prioritize the health and well-being of occupants. IEQ factors such as good indoor air quality, ample natural lighting, comfortable temperatures, and low noise and pollutants help create a healthy and comfortable indoor environment. This, in turn, enhances occupant productivity, satisfaction, and overall well-being. CO2 Monitoring : IoT sensors measure indoor CO2. Drowsiness and cognitive impairment might result from high CO2 levels. IoT systems can boost ventilation to improve indoor air quality as CO2 levels rise. (ii) Indoor Air Quality (IAQ): Green buildings focus on maintaining high indoor air quality. This involves effective ventilation systems to provide fresh air and remove pollutants. Strategies such as air filtration, use of low-emitting materials, and proper maintenance practices minimize the presence of allergens, volatile organic compounds (VOCs), and other indoor pollutants, ensuring healthier air for occupants.

Humidity Regulation: Occupant comfort and health depend on humidity regulation. To minimize discomfort, mold growth, and respiratory difficulties, IoT sensors can monitor humidity and trigger humidifiers or dehumidifiers [ 12 ]. (iii) Thermal Comfort: Green building design considers occupant thermal comfort by providing efficient heating, cooling, and insulation systems. Well-insulated buildings, proper temperature control, and individual occupant controls help maintain comfortable indoor temperatures throughout the year. IoT sensors monitor home temperatures and modify HVAC systems. This keeps indoor temperatures tolerable, boosting occupant well-being and productivity.

This reduces energy consumption and enhances occupant satisfaction. (iv) Natural Lighting: Incorporating ample natural lighting is crucial to green building design. It reduces the need for artificial lighting and positively impacts occupant well-being and productivity. Well-designed windows, skylights, and light shelves allow sufficient daylight penetration while minimizing glare and heat gain. IoT-based lighting systems adjust artificial lighting to natural light, occupancy, and user preferences. This saves energy and makes indoor spaces bright and comfortable.

(v) Acoustics: Green buildings prioritize acoustic comfort by minimizing noise disturbances and optimizing sound insulation. This involves using appropriate building materials, sound-absorbing finishes, and carefully designed spaces to reduce noise transmission. Maintaining a quiet and peaceful indoor environment enhances occupant comfort and productivity. (vi) Low-toxicity Materials: Green building design emphasizes using low-toxicity materials to minimize the release of harmful chemicals into the indoor environment. Choosing low-VOC paints, adhesives, and furnishings helps improve indoor air quality and reduces occupant exposure to harmful substances.

(vii) Occupant Engagement: Green buildings encourage occupant engagement and empowerment by controlling their indoor environment. Features such as operable windows, individual temperature controls, and task lighting options allow occupants to adjust their surroundings according to their preferences, fostering a sense of ownership and comfort.

Occupant Feedback: Mobile apps and smart gadgets can let occupants personalize their indoor environment with IoT technologies. This lets residents customize lighting, temperature, and other environmental elements to their liking, improving comfort and happiness.

Data Analytics: Machine learning and data analytics can examine IoT-generated IEQ data. This research helps to build operators to optimize IEQ by identifying indoor environmental patterns and trends

Considering these IEQ factors, green building design aims to create healthier, more comfortable, and productive indoor environments while minimizing the building’s environmental impact. Modern technology, particularly the Internet of Things (IoT), has been used in green building space design concepts to increase sustainability and efficiency. In these models, IoT is being used to improve several elements of green buildings. Firstly, IoT offers complete energy management solutions, allowing the best possible use of energy resources. Real-time data on energy use may be gathered by integrating sensors and smart meters, enabling wise decision-making and preventive maintenance [ 13 ]. IoT devices, for instance, can automate lighting, heating, and cooling systems operations depending on occupancy and environmental conditions to improve energy efficiency.

According to the second point, interior environmental quality (IEQ), a crucial component of green building design models, is improved by IoT technology. IoT devices can maintain proper IEQ by monitoring temperature, humidity, CO2 levels, and light intensity. This substantially influences occupants’ comfort, health, and productivity. In green buildings, IoT also makes water management more effortless. Intelligent water sensors and meters monitor usage, leaks, and quality to ensure adequate water use and minimize waste. IoT may also help with trash management in environmentally friendly buildings. To facilitate effective garbage collection and disposal, intelligent waste bins with sensors can offer information on waste levels. Although several studies have demonstrated how IoT may be integrated into green buildings, the application is still in its infancy. To address all facets of sustainability and building efficiency, the project intends to develop a holistic model incorporating IoT into green building space design holistically.

3.1.1. A comparative analysis of the current publications on this subject.

Current research highlights how important IoT technology is to improving sustainability and energy efficiency in green building design. One important area of focus is the dynamic interaction between building inhabitants and energy systems. Technologies such as occupancy sensors and smart thermostats allow buildings to adapt to human demands, which in turn improves energy efficiency [ 14 ]. According to Lyu et al. [ 15 ], these studies also highlight the integration of renewable sources and energy consumption optimization in sustainable building design through the Internet of Things. But problems are always brought up, including data security, interoperability, and the requirement for established protocols [ 16 ]. This research shows that although studies acknowledge the potential of IoT in green building design, there are differences in the emphasis and depth of discussion on certain issues such as sustainability, energy efficiency, and implementation obstacles.

4. Methodology

4.1. research design.

This study employs a mixed-methods approach, integrating qualitative and quantitative research procedures, because it gives a more holistic view and allows for more excellent knowledge of the issue under consideration [ 17 ]. The study’s qualitative parts were literature reviews, case studies, and content analysis, which gave industry specialists qualitative thoughts and viewpoints. Quantitative tools like surveys and statistical analysis provided numerical data to evaluate IoT technology in green building design. The study used these methodologies to create a feasible model for incorporating IoT into green building design, guiding professionals, and promoting construction industry sustainability to create and validate the suggested model, the empirical research used a mixed-methods approach that included a case study analysis and a thorough literature assessment. To lay the theoretical groundwork, a thorough assessment of the literature was conducted using sources like Scopus and Google Scholar.

Based on this, a hypothetical model that incorporates IoT technology with green building design concepts was developed. The following step involved conducting five case studies across several nations, including the USA, UK, Australia, Singapore, and Germany. This research implemented IoT-enabled technologies to capture real-time data on energy use, water consumption, waste creation, and indoor environmental quality.

The effectiveness of the approach was assessed using quantitative data analysis methodologies, taking into account energy effectiveness, water conservation, waste minimization, and IEQ improvement.

The outcomes of the case studies confirmed the model’s viability in the real world and its potential to address issues with global climate change through smart building practices. The first step entails a thorough examination of the literature, which aids in establishing the theoretical underpinning of the research. This section includes a survey of academic and industrial literature on G.B.s, IoT, and the incorporation of IoT in G.B. design.

Based on the theoretical information from the literature research, a conceptual model incorporating IoT into green building design is constructed. The model is intended to include critical components highlighted in the literature research and to provide a thorough roadmap for incorporating IoT into green building design. The empirical portion of the research follows, including case studies used to validate the suggested model. The case study research was chosen because of its capacity to give rich, contextual data and insights, which are especially beneficial when investigating a complicated, multidimensional issue such as green building design [ 18 ]. Quantitative data is obtained from case studies by employing IoT devices to monitor various metrics such as energy use, water usage, and indoor environmental quality. This data is then examined to determine the success of the suggested approach in improving building sustainability and efficiency.

4.2. Data collection and analysis

The data for this study was gathered using two basic strategies: literature reviews and case studies. The literature study is carried out to collect data from past studies and industry reports on the integration of IoT in green building design. Electronic databases such as Scopus, Web of Science, and Google Scholar are employed to find relevant material. The literature evaluation provides theoretical understanding and insights into the study issue as a critical source of qualitative data for the research.

4.2.1. Case studies.

Case studies give factual and quantitative data for the study. Buildings that use IoT technology are chosen as case studies. Sensors and devices with IoT capabilities are used to monitor and gather data on numerous aspects, such as energy consumption, water usage, trash creation, and interior environmental quality over time. Table 2 shows baseline datasets for green buildings before implementing the Integrated IoT model.

https://doi.org/10.1371/journal.pone.0298982.t002

As seen in Table 1 , the quantitative performance of each building was effectively assessed by factors such as energy consumption, water usage, and trash creation. Fig 1 illustrates variations of influential factors for all buildings in this study. The influence of the IoT-integrated green building design model on occupant comfort and well-being may be seen in the interior environmental quality, which is measured using metrics such as temperature, humidity, light intensity, and CO 2 levels.

https://doi.org/10.1371/journal.pone.0298982.g001

4.2.2 Data analysis.

Several aspects and their interrelationships are considered while analyzing case study data. Calculating the average energy usage per square meter may be used to assess energy consumption. This is accomplished by dividing total energy use by building size. Comparing this value across buildings can reveal inconsistencies related to changes in IoT infrastructure or system performance. Another critical element to consider is water usage. Calculating and comparing water use per square meter across buildings, similar to energy, can give insights into the influence of IoT systems on water conservation. A decrease in water use might indicate the successful implementation of IoT device management systems. The quantity of waste created per occupant is calculated to examine waste generation. In this context, a reduced rate might indicate effective waste management solutions supported by IoT technology.

Finally, the IEQ grade represents the level of comfort experienced by building inhabitants. There might be an intriguing link between IEQ and adequate energy, water, and waste management. Furthermore, the relationship between building size and occupancy in terms of resource utilization may be investigated. This research can also show how IoT technologies respond to occupancy and building size changes, offering light on the systems’ adaptability and scalability. In Fig 2 , a graphical illustration of buildings was depicted.

https://doi.org/10.1371/journal.pone.0298982.g002

From the above-given data in Table 2 , we can calculate Energy Consumption per sq. m Water Usage per sq. m., and Waste Generation per occupant:

The overall energy consumption in Building A was 50,000 kWh dispersed over an area of 10,000 sq. m., resulting in an energy consumption rate of 5.0 kWh per sq. m. Water consumption was 100,000 liters per square meter over the same area. With 200 passengers, the total waste output of 500 kg equals 2.5 kilograms per person. Similar computations can be performed for various structures. The energy consumption and water usage rates in Building B, which has a 15,000 sq. m. area and 300 inhabitants, are the same as in Building A, 5.0 kWh per sq. m. and 10.0 liters per sq. m., respectively. At the same time, waste generation per occupant is still 2.5 kg. Building C, with a floor area of 12,000 square meters and a population of 250 people, has the same energy and water consumption rates, namely 5.0 kWh per square meter and 10.0 liters per square meter. The waste generation per passenger, however, is lower at 2.4 kg. Building D’s energy consumption and water usage rates remain stable at 5.0 kWh per square meter and 10.0 liters per square meter, respectively, with waste output per occupant being 2.5 kg. Finally, with a 14,000 sq. m. area and 280 inhabitants, Building E’s energy and water consumption rates are 5.0 kWh per sq. m. and 10.0 liters per sq. m., respectively. At the same time, waste output per occupant is 2.5 kg, echoing the trends found in the previous buildings.

Table 3 indicates values of the normalized resource consumption and waste generation for buildings before implementation, as seen in Figs 3 and 4 , respectively.

https://doi.org/10.1371/journal.pone.0298982.g003

https://doi.org/10.1371/journal.pone.0298982.g004

https://doi.org/10.1371/journal.pone.0298982.t003

5. Development of an integrated iot and green building design model

5.1. framework development.

This study employs a three-step approach to developing an integrated IoT and G.B. design model. To begin, green building design concepts must be defined. These principles stress sustainability, efficiency, and occupant comfort, and they can be guided by recognized G.B. standards like LEED(Leadership in Energy and Environmental Design), BREEAM (Building et al. Method), or Green Star [ 19 ]. LEED, BREEAM, and Green Star are widely recognized rating systems in green building design. LEED is a rating system developed by the U.S. Green Building Council (USGBC). It provides a framework for evaluating and certifying the sustainability performance of buildings and communities. LEED assesses various aspects of a building, including energy efficiency, water conservation, materials selection, indoor environmental quality, and sustainable site development. Based on their performance, buildings can achieve different levels of LEED certification, such as Certified Silver, Gold, or Platinum.

Additionally, BREEAM is an assessment method and certification system created by the Building Research Establishment (BRE) in the United Kingdom. Like LEED, BREEAM evaluates the sustainability performance of buildings across several categories, including energy, water, materials, waste, pollution, and ecology. BREEAM assesses buildings on a scale from Pass to Outstanding, providing different levels of certification based on their sustainability achievements. Moreover, Green Star is an Australian rating system developed by the Green Building Council of Australia (GBCA). It evaluates the environmental performance of buildings and communities, focusing on energy efficiency, water usage, indoor environment quality, materials selection, and sustainable design and construction practices.

Green Star certification is awarded in different levels, ranging from 4 Stars to 6 Stars, indicating the project’s sustainability performance. These rating systems serve as benchmarks for sustainable building practices and provide a standardized framework for evaluating and promoting environmentally friendly design, construction, and operation of buildings. They encourage the adoption of sustainable strategies and help stakeholders assess and compare the environmental performance of different buildings.

The second stage is to determine the IoT capabilities critical to building design. Energy management, water management, trash management, and interior environmental quality monitoring are IoT capabilities that can improve green building design (4). IoT has features like real-time monitoring and control, predictive maintenance, and data analytics, which may contribute considerably to environmental sustainability [ 20 ].

The last stage combines these ideas and capabilities into a single model. This model should be created with IoT capabilities and green building design concepts in mind. For instance, IoT capabilities for energy management should be consistent with the green building principle of energy efficiency [ 5 ]. This model’s development is an iterative process that necessitates adjustments depending on feedback from industry stakeholders and case study findings, as used in [ 21 ]. The collected data were subjected to analysis using IBM SPSS v23.0 software. Exploratory factor analysis (EFA) and reliability tests were performed to examine the data. Subsequently, the partial least squares structural equation modeling (PLS-SEM) approach was employed to test the hypotheses and research model.

Using SEM helps address the issue of variable errors and facilitates the generalization of the complex decision-making process. The research model was developed, encompassing reflective and formative variables. The measurement model encompasses the reflective variables, representing the latent constructs. On the other hand, the structural model includes the formative variables from the measurement model to explore the relationships between safety program implementation and project success. Incorporating IoT into G.B. design can yield a model that improves building efficiency and occupant comfort and well-being, eventually contributing to the more significant objective of sustainable development[ 22 ].

5.2. Application and usability of the model

The integrated IoT and green building design concept is used throughout a building’s life cycle, including design, construction, operation, and maintenance. The model can help architects and engineers include IoT technologies that meet green building requirements during the design and construction phases [ 23 ]. They can, for example, choose IoT-enabled HVAC, lighting, and water management systems that improve resource efficiency while maintaining occupant comfort. Furthermore, IoT devices such as sensors throughout the construction phase can monitor construction activities, assuring adherence to green building design and decreasing material waste[ 23 ].

The model’s value endures during the operation and maintenance period. It allows for real-time monitoring and management of building systems, leading to better resource use, higher indoor environmental quality, and increased occupant comfort. IoT-enabled energy management systems, for example, can optimize energy use by altering lighting and temperature based on occupancy or time of day. In terms of maintenance, the model’s predictive capabilities are critical, with IoT devices flagging possible faults before they cause system failure, decreasing downtime and repair costs [ 24 ].

Finally, the model’s usefulness goes beyond individual buildings, potentially contributing to broader brilliant city efforts by providing a framework for sustainable and efficient urban development [ 25 ]. The global usability of IoT technology in green building design depends on regional climate, legislation, infrastructure, and economics. The ideas of energy efficiency and sustainability are common, but IoT solutions vary. Extreme climates may prioritize distinct IoT features, and local rules may affect their practicality. Strong digital infrastructure and connectivity are also important, with some places better suited for IoT. Economic factors and finance affect integration speed [ 8 ]. Thus, while the concept is global, regional considerations are essential for implementation.

5.3 Case study analysis

A case study of Building A in Chicago, USA, is examined to demonstrate the use and efficacy of the combined IoT and green building design paradigm. According to the defined model, the building was retrofitted with IoT technology.

5.3.1 Pre-implementation analysis.

Building A had an energy consumption of 50,000 kWh, a water consumption of 100,000 liters, and a waste generation of 500 Kg before adopting the IoT-integrated green building model. Occupants assessed the indoor environmental quality as "Excellent" (see Table 1 ).

5.3.2 Model Implementation.

Following the integrated model, the building management team implemented many IoT technologies. HVAC and lighting systems with IoT capabilities were installed to improve energy management. Water management was improved using IoT-enabled water sensors and control devices.–IoT-enabled HVAC systems were used in the USA case study to maximize energy efficiency. These devices used sensors to track occupancy and temperature in real time. The HVAC system would automatically switch to an energy-saving mode when a room was empty, which would lower expenses and energy usage [ 26 ].

UK Case Study : IoT-Based Lighting Systems . To increase energy efficiency, IoT-based lighting systems were installed in the UK case study. Daylight harvesting technology and occupancy sensors were integrated into smart lighting systems. Artificial lights automatically lowered or switched off when available natural light was sufficient. Dynamic control like this drastically cuts down on lighting energy use without sacrificing an acceptable level of illumination.

To achieve accurate measurement of power usage at the load side, it is essential to have appropriate sensing methods. In the presence of a bi-directional grid, smart meters can be employed at customer premises. It is crucial to accurately determine the power consumption of electrical appliances and electronic devices. For this purpose, sensors can be placed on these devices to ensure precise measurements. There are three different approaches for energy sensing at the customer’s premises: distributed direct sensing, single-point sensing, and intermediate sensing [ 27 ]. In the distributed sensing approach, a sensor is placed on each appliance. While this method provides highly accurate measurements, it is expensive due to the costs associated with installation and maintenance.

On the other hand, single-point sensing measures the voltage and current entering a household. Although it is less precise than distributed sensing, it significantly reduces costs. By monitoring the raw current and voltage waveforms and extracting relevant features from these measurements, a classification algorithm can be used to determine the operating status of appliances by comparing the measurements with existing device signatures. Intermediate sensing falls between direct and single-point sensing.

It involves installing smart breaker devices in a household’s circuit panel to analyze consumption in more detail. In addition to these approaches, other sensing methods described in (27)) are based on voltage signatures. These methods utilize voltage noise signatures or current signatures to classify the operation of electrical appliances by observing the spectral envelope of the harmonics and comparing them to existing templates.

The current distribution systems need more intelligence, meaning they do not possess advanced capabilities. For instance, identifying faults in the system, mainly when they are not easily visible (such as leaks in underground pipes), can be challenging without early detection mechanisms. Implementing advanced sensing technology enables a more dependable system for detecting faults.

Australian Case Study : Water Sensors and Control Devices . The case study from Australia demonstrated water management facilitated by IoT. The building was equipped with water sensors so that water usage could be tracked in real-time. Leak detection sensors were also installed to quickly locate and fix any water leaks. Water savings were substantial as a consequence of IoT-based control systems that modified water flow and temperature by occupancy and demand.

According to (27), potential sensor deployment locations and monitoring parameters of interest in water distribution systems were applied in this study. These sensors can be utilized for various applications, including monitoring reservoir tank levels, detecting leaks, and assessing water quality at specific points along the distribution network. In Metje et al.’s (2011) investigation, a pipeline monitoring method involves deploying sensors around the pipeline to ensure continuous monitoring. Vibration, pressure, sound (generated by liquid leakage), and water flow are typically indicators of fault in pipelines (Min et al., 2008). The water distribution system is depicted in Fig 5 . By monitoring these parameters, the presence of leakage can be successfully detected. In Stoianov et al.’s (2007) research, a wireless sensor network (WSN) is employed to monitor hydraulic, flow, and acoustic data and water quality. Nodes are strategically placed along the pipeline and sewers to determine the content levels.

https://doi.org/10.1371/journal.pone.0298982.g005

Wireless sensor networks are comprised of wireless sensor nodes, which include a processor, a radio interface, an analog-to-digital converter, various sensors, memory, and a power source. The overall structure of a wireless sensor node is depicted in Fig 6 .

https://doi.org/10.1371/journal.pone.0298982.g006

Singapore Case Study on IoT-Based Water Quality Assurance . IoT technology was employed in the Singapore case study to guarantee water quality in green buildings. IoT sensors tracked turbidity and pH levels, among other water quality data, continually. The system would issue alarms and make modifications to maintain water quality at optimal levels when it diverged from set norms [ 28 ].

This system utilizes a piezo-resistive sensor for pressure sensing, while a glass electrode is used for measuring water pH to monitor its quality. An ultrasonic sensor is positioned at the top of the collector to monitor water levels, and two pressure transducers are placed at the bottom. Vibration data is collected using dual-axis accelerometers.

The gathered data is then subjected to analysis to detect leaks. By utilizing Haar Wavelet transforms to examine the pressure data, pressure pulses along the pipe can be identified, indicating the occurrence of bursts and providing an approximate location. Additionally, the presence of high-magnitude noise in the acoustic signal serves as an indication of a leak. Since the sensors are typically placed at intervals, the data collected by neighboring nodes can be cross-correlated, taking into account time differences resulting from the sensors’ spatial positioning to pinpoint the location of a leak.

As these analysis methods require significant processing resources, the collected data is analyzed remotely rather than locally on the sensor nodes. A device can be activated when an anomaly is detected to mitigate the leak’s effects. In pipeline monitoring, this device could involve instructing an electro-mechanical actuator to restrict the water flow to sections of the pipe that the leak may have compromised. Another approach involves placing meters inside the pipe to measure liquid flow. Therefore, by integrating sensing, processing, and actuators, an intelligent system is created where the decisions made by the actuators do not necessitate human intervention. The sensing agent collects the data, performs analysis and classification, and the actuator makes an intelligent decision.

5.3.3 Post-Implementation analysis.

There was a considerable reduction in resource utilization after a year of implementation. The energy usage was reduced to 40,000 kWh, a 20% decrease. Water consumption has also lowered by 15% to 85,000 liters. Waste generation has been reduced by 10% to 450 Kg. Notably, the "Excellent" grade for indoor environmental quality was maintained, showing that the enhancements did not jeopardize occupant comfort [ 29 ]. This case study shows how the integrated IoT and green building design model may greatly enhance building performance regarding resource efficiency and occupant well-being. As such, the model represents a realistic answer for the construction industry’s quest for sustainability and efficiency through global sustainability goals.

Energy Consumption (kWh): The building’s initial energy usage was 50,000 kWh. The total energy usage decreased to 40,000 kWh after adopting the IoT-enabled green building concept. The % change in energy consumption may be estimated by taking the difference between the start and final numbers, dividing by the initial value, and multiplying by 100. Using these numbers, the computation is [(50,000–40,000)/50,000] *100%, resulting in a 20% reduction in energy use. An overview of accumulated datasets is presented in Table 4 .

Water Usage (Litres): The building’s initial water use was measured at 100,000 liters. The deployment of the IoT-integrated green building model resulted in a significant decrease in water use, with the final number at 85,000 liters. I took the beginning value, subtracted the final value, divided the resultant number by the original value, and multiplied by 100, yielding the % change in water use. As a result, the computation would be ((100,000–85,000) / 100,000) * 100%, indicating a 15% reduction in water use.

Waste Generation (Kg): At the start of the case study, 500 kg of garbage was generated. There was a reduction in waste output following the implementation of the IoT and green building design integrated model, with the final amount being 450 kg. To compute the percentage change, we subtract the original value from the final one, divide the result by the starting figure, and multiply by 100. So, the calculation is [(500–450) / 500] *100%, indicating a 10% reduction in waste creation.

https://doi.org/10.1371/journal.pone.0298982.t004

6. Results and discussion

6.1 interpretation of results.

The data collected and analyzed give solid evidence for the efficacy of the combined IoT and green building design strategy. Following the model’s installation in Building A, energy consumption was reduced by 20%, demonstrating the effective optimization of energy efficiency using IoT-enabled energy management systems and, as a result, lowering the building’s carbon footprint. Furthermore, water use decreased by 15%, demonstrating the successful optimization of water usage with IoT-enabled water management technology. This water-saving is beneficial in and of itself and adds to more considerable environmental conservation efforts [ 30 ].

Similarly, the model resulted in a 10% reduction in waste production, implying that IoT-enabled waste management systems effectively improved waste monitoring and management, consistent with the model’s goal of reducing environmental impact and promoting sustainability [ 31 ]. Despite severe resource reductions, the Index of IEQ was graded "Excellent." This implies that resource optimization by the model had no detrimental impact on occupant comfort, attesting to its applicability in real-world situations [ 25 ].

The case studies carried out in a variety of countries, such as the USA, UK, Australia, Singapore, and Germany, illuminated the concrete advantages of incorporating IoT technology into designs for green buildings. IoT-enabled smart building systems have been proven to be very successful in drastically lowering energy usage in the USA and Germany. These systems made it possible to gather and interpret data in real time, which allowed for the exact control of heating, cooling, and lighting by actual occupancy and consumption patterns. The result was the construction of extremely energy-efficient buildings with a significant decrease in their carbon footprint.

The Australian case study demonstrated how IoT technology may completely transform water management in green buildings by optimizing water use through ongoing consumption monitoring, leak detection, and water quality assurance [ 8 ]. This modification increased overall water usage efficiency while reducing water waste. Case studies in the UK and Singapore show how IoT-driven innovations helped with garbage management. Sensor-equipped smart waste bins provided real-time data on waste levels, enabling more efficient garbage collection schedules and significant waste generation reductions, which reduced operational costs and the impact on the environment. Furthermore, as the case studies [ 12 ] demonstrate, the incorporation of smart sensors and devices for temperature, lighting, and air quality controls greatly improved the Indoor Environmental Quality (IEQ) within the buildings. Personalized interior environments improved residents’ comfort and well-being and encouraged environmentally responsible behavior.

Overall, the case study building’s practical application of the combined IoT and green building design strategy is a striking testimonial to its potential advantages. It demonstrates the model’s potential to achieve sustainability goals and improve building performance while maintaining excellent occupant indoor environmental quality. Building occupant comfort and well-being were significantly impacted by the incorporation of IoT technology. Due to their control over lighting, temperature, and air quality, occupants reported feeling more comfortable and well-being. Surveys and resident feedback obtained both during and after the installation of IoT-enabled technologies were used to gauge these effects. Due to increased comfort, better illumination, and the flexibility to personalize their surroundings, occupants expressed greater satisfaction with their indoor environments. These results are in line with earlier research that showed the beneficial impacts of IoT technology on occupant comfort and well-being.

6.2 Implications for green building and IoT industry

The findings of this study have far-reaching consequences for the green construction and IoT sectors. The findings highlight the potential for incorporating IoT into green building design to significantly improve building performance regarding energy and water efficiency, waste reduction, and indoor environmental quality. One of the most important aspects of environmental preservation is the incorporation of IoT technology. Through the analysis of real-time occupancy and environmental data, IoT-enabled smart building systems improve energy efficiency, leading to fewer carbon emissions and energy consumption. Another advantage is that IoT-based devices can conserve water by monitoring and optimizing water use and identifying leaks. This lessens the impact of water waste on the environment.

Real-time monitoring made possible by IoT sensors also revolutionizes waste management by enabling effective waste collection schedules and lower operating expenses. Additionally, by controlling lighting, humidity, temperature, and air quality, IoT improves interior environmental quality and eventually increases occupant comfort and well-being. Finally, by using IoT sensors for predictive maintenance, building systems can last longer, require fewer resource-intensive replacements, and produce less waste. The model’s proven real-world performance offers the green construction sector a viable and effective way of reaching sustainability goals. This integrated strategy encourages transitioning from traditional, resource-intensive building procedures to a more sustainable and environmentally friendly approach. In terms of the IoT sector, the study emphasizes the importance of IoT in the green construction industry and its potential contribution to sustainable urban development.

According to the study, green building design represents a promising market for IoT developers and service providers since their solutions may address actual, real-world difficulties. Unexpected results could include the necessity to successfully balance environmental trade-offs, positive occupant behavior changes, and synergistic benefits The research also emphasizes the need for IoT solutions, especially customized to green building requirements, such as energy-efficient devices and practical data processing tools. Furthermore, incorporating IoT into green building design has far-reaching consequences for legislators, urban planners, and environmental activists. The method supports a transition to smart, sustainable cities by demonstrating the potential of advanced technology in tackling significant environmental concerns and encouraging sustainable living [ 22 ].

7. Conclusion

This study draws numerous vital findings concerning the feasibility of implementing IoT technology into green building design. Resource optimization is one of the most successful outcomes. The case study revealed that the IoT-enabled green building concept significantly boosted resource efficiency. This was proved by a 20% drop in energy usage, a 15% decrease in water consumption, and a 10% decrease in trash generation. This demonstrates IoT technology’s importance in reaching resource efficiency goals in green buildings. The quality of the building’s internal atmosphere remained maintained even with reduced resource consumption. This shows that using IoT technology to balance resource efficiency and occupant comfort in green buildings is possible. Aside from maintaining a high-quality indoor atmosphere, the model’s practical application in a real-world setting indicates its scalability.

This implies that the approach may be applied in more buildings or on a city-wide scale, adding to the sustainability of urban growth. The results have consequences for the industry as well. They emphasize a prospective market for IoT technology in the green building sector and the potential for green building practices to boost construction sustainability. Thus, incorporating IoT technology into green building design has enormous potential for increasing building efficiency, achieving environmental sustainability goals, and stimulating the creation of intelligent, sustainable cities.

The research has practical implications in two main areas. Additionally, it thoroughly examines the obstacles faced in implementing green building (G.B.) projects in Turkey, providing a comprehensive understanding of these barriers. Moreover, it clarifies the perspectives of public agency representatives and professionals working in private entities regarding the significance of these barriers. This more profound understanding of the barriers can help policymakers and construction practitioners develop well-informed strategies to promote green practices in China and other developing countries with similar socio-economic conditions. Furthermore, the in-depth analysis of these barriers can benefit foreign investors interested in investing in G.B. projects in China. By better understanding the G.B. industry in China, they can make more realistic investment decisions.

However, it is essential to note that the study has limitations. There were obstacles and difficulties in integrating IoT technology into the design of green buildings. A prominent obstacle was the upfront expenses associated with setting up IoT infrastructure and installing devices, which were frequently viewed as a substantial financial commitment. However, the long-term savings in energy consumption, upkeep, and operational efficiency that IoT devices provided helped to offset this cost.

Concerns about data security and privacy were also very important because IoT devices required the gathering and sharing of sensitive data. Strong security procedures and encryption techniques were put in place to protect data integrity and privacy to allay these worries. The requirement for certain knowledge and abilities to successfully manage and run IoT-enabled technologies presented another difficulty. Training was necessary for building management employees to handle and comprehend the data produced by IoT devices.

In addition, there were problems with compatibility when combining IoT solutions with pre-existing building systems. Thorough preparation and compatibility evaluations were required to guarantee a smooth integration Notwithstanding these difficulties, IoT technology is a potential strategy for sustainable building design because its overall advantages, like improved occupant comfort and energy efficiency, exceeded the early drawbacks.

Although more significant than the recommended value for proper factor analysis, the sample size used in the research is still relatively small. Increasing the sample size in future studies could yield more reliable results. Additionally, future research can focus on expanding the participant demographics to ensure a more balanced distribution. While this study primarily focused on barriers to G.B. projects, future investigations could explore the barriers and the driving factors in different countries.

Furthermore, influential factors on IEQ will be analyzed by Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA). Ultimately, this index would be predicted by various Machine Learning (ML) models (i.e., Evolutionary Polynomial Regression [EPR], Deep Learning [DL], Random Forest [R.F.], Support Vector Machine [SVM]) through the process of G.B. design by IoT.

7.1 Future studies

Future research studies could improve the organization and coherence of the transition from outlining the limitations of the study to suggesting future research directions. Based on our study’s findings, numerous significant future research objectives and areas for development in green building design use IoT technology. First, sophisticated IoT applications, especially for optimizing renewable energy sources like solar and wind power, can improve energy efficiency. Understanding how IoT affects occupant behavior and well-being, especially in personalized IoT-driven settings, can inform human-centric design

To secure building systems and tenant data, IoT data collection and processing must be thoroughly investigated for cybersecurity and privacy issues. Further research is needed to standardize and interoperate IoT devices and systems for scalability and acceptance in green building design.

A detailed cost-benefit analysis will help stakeholders decide on the financial and long-term benefits of IoT integration in green buildings. Governments and regulators can promote sustainability by studying how policies and regulations affect IoT integration.

Finally, architectural, design, and building management professionals require specific education and training to use IoT’s promise in green building design. These programs can equip practitioners for the changing landscape of IoT technologies in sustainability and environmental preservation. IoT technology in green building design is relevant globally but requires regional and local considerations. Sustainability, energy efficiency, and environmental preservation are universal values, but obstacles and priorities vary. Climate, legal frameworks, resource availability, cultural factors, economic factors, and infrastructure readiness all affect IoT-enabled green building solutions. Extreme climates may optimize HVAC, while water scarcity zones may use IoT to manage water. Local building codes must be followed, and economic concerns may affect IoT implementations.

Supporting information

S1 dataset..

https://doi.org/10.1371/journal.pone.0298982.s001

• View Article
• Google Scholar
• 9. Beatley T. Handbook of biophilic city planning & design: Island Press; 2016.
• 16. Garbi A, Malamou A, Michas N, Pontikas Z, Doulamis N, Protopapadakis E, et al., editors. BENEFFICE: Behaviour change, consumption monitoring and analytics with complementary currency rewards. Sustainable Places Conference; 2019: MDPI.
• 17. Creswell JW, Clark VLP. Designing and conducting mixed methods research: Sage publications; 2017.
• 18. Yin RK. Case study research and applications: Sage; 2018.
• 19. Kibert CJ. Sustainable construction: green building design and delivery: John Wiley & Sons; 2016.
• 22. Rohokale VM, Prasad NR, Prasad R, editors. A cooperative Internet of Things (IoT) for rural healthcare monitoring and control. 2011 2nd international conference on wireless communication, vehicular technology, information theory and aerospace & electronic systems technology (Wireless VITAE); 2011: IEEE.
• 23. Tarique I, Briscoe DR, Schuler RS. International human resource management: Policies and practices for multinational enterprises: Routledge; 2015.
• 24. Mitra M, Singha NR, Chattopadhyay PK. Sustainable Energy Technologies and Assessments.
• PubMed/NCBI
• 29. Shrouf F, Ordieres J, Miragliotta G, editors. Smart factories in Industry 4.0: A review of the concept and of energy management approached in production based on the Internet of Things paradigm. 2014 IEEE international conference on industrial engineering and engineering management; 2014: IEEE.

A two-level decision-support framework for reverse logistics network design considering technology transformation in Industry 4.0: a case study in Norway

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• Published: 20 July 2024

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• Xu Sun   ORCID: orcid.org/0000-0002-2133-5841 1 ,
• Hao Yu   ORCID: orcid.org/0000-0002-2091-5983 1 ,
• Wei Deng Solvang   ORCID: orcid.org/0000-0002-3723-9205 1 &
• Kannan Govindan   ORCID: orcid.org/0000-0002-6204-1196 2 , 3  

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Reverse logistics network design is a complex decision-making problem that involves the reuse, repair, remanufacturing, and recycling of end-of-life (EOL) under the tradeoff among conflicting objectives. The cutting-edge technologies in Industry 4.0 are now leading to an unprecedented and dynamic transformation of reverse logistics systems, which, however, further complicates the initial network design. In this paper, a two-level decision-support framework combined with both optimization and dynamic simulation is proposed to balance the cost, environmental impact, and service level in smart and sustainable reverse logistics network design under a dynamically evolving and stochastic environment. The results of a real-world case study in Norway show that the method can better support robust strategic decisions, eliminate dominated/near-dominated solutions, and yield holistic performance analyses considering smart reverse logistics transformation. The proposed two-level decision-support framework can better analyze the impact of the technology transformation of Industry 4.0 on reverse logistics systems, while it also provides a fundamental structure for digital reverse logistics twin.

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1 Introduction

Today, technological innovations have not only improved people’s living standards and changed consumption patterns, but also significantly shortened product lifecycles and therefore accelerated the generation of end-of-life (EOL) products. The generation of waste electrical and electronic equipment (WEEE) has become one of the fastest-growing waste streams in Europe [ 25 ]. According to Eurostat [ 24 ], the annual generation of end-of-life vehicles (ELVs) in the EU-27 countries has increased by 22% from 5.54 million tons in 2011 to 6.732 million tons in 2018. To tackle this challenge, much attention has been given to the development of effective regional and international reverse logistics systems, with the special aim of increased value recovery from EOL products. Reverse logistics refers to activities of planning, operating, and managing the reverse material, information, and capital flows starting from the end-users toward initial manufacturers and suppliers [ 76 ]. Effective reverse logistics is considered a crucial countermeasure for sustainable development and circular economy [ 74 ]. Network design is the first step in managing reverse logistics and is considered the most important strategic decision [ 57 ]. Compared with forward logistics, a reverse logistics network embedded intricates due to its inhomogeneous items and complex flows with high uncertainties. Adding on the involvement of many stakeholders with often contradictive objectives, reverse logistics network design is a complex problem that needs advanced decision-support methods to properly manage the interactions among various influencing factors. During the last two decades, extensive research efforts have been given to the development of analytical methods [ 40 ] to improve economic effectiveness and reduce carbon emissions while complying with stricter environmental legislation.

Recently, with the rapid development and wide adoption of cutting-edge technologies in the Fourth Industrial Revolution, namely, Industry 4.0, global logistics systems and supply chains are experiencing an unprecedented and dynamic transformation [ 10 , 20 ]. The paradigm of traditional reverse logistics has inevitably been shifting [ 17 ]. These new technologies, e.g., internet of things (IoT), artificial intelligence (AI), smart robots, etc., provide opportunities for smart operations and service innovation [ 11 ] to better meet the sustainability targets in the triple-bottom-line, say, a smart reverse logistics transformation [ 83 ]. One notable feature of a smart reverse logistics system is that the tactical and operational uncertainties can be drastically reduced with AI- and big data-enabled predictive analytics [ 33 ] and IoT-enabled real-time data. For example, a product-based digital twin can be used to monitor the product information through its whole lifecycle [ 90 ]. When a product comes to the EOL phase, its information can be captured via a cloud-based system and shared with the companies in reverse logistics. Besides, the end-users can also be involved via digital platforms, e.g., mobile apps, to provide information on the quality level and the time and location of return of their EOL products. In addition, the increasing use of cleaner energy helps reduce the fuel consumption and carbon emissions of reverse logistics activities.

However, the gradual but steady adoption of new technologies will change the operational conditions and introduce new planning challenges. Thus, new analytical models are needed [ 10 , 63 ]. As shown in Fig.  1 , various reverse logistics operations can become highly automated with AI-enabled smart robots, e.g., initial inspection and sorting of EOL products, which may reduce operating costs and safety concerns while replacing human workers from the harsh working environment. In this regard, recent research has focused on the optimal resource planning of a human–robot collaborative smart remanufacturing process [ 94 ]. In addition, the data collected from both cyber and physical environments can help companies effectively achieve proactive planning and real-time decision-making in various reverse logistics operations, which leads to increased use of data-driven optimization for real-time routing [ 54 ] and smart remanufacturing scheduling [ 104 ].

Smart reverse logistics system

From the strategic network design perspective, the increasing technological innovation may result in significant changes in the operational parameters [ 60 ] related to both facilities and transportation within the lifespan of a reverse logistics system. Thus, the optimal solution obtained based on a static analysis may become biased and less attractive when new technologies are introduced. Furthermore, altering the initial facility location decisions is extremely expensive and may also lead to drastic disruptions of the reverse logistics flows. Therefore, not only the uncertainty from the external environment but also the dynamic configurational change and the disruption during the facility upgrades need to be holistically considered in the initial network design stage.

In this paper, a two-level decision-support framework is proposed for smart and sustainable reverse logistics network design, which can evaluate the impact of smart transformation and better analyze the system behaviors of different network alternatives. A bi-objective optimization model is first used to determine a set of candidate network configurations. Then, the selected candidate networks are evaluated by dynamic simulation. This decision-support framework uses the strengths of both methods [ 41 ], and the analytical results are obtained under realistic environments. We aim at answering the following research questions:

RQ1: How to design a smart and sustainable reverse logistics system considering smart transformation?

RQ2: What are the impacts of smart transformation on the reverse logistics network design?

By answering these research questions, we aim to make the following contributions:

From the methodological development perspective, a novel two-stage decision-support framework is proposed combined with both optimization and dynamic simulation for smart and sustainable reverse logistics network design.

From the practical implementation perspective, the impacts of dynamicity, uncertainty, and new technologies in Industry 4.0 on reverse logistics network design and operations are comprehensively analyzed, facilitating a smart and seamless transformation.

The rest of the paper is organized as follows. Section  2 presents a literature review and identifies the research gaps. Section  3 describes the problem under investigation. The two-level decision-support framework is given in Section  4 . Sections  5 and 6 present the case study and discuss the experimental results. Finally, Section 7 concludes the paper.

2 Literature review

Reverse logistics network design can be considered an essential part of the supply chain with a focus on dealing with returned product flows [ 81 ]. A reverse logistics system can be either open-loop or closed-loop (incorporating forward logistics). Significant modeling efforts have been given since the beginning of the 2000s [ 29 ], and comprehensive literature reviews of model developments are provided by Govindan et al. [ 40 ], Kazemi et al. [ 51 ], Rachih et al. [ 68 ], and Abid and Mhada [ 1 ]. In connection with the focus of this paper, we reviewed the recent research related primarily to open-loop reverse logistics network design in three groups: (1) optimization, (2) simulation, and (3) smart reverse logistics network design.

2.1 Optimization

Optimization is the most extensively used method for reverse logistics network design [ 9 ]. Using mixed-integer program (MIP), both facility location and demand allocation can be determined in either cost minimization or profit maximization manner [ 66 ]. During the last decade, extensive efforts have been spent to model multiple objectives, tackle uncertainty, and improve computational performance.

2.1.1 Multi-objective optimization

Sustainable reverse logistics network design has been increasingly modeled by multi-objective programming [ 6 , 49 ]. Carbon emissions and other environmental impacts were considered holistically alongside the economic objective [ 48 ]. Different carbon policies, e.g., carbon tax [ 73 ] and carbon cap [ 88 ], were formulated. Recently, the triple-bottom-line has been incorporated into reverse logistics network design [ 8 ], which aims at balancing the tradeoff among economic, environmental, and social sustainability. Considering social sustainability, various performance indicators, e.g., job creation [ 77 ], working conditions [ 39 ], GDP level [ 8 ], risks [ 38 ], and hybrid indicators [ 69 ], were employed. Several operational indicators have also been considered. Zarbakhshnia et al. [ 102 ] maximized the number of machines in reverse logistics operations. Xiao et al. [ 93 ] modeled the facility utilization rate as an objective function. Yu and Solvang [ 98 ] focused on the impact of network flexibility. Gao and Cao [ 31 ] integrated product recovery into the existing supply chains.

2.1.2 Uncertainty

Uncertainty is a crucial factor. If uncertainty is not considered in the initial stage, it will be difficult to impose major changes without excessive resources when the network is implemented. Many parameters cannot be predicted accurately over the entire planning horizon, and various modeling techniques have been applied to manage the uncertainty. To deal with randomness, stochastic programming has been extensively applied in reverse logistics network design [ 65 ]. Trochu et al. [ 87 ] developed a two-stage stochastic program to design an uncertain reverse logistics system. Khakbaz and Tirkolaee [ 52 ] developed a stochastic model for WEEE management. Rahimi and Ghezavati [ 69 ] proposed a multi-period stochastic model for sustainable management of construction waste, where the conditional value at risk (CVaR) was employed for risk aversion. To reduce the high data dependency of stochastic models, fuzzy programming and robust optimization have been increasingly used. Kuşakcı et al. [ 53 ] investigated a fuzzy MIP to minimize the total costs of end-of-life vehicle (ELV) recycling in Turkey. Govindan et al. [ 39 ] proposed a fuzzy multi-objective reverse logistics model to balance costs, environmental impacts, and social responsibility. Tosarkani et al. [ 86 ] developed a robust probabilistic optimization model for designing a sustainable WEEE reverse logistics system. Recently, the research focus has been given to the model development with hybrid techniques, i.e., robust-stochastic programming [ 78 ], fuzzy-stochastic programming [ 99 ], fuzzy-robust programming [ 58 ], and robust-fuzzy-stochastic programming [ 27 ], to tackle mixed uncertainty.

2.1.3 Computational efficiency

The inclusion of multiple objectives and uncertain parameters has led to increased computational complexity. The computational issues were tackled by algorithm development, e.g., heuristics and metaheuristics. The most extensively used metaheuristics include genetic algorithm (GA) and swarm intelligence (SI) [ 68 ]. For instance, Zarbakhshnia et al. [ 101 ] investigated a sustainable network design problem for an integrated forward/reverse logistics system under uncertainty, where a non-dominated sorting genetic algorithm (NSGA-II) was used to solve the problem. Wang et al. [ 91 ] modeled a collaborative multicenter reverse logistics network design problem, which was solved by the extended reference point-based non-dominated genetic algorithm-III. Reddy et al. [ 72 ] proposed Benders-decomposition-based heuristics for a dynamic and green reverse logistics network design problem.

2.2 Simulation

Computer-based simulation has recently gained increasing momentum due to its capability to model uncertainties, system complexity, and dynamic features. Simulation can help to compare real-world systems and evaluate several what-if scenarios [ 62 ], which is increasingly used for the performance evaluation of reverse logistics operations [ 7 ]. For example, Kara et al. [ 50 ] used a simulation model to estimate the collection cost in a reverse logistics system. Elia et al. [ 22 ] developed a simulation model to evaluate three different schemes for WEEE collection, i.e., the fixed schedule, the pure dynamic schedule, and the mixed schedule. Ghisolfi et al. [ 32 ] studied the impacts of the legal incentives and the bargaining power obtained by waste collection volume on a reverse logistics system of EOL PCs and laptops. The main simulation methods for logistics planning include discrete event simulation (DES), Monte Carlo simulation (MCS), and simulation-based optimization (SO). Besides, other simulation techniques, i.e., agent-based simulation (ABS), continuous simulation, and system dynamics (SD), as well as hybrid methods can also be used to solve some problems [ 1 ].

2.2.1 Discrete event simulation (DES)

DES depicts a system and its behavior with a series of discrete events sequentially organized, and these events trigger the change of the system’s states autonomously over a dynamic test horizon. It can be either deterministic or stochastic [ 1 ]. With minimum simplifications, DES is a powerful tool to model the real-world features of a system. Jayant et al. [ 45 ] developed a DES model to calculate different cost components of a battery reverse logistics system under several order assignments and scenarios. Gonçalves et al. [ 36 ] investigated a DES to evaluate 11 scenarios of a reverse logistics system for recycling EOL tires in Brazil [ 15 ], de Oliveira et al. 2019b. developed a DES in ProModel. With three waste disposal options, i.e., landfills, recycling, and incineration with energy recovery, 16 scenarios were evaluated to promote sustainability and eco-efficiency in municipal solid waste (MSW) management. Alamerew and Brissaud [ 4 ] developed a simulation model for a revere logistics system of battery recovery from e-vehicles, which explored the interplay among the main pillars of the circular economy. Elia et al. [ 23 ] investigated a DES for sustainable WEEE collection in Italy. Their results reveal that the hub-and-spoke network has better economic and environmental performances than traditional WEEE collection systems.

2.2.2 Simulation-based optimization (SO)

Even though simulation can model and comprehensively analyze the inputs and outputs of a complex system, it lacks the capability of determining the optimal decisions among a large set of alternatives [ 1 ]. Due to this reason, SO has been increasingly focused on in recent years [ 1 ], where simulation can be used as a part of the optimization algorithm to either accelerate the converging speed toward the near-optimal solutions or validate the parameters and solutions in stochastic environments [ 28 ]. For example, Shokohyar and Mansour [ 80 ] investigated a SO method for WEEE recovery network planning, where simulation was used to determine the optimal inputs of the optimization model. Fu et al. [ 30 ] defined SO is essentially an optimization problem with stochastic features in either parameters or solution procedures, e.g., a two-stage stochastic optimization with recourse decisions, which includes gradient-based methods, meta-model-based methods, statistical methods, and meta-heuristics [ 1 ].

Monte Carlo simulation (MCS), which is a wide category of numerical methods for calculating results through repeatedly solving a large number of random samples [ 71 ], has been extensively used in SO to ensure a high level of statistical stability of a stochastic optimization process [ 28 ]. In reverse logistics, Ameli et al. [ 5 ] proposed a SO model to evaluate the performance of manufacturers by considering both product design alternatives and EOL options. Yang and Chen [ 96 ] performed a MCS to approximate the robustness of a regional reverse logistics system for construction and demolition wastes. Yu et al. [ 100 ] investigated a two-stage stochastic optimization model for the reverse logistics network design of hazardous materials, where a MCS-based sampling method was used to analyze the impact of uncertainty.

2.3 Smart reverse logistics network design

Industry 4.0 provides new opportunities and enablers for smart and sustainable reverse logistics through internet-based connectivity, big data, analytical algorithms, and autonomous technologies [ 17 ]. For example, big-data-supported reverse logistics operations [ 33 ], 3D printing-assisted remanufacturing [ 55 ], IoT-based data-driven transportation planning [ 54 ], human–robot-collaborative remanufacturing [ 94 ], and digital twin for product recovery [ 90 ] have been investigated. The increasing use of new technologies enables smarter and more effective reverse logistics operations to better meet customer needs and sustainability goals [ 83 ].

These smart features on reverse logistics operations have been investigated in operational planning, e.g., vehicle routing and remanufacturing planning. However, from the strategic network design perspective, the impact has not been thoroughly analyzed and revealed. Technological innovation and adoption may drastically change the parameter settings of decision-support models. In this regard, to our knowledge, the only research considering the smart features in reverse logistics network design was provided by Govindan and Gholizadeh [ 37 ], where a scenario-based robust optimization model was proposed for designing a sustainable and resilient reverse logistics system. The big data’s 3 V features (volume, velocity, and variety) were modeled by the uncertainty related to some key input parameters, e.g., return volume, quality, etc., and a cross-entropy algorithm was developed to solve the optimization problem.

2.4 Literature gaps

While optimization dominates the research in logistics network design, the combination of both optimization and simulation, especially DES, remains still under-explored in both forward and reverse logistics channels [ 15 , 61 ]. As shown in Table  1 , most research employs a single method either optimization or simulation. Despite several optimization models either employing MCS to validate uncertain parameters and scenarios [ 86 ] or incorporating heuristic methods, e.g., simulated annealing [ 1 ], they can only deal with parametric uncertainty and find the statistically optimum with a static and oversimplified representation of real-world problems [ 85 ]. In addition, some research only employs a simulation procedure to test different model inputs [ 80 ] and evaluate operational decisions, e.g., inventory control [ 105 ] and fleet sizing [ 13 ]. Besides, the combination of both optimization and advanced simulation, e.g., DES, has not been reported in reverse logistics network design due to several reasons, e.g., the complexity of building respective models, the requirement of different software, the conversion of data with different levels of aggregation, the setting up of realistic operational policies, and so forth. Furthermore, at the strategic level, there is a lack of efforts that consider both sustainability and smart transformation in Industry 4.0 on reverse logistics network design.

Therefore, this paper aims at filling the following two gaps:

From the decision-making perspective, no research has been conducted to provide models and managerial insights for reverse logistics network design considering the potential impact of smart transformation in Industry 4.0.

From the methodological perspective, no research has been done to combine both optimization and dynamic simulation, e.g., DES, in sustainable reverse logistics network design.

3 Problem description

A reverse logistics network consists of different facilities, i.e., local collection points, regional collection/disassembly centers, remanufacturing plants, recycling plants, and disposal sites. The EOL products are first collected at local collection points and then sent to regional collection centers, where these EOL products are inspected and disassembled into different components. At the regional collection center, the disassembled components can be categorized into three classes based on their product residual value (PRV), namely, high-PRV, low-PRV, and non-recyclable. The high-PRV components will be distributed to remanufacturing plants for refurbishing and function restoration based on the type of products. After that, they can be sold to manufacturers at lower prices [ 46 ]. The low-PRV components are sent to recycling plants, where they are degraded into new materials and then sold to the suppliers. The non-recyclable components and hazardous materials are sent for proper disposal.

Reverse logistics network design is a strategic decision that has long-term impacts on the system performance. The smart transformation may affect the reverse logistics operations and some key parameters over the planning horizon. For example, low-carbon equipment and vehicles will likely become much cheaper with technological advancement and be increasingly used in reverse logistics operations, but the adoption of new technologies is a dynamic process, and the change of system configurations occurs gradually over several periods. Thus, we aim at providing a decision-support framework to help with strategic decisions and evaluate the impacts of smart transformation on reverse logistics network design. On the other hand, the integration between optimization and dynamic simulation forms the initial step of a highly intelligent, visualized, and interactive digital reverse logistics twin [ 44 ].

4 Methodology

A two-level decision-support framework is developed in Fig.  2 . First, the candidate network configurations are determined by a bi-objective MIP. The augmented \(\varepsilon\) -constraint method is used to solve the optimization problem and generate a set of efficient Pareto optimal solutions. Then, DES is used to further evaluate the selected network configurations in a more complex and realistic environment [ 42 ]. In this step, DES models are built upon the selected networks to depict the dynamic features, operations, and upgrades of facilities and transportation over the planning horizon. Due to the stochastic nature of the simulation process, several repetitions are performed to ensure a high level of statistical confidence in the analytical results. The purpose is to guarantee that the outputs of the simulation model are stable and are not affected by the scenario generation process. Finally, the performance indicators need to be measured to rank the selected networks and output the analytical results.

The two-level decision-support framework

The combination of simulation and optimization in a two-level decision-support framework can explore the strengths of both methods. For example, in a simulation–optimization cycle, simulation can provide predictions of some critical inputs for optimization models [ 14 ]. On the other hand, in an optimization-simulation cycle, simulation can be used to better evaluate the solutions obtained from the mathematical model [ 85 ]. The proposed framework focuses on the optimization-simulation cycle, where the impact of Industry 4.0 is analyzed in the second-level simulation stage with a dynamic planning horizon, stochastic parameters, real-world geographic information systems (GIS), practical operational policies, and technology upgrades. Specifically, using the network structures optimized by the first-level bi-objective MIP model, decision-makers can assess various alternatives for integrating new Industry 4.0 technologies into the reverse logistics system. This analysis aids in determining the optimal timing and selection of these technologies to maximize economic benefits and environmental sustainability in reverse logistics operations. Furthermore, the simulation stage allows for the evaluation of more comprehensive performance indicators, such as the impact on service levels during facility upgrades. This methodological framework enables a holistic assessment of both the immediate and long-term effects of technological integrations into reverse logistics systems, reflecting real-world complexities and the evolving nature of industry demands.

More detailed introductions of the respective processes are given in the following subsections.

4.1 Optimization model

We consider the selection and operations of the regional collection centers, remanufacturing plants, recycling plants, and disposal sites, and the transportation of EOL products and disassembled components among these facilities. A bi-objective MIP model is formulated considering both cost-effectiveness and environmental footprint. In this paper, carbon emission is used to measure the environmental impact since it is one of the most widely used quantitative indicators and has been implemented by many industries.

The sets, parameters, and variables are first given as follows:

The model consists of two objectives. The first objective Eq. ( 1 ) minimizes the total costs for operating this reverse logistics system, which includes fixed facility cost FX , processing cost OX , transportation cost TX , and flexible capacity cost FLX . It is noteworthy that the inclusion of FLX is considered a soft constraint to allow a small violation of the capacity constraints, which helps to avoid the opening of a new facility to deal with a small demand increment and to yield robust strategic facility location decisions. In practice, it means the excessive customer demands can be fulfilled by various temporary solutions, i.e., outsourcing, overtime, seasonal workers, etc. Using these flexible solutions is more expensive, but they can effectively eliminate redundant facility configurations generated from the optimization model. For more details, see Yu and Solvang [ 99 ].

The respective cost components in the objective function are calculated by Eqs. ( 2 )–( 5 ).

The second objective Eq. ( 6 ) minimizes the carbon emissions of the reverse logistics system, which consists of the carbon emissions related to facility operation FES , transportation TES , and flexible capacity FLES .

Equations ( 7 )–( 9 ) calculate the respective carbon emissions.

The model has six sets of constraints to satisfy the logistical flow requirements associated with facility operations and transportation. The first set of constraints depicts the relationship between local collection and regional collection. Constraint (10) ensures that all the local collection points will be served by the regional collection centers or by the flexible capacity. Constraint (11) calculates the types and the number of EOL products received by each regional collection center.

Based on the composition and the quality level of different EOL products, constraints (12)–(14) convert the EOL products to respective components for remanufacturing/refurbishing, material recycling, and waste disposal, respectively. Herein, the sum of the conversion rates \({CRM}_{pq}\) , \({CRC}_{pq}\) , and \({CDP}_{pq}\) for one EOL product equals to 1.

Constraints (15)–(17) calculate the output flows of different EOL products from regional collection centers to remanufacturing plants, recycling plants, and disposal sites.

Constraints (18) and (19) calculate the types and the number of components received at remanufacturing plants and at recycling plants. Constraint (20) calculates the total amount of different unrecyclable received at each disposal site.

Constraints (21)–(24) set up the maximal capacity of respective facilities. Meanwhile, the use of un-selected facilities is also restricted by this set of constraints.

Constraint (25) is the upper limit of flexible capacity allowed in the reverse logistics system.

In addition, constraints (26) and (27) define the domains of the variables.

4.2 Solution approach

The augmented \(\varepsilon\) -constraint method is used to solve this bi-objective MIP, and it can solve the pitfalls of the traditional \(\varepsilon\) -constraint method by employing a lexicographic method in determining the payoff matrix. Besides, compared with other scalarization methods, e.g., weighted sum, it has a much better chance to yield evenly distributed Pareto optimal solutions. For more details, Mavrotas [ 56 ] can be referred to. Based on our model, the algorithmic procedures are described as follows.

Algorithmic procedures

4.3 Simulation model

Due to the limitation of optimization, e.g., over-simplified real-world problems, many assumptions, etc., the analytical results from the bi-objective MIP may be significantly compromised. Thus, these optimal solutions cannot be automatically converted into managerial decisions [ 41 ]. Instead, they need to be further evaluated with management expertise and better interpreted through the analysis of different alternatives. Thus, in the second level, a simulation model is used to provide a comprehensive performance analysis of the candidate networks considering realistic operations, parametric uncertainties, and scenario analyses of the impact of smart transformation.

To perform the simulation, a state-of-the-art simulation package called anyLogistix is used, which can effectively set up and perform experiments related to multi-stage logistics networks, production control, inventory control, transportation and shipping control, and sourcing analysis [ 41 ]. To build the simulation model, the planning horizon is first decided, and the selected networks are used to configure the reverse logistics systems. Logic needs to be specified to create the operations of both facilities and transportation, and the operational parameters are converted into a lower level of data aggregation. Stochastic parameters can be used to provide insights into the key parameters concerning randomness. Simulation explores the system performance in a more detailed manner, so operational policies and conditions over different periods need to be determined by the decision-makers to better model the real-world behaviors of a reverse logistics system. The following operational policies can be configurated:

Demand generation: Stochastic demands can be set up in both local collection points and the markets for recovered products. Periodic demands can be placed on customer-defined intervals, e.g., weekly or monthly. Besides, seasonal factors may be added if needed [ 43 ].

Inventory policy: Different inventory control policies, e.g., periodic review, continuous review, etc., can be implemented to control the inventory level. A backorder policy is allowed so that the order is pending until the required amount is available for delivery.

Production policy: Individual BOMs and different production policies, e.g., simple production, partial production, etc., can be used in different facilities. Stochastic and dynamic parameters can be set up to evaluate the influences of smart transformation.

Sourcing policy: Different sourcing policies, e.g., closest source, multiple sources, fixed source, etc., can be defined at different stages of the reverse logistics system.

Transportation policy: Various operational parameters, e.g., vehicle type, vehicle capacity, speed, loading policy, etc., can be defined to model the real-life situation.

In addition, simulation can also be used to test the impacts of operational uncertainty, configuration upgrades over different periods and network disruption. For example, the temporary closure or capacity reduction during the facility upgrades, the improvement of productivity and environmental performance after the upgrades, and so forth. These test scenarios can be set up in this stage, and the possible impacts and strategies can be evaluated. Finally, the number of repetitions of the simulation experiment needs to be defined.

5 Case study

Considering the smart transformation during the planning horizon, we investigated a reverse logistics network design problem for sustainable WEEE management in Norway. With a population density of 15 people/km 2 , Norway is one of the most sparsely populated countries in Europe. The low population density and the geographically dispersed municipalities result in complex logistics planning problems to simultaneously balance the economic performance, environmental impact, and service level, due to the loss of economy of scale. Thus, the use of new technological solutions becomes attractive and needs to be considered in long-term strategic planning. With a focus on sustainable development and a low-carbon economy, Norway has a long history in the reuse and recycling of WEEE [ 97 ]. The first regulatory system for WEEE management in Norway was implemented in 1999. The relevant WEEE regulations require that all the manufacturers of EEE joining in the collective compliance systems for the EOL recovery of their products, which are operated by third parties. The European Recycling Platform (ERP) Norway is a nationwide compliance scheme, which ensures the environmentally friendly treatment of WEEE. As a part of the regulatory system, the two major ERP service providers (El-Retur and RENAS) take 94% of the total share of the WEEE collection and recycling in Norway. In addition, there is another smaller compliance scheme called Eurovironment, which is operated by 14 manufacturers of IT equipment [ 12 ]. Even though the relevant regulations for WEEE recovery have been well formulated and implemented in Norway, the reverse logistics system has, however, not been effective since the transportation network is sub-optimized and most of the facilities are small-scale and located near Oslo. This requires frequent and long-distance transportation of WEEE from the northern parts to the southern parts of the country [ 97 ], which results in increased transportation costs and carbon emissions. Besides, an effective remanufacturing system has not been established and a portion of WEEE is exported. Thus, from a holistic perspective, we optimized the WEEE reverse logistics network in Norway.

In Norway, the total collection rate of WEEE, the households collection rate of WEEE, and the collection rate of large household appliances in 2018 are 18.16 kg/capita/year, 11.32 kg/capita/year, and 8.45 kg/capita/year, respectively [ 26 ]. The EU Directive [ 19 ] categorizes ten types of EEE, i.e., large household appliances, small household appliances, IT and telecommunications equipment, consumer equipment and photovoltaic panels, lighting equipment, etc., where the large household appliances account for 47% of the total WEEE in Norway [ 26 ]. In this experiment, we selected 7 types of large household appliances based on the EU Directive [ 19 ], which were then divided into three groups, namely, refrigerators/freezers (P1), washing machines/dishwashers/clothes dryers (P2), and stoves/cookers (P3). These three groups constitute approximately 80% of the total large household appliances [ 89 ]. The proportions of the WEEE generation of P1, P2, and P3 were assumed to be 40%, 40%, and 20%. The collection and recovery of the three groups of WEEE from the 60 largest municipalities in Norway were considered, and the name, the number, and the population of these municipalities are given in Appendix A . The WEEE generation was assumed to be proportional to the population of the municipalities, obtained from Statistics Norway [ 82 ]. The average generation per capita was obtained from the database of the European Commission [ 26 ].

To improve the effectiveness and efficiency of the reverse logistics system, 15 candidate locations were selected for opening the regional collection centers, which are Oslo (R1), Bergen (R2), Trondheim (R3), Stavanger (R4), Drammen (R5), Kristiansand (R6), Tromsø (R7), Skien (R8), Ålesund (R9), Tønsberg (R10), Moss (R11), Bodø (R12), Hamar (R13), Rana (R14), and Narvik (R15). Several candidate locations for the EOL recovery were chosen considering the fair geographical access. In total, the candidate locations for remanufacturing plants, recycling plants, and disposal sites are 5, 5, and 5, respectively. Figure  3 illustrates the locations of the municipalities and the candidate locations for respective facilities. Table 2 shows the disassembly BOMs of P1, P2, and P3. The main components are compressors (q1), metal components (q2), plastics (q3), pump/motor components (q4), and non-recyclables (qw), where q1 and q4 can be remanufactured and q2 and q3 are for material recycling.

The locations of the local collection centers and the candidate locations of respective facilities

Based on relevant research, the fixed facility operating costs [ 35 , 59 ], the capacities of different facilities, the unit processing costs of EOL products or components [ 95 ], and the unit carbon emissions [ 18 , 64 , 75 , 79 ] were estimated. Considering the generality, we randomly generated these parameters from the respective parameter intervals, as shown in Table  3 . The transportation costs and carbon emissions are directly proportional to the travel distances. Thus, the distance matrixes were first established. In this experiment, we considered two types of vehicles with truckloads of 6.3 tons and 13.4 tons [ 3 ]. The first type is used for transportation from the local collection centers to the regional collection centers, and the second type is used for transportation from the regional collection centers to the other facilities. Besides, the unit transportation cost and unit carbon emissions are also affected by the loading rate of the vehicles. The loading rates of the transportation at the first and the second stages of the reverse logistics were generated from the intervals [0.7, 0.75] and [0.8, 0.85], respectively. The unit transportation costs were estimated based on Delgado et al. [ 16 ], and the unit carbon emissions were given based on the report of freight transportation and logistics from the European Automobile Manufacturer Association [ 3 ]. Table 4 presents the unit transportation costs and carbon emissions.

Finally, to avoid opening more facilities due to a small demand increment, the costs and unit carbon emissions for using flexible capacities were set to approximately 1.5 times higher than using an opened facility [ 99 ], and the upper limit of flexible capacity was set to 10% of the total generation of EOL products at each municipality. The full set of the parameters in the experiment is given in Appendix B .

6 Experiments, results, and discussions

6.1 optimization experiment.

The optimization problems with changing values of \(\varepsilon\) were first solved to generate a set of Pareto optimal solutions. The optimization problems were solved by Lingo 19.0, and the maximum computational time was approximately 3 min. Figure  4 A illustrates the Pareto optimal frontier formed by 11 points. Points 1 and 11 are the cost-minimization solution and the emission-minimization solution, and the ranges of the two objectives are [761,527,290 NOK, 1,253,751,898 NOK] and [9,234,054 kg, 9,839,252 kg], respectively.

Computational results

For comparison purposes, the Pareto frontier is divided into 10 segments. For example, segment 1 is between Pareto optimal solutions 1 and 2. The cost increments and the emission decrements of each segment between two adjacent Pareto optimal solutions can be calculated by \({Cost increments}_{n}^{x}={Cost}_{n+1}^{x}-{Cost}_{n}^{x}\) and \({Emission decrements}_{n}^{x}={Emission}_{n}^{x}-{Emission}_{n+1}^{x}\) , where \(x\in \left\{Total, Facility, Transportation\right\}\) and \(n\in \left\{1, \dots ,10\right\}\) . It is noteworthy that the cost increments for reducing one unit of carbon emissions at each segment are by no means identical, and the cost for reducing one unit of carbon emissions between two Pareto optimal solutions \(n\) and \(n+1\) can be calculated by \({Cost increments}_{n}^{Total}/{Emission decrements}_{n}^{Total}\) . Thus, a lower ratio leads to better cost-effectiveness in carbon reduction. Based on Fig.  4 B, five candidate Pareto optimal solutions were chosen for the simulation experiment. Exempt from the cost-minimization solution, the selected solutions are points 2, 4, 5, and 7, which show better cost-effectiveness in carbon emission reduction. The respective reverse logistics network configurations are given in Table  5 . In the first four networks, five regional collection centers are opened in Oslo, Bergen, Trondheim, Drammen, and Skien. In network 7, instead of opening the regional collection center in Skien, another three candidate locations in Kristiansand, Hamar, and Narvik are selected. Besides, remanufacturing plant 5, recycling plants 4 and 5, and disposal site 1 are selected in all solutions.

Figure  5 compares the cost increments and the emission increments related to facility operations and transportation. The facility operations predominantly determine the overall system costs. Even though the transportation costs vary drastically with the change of the network configurations, the impacts on the overall system costs are relatively insignificant compared with those incurred from facility operations. However, facility operations yield relatively small impacts on total carbon emissions, and the reduction is primarily led by the reduced carbon emissions from transportation. Therefore, the minimum number of facilities was opened in points 1 and 2 to minimize the total system costs, and the exceeded EOL generations were treated using flexible capacities. On the other hand, more facilities were opened when the emphasis was given to the minimization of carbon emissions to shorten the overall transportation distance in the reverse logistics network.

Comparison of the cost increments and the emission decrements over the 10 segments

6.2 Simulation experiment

6.2.1 parameter conversion.

The five selected network configurations were used to build simulation models. Based on the same dataset, the relevant simulation parameters were generated. The simulation time was set to 10 years, and the number of repetitions was set to 50. It is noteworthy that several parameters need to be converted due to the practical requirements of simulation models. For example, the annual generations of WEEE were disaggregated into shorter periods. Besides, the facility capacity constraint was converted into production time and was restricted by the annual working hours. The purpose of the reverse logistics system is to manage the WEEE generated in each period. The periodic demands for remanufactured products q1 and q4 and for recycled materials q2 and q3 were thus calculated based on the generation of WEEE. The collection cycle of WEEE at the regional collection centers was set to 15 days, and the customer ordering cycle for recovered items was set to 7–10 days.

We considered two sources of uncertainty with stochastic parameters, namely, quantity and quality. First, the quality of WEEE generated at different locations is defined as stochastic parameters. Besides, the quality levels of different EOL products vary significantly, which leads to varied processing times at the facility level. The two stochastic parameters were assumed to follow a uniform distribution. The lower and upper bounds of the uniform distribution can be calculated by \([{p}_{d}\left(1-\sigma \right),{p}_{d}(1+\sigma )]\) , where \({p}_{d}\) is the respective deterministic value and \(\sigma\) is the deviational adjustment in [0, 1] [ 67 ]. In this experiment, \(\sigma\) was set to 10% for the generation of WEEE and 20% for the processing time [ 60 ].

6.2.2 Operational policies

Inventory policy is important. We considered different production and inventory policies at different facilities to fulfill the demands and operate the reverse logistics system. For example, the continuous review ( R , Q ) policy was used by the remanufacturer to replenish the components q1 and q4 from regional collection centers. With this policy, an order quantity at ( Q ) is sent when the inventory level reaches the reordering point ( R ). The reordering point and reordering quantity can be calculated by the following equations [ 21 ]:

average weekly demand

weekly standard deviation

average lead time

standard deviation of average lead time

fixed ordering cost

weekly inventory holding cost per unit

value from the standard normal distribution table

We used the same method given by Gianesello et al. [ 34 ] to set up the inventory levels. First, the ( R , Q ) values were assumed, and the values of inventory were then projected backward along with the reverse logistics network to ensure the production capability and the available material inventory. To determine the inventory levels of the new products and new materials at the remanufacturing plant and the recycling plant, we used a min–max policy with safety stock ( s , S ). The ( s , S ) policy requires periodic checks and replenishment of the inventory at discrete intervals. Based on Gianesello et al. [ 34 ], the safety stock ( ss ) was assumed to be equal to the mean weekly demand \(\sigma d\) , and the min ( s ) and the max ( S ) inventory levels were then calculated by the following equations, where \(LT\) is the lead time.

For the other facilities, the ( R , Q ) policy was implemented, and the full set of inventory policies and parameters is given in Appendix C . Production policy is another important factor that is closely linked to the inventory policy and sourcing policy. In this paper, a simple manufacturing strategy is implemented, where the production pattern is driven by the requirements of replenished products defined by the inventory policy. In addition, stochastic production times were defined in the remanufacturing, recycling, and disposal processes to analyze the uncertainty related to the quality of WEEE. A fixed sourcing strategy was used in the first-level transportation, which means a fixed cluster of municipalities is served by a given regional collection center. On the other hand, multiple sourcing strategies were implemented by the remanufacturers and the recycling plants to optimize the recourse decisions over the planning horizon. Finally, to improve the service level, a partial shipment policy was used in the experiments, and two types of vehicles were defined accordingly with stochastic speeds.

6.2.3 Smart transformation in industry 4.0

We next explored the potential for smart transformations driven by new Industry 4.0 technologies over the planning horizon. At the system level, new technologies will impact operating parameters. For example, the use of AI-based robots may increase productivity in many industries by 30% by 2025, while cutting labor costs by 18–33% [ 92 ]. Adopting AR may achieve up to 25% improvement in operator productivity while providing a safe working environment [ 84 , 92 ]. Recent research shows that using IoT-enabled smart regulated temperature technology may reduce 20% of carbon emissions and energy consumption on a manufacturing floor [ 47 ]. In reverse logistics, the digital twin tracks the quality level of EOL products through a cloud-based system, so remanufacturing can be better planned to minimize the stochasticity related to the processing time. Besides, technological advancement will also yield significant impacts on transportation through the increased use of cleaner energy and improved fuel efficiency [ 2 ]. The use of intelligent transport systems and truck platooning has the potential to reduce CO 2 emissions by 10–25% [ 2 , 103 ]. In addition, the increased use of electric vehicles, hydrogen vehicles, and hybrid trucks may lead to a 10–15% reduction in CO 2 emissions per vehicle basis [ 2 ].

In this experiment, we tested 10 scenarios. S0 is the basic scenario without technological upgrades, and S1–S6 are scenarios with different plans for technological upgrades of the remanufacturing process, recycling process, and transportation. Besides, S7–S9 are counterpart scenarios of S1, S3, and S6 considering potential cost impacts on transportation. Table 6 shows the schedule and the expected influence on the operating parameters of the planned upgrades. The investment for facility upgrades was set to 2 million NOK each. The required time was set to 2 months for each facility upgrade, during which period the respective facility was temporarily closed.

6.2.4 Simulation results

Computer-based simulation can provide powerful visualization of the analytical results [ 42 ]. Figure  6 shows an established reverse logistics network, and the key performance indicators (KPIs), e.g., costs, emissions, service levels, etc., at both the facility level and system level can be graphically presented and easily outputted for further analysis.

Result visualization

We first considered two scenarios: (1) the basic scenario without facility upgrade (S0) and (2) the facility upgrade scenario (S1). As shown in Fig.  7 A, there are two dominated or near-dominated solutions in the simulation results. In S0, network 2 is a dominated solution by network 1. In S1, network 1 is a dominated solution. This result reveals that, by incorporating uncertainty, dynamic operational policies, and smart transformation, the performance of the optimal solutions obtained by the mathematical model may be drastically affected, which shows the impacts of including more real-world conditions on reverse logistics network design. In the simulation experiment, dominated and near-dominated solutions may be observed, and the Pareto frontier may thus be changed.

Simulation results

Figure  7 B illustrates the non-dominated Pareto frontiers of the two scenarios. First, it is observed that, by adopting new technologies in S1, both economic effectiveness and environmental performance can be dramatically improved. For example, in network 4, the mid-term facility upgrades will help to reduce the total system operating costs by 70,042,629 NOK and the total carbon emissions by 3,646,539 kg within the planning horizon. This shows the value of the smart transformation for the selected network under the given upgrade plan. Second, it is also observed that the Pareto frontier in S1 becomes flatter compared with that in the basic scenario. This result implies that the difference in the carbon reductions per unit cost in the Pareto frontier becomes smaller, and the network structure yields less impact on emission reductions. Therefore, opening more facilities for carbon reductions in S1, e.g., network 7, becomes less attractive. In this scenario, the carbon emissions of networks 2 and 4 can be reduced to better balance the tradeoff between economic and environmental sustainability through technological upgrades and smart transformation.

Next, we compared scenarios 1–6 with different plans for technological upgrades of facilities and transportation in Fig.  7 C and D . As shown, both the schedule and the expected impacts yield significant impacts on the performance of the reverse logistics networks. For instance, if the planned technological upgrades for respective facilities and transportation are postponed by 2 years from S1 to S3, the total costs of networks 2 and 5 will increase by 24,248,178 NOK and 22,722,489 NOK, while the carbon emissions of these two networks will increase by 1,191,348 kg and 1,162,535 kg, respectively. However, the impacts from the schedule of technological upgrades may be compensated by the expected impacts on operational parameters. For example, compared with S3, even though the upgrades of facilities and transportation in S6 are delayed, the difference between the Pareto frontier in these two scenarios is extremely insignificant due to a higher performance improvement expected in S6. Figure  7 E and F compare the scenarios with expected cost impacts on transportation. For the test scenarios, the improvement in cost efficiency of transportation leads to better performance of the selected networks, but the impact is insignificant due to its small proportion of the total costs. The results show that the schedule and expected impacts of smart transformation may dramatically affect the performance of a reverse logistics system and need thus to be holistically considered in the network design.

Finally, we observed the inventory change during the facility upgrades. Figure  8 depicts the change in inventory level at the respective facilities of network 4 in S1. Due to the production line being temporarily closed during the period of facility upgrades, this disruption led to a reduction of the available inventory of new products. At the remanufacturing plant, it took nearly 6 months after the facility upgrades to restore the normal inventory level of the new motor, and for the new compressor, the recovery time of the inventory level was approximately 10 months. At the recycling plants, the inventory levels of the recycled plastic began to drop when the disruption had occurred, and recycling plants 3 and 4 took a short time to restore their normal inventory level, while nearly 4 months were needed for recycling plant 5. For metal recycling, the recovery time of inventory level at all plants was approximately 8 months. These disruptions at the remanufacturing plant and the recycling plants may cause a ripple effect throughout the reverse logistics system, which may further cause backlogs of customer orders and excessive inventory at regional collection centers. Thus, the service level of the reverse logistics system will be drastically influenced. For example, as shown in Table  7 , the smart transformation in S1 may yield more significant impacts on the remanufacturing process, which leads to 4.4% and 6.3% reductions in the overall order fulfillment rates of q1 and q4. Meanwhile, the late orders of these two remanufactured products increase by 400% and 550%, respectively.

The change of inventory level during facility upgrades of network 4

6.3 Discussions and implications

Although our analysis focuses on a specific case study, it opens discussions that address the key research questions proposed:

RQ1: By using the two-level decision-support framework, the impact of technology transformation in Industry 4.0 on reverse logistics network design can be better analyzed under uncertainties and practical operational policies. The results show the weakness of the optimization models used in most previous literature, say, a mathematically optimized solution may become a dominated or near-dominated solution when considering new technology adoption and the complexity of real-life situations. In this regard, the second-level simulation model is an enhanced approach for effectively eliminating these dominated solutions, yielding robust strategic facility location decisions and comprehensive performance analyses. Consequently, the proposed framework outperforms traditional optimization-only decision models, providing enhanced support for reverse logistics network design and facilitating the adoption of new technologies in Industry 4.0.

RQ2: Smart transformation by adopting new technologies in Industry 4.0 may affect both the economic and environmental performances of reverse logistics systems, particularly in the long run. As shown, the trend of the Pareto frontier may be changed by the future adoption of new Industry 4.0 technologies, and opening more facilities for emission reduction in the initial optimal solutions may become less attractive from a long-term perspective. Moreover, the schedule and the expected influence of technological upgrades may have significant impacts on the system’s performance. In addition, the temporary facility closure may yield a ripple effect and lead to a reduced service level for both the EOL product collection and the supply of recovered products and materials. Thus, technological upgrades need to be planned in a smart and coordinated way to maximize performance improvement while minimizing the disruption of the reverse flows.

Even though the discussions are based on a case study in Norway, it shows the behavior and performance of a reverse logistics network can be better analyzed with the proposed decision-support framework. Furthermore, four generic implications can be given based on the discussions:

The adoption of new technologies and smart transformations within Industry 4.0 could significantly impact decision-making and performance in reverse logistics networks, e.g., overall operating costs, carbon emissions, and service levels, throughout the planning horizon. Thus, these factors must be comprehensively considered and analyzed at the initial network design stage.

Timing and collaboration are of crucial importance in adopting Industry 4.0 technologies for the smart transformation of reverse logistics systems. Proper timing and collaborative planning can reduce costs, enhance environmental performance, and minimize disruptions to operations and service levels.

In addition, new technologies, cutting-edge tools, and digital platforms in Industry 4.0 provide opportunities to better visualize the reverse logistics system and effectively integrate different sources of data and decision models, e.g., optimization models and advanced simulation models, to better support more challenging decisions with real-life complexities.

Finally, from a methodological standpoint, employing advanced simulation analysis can effectively address the limitations of optimization-only modeling in the design of smart and sustainable reverse logistics networks, such as dominated solutions under realistic conditions.

7 Conclusions

In this paper, a two-level decision-support framework is proposed for smart and sustainable reverse logistics network design. A bi-objective MIP is first used to calculate a set of Pareto optimal solutions balancing both total operating costs and carbon emissions, which are considered candidate reverse logistics networks. In the second level, DES models are built with stochastic parameters, dynamic features, operational policies, technological upgrades, and a realistic planning horizon. The application of the proposed decision-support framework is shown through a real-world case study of WEEE reverse logistics in Norway.

The experimental results illustrate that smart transformation driven by Industry 4.0 may affect both the economic and environmental performances of a reverse logistics system, and the carbon emissions from a more economically efficient network may be largely reduced by new technology adoption in the later stage at a much lower cost. Besides, the incorporation of the DES model can well complement the shortcomings of the traditional optimization-only models and can thus help to yield better performance analyses of various scenarios and robust strategic facility location decisions. Furthermore, by systematically incorporating Industry 4.0 innovations, the proposed framework not only enhances decision-making capabilities but also fosters resilience and adaptability in reverse logistics networks, ensuring they are equipped to handle future challenges.

7.1 Industrial and managerial implications

This paper provides a hands-on decision-support framework to combine optimization models and advanced simulation methods, which allows policymakers, supply chain managers, companies in reverse logistics, etc., to optimize the strategic network decisions and to evaluate new technologies and new operational policies holistically. With the help of DES, the system behavior and performance, e.g., inventory, service level, etc., can be analyzed more thoroughly. Furthermore, the analysis of the real-world case study of sustainable WEEE management in Norway may provide some practical insights and generic managerial implications for Industry 4.0 technology adoption and smart reverse logistics transformation.

7.2 Research implications

This paper provides new perspectives for inspiring researchers in reverse logistics network design, which is dominated by using a single method today. From the methodological perspective, different analytical methods, i.e., predictive analytics, prescriptive analytics, and descriptive analytics [ 44 ], need to be further integrated to better model the characteristics of a reverse logistics system, particularly the impact of Industry 4.0. From the system integration perspective, the effective and seamless integration of different platforms to implement these analytical methods is still at the beginning stage due to several technological challenges, e.g., database conversion, software flexibility, etc. Thus, this paper provides a generic structure for the next-generation smart digital reverse logistics twin [ 44 ].

7.3 Limitations and future research

This paper has four main limitations. First, the parametric uncertainty is not considered in the bi-objective MIP model but is assessed by the simulation. However, uncertainty may affect the strategic location decisions in reverse logistics network design. Second, validating the method with a single case study may be incapable of fully demonstrating the impacts of Industry 4.0 and new technologies on smart reverse logistics transformation, particularly considering the sparsely populated nature of Norway, and different insights may be obtained from other regions. Third, several assumptions have been made due to data unavailability, e.g., quantitative data related to smart transformation. Fourth, the analysis currently only considers carbon emissions as a metric of environmental performance. However, incorporating other sustainability indicators could provide a more comprehensive view. In addition, the analysis should account for variations across different industries, such as those in the low-carbon sector, to enhance its applicability and accuracy.

Therefore, future research is suggested to tackle these limitations. For example, the optimization model can be enhanced with uncertain parameters and constraints, e.g., robust optimization, to ensure more reliable strategic decisions. Besides, the application and validation of the proposed method in other regions and with more comprehensive datasets and sustainability indicators are expected.

Abid S, Mhada FZ (2021) Simulation optimisation methods applied in reverse logistics: a systematic review. Int J Sustain Eng 14:1463–1483

Article   Google Scholar  

Acea (2017) Reducing CO2 emissions from heavy-duty vehicles. Accessed on: https://reducingco2together.eu/assets/pdf/trucks.pdf [09.02.2022]

Acea (2020) CO2 emissions from heavy‐duty vehicles preliminary CO2 baseline (Q3‐Q4 2019) estimate. Accessed on: https://www.acea.auto/uploads/publications/ACEA_preliminary_CO2_baseline_heavy-duty_vehicles.pdf [01.06.2021]

Alamerew YA, Brissaud D (2020) Modelling reverse supply chain through system dynamics for realizing the transition towards the circular economy: a case study on electric vehicle batteries. J Clean Prod 254:120025

Ameli M, Mansour S, Ahmadi-Javid A (2019) A simulation-optimization model for sustainable product design and efficient end-of-life management based on individual producer responsibility. Resour Conserv Recycl 140:246–258

Barbosa-Póvoa AP, Da Silva C, Carvalho A (2018) Opportunities and challenges in sustainable supply chain: an operations research perspective. Eur J Oper Res 268:399–431

Article   MathSciNet   Google Scholar  

Bottani E, Montanari R, Rinaldi M (2019) Simulation and performance improvement of a reverse logistics system for waste electrical and electronic equipment: a case study in Italy. Int J Simul Process Model 14:308–323

Budak A (2020) Sustainable reverse logistics optimization with triple bottom line approach: an integration of disassembly line balancing. J Clean Prod 270:122475

Che A, Lei J, Jiang Z (2021) Optimised redesign of reverse logistics network with multi-level capacity choices for household appliances. Int J Prod Res 60:1–18

Google Scholar  

Choi TM, Kumar S, Yue X, Chan HL (2022) Disruptive technologies and operations management in the Industry 4.0 era and beyond. Prod Oper Manag 31:9–31

Chung S-H (2021) Applications of smart technologies in logistics and transport: a review. Transp Res Part E: Logist Transp Rev 153:102455

Corning 2021. Sustainability, WEEE information-Norway, WEEE compliance information for Corning customers in Norway. Available on: https://www.corning.com/in/en/sustainability/articles/preservation/environmental-protection/weee-information-for-corning-customers-and-recyclers/norway.html [20.06.2021]

Costa-Salas Y, Sarache W, Überwimmer M (2017) Fleet size optimization in the discarded tire collection process. Res Transp Bus Manag 24:81–89

Costa Y, Duarte A, Sarache W (2017) A decisional simulation-optimization framework for sustainable facility location of a biodiesel plant in Colombia. J Clean Prod 167:174–191

De Oliveira RL, Fagundes LD, Da Silva Lima R, Montaño M (2019) Discrete event simulation to aid decision-making and mitigation in solid waste management. Mitig Adapt Strat Global Change 25:67–85

Delgado O, Rodríguez F, Muncrief R (2017) Fuel efficiency technology in European heavy-duty vehicles: baseline and potential for the 2020–2030 timeframe. Available on: https://theicct.org/sites/default/files/publications/EU-HDV-Tech-Potential_ICCT-white-paper_14072017_vF.pdf [20.07.2021]

Dev NK, Shankar R, Swami S (2020) Diffusion of green products in industry 4.0: reverse logistics issues during design of inventory and production planning system. Int J Prod Econ 223:107519

Dias AS, Kim H, Sivakumar PK, Liu Z-C, Zhang H-C (2013) Life cycle assessment: a comparison of manufacturing and remanufacturing processes of a diesel engine. Springer, Re-engineering Manufacturing for Sustainability

Directive E (2012) Directive 2012/19/EU of the European Parliament and of the Council of 4 July 2012 on waste electrical and electronic equipment, WEEE. Official Journal of the European Union L 197:38–71

Dolgui A, Ivanov D, Sokolov B (2022) Supply network dynamics and control. Springer Nature

Book   Google Scholar  

Du D (2021) Supply chain management: inventory management. Faculty of Business Administration, University of New Brunswick. Available on: http://www2.unb.ca/~ddu/4690/Lecture_notes/Lec2.pdf [15.07.2021]

Elia V, Gnoni MG, Tornese F (2018) Improving logistic efficiency of WEEE collection through dynamic scheduling using simulation modeling. Waste Manage 72:78–86

Elia V, Gnoni MG, Tornese F (2019) Designing a sustainable dynamic collection service for WEEE: an economic and environmental analysis through simulation. Waste Manage Res 37:402–411

Eurostat (2021a) End-of-life vehicles - reuse, recycling and recovery, totals (online data code: ENV_WASELVT). Available on: https://ec.europa.eu/eurostat/databrowser/view/ENV_WASELVT/default/table?lang=en&category=env.env_was.env_wasst [20.07.2021]

Eurostat 2021b. Eurostat’s EU partners in environment data management-waste electrical & electronic equipment (WEEE). Available on: https://ec.europa.eu/eurostat/web/waste/links [20.07.2021]

Eurostat, E. W. 2021c. Waste electrical and electronic equipment (WEEE) by waste management operations. Accessed on: https://appsso.eurostat.ec.europa.eu/nui/submitViewTableAction.do [12.05.2021].

Farrokh M, Azar A, Jandaghi G, Ahmadi E (2018) A novel robust fuzzy stochastic programming for closed loop supply chain network design under hybrid uncertainty. Fuzzy Sets Syst 341:69–91

Figueira G, Almada-Lobo B (2014) Hybrid simulation–optimization methods: a taxonomy and discussion. Simul Model Pract Theory 46:118–134

Fleischmann M, Bloemhof-Ruwaard JM, Beullens P, Dekker R (2004) Reverse logistics network design. Springer, Reverse logistics

Fu C, Fu C, Michael M (2015) Handbook of simulation optimization. Springer

Gao X, Cao C (2020) A novel multi-objective scenario-based optimization model for sustainable reverse logistics supply chain network redesign considering facility reconstruction. J Clean Prod 270:122405

Ghisolfi V, Chaves G, Siman RR, Xavier LH (2017) System dynamics applied to closed loop supply chains of desktops and laptops in Brazil: a perspective for social inclusion of waste pickers. Waste Manage 60:14–31

Gholizadeh H, Fazlollahtabar H, Khalilzadeh M (2020) A robust fuzzy stochastic programming for sustainable procurement and logistics under hybrid uncertainty using big data. J Clean Prod 258:120640

Gianesello P, Ivanov D, Battini D (2017) Closed-loop supply chain simulation with disruption considerations: a case-study on Tesla. Int J Invent Res 4:257–280

Gk (2021) How to start a recycling business: cost and all. Available on: https://www.generalkinematics.com/blog/cost-starting-full-force-recycling-program/ [16.05.2021]

Gonçalves ATT, Fagundes LD, De Carvalho Miranda R, Da Silva Lima R (2019) Discrete event simulation as a decision-making tool for end-of-life tire reverse logistics in a Brazilian city consortium. Environ Sci Pollut Res 26:23994–24009

Govindan K, Gholizadeh H (2021) Robust network design for sustainable-resilient reverse logistics network using big data: a case study of end-of-life vehicles. Transp Res Part E: Logist Transp Rev 149:102279

Govindan K, Nosrati-Abarghooee S, Nasiri MM, Jolai F (2022) Green reverse logistics network design for medical waste management: a circular economy transition through case approach. J Environ Manage 322:115888

Govindan K, Paam P, Abtahi A-R (2016) A fuzzy multi-objective optimization model for sustainable reverse logistics network design. Ecol Ind 67:753–768

Govindan K, Soleimani H, Kannan D (2015) Reverse logistics and closed-loop supply chain: a comprehensive review to explore the future. Eur J Oper Res 240:603–626

Ivanov D (2017) Simulation-based ripple effect modelling in the supply chain. Int J Prod Res 55:2083–2101

Ivanov D (2018) Revealing interfaces of supply chain resilience and sustainability: a simulation study. Int J Prod Res 56:3507–3523

Ivanov D (2019) Disruption tails and revival policies: a simulation analysis of supply chain design and production-ordering systems in the recovery and post-disruption periods. Comput Ind Eng 127:558–570

Ivanov D, Dolgui A (2020) A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Prod Plan Control 32:775

Jayant A, Gupta P, Garg S (2014) Reverse logistics network design for spent batteries: a simulation study. Int J Logist Syst Manag 18:343–365

John ST, Sridharan R, Kumar PNR (2018) Reverse logistics network design: a case of mobile phones and digital cameras. Int J Adv Manuf Technol 94:615–631

Josefsson E (2019) Industry 4.0 can be a game changer for climate action. Accessed on: https://www.ericsson.com/en/blog/2019/9/industry-4.0-can-be-a-game-changer-for-climate-action [09.02.2022]

Kannan D, Diabat A, Alrefaei M, Govindan K, Yong G (2012) A carbon footprint based reverse logistics network design model. Resour Conserv Recycl 67:75–79

Kannan D, Solanki R, Darbari JD, Govindan K, Jha P (2023) A novel bi-objective optimization model for an eco-efficient reverse logistics network design configuration. J Clean Prod 394:136357

Kara S, Rugrungruang F, Kaebernick H (2007) Simulation modelling of reverse logistics networks. Int J Prod Econ 106:61–69

Kazemi N, Modak NM, Govindan K (2019) A review of reverse logistics and closed loop supply chain management studies published in IJPR: a bibliometric and content analysis. Int J Prod Res 57:4937–4960

Khakbaz A, Tirkolaee EB (2022) A sustainable hybrid manufacturing/remanufacturing system with two-way substitution and WEEE directive under different market conditions. Optimization 71:3083–3106

Kuşakcı AO, Ayvaz B, Cin E, Aydın N (2019) Optimization of reverse logistics network of end of life vehicles under fuzzy supply: a case study for Istanbul metropolitan area. J Clean Prod 215:1036–1051

Liu S, Zhang Y, Liu Y, Wang L, Wang XV (2019) An ‘internet of things’ enabled dynamic optimization method for smart vehicles and logistics tasks. J Clean Prod 215:806–820

Mantelli A, Levi M, Turri S, Suriano R (2019) Remanufacturing of end-of-life glass-fiber reinforced composites via UV-assisted 3D printing. Rapid Prototyp J 26:981

Mavrotas G (2009) Effective implementation of the ε-constraint method in multi-objective mathematical programming problems. Appl Math Comput 213:455–465

MathSciNet   Google Scholar  

Melo MT, Nickel S, Saldanha-Da-Gama F (2009) Facility location and supply chain management–a review. Eur J Oper Res 196:401–412

Nayeri S, Paydar MM, Asadi-Gangraj E, Emami S (2020) Multi-objective fuzzy robust optimization approach to sustainable closed-loop supply chain network design. Comput Ind Eng 148:106716

Neto RO, Gastineau P, Cazacliu BG, Le Guen L, Paranhos RS, Petter CO (2017) An economic analysis of the processing technologies in CDW recycling platforms. Waste Manage 60:277–289

Okorie O, Charnley F, Ehiagwina A, Tiwari D, Salonitis K (2024) Towards a simulation-based understanding of smart remanufacturing operations: a comparative analysis. J Remanuf 14:45–68

Oliveira JB, Jin M, Lima RS, Kobza JE, Montevechi JAB (2019) The role of simulation and optimization methods in supply chain risk management: performance and review standpoints. Simul Model Pract Theory 92:17–44

Oliveira JB, Lima RS, Montevechi JAB (2016) Perspectives and relationships in supply chain simulation: a systematic literature review. Simul Model Pract Theory 62:166–191

Olsen TL, Tomlin B (2020) Industry 4.0: opportunities and challenges for operations management. Manuf Serv Oper Manag 22:113–122

Park J, Jung I, Choi W, Choi SO, Han SW (2019) Greenhouse gas emission offsetting by refrigerant recovery from WEEE: a case study on a WEEE recycling plant in Korea. Resour Conserv Recycl 142:167–176

Pishvaee MS, Jolai F, Razmi J (2009) A stochastic optimization model for integrated forward/reverse logistics network design. J Manuf Syst 28:107–114

Pishvaee MS, Kianfar K, Karimi B (2010) Reverse logistics network design using simulated annealing. Int J Adv Manuf Technol 47:269–281

Pishvaee MS, Torabi SA (2010) A possibilistic programming approach for closed-loop supply chain network design under uncertainty. Fuzzy Sets Syst 161:2668–2683

Rachih H, Mhada FZ, Chiheb R (2019) Meta-heuristics for reverse logistics: a literature review and perspectives. Comput Ind Eng 127:45–62

Rahimi M, Ghezavati V (2018) Sustainable multi-period reverse logistics network design and planning under uncertainty utilizing conditional value at risk (CVaR) for recycling construction and demolition waste. J Clean Prod 172:1567–1581

Ramos TRP, Gomes MI, Barbosa-Póvoa AP (2014) Planning a sustainable reverse logistics system: balancing costs with environmental and social concerns. Omega 48:60–74

Raychaudhuri S (2008) Introduction to Monte Carlo simulation. Proceeding of the (2008) Winter Simulation Conference, Miami, FL, USA. IEEE 91–100. https://doi.org/10.1109/WSC.2008.4736059

Reddy KN, Kumar A, Choudhary A, Cheng TE (2022) Multi-period green reverse logistics network design: an improved Benders-decomposition-based heuristic approach. Eur J Oper Res 303:735–752

Reddy KN, Kumar A, Sarkis J, Tiwari MK (2020) Effect of carbon tax on reverse logistics network design. Comput Ind Eng 139:106184

Rentizelas A, Trivyza N, Oswald S, Siegl S (2021) Reverse supply network design for circular economy pathways of wind turbine blades in Europe. Int J Prod Res 60:1795

Ritchie N, Smith C (2009) Comparison of greenhouse gas emissions from waste-to-energy facilities and the Vancouver landfill. City of Vancouver

Rogers DS, Tibben-Lembke R (2001) An examination of reverse logistics practices. J Bus Logist 22:129–148

Safdar N, Khalid R, Ahmed W, Imran M (2020) Reverse logistics network design of e-waste management under the triple bottom line approach. J Clean Prod 272:122662

Shahparvari S, Soleimani H, Govindan K, Bodaghi B, Fard MT, Jafari H (2021) Closing the loop: redesigning sustainable reverse logistics network in uncertain supply chains. Comput Ind Eng 157:107093

Shi J, Li T, Peng S, Liu Z, Zhang H, Jiang Q (2015) Comparative life cycle assessment of remanufactured liquefied natural gas and diesel engines in China. J Clean Prod 101:129–136

Shokohyar S, Mansour S (2013) Simulation-based optimisation of a sustainable recovery network for waste from electrical and electronic equipment (WEEE). Int J Comput Integr Manuf 26:487–503

Srivastava SK (2008) Network design for reverse logistics. Omega 36:535–548

Ssb 2021. Population of municipalities in Norway (2021). Accessed on: https://www.ssb.no/en/statbank/table/11366/tableViewLayout1/ [04.05.2021]

Sun X, Yu H, Solvang WD (2022) Towards the smart and sustainable transformation of Reverse Logistics 4.0: a conceptualization and research agenda. Environ Sci Pollut Res 29:69275

Symons K (2021) Green-tech and Industry 4.0: supporting a sustainable future. Accessed on: https://www.orange-business.com/en/blogs/green-tech-and-industry-40-supporting-sustainable-future [09.02.2022]

Timperio G, Tiwari S, Gaspar Sánchez JM, García Martín RA, De Souza R (2020) Integrated decision support framework for distribution network design. Int J Prod Res 58:2490–2509

Tosarkani BM, Amin SH, Zolfagharinia H (2020) A scenario-based robust possibilistic model for a multi-objective electronic reverse logistics network. Int J Prod Econ 224:107557

Trochu J, Chaabane A, Ouhimmou M (2019) A two-stage stochastic optimization model for reverse logistics network design under dynamic suppliers’ locations. Waste Manage 95:569–583

Trochu J, Chaabane A, Ouhimmou M (2020) A carbon-constrained stochastic model for eco-efficient reverse logistics network design under environmental regulations in the CRD industry. J Clean Prod 245:118818

Vailshery LS (2017) Major electrical household appliances sales value in Norway 2016, by type of product. Accessed on: https://www.statista.com/statistics/746662/major-electrical-household-appliances-sales-value-in-norway-by-type-of-product/ [10.05.2021]

Wang XV, Wang L (2019) Digital twin-based WEEE recycling, recovery and remanufacturing in the background of Industry 4.0. Int J Prod Res 57:3892–3902

Wang Y, Zhe J, Wang X, Fan J, Wang Z, Wang H (2022) Collaborative multicenter reverse logistics network design with dynamic customer demands. Expert Syst Appl 206:117926

Wef 2017. Technology and innovation for the future of production: accelerating value creation. Accessed on: https://www3.weforum.org/docs/WEF_White_Paper_Technology_Innovation_Future_of_Production_2017.pdf [10.02.2022]

Xiao Z, Sun J, Shu W, Wang T (2019) Location-allocation problem of reverse logistics for end-of-life vehicles based on the measurement of carbon emissions. Comput Ind Eng 127:169–181

Xu W, Cui J, Liu B, Liu J, Yao B, Zhou Z (2021) Human-robot collaborative disassembly line balancing considering the safe strategy in remanufacturing. J Clean Prod 324:129158

Yan R, Yan B (2019) Location model for a remanufacturing reverse logistics network based on adaptive genetic algorithm. Simul-Trans Soc Model Simul Int 95:1069–1084

Yang CX, Chen JG (2020) Robust design for a multi-echelon regional construction and demolition waste reverse logistics network based on decision maker’s conservative attitude. J Clean Prod 273:122909

Ylä-Mella J, Poikela K, Lehtinen U, Tanskanen P, Román E, Keiski RL, Pongrácz E (2014) Overview of the WEEE directive and its implementation in the Nordic countries: national realisations and best practices. J Waste Manag 2014:457372

Yu H, Solvang WD (2018) Incorporating flexible capacity in the planning of a multi-product multi-echelon sustainable reverse logistics network under uncertainty. J Clean Prod 198:285–303

Yu H, Solvang WD (2020) A fuzzy-stochastic multi-objective model for sustainable planning of a closed-loop supply chain considering mixed uncertainty and network flexibility. J Clean Prod 266:121702

Yu H, Sun X, Solvang WD, Laporte G, Lee CKM (2020) A stochastic network design problem for hazardous waste management. J Clean Prod 277:123566

Zarbakhshnia N, Kannan D, Mavi RK, Soleimani H (2020) A novel sustainable multi-objective optimization model for forward and reverse logistics system under demand uncertainty. Ann Oper Res 295:843–880

Zarbakhshnia N, Soleimani H, Goh M, Razavi SS (2019) A novel multi-objective model for green forward and reverse logistics network design. J Clean Prod 208:1304–1316

Zhang L, Chen F, Ma X, Pan X (2020) Fuel economy in truck platooning: a literature overview and directions for future research. J Adv Transp 2020:2604012

Zhang Y, Liu S, Liu Y, Yang H, Li M, Huisingh D, Wang L (2018) The ‘internet of things’ enabled real-time scheduling for remanufacturing of automobile engines. J Clean Prod 185:562–575

Zolfagharinia H, Hafezi M, Farahani RZ, Fahimnia B (2014) A hybrid two-stock inventory control model for a reverse supply chain. Transp Res Part E: Logist Transp Rev 67:141–161

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Acknowledgements

Thanks are due to the editor and the anonymous reviewers for their invaluable comments and suggestions.

Open access funding provided by UiT The Arctic University of Norway (incl University Hospital of North Norway) This research is supported by the Industry 5.0 enabled Smart Logistics: A Global Perspective project financed by the Norwegian Directorate for Higher Education and Skills (HK-dir) under the Utforsk Programme (Grant: UTF-2021/10166) and by the UiT Aurora project MASCOT.

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Department of Industrial Engineering, UiT The Arctic University of Norway, 8514, Narvik, Norway

Xu Sun, Hao Yu & Wei Deng Solvang

Centre for Sustainable Operations and Resilient Supply Chains, Adelaide Business School and Institute for Sustainability Energy and Resources, University of Adelaide, Adelaide, SA, 5005, Australia

Kannan Govindan

School of Business, Woxsen University, Sadasivpet, Telangana, India

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Xu Sun: conceptualization, methodology, data curation, software, investigation, formal analysis, validation, writing—original draft, writing—review and editing. Hao Yu: conceptualization, methodology, data curation, software, investigation, formal analysis, validation, funding acquisition, writing—original draft, writing—review and editing. Wei Deng Solvang: conceptualization, funding acquisition, writing—review and editing. Kannan Govindan: conceptualization, writing—review and editing.

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Correspondence to Hao Yu .

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Sun, X., Yu, H., Solvang, W.D. et al. A two-level decision-support framework for reverse logistics network design considering technology transformation in Industry 4.0: a case study in Norway. Int J Adv Manuf Technol (2024). https://doi.org/10.1007/s00170-024-14121-6

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Received : 26 March 2024

Accepted : 08 July 2024

Published : 20 July 2024

DOI : https://doi.org/10.1007/s00170-024-14121-6

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24 July 2024

Airbus partners with avolon to explore future of hydrogen aviation.

Farnborough, 24 July 2024 -  Airbus has announced a new partnership with aircraft lessor, Avolon, to study the potential of hydrogen-powered aircraft, marking the very first collaboration of the ZEROe Project with an operating lessor. 

Announced at the Farnborough Airshow, Airbus and Avolon will investigate how future hydrogen-powered aircraft could be financed and commercialised, and how they might be supported by the leasing business model.

Airbus is putting significant resources into exploring how the industry can introduce hydrogen-powered aircraft and how it works on the ground with airports and airlines. The development of a viable hydrogen ecosystem is a key enabler of the industry’s goal to reach near zero emissions.

Paul Geaney, President and Chief Commercial Officer, Avolon, commented, “Joining the ZEROe Project is another step in Avolon’s sustainability journey and we look forward to building on our long-standing partnership with Airbus to consider how the next generation of aircraft will be financed and commercialised. It will take a wide ecosystem of contributors to overcome the challenges of hydrogen powered commercial flight, and Airbus is playing a crucial role in bringing partners together. While we continue to focus on supporting our customers in modernising their fleets with lower emissions aircraft, it is also vital we look beyond that at what can further drive our industry’s decarbonisation.”

Airbus Vice President ZEROe Project, Glenn Llewellyn, said,  “There is real value in bringing together industry players to help solve the challenges facing aviation. We know we can’t solve decarbonisation alone and welcome Avolon’s expertise and worldwide leadership in the aircraft leasing business. Working together to consider how the transition can be commercialised and financed for airline customers is crucial to success.”

Notes to editors 

Airbus is actively engaging with key partners at a regional and international level to facilitate the development of the hydrogen ecosystem. This is an essential step to get hydrogen powered aircraft in the air and help meet global aviation decarbonisation targets.

Airbus has also launched the “Hydrogen Hub at Airports'' programme to promote the further expansion of hydrogen infrastructure in aviation. To date, 18 Hydrogen Hubs at Airports have been launched. The Airbus ZEROe team is also actively engaged with more than 10 airlines to jointly study the deployment of hydrogen-powered aircraft in the future. Further information about Airbus’ hydrogen journey can be found  here . 

Avolon, established in 2010, has built a leading position in the global aircraft leasing industry and is ideally positioned to work with Airbus on exploring the potential of hydrogen aviation.

More information on Airbus at the Farnborough International Airshow is available  here .

#hydrogen #ZEROe #FIA2024

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