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• Published: 22 August 2024

Conceptual structure and the growth of scientific knowledge

• Kara Kedrick   ORCID: orcid.org/0000-0002-3410-5834 1 ,
• Ekaterina Levitskaya 2 &
• Russell J. Funk   ORCID: orcid.org/0000-0001-6670-4981 3  

Nature Human Behaviour ( 2024 ) Cite this article

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• Science, technology and society

How does scientific knowledge grow? This question has occupied a central place in the philosophy of science, stimulating heated debates but yielding no clear consensus. Many explanations can be understood in terms of whether and how they view the expansion of knowledge as proceeding through the accretion of scientific concepts into larger conceptual structures. Here we examine these views empirically by analysing 2,605,224 papers spanning five decades from both the social sciences (Web of Science) and the physical sciences (American Physical Society). Using natural language processing techniques, we create semantic networks of concepts, wherein noun phrases become linked when used in the same paper abstract. We then detect the core/periphery structures of these networks, wherein core concepts are densely connected sets of highly central nodes and periphery concepts are sparsely connected nodes that are highly connected to the core. For both the social and physical sciences, we observe increasingly rigid conceptual cores accompanied by the proliferation of periphery concepts. Subsequently, we examine the relationship between conceptual structure and the growth of scientific knowledge, finding that scientific works are more innovative in fields with cores that have higher conceptual churn and with larger cores. Furthermore, scientific consensus is associated with reduced conceptual churn and fewer conceptual cores. Overall, our findings suggest that while the organization of scientific concepts is important for the growth of knowledge, the mechanisms vary across time.

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Data availability.

The WoS data and the APS data are available from the Web of Science and the American Physical Society, respectively, but restrictions apply to the availability of these data, which were used under licence for the current study and so are not publicly available. If you are interested in accessing the WoS data, you can request access to the API through Clarivate, which requires an additional subscription or permission ( https://clarivate.com/products/scientific-and-academic-research/research-discovery-and-workflow-solutions/webofscience-platform/web-of-science-core-collection/ ). For access to the APS data, you can request permission directly from their website ( https://journals.aps.org/datasets/ ).

Code availability

The Python v.3 and Stata v.18 code we used to analyse and visualize the data for the current study are publicly available via Zenodo at https://doi.org/10.5281/zenodo.11533199 (ref. 49 ).

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Acknowledgements

We thank the National Science Foundation for financial support of work related to this project (grants no. 1829168 to R.J.F and no. 1932596 to R.J.F). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We also thank D. Hirschman, M. Park and Y. J. Kim for feedback on an earlier version of this work, and T. Gebhart for many helpful conversations and assistance with data and computation. Our work was presented as a poster at the 2nd Annual International Conference on the Science of Science and Innovation, as a poster at the 43rd Annual Meeting of the Cognitive Science Society, as a lightning talk at Networks 2021: A Joint Sunbelt and NetSci Conference, and as a poster at the 3rd North American Social Networks Conference.

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Kara Kedrick

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The study was conceptualized and designed by K.K., E.L. and R.J.F. The data analysis was conducted by K.K. and R.J.F. The manuscript was initially drafted by K.K., E.L. and R.J.F., with subsequent revisions made by K.K. and R.J.F.

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Extended data

Extended data fig. 1 concepts extracted from the text of an abstract..

This figure shows an example abstract from the APS data; the highlighted text indicates single-word and multi-word noun phrases identified as concepts using our extraction algorithm. Reproduced with permission from ref. 50 , American Physical Society.

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Kedrick, K., Levitskaya, E. & Funk, R.J. Conceptual structure and the growth of scientific knowledge. Nat Hum Behav (2024). https://doi.org/10.1038/s41562-024-01957-x

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Virtual power plants: an in-depth analysis of their advancements and importance as crucial players in modern power systems

• Sobhy Abdelkader 1 , 2 ,
• Jeremiah Amissah 1 &
• Omar Abdel-Rahim 1 , 3  

Energy, Sustainability and Society volume  14 , Article number:  52 ( 2024 ) Cite this article

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Virtual power plants (VPPs) represent a pivotal evolution in power system management, offering dynamic solutions to the challenges of renewable energy integration, grid stability, and demand-side management. Originally conceived as a concept to aggregate small-scale distributed energy resources, VPPs have evolved into sophisticated enablers of diverse energy assets, including solar panels, wind turbines, battery storage systems, and demand response units. This review article explores the evolution of VPPs and their pivotal roles as major stakeholders within contemporary power systems. The review opens with a definition of VPPs that clarifies both their fundamental traits and technological foundations. A historical examination of their development highlights major turning points and milestones that illustrate their transforming journey.

The methodology used for this article entailed a thorough examination to identify relevant studies, articles, and scholarly works related to virtual power plants. Academic databases were used to gather relevant literature. The literature was organized into categories helping to structure and present information in a logical flow based on the outline created for the review article . The discussions in the article show that the various functions that VPPs perform in power systems are of major interest. VPPs promote the seamless integration of renewable energy sources and provide optimum grid management by aggregating distributed energy resources, which improves sustainability. One of the important components of this evaluation involves taking market and policy considerations. Examining worldwide market patterns and forecasts reveals that VPP usage is rising, and that regulatory frameworks and incentives have a bigger impact on how well they integrate.

Overcoming obstacles is a necessary step towards realizing full VPP potential. For VPPs to be widely adopted, it is still essential to address technological and operational challenges as they arise. Diverse stakeholders must work together to overcome market obstacles and promote the expansion of the VPP market. This analysis highlights the potential for VPPs to propel the evolution of contemporary power systems toward a more sustainable and effective future by highlighting areas for future research and development.

There is an urgent need for creative and sustainable alternatives as the world’s need for energy rises, while fossil fuel-based power generation methods are increasingly scrutinized for their environmental effects [ 1 ]. Centralized alternating current power networks have been widely installed and used worldwide since the 1880s. Evaluations from the 2023 statistical global energy review [ 2 ] revealed that about 82% of the world’s primary energy source comes from fossil fuels like coal oil, and natural gas but their utilization produces greenhouse gas emissions that harm the environment and cause climate warming which has triggered the current global climate crisis [ 3 ]. The contribution of the different sources to world energy consumption is shown in Fig.  1 .

Global energy sources data

On the other hand, energy demand has grown significantly as a result of global economic growth. The demand for electricity has increased steadily over the past decades, by an average of 15%, and is anticipated to increase by 30% by 2040 [ 4 ]. This calls for innovative ideas to support the demand while looking out for the environment. Therefore, distributed energy resources (DERs) must be considered to lessen the detrimental environmental impacts of fossil fuels [ 1 ]. DERs are decentralized energy systems that produce, consume and store energy and are preferably located close to where electricity is consumed. These resources include batteries, wind turbines, solar panels, etc. DERs have been integrated in the power system networks (PSN) and have reduced the effects of energy generation from fossil fuels, furnishing stakeholders with economic and technical benefits [ 5 ]. While DERs offer power systems opportunities, they also bring with them challenges because of their intermittent and stochastic nature. DERs are often described as stochastic and intermittent due to their inherent characteristics and the factors that influence their generation. This nature of DERs is caused by elements including weather changes, operational uncertainties like maintenance, and equipment performance, which can result in unanticipated variations in DER generated or connected output. Instability in the grid is brought on by the rising use of DERs on the demand side, which worsens load demand fluctuations. As a result, real-time monitoring and dispatching are essential for the grid’s safe operation [ 6 , 7 , 8 , 9 ]. Furthermore, the power system needs more adaptability, which can be provided by several mechanisms, such as demand-side management, and energy storage systems (ESS). The only way to properly use these sources to increase their grid contributions is through optimal coordination between different agents [ 10 ].

Over the years, various research has been conducted to address the above challenges and many solutions have been proposed. VPPs have emerged as a ground-breaking solution in an era of energy transition and growing emphasis on sustainable power generation, altering the landscape of contemporary power systems [ 11 ]. VPPs have evolved as key players in promoting efficiency, flexibility, and resilience in the energy industry thanks to their capacity to integrate a variety of energy supplies and improve grid management [ 12 , 13 ].

A VPP is an energy management system that aggregates and coordinates diverse array of DERs, including photovoltaics, wind turbines, battery energy storage systems (BESS), and demand response technologies. The primary function of a VPP is to optimize the collection of these DERs in response to grid conditions, energy demand, and market signal. Through advanced control algorithms and real-time monitoring capabilities, VPPs dynamically adjust energy dispatch schedules, balances supply and demand, and enhance grid stability and reliability.

It is important to note that the concept of VPPs shares some basic similarities with that of the smart grid. However, unlike the VPP which focuses on the aggregation and optimization of DERs, smart grid, on the other hand, encompasses a broader range of functionalities aimed at modernizing the entire electricity supply chain. It can be said that the VPP augment the operation of the smart grid by providing ancillary support like supply and demand balancing to the smart grid.

The combination of these various resources enables the VPP to function as a cohesive and adaptable entity, to be able to react in real-time to grid signals and market conditions [ 14 , 15 ]. In the late 1990s, a pioneering shift in energy research and innovation emerged with the exploration of aggregating distributed resources into a unified virtual power entity, laying the groundwork for the conceptualization and development of VPPs [ 13 ]. Since then, VPPs have evolved from theoretical notions to real-world applications owing to technical developments, and breakthroughs in communication technology. The adoption of VPPs has been hastened by the spread of smart grid technologies and the rise of renewable energy resources (RERs), making them a crucial component of contemporary power systems [ 12 , 16 ].

It is impossible to overstate the importance of VPPs as significant participants in contemporary power systems. VPPs are essential for facilitating the seamless integration of intermittent renewable resources into power grids as they shift from fossil fuel-based generation to renewable-dominated systems [ 3 , 17 , 18 ]. In addition, VPPs can control electricity consumption patterns to correspond with variations in renewable generation. Demand-side management improves grid reliability and efficiency by lowering peak demand and reducing grid congestion [ 19 , 20 ]. VPPs also significantly contribute to the optimization of the energy market. VPPs are crucial actors in the developing electricity market because of their involvement in energy trading and the provision of ancillary services, which help to stabilize prices and maintain system resilience [ 11 , 21 ]. A typical architecture of a VPP is shown in Fig.  2 . With the aid of technology like cloud computing, a VPP aggregates various power consumers, ESS, and power generators to provide flexible adjustments. A communication protocol is used by the components of a VPP to transfer data to the VPP communication system. This communication protocol enables efficient coordination for the VPP to adjust energy production which allows supply to the grid with dependable cost-effective electricity via the electricity market [ 22 ]. The data acquisition platform aids in gathering information about the generation, consumption, and state of charge of the portfolio of DERs for optimal decision-making.

Architecture of a VPP

From the above discussion, it is clear that VPPs have become an important player in modern power systems, providing a dynamic and revolutionary method of managing energy. The idea of VPPs has recently received a lot of interest in energy systems. Studies have provided insightful information by highlighting their potential to transform the way we produce, distribute, and use power. It is critical to understand that this dynamic and developing discipline poses several notable issues, gaps, and areas that require added research.

In the review presented in [ 23 ], an overview of VPP operations, including the integration of DERs, controlled loads, and EVs for resource aggregation and cooperative optimization as well as market and grid operations, is the goal. The evaluation did however not discuss regulatory and policy issues that might affect how widely VPPs are used and implemented in the power market.

Also, the difficulties, solutions, and prospects related to the conceptual review of the conversion of a microgrid to a VPP have also been covered by [ 24 ]. The overview examines RERs integration, opportunities for VPPs in the field of smart distribution systems, and effective management mechanisms. The management mechanism, however, did not discuss the optimization of the DERs for optimal operation. Authors in [ 25 ] gave a thorough overview of the VPP concept and its potential advantages in integrating DERs to assist grid security and stability. Resource optimization, as a main part of the VPP operation, is not covered in this study. Also, Ref. [ 11 ] provided an overview of VPP models and how they interacted with various energy markets. Finding the most profitable VPP scheme to be implemented in each regulatory environment is the focus. DER integration challenges, which affect the operation of VPPs in the energy markets, are not considered in this study. In [ 26 ], the idea of VPPs to participate in various energy markets is proposed. The model evaluates the VPP's technical and commercial prospects. Engaging in various energy markets revolves around sharing of data between the VPP and operators of the markets. The issue of data privacy and cybersecurity was not included in this study. Authors in [ 27 ] provided a review with a focus on integrating DERs into the electricity grid. The assessment gave a summary of the development and use of VPP for carbon reduction in the Chinese power system. The study, however, did not cover technologies that can improve the management and operation of VPPs, notably in addressing the intermittent and volatile nature of DERs. In the domain of energy management, authors of [ 28 ] provided a summary of resource scheduling in VPPs and addressed questions on scheduling procedures. However, despite concentrating on both technical and economic elements of scheduling in VPPs, this analysis did not address potential influences like the state of the energy markets that could have an impact on the scheduling issue. The case of a multi-energy coupled VPP has been presented in [ 29 ]. The purpose of this study was to address the advantages of multi-energy linked VPPs engaging in various energy markets. The issue of enhanced communication technology, data privacy and cybersecurity are some of the challenges which were not featured in this study.

The idea and structure of VPPs are concisely described in [ 30 ] with regard to its two main goals—energy management and power markets. Solutions are suggested to alleviate the problems with DER uncertainties that were highlighted. In order to create future sustainable power grids, authors of [ 3 ] have presented a comprehensive overview of the cutting-edge VPP technology. The study discusses recent technological advancements as well as the significant economic benefits of VPPs. However, this study did not cover the legislation that specifies how VPPs can access and participate in the energy markets. Below are some of the gaps found in existing literature:

Analysis of cybersecurity and data privacy as crucial elements in the VPP development.

Environmental and sustainability focus. The SDGs that VPPs could support, and how the support can be achieved.

Rigor analysis of legislation or regulations which will dictate the operation of the VPP.

Considering the above research gaps in literature, this review article advances the knowledge of energy systems by providing a thorough analysis of VPPs, their historical development, and their crucial roles as essential stakeholders in modern power systems. There will be focus on technical and market operations, real-world case studies, the identification of challenges and prospects, the emphasis on technical and market operations highlight the relevance and transformative potential of VPPs in creating sustainable and effective energy ecosystems. The contributions of this paper can be summarized as follows:

Comprehensive understanding of VPPs to provide readers with a concise definition, key traits, and core values of VPPs.

Tracing historical developments of VPPs from their theoretical roots to their current popularity.

Emphasis on VPPs as key stakeholders in modern power systems. This emphasis highlights the vital role that VPPs play in ensuring grid stability, fostering the integration of RES, and promoting sustainability.

Integration of technical and market aspects by providing a comprehensive analysis of VPP operation. This integration is crucial as it shows that VPPs actively participate in energy markets and actively optimize energy resources, which facilitates effective electricity trading and grid balancing.

Application of cybersecurity and data privacy techniques that protect the VPP from cyber threats, assuring grid stability, data integrity, and consumer trust in the ever-changing energy sector.

Real-world case studies of VPP deployments to offer insights and experiences.

Discussion of the regulatory frameworks that control how VPP operates.

Identification of challenges, providing recommendations, and prospects.

VPP advancements

The traditional centralized power generation model is being replaced by a decentralized, adaptable, and sustainable system thanks to VPP, which represents a revolutionary paradigm in the energy sector. Early theoretical ideas from the late twentieth century established the foundation for the development of VPPs and their eventual prominence in modern power systems [ 31 , 32 ]. This part of the paper will focus on the evolutionary journey of VPPs, highlighting the early concepts, key milestones, and technological advancements that shaped their development into critical enablers of modern energy ecosystems.

The embryonic stage (1990s–2000s)

Although the idea of VPPs was initially put forth in the 1997 [ 13 ] by Dr. Shimon Awerbuch, it did not really take off until the early 2000s. Early academic publications proposed the idea of coordinating and optimizing a portfolio of distributed energy resources to increase operational effectiveness and grid reliability. However, due to limited technological capabilities and a lack of enabling legal frameworks, the practical deployment of VPPs remained primarily theoretical at this point. Also, the absence of developed distributed generating technology, the high cost of communication and control systems, and the regulatory uncertainties surrounding VPPs were some of the causes of lack of practical deployment. References [ 33 , 34 , 35 , 36 , 37 , 38 ] provides a description of the early years concept of the VPP, its difficulties, including consumer resistance to participating, economic viability in infrastructure setup, investors' perceptions of risk, and grid operators' reluctance to adopt the unique strategy.

The breakthrough stage (2010s–2020)

The growth years presented milestones and key turning points in VPP deployment from the early years. At this point, the VPP has encountered rapid growth as a result of increasing interest in adoption of distributed generation technology, decreasing communication and control system costs, and expanding regulatory backing for VPPs. In a declaration on the future of the European electricity market that was issued in 2011, the European Commission emphasized the potential of VPPs to increase grid flexibility and integrate renewable energy. This communication aided in increasing policymakers’ and stakeholders’ understanding of VPPs [ 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. Later, in March 2023, it was amended in Strasbourg, France, by recommending an expansion of the EU electricity market structure to further integrate RESs, improve customer protection and industrial competitiveness [ 46 ]. Notable milestones of the growth years include grid integration [ 47 ], market participation [ 48 ], technological advancement, and demand response programs[ 49 ], allowing aggregated DERs to respond to grid signals and enhance grid stability [ 50 ]. This marked the initial practical application of VPPs, showcasing their ability to support grid operations.

The future (2021 and beyond)

The demand for flexible grids and the incorporation of RESs is anticipated to drive further growth of VPP. VPPs are viewed as one of the techniques to lower carbon emissions and increase energy efficiency [ 51 ]. The key drivers for this growth are the increasing deployment of distributed generation technologies (DGT), falling cost of communication and control systems, growing regulatory support for VPPs, and also prosumers who want to receive incentives for their surplus generation [ 45 ].

In summary, it is evident that early theoretical insights were followed by practical and revolutionary applications in modern power systems as VPPs evolved. The development of VPPs into essential enablers of decentralized, flexible, and sustainable energy ecosystems has been shaped by significant turning points and milestones, as well as technological development and innovations. A thorough summary is provided in Table  1 for further reading.

VPP planning, roles, and sustainability

VPP planning is a crucial and multifaceted process that entails strategic design, coordination, and optimization to provide effective and dependable energy management. The main goal of VPP planning is to maximize the advantages for both grid operators and consumers while optimizing the potential of varied DERs and guaranteeing their seamless integration with the power grid. The planning approach necessitates a thorough comprehension of the energy landscape, individual DER capabilities, market dynamics, and regulatory frameworks.

To ensure that VPPs perform as planned and expected, their technological constraints must be recognized and measured [ 55 ]. Before interacting with external and internal elements, the VPP schedules and plans its operations. It is also a good performance criterion for the VPP to keep accurate data to engage the electricity market and reap favorable effects by analyzing the uncertainties resulting from elements like weather and producing forecasts with a high level of assertiveness [ 56 ]. The issue of forecasting will be discussed later in the section dedicated to the roles of VPPs. The VPP operations may be constrained by infrastructure, technological, and technical limits [ 57 ]. The model shown in [ 26 ] emphasizes the importance of effectively measuring and managing controllable loads in heating, ventilation, and air conditioning (HVAC) systems. Also, it emphasizes the significance of photovoltaic (PV) and BESS influences in determining the viability and adaptability of a VPP. VPPs can improve their coordination with all stakeholders by developing a methodical technique for evaluating and controlling power availability at time intervals. Surely, this enhances the performance of the VPP and enables a more seamless interaction with the power grid.

VPP planning also includes economic and legal factors in addition to the technical ones. The aspects of technical and economic frameworks of the VPP will be delved deeper in the sections dedicated to the technical and economic aspects of VPPs. It is important to note that good operational planning directly affects good economic outcomes [ 55 ]. The economic viability of the VPP and its prospective revenue streams, including energy trading [ 58 ], demand response participation [ 59 ], and the supply of ancillary services [ 21 ], are assessed using financial models and cost–benefit analysis [ 60 ]. Collaboration with grid operators, legislators, and other stakeholders is also necessary for successful VPP planning to overcome regulatory obstacles and build an environment that facilitates VPP integration. To ensure effective planning, the VPP should be continuously monitored and improved to respond to shifting grid conditions and market dynamics [ 61 ]:

VPP planning opens the way for a more resilient, and sustainable energy future by integrating technological, economic, and regulatory factors. It has enormous potential to optimize resource use, improve grid stability, and contribute to the global quest for a reduction in carbon emissions produced by energy systems. It is therefore imperative that stakeholders comprehend the complexities of VPP planning to influence the energy industry’s future and advance the cause for greener and a more sustainable and effective energy future. This planning phase can be summarized as: aggregating existing and new energy resources.

Ownership structure: The internal ownership structure of VPPs can vary depending on the specific implementation and stakeholders involved. It may involve collaboration between multiple stakeholders including energy producers, consumers, and aggregators.

Regulating and market considerations governing energy markets and grid operations.

Implementation of an energy management system to provide functionalities such as real-time monitoring, forecasting, dispatching, and scheduling energy resources to meet grid requirements and maximize economic benefits.

Agreement formulation such as power purchase agreements.

Profit sharing mechanisms taking into consideration factors such as investment contributions, operational cost, risk allocation, etc.

Compensation structures for various stakeholders involved in the VPP including incentives for demand response participations from consumers.

The way electricity is produced, controlled, and used has been revolutionized by VPPs as explained in the previous sections. VPPs are flexible and dynamic entities that perform a variety of roles in modern power systems. Because of the variety and importance of their tasks, they are key players in creating an energy ecosystem that is sustainable, effective, and resilient. The following are the main responsibilities of VPPs in power systems.

Aggregation of DERs: Various DERs, such as solar panels, wind turbines, ESS, EVs, and demand response loads are gathered by VPPs. VPPs construct an adaptable and manageable portfolio of assets by combining these decentralized resources into a single virtual entity. Through this aggregation, grid management is improved, enabling the VPP to maximize DER usage in response to grid signals. The DERs’ activity within the VPP is managed and coordinated by the VPP operators. The main responsibility is resource optimization and involvement in energy markets.

The authors of [ 62 ] described the aggregator concept as a central control node that collects information from both the power grid and controlled loads. A load aggregator can also serve as a conduit between the controllable loads and the grid operator, allowing the regulated management to consider user and grid benefits simultaneously. When interfacing with the power market, aggregators are employed in power charging models for EVs to help optimize the batteries’ charging as well as the modeling of driving patterns and price estimates [ 63 ]. As DERs are dispatched depending on compensation rates and power levels, an aggregator can stand in for them to maximize profits [ 64 ]. Furthermore, in [ 65 ], for a power market with bilateral contracts, the aggregator has the facility to select between various power plants based on power-cost-based offers.

Grid stabilization and reliability: VPPs make a major contribution to the reliability and stability of the grid. VPPs maintain a stable and steady supply of electricity while minimizing the possibility of blackouts and voltage variations by balancing energy generation and consumption from various DERs [ 66 ]. They are able to provide ancillary services like frequency regulation and voltage management, which are essential for preserving grid stability [ 67 ]. The general stability and dependability of the electrical system are the responsibility of grid operators. In accordance with grid norms and standards, the grid operators work with VPP operators to incorporate DERs.

Renewable energy integration: In 2016, in Paris, an emission reduction plan was enacted which has made the use of DERs very essential [ 68 , 69 , 70 ]. This integration is the VPP operator’s responsibility. This is accomplished by coordinating the operation of diverse RERs, such as solar panels, wind turbines, and such that they work as a unified system. However, due to their erratic nature, integrating RESs into the power systems presents its own challenges [ 71 , 72 ]. These challenges come about because of generation fluctuations due to weather conditions and time of the day. The variability adds complexity to power system operations. For instance, rapid changes in wind speed or cloud cover can result in fluctuations in generation, requiring grid operators to make quick adjustments to maintain system stability. VPPs take on this problem by combining several RESs and using intelligent management processes, they make it easier for the integration of the RESs effectively. They ensure the integration of these RESs to provide a steady supply of electricity while lowering reliance on conventional fossil fuel-based power plants.

Authors in [ 72 ] proposed a solution for integration of RESs into the grid to maintain power quality. This is important because RESs are becoming increasingly popular due to their environmental benefits, but they can also introduce power quality issues. This is a challenge that a VPP is sought to address. Large scale penetration of RESs means a hike in capital and operational cost. Authors in [ 73 ] discussed a mechanism that could aid in lowering the high cost of RESs integration and bringing electricity prices into affordable band. Spreading the benefits of renewable integration into the spheres of agriculture, where in [ 74 ], authors have created a mechanism to encourage energy-efficient agriculture by minimizing dependency on fossil fuels for water-table pumping. Through the aggregation and optimization of DERs, VPPs enable farmers to reduce their dependency on fossil fuels while enhancing energy efficiency and resilience in agricultural practices. This synergy not only fosters economic sustainability for farmers, but also contributes to the broader goal of renewable energy integration, paving the way for a greener energy future.

Successful integration depends on several important aspects. Forecasting methods that accurately estimate the patterns of RESs generation must be put in place [ 75 , 76 ]. This allows better grid management and optimization of the DERs. The VPP employs such tools to better manage the generation of DERs. A summary of various forecasting techniques provided in the literature is listed in Table  2 . Analysis of forecasting models to aid in the integration of RESs in the context of VPPs has been provided in [ 77 ].

Moreover, for optimal integration of RESs, the power grid must be modernized with smart technologies. Real-time monitoring, control, and communication between DERs and grid infrastructure are made possible using smart approaches like the VPP [ 16 , 78 , 79 ]. This improves the reliability and effectiveness of the grid. Additionally, VPPs provide beneficial grid functions, such as frequency regulation [ 67 ] and voltage control [ 80 ] in addition to balancing energy supply and demand [ 81 ]. These services boost the grid’s dependability and resilience even more, promoting a stronger energy infrastructure that can handle the rising proportion of RESs.

The VPP approach to integrating RESs into the power grid is a cutting-edge strategy that is revolutionizing the way energy is produced, distributed, and consumed. VPPs offer an effective response to the problems caused by intermittent renewables by utilizing the combined potential of DERs and modern technology. VPPs will unquestionably be essential in advancing the transition to a cleaner, more dependable, and efficient energy system as the world progresses toward a sustainable energy future.

DER technologies applied in VPPs

In VPPs, various DERs are used, including solar panels, wind turbines, ESS, EVs, and demand response loads. These DERs are aggregated and optimized within the VPPs, allowing for efficient management and coordination [ 55 ]. By harnessing the collective capacity of diverse DERs, VPPs enhance grid stability, enable renewable energy integration, and support demand response strategies, contributing to a more sustainable and flexible energy ecosystem. A VPP should ensure that DER integration keeps the system operating properly by ensuring the stakeholders’ continual consumption requirements [ 92 ]. Various DER technologies applied in VPPs in the reviewed literature are summarized in Table  3 .

Out of the 15 References evaluated regarding DER technologies used in VPPs, it is evident from Table  3 that wind turbines and solar panels hold the largest share, as shown in Fig.  3 . It proves how easily the technology of wind turbines and solar panels have been embraced. However, more renewables should be added to the energy mix to hasten the shift to a less carbon-oriented energy landscape.

DER application in literature

VPP sustainability focus

One of the viable ways to address numerous Sustainable Development Goals (SDGs) of the United Nations (UN) and contribute to a more sustainable energy future is through VPPs. By encouraging the integration of RESs and boosting energy efficiency, VPPs, as a fundamental enabler of the energy transition, contribute significantly to achieving SDG 7 (Affordable and Clean Energy). VPPs promote the integration of sustainable energy into the power grid by aggregating and optimizing DERs thereby lowering greenhouse gas emissions and addressing climate change (SDG 13—Climate Action).

Additionally, through promoting technological advancements and innovation in the energy industry, VPPs provide a substantial contribution to SDG 9 (Industry, Innovation, and Infrastructure). VPPs promote grid modernization and improve overall energy infrastructure by integrating smart grid technologies, advanced analytics, and artificial intelligence. These developments result in more effective and adaptable energy systems, advancing the objectives of SDG 9 to develop robust infrastructure and encourage sustainable industrialization.

However, while VPPs offer considerable potential for achieving various SDGs, several challenges must be addressed to ensure their long-term sustainability. Access to VPP technologies must be equally available, as this can influence SDG 1 (No Poverty) and SDG 10 (Reduced Inequalities). For VPPs to be deployed in a way that supports SDG goals for eradicating poverty and minimizing inequality, marginalized people and neglected areas must be able to benefit from them. In simple terms, it is essential to make sure that everyone has an equal opportunity to profit from VPPs to realize SDG 1 and SDG 10. This calls for figuring out ways to make technology more accessible and inexpensive for everyone, especially those living in rural or underdeveloped areas. By doing this, VPPs may contribute to the development of a more just and sustainable energy future in which everyone, regardless of financial situation, has access to safe and dependable energy.

Furthermore, the environmental impact of VPPs [ 108 ] and their associated technologies require careful consideration to achieve SDG 12 (Responsible Consumption and Production). Lithium-ion batteries, which are used in ESS, are one example of a crucial mineral and material whose demand is on the rise, prompting questions regarding responsible sourcing, recycling, and end-of-life management. It is not a surprise that there has been extensive literature on ways to increase the lifespan of lithium-ion batteries [ 109 ]. Authors in [ 110 ] proposed a precise lifespan model for the battery cells used in VPP applications. To reduce the negative environmental and social effects of VPP deployment, sustainable methods must be implemented in material sourcing and VPP operation.

Moreover, numerous steps can be taken to guarantee the sustainability of a VPP itself. Stakeholders must work together to build supporting regulatory frameworks and financial incentives for VPP development. VPPs will become more widely available and long-lasting if investments are encouraged in their research, development, and implementation. This will also encourage technological breakthroughs and cost reductions. Also, a successful integration of VPPs into the energy economy depends on raising consumer awareness and engagement. The acceptance of VPP technology can be increased by educating consumers about the advantages of VPP participation, such as lower energy costs and increased grid reliability [ 111 , 112 ].

To sum up, VPPs have a significant potential to help achieve several SDGs pertaining to renewable energy, tackling climate change, and sustainable infrastructure. They support SDGs 7 and 9 by fostering the integration of RESs and improving energy efficiency. To achieve more general sustainability goals, it is necessary to address issues with fair access to VPP advantages and responsible use and production. VPPs are critical enablers of a greener, more inclusive, and resilient energy future and can help accomplish specific SDGs by establishing supportive policies, encouraging innovation and consumer engagement. Using VPP's revolutionary potential in promoting the UN’s sustainability agenda [ 113 ] requires advocating for and making contributions to their sustainable deployment and optimization.

Cybersecurity and data privacy

The protection of the grid’s stability and dependability is one of the main justifications for prioritizing cybersecurity in VPP application. As crucial nodes in the grid, VPPs coordinate the functioning of DERs and provide a constant and reliable supply of electricity. A cyber-attack on a VPP has the potential to impair energy production, distribution, and grid management, resulting in power outages [ 114 ] and large financial losses.

The efficient operation of VPPs depends on data integrity [ 115 ]. For making decisions about the generation, distribution, and use of energy, VPPs depend on accurate data. Cybersecurity measures guard against data alteration or manipulation, ensuring that VPP operators have reliable data for maximizing energy resources and delivering crucial grid services. In order to increase consumer and prosumer confidence in VPP services, data privacy procedures on data collection and usage are essential [ 116 ].

VPPs are desirable targets for cybercriminals because of their crucial functions in grid management and their strength in the marketplace. VPPs are shielded by cybersecurity from a variety of dangers, such as malware and hacker attempts [ 117 ]. To address the cybersecurity issues, various approaches have been suggested and has been categorized by [ 118 ] as human and non-human approaches. Human approaches like updates and incremental patches installation aids in robust security posture, addressing vulnerabilities in software, but also require reboots causing downtime to regular operations. Engaging in customer interactions also creates awareness to recognize and respond to potential threats. However, allocating time and resources may be challenging for organizations with limited budgets and manpower.

Non-human approaches like the adoption of blockchain technology reduce the risk of single point failure as the technology operates on a decentralized network. This enhances resilience, making it more challenging for attackers to compromise the entire system. Another non-human approach is cloud computing which typically encrypts data during transmission and storage. This safeguards sensitive information from interception or unauthorized access.

Data privacy and cybersecurity are essential elements of VPP operations. They protect against cyberthreats, guarantee data integrity, enhance grid stability [ 119 ], promote consumer trust, enable regulatory compliance, and support the viability of VPPs financially. To ensure a secure, dependable, and sustainable energy future, cybersecurity and data privacy must be prioritized as VPPs continue to develop and broaden their role in contemporary energy systems [ 120 ].

Regulation and compliance

The operation of VPPs is greatly influenced by legislative or regulatory activities. This section will cover the regulatory structure that governs VPPs, emphasizing significant importance and their effects on the energy industry.

In the domain of grid integration standard and requirements, regulating bodies establish grid codes and integration standards that the VPP must adhere to when connecting to the electrical grid. The safe and dependable grid integration of DERs is ensured by these standards. The basis for secure VPP functioning is grid codes and standards. A manual for connecting DERs to the utility grid is provided by the IEC 62786. DER planning, operation, protection, and connectivity to distribution networks are the key applications. A global agreement on the use of DER in electrical power systems is being sought through the IEEE 1547 set of standards. This standard has received widespread acceptance on a global scale in outlining the requirements for the design, implementation, testing, and security of all sorts of DERs. Due to the increased penetration of DERs and the need to maintain system stability, the IEEE 1547 has recently been updated to IEEE 1547-2018 and IEEE 1547.1-2020 [ 121 ]. A crucial series of standards released to control the grid’s interconnection and operability is the IEEE 2030. It is modified to implement cutting-edge communication and information technologies that provide interoperability solutions for the promotion of DER connectivity.

The European Committee for Electrotechnical Standardization (CENLEC), which is made up of 34 European Nations, oversees standardization efforts to increase commercial viability and foster technological growth. The CENLEC released the EN 50549-1 and EN 50549-2 DER integration standards with the goal of addressing all DER capabilities that are necessary for operation in tandem with distribution networks [ 121 ].

Also, there may be regional variations in regulations governing the integration of DERs with the grid [ 121 ]. For example, Canadian standards C22.3 No. 9 and C22.2 No. 257 offer technical advice for DER integration with the grid at medium and low voltage under 50 kV and low voltage systems under 0.6 kV, respectively. The British standard BS EN50438:2007 also offers technical advice for DER interconnection. The VDE-AR-N 4105 standard in Germany also offers technical recommendations for connecting DERs and low voltage systems. The JEAG.9701-2001 standard in Japan offers technical recommendations for distributed generating grid-connection. The standard permits DER owners to sell surplus energy to utility grids and mandates that power grids supply DER owners with backup power.

Various environmental and sustainability regulations may pertain to different jurisdictions [ 122 ], and they may provide incentives or requirements for VPPs to assist the integration of RERs and the reduction of emissions. In certain regions, these rules may have an impact on how VPPs function. The level of support for VPPs that use RERs may vary depending on the targets and incentives that jurisdictions set for renewable energy [ 123 ].

VPP operators and stakeholders must negotiate a complicated regulatory environment that is unique to their locations. It is essential for the implementation and operation of VPPs to comprehend and follow local legislations. Furthermore, as VPPs become more crucial to the world’s energy landscape, regulators and industry participants must cooperate to unify rules and encourage uniformity in grid integration techniques across various jurisdictions.

Technical aspects of VPPs

The technical operations of a VPP involve a series of complex and coordinated processes to efficiently manage and optimize the aggregated DERs within the VPP. According to Ref. [ 124 ], the technical features of VPPs provide dynamic interaction for the integration of power distribution based on auxiliary services. These technical operations can vary depending on the specific architecture and goals of the respective VPP. This section of the paper delves into the technical intricacies of VPPs and explores their roles as key enablers in the transition toward a sustainable and resilient energy future. Some of these technical aspects of the VPPs are emphasized below:

Resource optimization and scheduling: In a VPP, resource optimization and scheduling of various DERS are essential to achieve efficient and reliable energy management [ 28 , 125 ]. It is also important to note that advanced algorithms and real-time data analytics [ 76 ] as summarized earlier in Table  2 are employed to forecast energy generation and demand profiles, ensuring dynamic resource optimization. The VPP intelligently dispatches DERs based on grid conditions and market signals, balancing supply and demand to enhance grid stability and maximize revenue generation [ 126 ]. By coordinating diverse DERs, VPPs optimize energy use, contribute to renewable integration, and support grid flexibility, making them crucial enablers in the transition to a sustainable resilient energy ecosystem.

A summary of the relevant literature in accordance with resource optimization and scheduling is provided in Table 4 .

Load balancing and grid support/ancillary service: The load balancing and grid support functions of a VPP are very crucial [ 135 ]. The VPP dynamically modifies energy generation and consumption to fit grid demands by aggregating and optimizing various DERs. While storing excess energy during times of low demand, the VPP can supply additional power from DERs during times of peak demand to balance out high demand. This load-balancing ability makes VPPs essential for guaranteeing a dependable and resilient electricity supply since it improves grid stability, lowers grid stress, and adds to overall grid support.

In addition to its role of aggregating and optimizing DERs, a VPP offers a range of essential ancillary services. These services include frequency regulation. This is achieved by maintaining grid frequency within acceptable bounds through rapid power adjustment [ 136 , 137 , 138 , 139 ]. VPPs also provide voltage support by injecting or absorbing reactive power to stabilize voltage levels [ 80 , 140 , 141 ].

Moreover, VPPs contribute to peak regulation, managing demand during high load periods to alleviate grid stress [ 142 , 143 , 144 ]. The comprehensive suite of ancillary services offered by VPPs ensures grid stability, enhances reliability, and facilitates the integration of RESs, making them vital assets in modern power systems.

Demand response and load management: A VPP inherent components of demand response and load control enable effective energy usage. By actively communicating with connected consumers to alter electricity consumption in response to grid circumstances and price signals, VPPs participate in demand response. In order to avoid peak demand times and lessen grid load, VPPs optimize the scheduling of operations and equipment that consume a lot of electricity [ 59 , 81 , 96 ]. This demand-side flexibility not only supports grid stability, but also empowers consumers to actively participate in energy conservation, contributing to a sustainable energy ecosystem [ 66 , 145 ]. The VPP’s ability to efficiently balance energy supply and demand through demand response and load management strategies makes it a pivotal stakeholder in modern power systems.

The technical aspects of VPPs represent a dynamic and transformative force in the energy sector. VPPs provide effective renewable energy integration, grid stability, and demand response capabilities by aggregating and optimizing various DERs.

Market/economical aspect of VPP

VPPs provide an appealing scenario for the future of energy systems in terms of their commercial and financial prepositions. VPPs can completely alter the economics of electricity generation and consumption as they are dynamic aggregators of various DERs. VPPs maximize the use of DERs, optimize income generation, and improve participation in the energy market [ 11 ]. The VPP does this via real-time data analytics, complex forecasting algorithms, and clever energy trading methods. As a result of their capacity to offer a versatile and dispatchable portfolio of assets (DERs), VPPs are better equipped to meet swiftly to dynamic market conditions, such as energy pricing and demand patterns. VPPs deliver a strong economic case for sustainability, affordability, and resilience in the energy ecosystem by making it possible to efficiently deploy renewable sources of energy, support demand response programs, and provide ancillary services to the grid. VPPs technology’s commercial implications hold significant promise for developing a more effective, competitive, and customer-focused energy landscape as it continues to advance.

Currently, the majority of jurisdictions have already started deregulation or liberalization and competition-opening process in their individual power markets [ 11 ]. In order to finance new infrastructure investments, increase the economic efficiency of power company operations, and particularly lower the ultimate prices of electricity delivery, deregulation or privatization has been advocated [ 146 ]. A vertical structure as stipulated by [ 146 ], where all activities were merged, was replaced with an organization where generation, transmission, distribution, and commerce work separately as a result of this reform in the energy sector.

Additionally, the large integration of renewables into the power grid that characterizes the contemporary energy landscape suggests a greater need for the system’s balancing mechanism due to the random nature of the RESs generation schedule. One significant benefit of VPPs is that they boost their shared profit by selling energy on behalf of the DER owners to improve the balancing mechanism when they access the wholesale electricity markets. The participation of VPPs in various electricity markets is covered in this section.

Day-ahead market: Day-ahead market refers to the buying and selling of electricity on the day before the actual production and delivery. VPPs actively participate in the day-ahead market by supplying their aggregated portfolio of DERs for electricity trading. VPPs forecast energy generation trends for the next day using advanced forecasting and data analytics. Based on these insights and market prices, VPPs strategically bid these aggregated resources to optimize revenue generation [ 84 , 147 , 148 , 149 , 150 , 151 ].

Ancillary service market: VPPs actively participate in the ancillary services market by providing critical assistance to the electric grid. The VPP does this by dynamically altering the output of their aggregated DERs. VPPs respond in real-time to grid signals to maintain stability, assure a continuous power supply, and improve grid reliability. With this, VPPs play an important role in supporting grid operations and optimizing grid performance. Several studies have incorporated the ability to engage in ancillary services markets into VPP modeling in order to enable regulation that ensures the security of electricity supply [ 26 , 143 , 150 , 152 , 153 , 154 , 155 , 156 ].

Reserve market: In the reserve market, VPPs actively participate by offering their combined output of DER as a reserve capacity to support the grid’s reliability. VPPs reserve a portion of their generated power from the DERs, ready to be dispatched within short notice to address sudden changes in electricity demand and supply or even an outage of grid operator’s outage of generators. By participating in the reserve market, VPPs offer a valuable and flexible solution for grid operators to maintain grid reliability. As VPP technology advances, their involvement in the reserve market will become ever more vital in contributing to the efficient and secure operation of the electric grid. Various strategies to make ideal or optimal reserve market decisions have been studied in several papers. According to the findings of these studies, the reserve market is more significant at times of peak demand since a contingency can have a higher impact [ 26 , 127 , 157 , 158 , 159 , 160 ].

Intra-day/real-time market: The VPP actively participates in the intra-day market by precisely adjusting the energy traded in the day-ahead market. The VPP strategically optimizes its DER dispatch and offers flexible resources in response to dynamic market prices and grid needs [ 11 ].

Although intraday markets enable VPPs to adjust scheduled energy after the day-ahead market, an exchange power imbalance may still emerge as the dispatch time approaches. VPPs can thus participate in real-time balancing markets to avoid penalties. The goal of the real-time market is to reduce the imbalance errors and their associated cost. The various electricity markets in which the VPP participates are provided in Table 5 to outline the key characteristics. Figure 4 also gives a graphical analysis of the key characteristics of the electricity market that the VPP operates in.

Electricity markets characteristics

Real-world implementation of VPPs

VPPs in the real world provide fascinating insights on their revolutionary impact on contemporary power systems. VPP implementations around the world demonstrate their adaptability in maximizing DERs. These examples elaborate on the value of VPPs in grid stability, renewable generation, and demand response. VPP projects are becoming more common, proving their potential to revolutionize energy systems. The VPP market is expected to grow from $1.3billion in 2019 to $5.9billion in 2027, with a compound annual growth rate of 21.3% from 2020 to 2027 [ 25 ]. In Norway, Statkraf is the world’s largest VPP with a capacity of 10GW from over 1000 aggregated assets. Recently, Tesla announced to scale up the south Australia VPP which connects assets from 4000 to 50,000 homes, which will make it the world’s largest VPP [ 172 ]. Storing and distributing power from residential and commercial customers, Tesla’s Powerpacks and Powerwall promote grid dependability and the integration of renewable energy. These real-world examples demonstrate how important VPPs are in creating a global energy ecosystem that is robust, efficient, and sustainable. Selected real-world applications [ 124 , 172 ] are summarized in Table  6 .

Applications of VPPs in the real world have offered an important lesson that will guide their development, deployment, and scalability. Key insights from these applications include the following but not limited to:

Flexibility and scalability: The significance of developing flexible and scalable systems has been shown by the successful VPP deployments. VPPs support a variety of DERs and adjust to shifting market dynamics and grid conditions.

Integration of DERs: For the VPP to operate at its best, several DERs must be integrated into a single, coordinated system. Advanced data analytics and control algorithms are essential for managing DERs efficiently and maximizing their contributions, as demonstrated by real-world applications.

Interoperability and interconnection: VPPs generally operate in sophisticated energy ecosystems with a variety of stakeholders. Smooth VPP integration and operation require interoperability and seamless interconnection with grid operators, and other market participants.

Market participation: The significance of active market participation has been emphasized by real-world VPP applications. Using effective energy trading techniques and intelligent bidding in electricity markets. VPPs can maximize income production and assist the integration of RESs at a fair price.

The ongoing development and deployment of VPPs can be improved by taking lessons from these practical applications, ensuring that they continue to contribute to a sustainable, effective, and decentralized energy future.

However, despite the successes chalked up by these projects, there are still challenges that must be addressed. Cybersecurity threats, consumer engagement, data management and analytics, achieving a positive return on investment and profitability are some of the model challenges that these projects face. Collaboration between stakeholders is necessary to overcome these obstacles.

Conclusions

VPPs have become transformative solutions revolutionizing the modern energy landscape. Applications in the real world have sounded their importance and have also demonstrated the adaptability and advantages of VPPs. VPPs have shown that they can promote the integration of renewable energy sources, aggregate and optimize a variety of DERs, and facilitate effective demand response.

Flexibility and scalability, which enable seamless adaptability to shifting grid conditions and market dynamics, have been shown to be essential for successful VPP adoption. VPPs have been able to improve cost-effective renewable energy integration and optimize revenue generation through active market participation and smart bidding tactics. Additionally, for VPPs including residential or commercial participants, consumer engagement and education are crucial for assuring buy-in and demand response programs.

Embracing the lessons learnt in the referenced literature, a VPP stands as a pivotal enabler in our journey towards a sustainable, decentralized, and resilient energy future. There can be an effective and customer-focused energy ecosystem that leads the path for a greener and more sustainable society by fully utilizing VPPs and maximizing their important contributions.

The ability of VPPs to maximize DERs, boost renewable energy integration, and improve grid stability makes them a crucial element in reaching a sustainable energy future. A VPP has the undisputed potential to change the energy landscape. The successful operation of VPPs in the modern era depends on a judicious blend of cutting-edge technology, supportive regulatory frameworks, and seamless connectivity with the existing electricity infrastructure. The aggregation and control of various DERs can be optimized by using real-time data analytics, artificial intelligence, and smart grid technologies. However, VPPs must overcome several obstacles, such as data security, grid interconnection, and scalability to realize their full potential. In a dynamic energy environment, taking care of these issues is essential to ensure the proper operation of VPPs.

Also, the development of flexible regulatory frameworks that support VPP implementation and market involvement is essential for the efficient operation of VPPs. The seamless integration of VPPs into current energy markets and the promotion of novel business models are made possible by clear regulations on market access, price structures, and grid services. Overall, an effective operation of VPPs in this era and beyond will depend on the following:

Advanced technological integration such as data analytics, smart grid technologies which are vital real-time data processing, accurate forecasting, and efficient optimization.

Regulatory support to encourage supportive and accommodative regulatory frameworks that will promote VPP deployment, and market participation.

Implementation of robust data security measures to protect sensitive information, guarantee consumer privacy, and safeguard against potential cyberattacks.

Implementing these recommendations will help shape and harness the potential of VPPs to transform the energy industry. With correct planning, VPPs will significantly contribute to the modern era’s goals of energy resource optimization, grid stability enhancement, and improved integration of RESs.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analyzed during this work.

Abbreviations

Artificial Neural Network

Biogas/biomass power

Battery energy storage system

Combined heat and power

Convolutional Neural Network

Controlled load

• Distributed energy resources

Distributed generation

Distribution system operator

Energy storage system

European Union

Electric vehicles

Gas turbine

Heat pump power

Heating, ventilation, and air conditioning

Internet of Things

Long short-term memory

Mixed Integer Linear Programming

Model predictive control

Nuclear power

Pumped hydro storage

Programmable logic control

Power System Network

Particle Swarm Optimization

Photovoltaic

Renewable energy resources

• Renewable energy sources

Sustainable Development Goals

Thermal power

Transmission system operator

United Nations

Virtual power plant

Wind turbine

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Virtual Power Plants: The Future of Renewable Power? https://www.linkedin.com/pulse/virtual-power-plants-future-renewable-ashik-kalam . Accessed 19 Sept 2023

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Abdelkader, S., Amissah, J. & Abdel-Rahim, O. Virtual power plants: an in-depth analysis of their advancements and importance as crucial players in modern power systems. Energ Sustain Soc 14 , 52 (2024). https://doi.org/10.1186/s13705-024-00483-y

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Urban polycentricity and architectural heritage: a promethee-based multicriteria approach.

1. Introduction

2. literature review, 2.1. polycentricity with a focus on the intraurban scale, 2.2. ottoman architecture heritage of the 19th–20th centuries, 2.3. promethee as a multicriteria decision analysis method, 3. materials and methods, 3.1. methodological approach, 3.2. research area, 3.3. polycentricity methodology, 3.3.1. subindex a’—morphological polycentricity, 3.3.2. ottoman architecture assets defining the polycentric zones, 3.3.3. application of visual promethee—net flow index calculation.

• Definition of alternative actions/zones
• Definition of decision criteria
• Weight assignment to each criterion
• Evaluation of each zone’s performance against each criterion—Definition of a qualitative scale
• Very bad (VB).
• Average (A).
• Very Good (VG).

4.1. Morphological Polycentricity Analysis Results

4.1.1. primacy subindex, 4.1.2. rank-size rule subindex, 4.2. promethee methodology results—introduction of pah index, 4.2.1. ranking of the zones, 4.2.2. promethee complete ranking—pah index, 4.3. sensitivity analysis, 5. discussion, limitations, 6. conclusions, author contributions, data availability statement, conflicts of interest.

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Sofianou, E.; Papathanasiou, J.; Aretoulis, G. Urban Polycentricity and Architectural Heritage: A PROMETHEE-Based Multicriteria Approach. Buildings 2024 , 14 , 2659. https://doi.org/10.3390/buildings14092659

Sofianou E, Papathanasiou J, Aretoulis G. Urban Polycentricity and Architectural Heritage: A PROMETHEE-Based Multicriteria Approach. Buildings . 2024; 14(9):2659. https://doi.org/10.3390/buildings14092659

Sofianou, Evina, Jason Papathanasiou, and George Aretoulis. 2024. "Urban Polycentricity and Architectural Heritage: A PROMETHEE-Based Multicriteria Approach" Buildings 14, no. 9: 2659. https://doi.org/10.3390/buildings14092659

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Home » Conceptual Framework – Types, Methodology and Examples

Conceptual Framework – Types, Methodology and Examples

Table of Contents

Conceptual Framework

Definition:

A conceptual framework is a structured approach to organizing and understanding complex ideas, theories, or concepts. It provides a systematic and coherent way of thinking about a problem or topic, and helps to guide research or analysis in a particular field.

A conceptual framework typically includes a set of assumptions, concepts, and propositions that form a theoretical framework for understanding a particular phenomenon. It can be used to develop hypotheses, guide empirical research, or provide a framework for evaluating and interpreting data.

Conceptual Framework in Research

In research, a conceptual framework is a theoretical structure that provides a framework for understanding a particular phenomenon or problem. It is a key component of any research project and helps to guide the research process from start to finish.

A conceptual framework provides a clear understanding of the variables, relationships, and assumptions that underpin a research study. It outlines the key concepts that the study is investigating and how they are related to each other. It also defines the scope of the study and sets out the research questions or hypotheses.

Types of Conceptual Framework

Types of Conceptual Framework are as follows:

Theoretical Framework

A theoretical framework is an overarching set of concepts, ideas, and assumptions that help to explain and interpret a phenomenon. It provides a theoretical perspective on the phenomenon being studied and helps researchers to identify the relationships between different concepts. For example, a theoretical framework for a study on the impact of social media on mental health might draw on theories of communication, social influence, and psychological well-being.

Conceptual Model

A conceptual model is a visual or written representation of a complex system or phenomenon. It helps to identify the main components of the system and the relationships between them. For example, a conceptual model for a study on the factors that influence employee turnover might include factors such as job satisfaction, salary, work-life balance, and job security, and the relationships between them.

Empirical Framework

An empirical framework is based on empirical data and helps to explain a particular phenomenon. It involves collecting data, analyzing it, and developing a framework to explain the results. For example, an empirical framework for a study on the impact of a new health intervention might involve collecting data on the intervention’s effectiveness, cost, and acceptability to patients.

Descriptive Framework

A descriptive framework is used to describe a particular phenomenon. It helps to identify the main characteristics of the phenomenon and to develop a vocabulary to describe it. For example, a descriptive framework for a study on different types of musical genres might include descriptions of the instruments used, the rhythms and beats, the vocal styles, and the cultural contexts of each genre.

Analytical Framework

An analytical framework is used to analyze a particular phenomenon. It involves breaking down the phenomenon into its constituent parts and analyzing them separately. This type of framework is often used in social science research. For example, an analytical framework for a study on the impact of race on police brutality might involve analyzing the historical and cultural factors that contribute to racial bias, the organizational factors that influence police behavior, and the psychological factors that influence individual officers’ behavior.

Conceptual Framework for Policy Analysis

A conceptual framework for policy analysis is used to guide the development of policies or programs. It helps policymakers to identify the key issues and to develop strategies to address them. For example, a conceptual framework for a policy analysis on climate change might involve identifying the key stakeholders, assessing their interests and concerns, and developing policy options to mitigate the impacts of climate change.

Logical Frameworks

Logical frameworks are used to plan and evaluate projects and programs. They provide a structured approach to identifying project goals, objectives, and outcomes, and help to ensure that all stakeholders are aligned and working towards the same objectives.

Conceptual Frameworks for Program Evaluation

These frameworks are used to evaluate the effectiveness of programs or interventions. They provide a structure for identifying program goals, objectives, and outcomes, and help to measure the impact of the program on its intended beneficiaries.

Conceptual Frameworks for Organizational Analysis

These frameworks are used to analyze and evaluate organizational structures, processes, and performance. They provide a structured approach to understanding the relationships between different departments, functions, and stakeholders within an organization.

Conceptual Frameworks for Strategic Planning

These frameworks are used to develop and implement strategic plans for organizations or businesses. They help to identify the key factors and stakeholders that will impact the success of the plan, and provide a structure for setting goals, developing strategies, and monitoring progress.

Components of Conceptual Framework

The components of a conceptual framework typically include:

• Research question or problem statement : This component defines the problem or question that the conceptual framework seeks to address. It sets the stage for the development of the framework and guides the selection of the relevant concepts and constructs.
• Concepts : These are the general ideas, principles, or categories that are used to describe and explain the phenomenon or problem under investigation. Concepts provide the building blocks of the framework and help to establish a common language for discussing the issue.
• Constructs : Constructs are the specific variables or concepts that are used to operationalize the general concepts. They are measurable or observable and serve as indicators of the underlying concept.
• Propositions or hypotheses : These are statements that describe the relationships between the concepts or constructs in the framework. They provide a basis for testing the validity of the framework and for generating new insights or theories.
• Assumptions : These are the underlying beliefs or values that shape the framework. They may be explicit or implicit and may influence the selection and interpretation of the concepts and constructs.
• Boundaries : These are the limits or scope of the framework. They define the focus of the investigation and help to clarify what is included and excluded from the analysis.
• Context : This component refers to the broader social, cultural, and historical factors that shape the phenomenon or problem under investigation. It helps to situate the framework within a larger theoretical or empirical context and to identify the relevant variables and factors that may affect the phenomenon.
• Relationships and connections: These are the connections and interrelationships between the different components of the conceptual framework. They describe how the concepts and constructs are linked and how they contribute to the overall understanding of the phenomenon or problem.
• Variables : These are the factors that are being measured or observed in the study. They are often operationalized as constructs and are used to test the propositions or hypotheses.
• Methodology : This component describes the research methods and techniques that will be used to collect and analyze data. It includes the sampling strategy, data collection methods, data analysis techniques, and ethical considerations.
• Literature review : This component provides an overview of the existing research and theories related to the phenomenon or problem under investigation. It helps to identify the gaps in the literature and to situate the framework within the broader theoretical and empirical context.
• Outcomes and implications: These are the expected outcomes or implications of the study. They describe the potential contributions of the study to the theoretical and empirical knowledge in the field and the practical implications for policy and practice.

Conceptual Framework Methodology

Conceptual Framework Methodology is a research method that is commonly used in academic and scientific research to develop a theoretical framework for a study. It is a systematic approach that helps researchers to organize their thoughts and ideas, identify the variables that are relevant to their study, and establish the relationships between these variables.

Here are the steps involved in the conceptual framework methodology:

Identify the Research Problem

The first step is to identify the research problem or question that the study aims to answer. This involves identifying the gaps in the existing literature and determining what specific issue the study aims to address.

Conduct a Literature Review

The second step involves conducting a thorough literature review to identify the existing theories, models, and frameworks that are relevant to the research question. This will help the researcher to identify the key concepts and variables that need to be considered in the study.

Define key Concepts and Variables

The next step is to define the key concepts and variables that are relevant to the study. This involves clearly defining the terms used in the study, and identifying the factors that will be measured or observed in the study.

Develop a Theoretical Framework

Once the key concepts and variables have been identified, the researcher can develop a theoretical framework. This involves establishing the relationships between the key concepts and variables, and creating a visual representation of these relationships.

Test the Framework

The final step is to test the theoretical framework using empirical data. This involves collecting and analyzing data to determine whether the relationships between the key concepts and variables that were identified in the framework are accurate and valid.

Examples of Conceptual Framework

Some realtime Examples of Conceptual Framework are as follows:

• In economics , the concept of supply and demand is a well-known conceptual framework. It provides a structure for understanding how prices are set in a market, based on the interplay of the quantity of goods supplied by producers and the quantity of goods demanded by consumers.
• In psychology , the cognitive-behavioral framework is a widely used conceptual framework for understanding mental health and illness. It emphasizes the role of thoughts and behaviors in shaping emotions and the importance of cognitive restructuring and behavior change in treatment.
• In sociology , the social determinants of health framework provides a way of understanding how social and economic factors such as income, education, and race influence health outcomes. This framework is widely used in public health research and policy.
• In environmental science , the ecosystem services framework is a way of understanding the benefits that humans derive from natural ecosystems, such as clean air and water, pollination, and carbon storage. This framework is used to guide conservation and land-use decisions.
• In education, the constructivist framework is a way of understanding how learners construct knowledge through active engagement with their environment. This framework is used to guide instructional design and teaching strategies.

Applications of Conceptual Framework

Some of the applications of Conceptual Frameworks are as follows:

• Research : Conceptual frameworks are used in research to guide the design, implementation, and interpretation of studies. Researchers use conceptual frameworks to develop hypotheses, identify research questions, and select appropriate methods for collecting and analyzing data.
• Policy: Conceptual frameworks are used in policy-making to guide the development of policies and programs. Policymakers use conceptual frameworks to identify key factors that influence a particular problem or issue, and to develop strategies for addressing them.
• Education : Conceptual frameworks are used in education to guide the design and implementation of instructional strategies and curriculum. Educators use conceptual frameworks to identify learning objectives, select appropriate teaching methods, and assess student learning.
• Management : Conceptual frameworks are used in management to guide decision-making and strategy development. Managers use conceptual frameworks to understand the internal and external factors that influence their organizations, and to develop strategies for achieving their goals.
• Evaluation : Conceptual frameworks are used in evaluation to guide the development of evaluation plans and to interpret evaluation results. Evaluators use conceptual frameworks to identify key outcomes, indicators, and measures, and to develop a logic model for their evaluation.

Purpose of Conceptual Framework

The purpose of a conceptual framework is to provide a theoretical foundation for understanding and analyzing complex phenomena. Conceptual frameworks help to:

• Guide research : Conceptual frameworks provide a framework for researchers to develop hypotheses, identify research questions, and select appropriate methods for collecting and analyzing data. By providing a theoretical foundation for research, conceptual frameworks help to ensure that research is rigorous, systematic, and valid.
• Provide clarity: Conceptual frameworks help to provide clarity and structure to complex phenomena by identifying key concepts, relationships, and processes. By providing a clear and systematic understanding of a phenomenon, conceptual frameworks help to ensure that researchers, policymakers, and practitioners are all on the same page when it comes to understanding the issue at hand.
• Inform decision-making : Conceptual frameworks can be used to inform decision-making and strategy development by identifying key factors that influence a particular problem or issue. By understanding the complex interplay of factors that contribute to a particular issue, decision-makers can develop more effective strategies for addressing the problem.
• Facilitate communication : Conceptual frameworks provide a common language and conceptual framework for researchers, policymakers, and practitioners to communicate and collaborate on complex issues. By providing a shared understanding of a phenomenon, conceptual frameworks help to ensure that everyone is working towards the same goal.

When to use Conceptual Framework

There are several situations when it is appropriate to use a conceptual framework:

• To guide the research : A conceptual framework can be used to guide the research process by providing a clear roadmap for the research project. It can help researchers identify key variables and relationships, and develop hypotheses or research questions.
• To clarify concepts : A conceptual framework can be used to clarify and define key concepts and terms used in a research project. It can help ensure that all researchers are using the same language and have a shared understanding of the concepts being studied.
• To provide a theoretical basis: A conceptual framework can provide a theoretical basis for a research project by linking it to existing theories or conceptual models. This can help researchers build on previous research and contribute to the development of a field.
• To identify gaps in knowledge : A conceptual framework can help identify gaps in existing knowledge by highlighting areas that require further research or investigation.
• To communicate findings : A conceptual framework can be used to communicate research findings by providing a clear and concise summary of the key variables, relationships, and assumptions that underpin the research project.

Characteristics of Conceptual Framework

key characteristics of a conceptual framework are:

• Clear definition of key concepts : A conceptual framework should clearly define the key concepts and terms being used in a research project. This ensures that all researchers have a shared understanding of the concepts being studied.
• Identification of key variables: A conceptual framework should identify the key variables that are being studied and how they are related to each other. This helps to organize the research project and provides a clear focus for the study.
• Logical structure: A conceptual framework should have a logical structure that connects the key concepts and variables being studied. This helps to ensure that the research project is coherent and consistent.
• Based on existing theory : A conceptual framework should be based on existing theory or conceptual models. This helps to ensure that the research project is grounded in existing knowledge and builds on previous research.
• Testable hypotheses or research questions: A conceptual framework should include testable hypotheses or research questions that can be answered through empirical research. This helps to ensure that the research project is rigorous and scientifically valid.
• Flexibility : A conceptual framework should be flexible enough to allow for modifications as new information is gathered during the research process. This helps to ensure that the research project is responsive to new findings and is able to adapt to changing circumstances.

Advantages of Conceptual Framework

Advantages of the Conceptual Framework are as follows:

• Clarity : A conceptual framework provides clarity to researchers by outlining the key concepts and variables that are relevant to the research project. This clarity helps researchers to focus on the most important aspects of the research problem and develop a clear plan for investigating it.
• Direction : A conceptual framework provides direction to researchers by helping them to develop hypotheses or research questions that are grounded in existing theory or conceptual models. This direction ensures that the research project is relevant and contributes to the development of the field.
• Efficiency : A conceptual framework can increase efficiency in the research process by providing a structure for organizing ideas and data. This structure can help researchers to avoid redundancies and inconsistencies in their work, saving time and effort.
• Rigor : A conceptual framework can help to ensure the rigor of a research project by providing a theoretical basis for the investigation. This rigor is essential for ensuring that the research project is scientifically valid and produces meaningful results.
• Communication : A conceptual framework can facilitate communication between researchers by providing a shared language and understanding of the key concepts and variables being studied. This communication is essential for collaboration and the advancement of knowledge in the field.
• Generalization : A conceptual framework can help to generalize research findings beyond the specific study by providing a theoretical basis for the investigation. This generalization is essential for the development of knowledge in the field and for informing future research.

Limitations of Conceptual Framework

Limitations of Conceptual Framework are as follows:

• Limited applicability: Conceptual frameworks are often based on existing theory or conceptual models, which may not be applicable to all research problems or contexts. This can limit the usefulness of a conceptual framework in certain situations.
• Lack of empirical support : While a conceptual framework can provide a theoretical basis for a research project, it may not be supported by empirical evidence. This can limit the usefulness of a conceptual framework in guiding empirical research.
• Narrow focus: A conceptual framework can provide a clear focus for a research project, but it may also limit the scope of the investigation. This can make it difficult to address broader research questions or to consider alternative perspectives.
• Over-simplification: A conceptual framework can help to organize and structure research ideas, but it may also over-simplify complex phenomena. This can limit the depth of the investigation and the richness of the data collected.
• Inflexibility : A conceptual framework can provide a structure for organizing research ideas, but it may also be inflexible in the face of new data or unexpected findings. This can limit the ability of researchers to adapt their research project to new information or changing circumstances.
• Difficulty in development : Developing a conceptual framework can be a challenging and time-consuming process. It requires a thorough understanding of existing theory or conceptual models, and may require collaboration with other researchers.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Concept Papers in Research: Deciphering the blueprint of brilliance

Concept papers hold significant importance as a precursor to a full-fledged research proposal in academia and research. Understanding the nuances and significance of a concept paper is essential for any researcher aiming to lay a strong foundation for their investigation.

Table of Contents

What Is Concept Paper

A concept paper can be defined as a concise document which outlines the fundamental aspects of a grant proposal. It outlines the initial ideas, objectives, and theoretical framework of a proposed research project. It is usually two to three-page long overview of the proposal. However, they differ from both research proposal and original research paper in lacking a detailed plan and methodology for a specific study as in research proposal provides and exclusion of the findings and analysis of a completed research project as in an original research paper. A concept paper primarily focuses on introducing the basic idea, intended research question, and the framework that will guide the research.

Purpose of a Concept Paper

A concept paper serves as an initial document, commonly required by private organizations before a formal proposal submission. It offers a preliminary overview of a project or research’s purpose, method, and implementation. It acts as a roadmap, providing clarity and coherence in research direction. Additionally, it also acts as a tool for receiving informal input. The paper is used for internal decision-making, seeking approval from the board, and securing commitment from partners. It promotes cohesive communication and serves as a professional and respectful tool in collaboration.

These papers aid in focusing on the core objectives, theoretical underpinnings, and potential methodology of the research, enabling researchers to gain initial feedback and refine their ideas before delving into detailed research.

Key Elements of a Concept Paper

Key elements of a concept paper include the title page , background , literature review , problem statement , methodology, timeline, and references. It’s crucial for researchers seeking grants as it helps evaluators assess the relevance and feasibility of the proposed research.

Writing an effective concept paper in academic research involves understanding and incorporating essential elements:

How to Write a Concept Paper?

To ensure an effective concept paper, it’s recommended to select a compelling research topic, pose numerous research questions and incorporate data and numbers to support the project’s rationale. The document must be concise (around five pages) after tailoring the content and following the formatting requirements. Additionally, infographics and scientific illustrations can enhance the document’s impact and engagement with the audience. The steps to write a concept paper are as follows:

1. Write a Crisp Title:

Choose a clear, descriptive title that encapsulates the main idea. The title should express the paper’s content. It should serve as a preview for the reader.

2. Provide a Background Information:

Give a background information about the issue or topic. Define the key terminologies or concepts. Review existing literature to identify the gaps your concept paper aims to fill.

3. Outline Contents in the Introduction:

Introduce the concept paper with a brief overview of the problem or idea you’re addressing. Explain its significance. Identify the specific knowledge gaps your research aims to address and mention any contradictory theories related to your research question.

4. Define a Mission Statement:

The mission statement follows a clear problem statement that defines the problem or concept that need to be addressed. Write a concise mission statement that engages your research purpose and explains why gaining the reader’s approval will benefit your field.

5. Explain the Research Aim and Objectives:

Explain why your research is important and the specific questions you aim to answer through your research. State the specific goals and objectives your concept intends to achieve. Provide a detailed explanation of your concept. What is it, how does it work, and what makes it unique?

6. Detail the Methodology:

Discuss the research methods you plan to use, such as surveys, experiments, case studies, interviews, and observations. Mention any ethical concerns related to your research.

7. Outline Proposed Methods and Potential Impact:

Provide detailed information on how you will conduct your research, including any specialized equipment or collaborations. Discuss the expected results or impacts of implementing the concept. Highlight the potential benefits, whether social, economic, or otherwise.

8. Mention the Feasibility

Discuss the resources necessary for the concept’s execution. Mention the expected duration of the research and specific milestones. Outline a proposed timeline for implementing the concept.

9. Include a Support Section:

Include a section that breaks down the project’s budget, explaining the overall cost and individual expenses to demonstrate how the allocated funds will be used.

10. Provide a Conclusion:

Summarize the key points and restate the importance of the concept. If necessary, include a call to action or next steps.

Although the structure and elements of a concept paper may vary depending on the specific requirements, you can tailor your document based on the guidelines or instructions you’ve been given.

Here are some tips to write a concept paper:

Example of a Concept Paper

Here is an example of a concept paper. Please note, this is a generalized example. Your concept paper should align with the specific requirements, guidelines, and objectives you aim to achieve in your proposal. Tailor it accordingly to the needs and context of the initiative you are proposing.

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Importance of a Concept Paper

Concept papers serve various fields, influencing the direction and potential of research in science, social sciences, technology, and more. They contribute to the formulation of groundbreaking studies and novel ideas that can impact societal, economic, and academic spheres.

A concept paper serves several crucial purposes in various fields:

In summary, a well-crafted concept paper is essential in outlining a clear, concise, and structured framework for new ideas or proposals. It helps in assessing the feasibility, viability, and potential impact of the concept before investing significant resources into its implementation.

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Role of AI in Writing Concept Papers

The increasing use of AI, particularly generative models, has facilitated the writing process for concept papers. Responsible use involves leveraging AI to assist in ideation, organization, and language refinement while ensuring that the originality and ethical standards of research are maintained.

AI plays a significant role in aiding the creation and development of concept papers in several ways:

1. Idea Generation and Organization

AI tools can assist in brainstorming initial ideas for concept papers based on key concepts. They can help in organizing information, creating outlines, and structuring the content effectively.

2. Summarizing Research and Data Analysis

AI-powered tools can assist in conducting comprehensive literature reviews, helping writers to gather and synthesize relevant information. AI algorithms can process and analyze vast amounts of data, providing insights and statistics to support the concept presented in the paper.

3. Language and Style Enhancement

AI grammar checker tools can help writers by offering grammar, style, and tone suggestions, ensuring professionalism. It can also facilitate translation, in case a global collaboration.

4. Collaboration and Feedback

AI platforms offer collaborative features that enable multiple authors to work simultaneously on a concept paper, allowing for real-time contributions and edits.

5. Customization and Personalization

AI algorithms can provide personalized recommendations based on the specific requirements or context of the concept paper. They can assist in tailoring the concept paper according to the target audience or specific guidelines.

6. Automation and Efficiency

AI can automate certain tasks, such as citation formatting, bibliography creation, or reference checking, saving time for the writer.

7. Analytics and Prediction

AI models can predict potential outcomes or impacts based on the information provided, helping writers anticipate the possible consequences of the proposed concept.

8. Real-Time Assistance

AI-driven chat-bots can provide real-time support and answers to specific questions related to the concept paper writing process.

AI’s role in writing concept papers significantly streamlines the writing process, enhances the quality of the content, and provides valuable assistance in various stages of development, contributing to the overall effectiveness of the final document.

Concept papers serve as the stepping stone in the research journey, aiding in the crystallization of ideas and the formulation of robust research proposals. It the cornerstone for translating ideas into impactful realities. Their significance spans diverse domains, from academia to business, enabling stakeholders to evaluate, invest, and realize the potential of groundbreaking concepts.

Frequently Asked Questions

A concept paper can be defined as a concise document outlining the fundamental aspects of a grant proposal such as the initial ideas, objectives, and theoretical framework of a proposed research project.

A good concept paper should offer a clear and comprehensive overview of the proposed research. It should demonstrate a strong understanding of the subject matter and outline a structured plan for its execution.

Concept paper is important to develop and clarify ideas, develop and evaluate proposal, inviting collaboration and collecting feedback, presenting proposals for academic and research initiatives and allocating resources.

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It helps a lot for my concept paper.

Information is key to the guidelines of a concept paper

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• What Is a Conceptual Framework? | Tips & Examples

What Is a Conceptual Framework? | Tips & Examples

Published on August 2, 2022 by Bas Swaen and Tegan George. Revised on March 18, 2024.

A conceptual framework illustrates the expected relationship between your variables. It defines the relevant objectives for your research process and maps out how they come together to draw coherent conclusions.

Keep reading for a step-by-step guide to help you construct your own conceptual framework.

Table of contents

Developing a conceptual framework in research, step 1: choose your research question, step 2: select your independent and dependent variables, step 3: visualize your cause-and-effect relationship, step 4: identify other influencing variables, frequently asked questions about conceptual models.

A conceptual framework is a representation of the relationship you expect to see between your variables, or the characteristics or properties that you want to study.

Conceptual frameworks can be written or visual and are generally developed based on a literature review of existing studies about your topic.

Your research question guides your work by determining exactly what you want to find out, giving your research process a clear focus.

However, before you start collecting your data, consider constructing a conceptual framework. This will help you map out which variables you will measure and how you expect them to relate to one another.

In order to move forward with your research question and test a cause-and-effect relationship, you must first identify at least two key variables: your independent and dependent variables .

• The expected cause, “hours of study,” is the independent variable (the predictor, or explanatory variable)
• The expected effect, “exam score,” is the dependent variable (the response, or outcome variable).

Note that causal relationships often involve several independent variables that affect the dependent variable. For the purpose of this example, we’ll work with just one independent variable (“hours of study”).

Now that you’ve figured out your research question and variables, the first step in designing your conceptual framework is visualizing your expected cause-and-effect relationship.

We demonstrate this using basic design components of boxes and arrows. Here, each variable appears in a box. To indicate a causal relationship, each arrow should start from the independent variable (the cause) and point to the dependent variable (the effect).

It’s crucial to identify other variables that can influence the relationship between your independent and dependent variables early in your research process.

Some common variables to include are moderating, mediating, and control variables.

Moderating variables

Moderating variable (or moderators) alter the effect that an independent variable has on a dependent variable. In other words, moderators change the “effect” component of the cause-and-effect relationship.

Let’s add the moderator “IQ.” Here, a student’s IQ level can change the effect that the variable “hours of study” has on the exam score. The higher the IQ, the fewer hours of study are needed to do well on the exam.

Let’s take a look at how this might work. The graph below shows how the number of hours spent studying affects exam score. As expected, the more hours you study, the better your results. Here, a student who studies for 20 hours will get a perfect score.

But the graph looks different when we add our “IQ” moderator of 120. A student with this IQ will achieve a perfect score after just 15 hours of study.

Below, the value of the “IQ” moderator has been increased to 150. A student with this IQ will only need to invest five hours of study in order to get a perfect score.

Here, we see that a moderating variable does indeed change the cause-and-effect relationship between two variables.

Mediating variables

Now we’ll expand the framework by adding a mediating variable . Mediating variables link the independent and dependent variables, allowing the relationship between them to be better explained.

Here’s how the conceptual framework might look if a mediator variable were involved:

In this case, the mediator helps explain why studying more hours leads to a higher exam score. The more hours a student studies, the more practice problems they will complete; the more practice problems completed, the higher the student’s exam score will be.

Moderator vs. mediator

It’s important not to confuse moderating and mediating variables. To remember the difference, you can think of them in relation to the independent variable:

• A moderating variable is not affected by the independent variable, even though it affects the dependent variable. For example, no matter how many hours you study (the independent variable), your IQ will not get higher.
• A mediating variable is affected by the independent variable. In turn, it also affects the dependent variable. Therefore, it links the two variables and helps explain the relationship between them.

Control variables

Lastly,  control variables must also be taken into account. These are variables that are held constant so that they don’t interfere with the results. Even though you aren’t interested in measuring them for your study, it’s crucial to be aware of as many of them as you can be.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

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How to Write Conceptual Papers in the Social Sciences

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This book is a practical guide on how to write conceptual papers and use conceptual generalization as a research methodology. Divided into two parts, the book first focuses on the scientific foundation for conceptual generalization, to identify what is a conceptual model and how conceptual models can be developed. Part two focuses on how to write a winning conceptual thesis, covering conceptual generalisation and empirical generalisation, and discusses research problems and questions, and how to analyse them.

The authors cover different conceptual and analytical models to offer students a multitude of tools to visualize, interpret and uncover relationships and patterns. For example, they explore the thought experiment, analytical models, empirical causal models, analytical forms and data mining models, and outline a strategy for developing conceptual models to assist with students who wish to design their own conceptual paper. Students gain a clear understanding of the driving forces in the research process, how to define a research problem, how to analysis the problem and develop research strategies. Moving from concepts to hypotheses, the book also covers the main types of errors that may be encountered as students learn about understanding the development of models and how to develop a theory.

Also including a checklist for students, and a list of definitions and concepts, this is the ideal resource for advanced undergraduate and postgraduate students, and researchers, in the social sciences.

TABLE OF CONTENTS

Part i | 18  pages, conceptual generalization, chapter 1 | 16  pages, conceptual generalizations, part ii | 110  pages, how to write a winning conceptual thesis, chapter 2 | 9  pages, general considerations, chapter 3 | 6  pages, research problems and questions, chapter 4 | 7  pages, analysis of the research problem, chapter 5 | 6  pages, our mental tools, chapter 6 | 6  pages, suggestions for developing research strategies, chapter 7 | 7  pages, the main types of errors, chapter 8 | 6  pages, from concepts to hypotheses, chapter 9 | 4  pages, types of hypothesis, chapter 10 | 4  pages, systematization, chapter 11 | 4  pages, simplification, chapter 12 | 5  pages, chapter 13 | 4  pages, interpretation, chapter 14 | 7  pages, uncovering patterns, chapter 15 | 5  pages, understanding and explaining, chapter 16 | 9  pages, development of models, chapter 17 | 6  pages, theory development, chapter 18 | 3  pages, reflections, chapter 19 | 2  pages, chapter 20 | 8  pages, definitions of terms and concepts.

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Designing conceptual articles: four approaches

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Introduction

The major academic journals in the field of marketing acknowledge the need for good conceptual papers that can “bridge existing theories in interesting ways, link work across disciplines, provide multi-level insights, and broaden the scope of our thinking” (Gilson and Goldberg 2015, p. 128). Indeed, many of the most impactful marketing papers of recent decades are conceptual as this type of research enables theory building unrestricted by the demands of empirical generalization (e.g., Vargo and Lusch 2004). Authors crafting conceptual papers can find valuable advice on problematizing (Alvesson and Sandberg 2011), theorizing and theory building (Corley and Gioia 2011; Cornelissen 2017; Shepherd and Suddaby 2017), and the types of conceptual contribution that warrant publication (Corley and Gioia 2011; MacInnis 2011). However, a lack of commonly accepted templates or “recipes” for building the paper means that writing a conceptual piece can be a struggle (Cornelissen 2017). As a result, reviewers often face conceptual papers that offer little more than a descriptive literature review or interesting but disjointed ideas.

In empirical papers, the recipe typically is the research design that provides the paper structure and logic, guiding the process of developing new knowledge and offering conventions for reporting the key elements of the research (Flick 2018, p. 102). The research design explains how the ingredients of the study were selected, acquired, and analyzed to effectively address the research problem, and reviewers can evaluate the robustness of this process by reference to established conventions in the existing literature. As conceptual papers generally do not fit the mold of empirical research, authors and reviewers lack any such recipe book, making the critical issue of analytical rigor more challenging.

This paper addresses issues of methodology and research design for conceptual papers. The discussion is built on previous “how to” guides to conceptual research, and on examples from high quality journals to identify and illustrate different options for conceptual research design. This paper discusses four templates—Theory Synthesis, Theory Adaptation, Typology, and Model—and explicates their aims, their approach to theory use, and their contribution potential. The paper does not focus on theory building itself but supports it, as analytical rigor is a prerequisite for high quality theorizing. Nor is the focus on literature reviews or meta-analyses; while these are important non-empirical forms of research, there are well articulated existing guidelines for such articles (see for example Webster and Watson 2002; Palmatier et al. 2018).

The ultimate goal of this paper is to direct scholarly attention to the importance of a systematic approach to developing a conceptual paper. Experienced editors and reviewers have noted that researchers sometimes underestimate how difficult it is to write a rigorous conceptual paper and consider this an easy route to publishing—an essay devoid of deeper scholarship (Hirschheim 2008). In reality, developing a cogent argument and building a supporting theoretical explanation requires tacit knowledge and skills that doctoral programs seldom teach (Yadav 2010; King and Lepak 2011). As Fulmer puts it, “in a theoretical paper the author is faced with a mixed blessing: greater freedom and page length within which to develop theory but also more editorial rope with which to hang him/herself” (2012, p. 330).

The paper is organized as follows. The next section outlines key methodological requirements for conceptual studies. Four common types of research design are then identified and discussed with supporting examples. The article ends with conclusions and recommendations for marketing scholars undertaking, supervising, or reviewing conceptual research.

Conceptual papers: some methodological requirements

The term “research design” refers to decisions about how to achieve research goals, linking theories, questions, and goals to appropriate resources and methods (Flick 2018, p. 102). In short, the research design is a plan for collecting and analyzing evidence that helps to answer the question posed (Ragin 1994, p. 191). Like any design, the research design should improve usability ; a good research design is the optimal tool for addressing the research problem, and it communicates the logic of the study in a transparent way. In principle, any piece of research should be designed to deliver trustworthy answers to the question posed in a credible and justified manner.

An empirical research design typically involves decisions about the underlying theoretical framing of the study as well as issues of data collection and analysis (e.g. Miller and Salkind 2002). Imagine, for example, an empirical paper where the authors did not argue for their sampling criteria or choice of informants, or failed to define the measures used or to show how the results were derived from the data. It can be argued that conceptual papers entail similar considerations (Table 1), as the omission of equivalent elements would create similar confusion. In other words, a well-designed conceptual paper must explicitly justify and explicate decisions about key elements of the study. The following sections elaborate more specifically on designing and communicating these “methodological” aspects of conceptual papers.

Table 1. Research design elements in conceptual papers

Explicating and justifying the choice of theories and concepts

Empirical and conceptual papers ultimately share a common goal: to create new knowledge by building on carefully selected sources of information combined according to a set of norms. In the case of conceptual papers, arguments are not derived from data in the traditional sense but involve the assimilation and combination of evidence in the form of previously developed concepts and theories (Hirschheim 2008). In that sense, conceptual papers are not without empirical insights but rather build on theories and concepts that are developed and tested through empirical research.

In an empirical study, the researcher determines what data are needed to address the research questions and specifies sampling criteria and research instruments accordingly. In similar fashion, a conceptual paper should explain how and why the theories and concepts on which it is grounded were selected. In simple terms, there are two possible points of departure. The first option is to start from a focal phenomenon that is observable but not adequately addressed in the existing research. The authors may inductively identify differing conceptualizations of that phenomenon, and then argue that the aspect of interest is best addressed in terms of particular concepts or theories. That is, the choice of concepts is based on their fit to the focal phenomenon and their complementary value in conceptualizing it. One key issue here is how the researcher conceptualizes the empirical phenomenon; in selecting particular concepts and theories, the researcher is de facto making an argument about the conceptual ingredients of the empirical phenomenon in question.

A second and perhaps more common approach is to start from a focal theory by arguing that a particular concept, theory, or research domain is internally incoherent or incomplete in some important respect and then introducing other theories to bridge the observed gaps. In this case, the choice of theories or concepts is based on their ability to address the observed shortcoming in the existing literature, i.e. their supplementary value. This simplified account raises a critical underlying question: what is the value that each selected concept, literature stream, or theory brings to the study, and why are they selected in preference to something else?

Explicating the role of different theories and concepts in the analysis

Conceptual papers typically draw on multiple concepts, literature streams, and theories that play differing roles. It is difficult to imagine a (published) empirical paper where the reader could not distinguish empirical data from the literature review. In a conceptual paper, however, it is sometimes difficult to tell which theories provide the “data” and which are framing the analysis. In this regard, Lukka and Vinnari (2014) drew a useful distinction between domain theory and method theory. A domain theory is “a particular set of knowledge on a substantive topic area situated in a field or domain” (ibid, p. 1309)—that is, an area of study characterized by a particular set of constructs, theories, and assumptions (MacInnis 2011). A method theory, on the other hand, is “a meta-level conceptual system for studying the substantive issue(s) of the domain theory at hand” (Lukka and Vinnari 2014, p. 1309). For example, Brodie et al. (2019) sought to advance engagement research (domain theory) by drawing new perspectives from service-dominant logic (method theory). The distinction is relative rather than absolute; whether a particular theory is domain or method theory depends on its role in the study in question (Lukka and Vinnari 2014). Indeed, a single study can accommodate multiple domain and method theories.

In a conceptual paper, one crucial function of the research design is to explicate the role of each element in the paper; failure to explain this is likely to render the logic of “generating findings” practically invisible to the reader. Defining the roles of different theories also helps to indicate the paper’s positioning, and how its contribution should be evaluated. Typically, the role of the method theory is to provide some new insight into the domain theory—for example, to expand, organize, or offer a new or alternative explanation of concepts and relationships. This means that contribution usually centers on the domain theory, not the method theory (Lukka and Vinnari 2014). For example, marketing scholars often use established theories such as resource-based theory, institutional theory, or practice theory as method theories, but any suitable framework (even from other disciplines) can play this role.1

Making the chain of evidence visible and easy to grasp

Conceptual papers typically focus on proposing new relationships among constructs; the purpose is thus to develop logical and complete arguments about these associations rather than testing them empirically (Gilson and Goldberg 2015). The issue of how to develop logical arguments is hence pivotal. As well as arguing that concepts are linked, authors must provide a theoretical explanation for that link. As that explanation demonstrates the logic of connections between concepts, it is critical for theory building (King and Lepak 2011).

In attempting to analyze what constitutes a good argument, Hirschheim (2008) adopted a framework first advanced by the British philosopher Toulmin (1958), according to which an argument has three necessary components: claims, grounds, and warrants. Claims refer to the explicit statement or thesis that the reader is being asked to accept as true—the outcome of the research. Grounds are the evidence and reasoning used to support the claim and to persuade the reader. In a conceptual paper, this evidence is drawn from previous studies rather than from primary data. Finally, warrants are the underlying assumptions or presuppositions that link grounds to claims. Warrants are often beliefs implicitly accepted within the given research domain—for example the assumption that organizations strive to satisfy their customers. In a robust piece of research, claims should be substantiated by sufficient grounds, and should be of sufficient significance to make a worthwhile contribution to knowledge (Hirschheim 2008).

In practice, the chain of evidence in a conceptual paper is made visible to the reader by explicating the key steps in the argument. How is the studied phenomenon conceptualized? What are the study’s implicit assumptions, stemming from its theoretical underpinnings? Are the premises and axioms used to ground the arguments sufficiently explicit to enable another researcher to arrive at similar analytical conclusions? Conceptual clarity, parsimony, simplicity, and logical coherence are important qualities of any academic study but are arguably all the more critical when developing arguments without empirical data.

A paper’s structure is a strong determinant of how easy it is to follow the chain of argumentation. While there is no single best way to structure a conceptual paper, what successful papers have in common is a careful matching of form and structure to theoretical purpose of the paper (Fulmer 2012). The structure should therefore reflect both the aims of the research and the role of the various lenses deployed to achieve those aims—in other words, the structure highlights what the authors seek to explain. A clear structure also contributes to conceptual clarity by making the hierarchy of concepts and their elements intuitively available to the reader, eliminating any noise that might distort the underlying message. As Hirschheim (2008) noted, a clear structure ensures a place for everything—omitting nothing of importance—and puts everything in its place, avoiding redundancies.

Common types of research design in conceptual papers

In marked contrast to empirical research, there is no widely shared understanding of basic types of research design in respect to conceptual papers, with the exception of literature reviews and meta-analyses. To address this issue, the present study considers four such types: Theory Synthesis, Theory Adaptation, Typology , and Model (see Table 2). These types serve to clarify differences of methodological approach—that is, how the argument is structured and developed—rather than the types of conceptual contributions that are the main consideration of MacInnis (2011). The four types discussed here derive from an analysis of goal setting, structuring, and logic of argumentation in multiple articles published in high quality journals. It should be said that the list is not exhaustive, and other researchers would no doubt have formulated differing perspectives. Nevertheless, the presented scheme can inspire researchers to explore and explicate one’s approach to conceptual research, and perhaps to formulate an alternative approach. It should also be noted that the goals of a conceptual article can be as varied as in any other form of academic research. Table 2 identifies some possible or likely goals for each suggested type; these are not mutually exclusive and are often combined.

Table 2. Conceptual papers: Common types of research design

*For simplicity, “theory” refers here both to theories and to what might better be described as literature fields or research streams

Theory synthesis

A theory synthesis paper seeks to achieve conceptual integration across multiple theories or literature streams. Such papers offer a new or enhanced view of a concept or phenomenon by linking previously unconnected or incompatible pieces in a novel way. Papers of this type contribute by summarizing and integrating extant knowledge of a concept or phenomenon. According to MacInnis (2011), summarizing helps researchers see the forest for the trees by encapsulating, digesting, and reducing what is known to a manageable whole. Integration enables researchers to see a concept or phenomenon in a new way by transforming previous findings and theory into a novel higher-order perspective that links phenomena previously considered distinct (MacInnis 2011). For example, a synthesis paper might chart a new or unstructured phenomenon that has previously been addressed in piecemeal fashion across diverse domains or disciplines. Such papers may also explore the conceptual underpinnings of an emerging theory or explain conflicting research findings by providing a more parsimonious explanation that pulls disparate elements into a more coherent whole.

This kind of systematization is especially helpful when research on a given topic is fragmented across different literatures, helping to identify and underscore commonalities that build coherence (Cropanzano 2009). For example, in their review of conceptualizations of customer experience across multiple literature fields, Becker and Jaakkola’s (2020) analysis of the compatibility of various elements and assumptions provided a new integrative view that could be generalized across settings and contexts. In more mature fields, synthesis can help to identify gaps in the extant research, which is often the goal of systematic literature reviews. However, gap spotting is seldom a sufficient source of contribution as the main aim of a conceptual paper should be to enhance existing theoretical understanding on the studied phenomenon or concept. The synthesis paper represents a form of theorizing that emphasizes narrative reasoning that seeks to unveil “big picture” patterns and connections rather than specific causal mechanisms (Delbridge and Fiss 2013).

Although there is sometimes a fine line between theory synthesis and literature review, there remains a clear distinction between the two. While a well-crafted literature review takes stock of the field and can provide valuable insights into its development, scope, or future prospects, it remains within the existing conceptual or theoretical boundaries, describing extant knowledge rather than looking beyond it. In the case of a conceptual paper, the literature review is a necessary tool but not the ultimate objective. Moreover, in a theory synthesis paper, the role of the literature review is to unravel the components of a concept or phenomenon and it must sometimes reduce or exclude incommensurable elements. A lack of elegance occurs when authors attempt to hammer together separate research ideas in a series of “minireviews” instead of attending to a single conceptual theme (Cropanzano 2009). For example, a literature review that seeks to integrate multiple research perspectives may instead merely summarize in separate chapters what each has to say about the concept. Typically, different research perspectives employ differing terms and structure, or categorize conceptual elements in distinct ways. Integration and synthesis requires that the researcher explicates and unravels the conceptual underpinnings and building blocks that different perspectives use to conceptualize a phenomenon, and the looks for common ground on which to build a new and enhanced conceptualization.

A theory synthesis paper may seek to increase understanding of a relatively narrow concept or empirical phenomenon. For example, Lemon and Verhoef (2016) summarized the conceptual background and extant conceptualizations of customer journeys to produce a new integrative view. They framed the journey phenomenon in terms of the consumer purchasing process and organized the extant research within this big picture. Similarly, arguing that the knowledge base of relationship marketing and business networks perspectives was unduly fragmented, Möller (2013) deployed a metatheoretical lens to construct an articulated theory map that accommodated various domain theories, leading to the development of two novel middle-range theories.

Ultimately, a theory synthesis paper can integrate an extensive set of theories and phenomena under a novel theoretical umbrella. One good example is Vargo and Lusch’s (2004) seminal article, which pulled together key ingredients from diverse fields such as market orientation, relationship marketing, network management, and value management into a novel integrative narrative to formulate the more parsimonious framework of service-dominant logic. In so doing, they drew on resource based theory, structuration theory, and institutional theory as method theories to organize and synthesize concepts and themes from middle-range literature fields (e.g., Vargo and Lusch 2004, 2016). While extant research provided the basis for a novel framework, existing concepts were decomposed into such fine-grained ingredients that the resulting integration was a new theoretical view in its own right rather than a summary of existing concepts.

Theory adaptation

Papers that focus on theory adaptation seek to amend an existing theory by using other theories. While empirical research may gradually extend some element of theory within a given context, theory-based adaptation attempts a more immediate shift of perspective. Theory adaptation papers develop contribution by revising extant knowledge—that is, by introducing alternative frames of reference to propose a novel perspective on an extant conceptualization (MacInnis 2011). The point of departure for such papers, then, is the problematization of a particular theory or concept. For example, the authors might argue that certain empirical developments or insights from other streams of literature render an existing conceptualization insufficient or conflicted, and that some reconfiguration or shift of perspective or scope is needed to better align the concept or theory to its purpose or to reconcile certain inconsistencies. Typically, the researcher draws from another theory that is equipped to guide this shift. The contribution of this type of a paper is often positioned to the domain where the focal concept is situated.

The starting point for the theory adaptation paper is the theory or concept of interest (domain theory). Other theories are used as tools, or method theories (Lukka and Vinnari 2014) to provide an alternative frame of reference to adjust or expand its conceptual scope. One “method” of adaptation is to switch the level of analysis; for example, Alexander et al. (2018) provided new insights into the influence of institutions on customer engagement by shifting from a micro level analysis of customer relationships—the prevailing view in the field—to meso and macro level views, adapting Chandler and Vargo’s (2011) process of oscillating foci. Another option is to use an established theory to explore new aspects of the domain theory (Yadav 2010). As one example of this type of design, Brodie et al. (2019) argued for the practical and theoretical importance of expanding the scope of engagement research in two ways: from a focus on consumers to a broad range of actors, and from dyadic firm-customer relationships to networks. As well as justifying why a particular extension or change of focus is needed, a theory adaptation paper must also show that the selected method theory is the best available option. For example, Brodie et al. (2019) explained that they employed service-dominant logic to broaden the conceptual scope of engagement research because it offered a lens for understanding actor-to-actor interactions in networks. Similarly, Hillebrand et al. (2015) used multiplicity theory to revise existing perspectives on stakeholder marketing by viewing stakeholder networks as continuous rather than discrete. They argued that this provides a more accurate understanding of markets characterized by complex value exchange and dispersed control.

A typology paper classifies conceptual variants as distinct types. The aim is to develop a categorization that “explains the fuzzy nature of many subjects by logically and causally combining different constructs into a coherent and explanatory set of types” (Cornelissen 2017). A typology paper provides a more precise and nuanced understanding of a phenomenon or concept, pinpointing and justifying key dimensions that distinguish the variants.

Typology papers contribute through differentiation— distinguishing, dimensionalizing, or categorizing extant knowledge of the phenomenon, construct, or theory in question (MacInnis 2011). Typologies reduce complexity (Fiss 2011). They demonstrate how variants of an entity differ, and hence organize complex networks of concepts and relationships, and may help by recognizing their differing antecedents, manifestations, or effects (MacInnis 2011). Typologies also offer a multidimensional view of the target phenomenon by categorizing theoretical features or dimensions as distinct profiles that offer coordinates for empirical research (Cornelissen 2017). For example, the classic typologies elaborated by Mills and Margulies (1980) and Lovelock (1983) assigned services to categories reflecting different aspects of the relationship between customers and the service organization, facilitating prediction of organizational behavior and marketing action. These theory-based typologies have informed numerous empirical applications.

The starting point for a typology paper is typically recognition of an important but fragmented research domain characterized by differing manifestations of a concept or inconsistent findings regarding drivers or outcomes. The researcher accumulates knowledge of the focal topic and then organizes it to capture the variability of particular characteristics of the concept or phenomenon. For example, after exploring different approaches to service innovation, Helkkula et al. (2018) proposed a typology of four archetypes. They suggested that variance within the extant research could be explained by differences of theoretical perspective and argued that each type had distinct implications for value creation.

The dimensions of a typology can also be differentiated by applying another theory (i.e. methods theory) that provides a logical explanation of why differences exist and why they are relevant. For example, to examine the boundaries of resource integration, Dong and Sivakumar (2017) developed a typology of customer participation, using dimensions drawn from resource-based theory, to address the fundamental resource deployment questions of whether there is a choice in terms of who performs a task and what task is performed (Kozlenkova et al. 2014).

Snow and Ketchen Jr. (2014) argued that well-developed typologies are more than just classification systems; rather, a typology articulates relationships among constructs and facilitates testable predictions (cf. Doty and Glick 1994). In this way, a typology can propose multiple causal relationships in a given setting (Fiss 2011). While a typology paper enhances understanding of a phenomenon by delineating its key variants, it can be seen to differ from a synthesis or adaptation paper by virtue of its explanatory character. This is the typology’s raison d’etre; types always explain something, and the dimensions that distinguish types account for the different drivers, outcomes, or contingencies of particular variants of the phenomenon. By accommodating asymmetric causal relations, typologies facilitate the development of configurational arguments beyond simple correlations (Fiss 2011).

The model paper seeks to build a theoretical framework that predicts relationships between concepts. A conceptual model describes an entity and identifies issues that should be considered in its study: it can describe an event, an object, or a process, and explain how it works by disclosing antecedents, outcomes, and contingencies related to the focal construct (Meredith 1993; MacInnis 2011). This typically involves a form of theorizing that seeks to create a nomological network around the focal concept, employing a formal analytical approach to examine and detail the causal linkages and mechanisms at play (Delbridge and Fiss 2013). A model paper identifies previously unexplored connections between constructs, introduces new constructs, or explains why elements of a process lead to a particular outcome (Cornelissen 2017; Fulmer 2012).

The model paper contributes to extant knowledge by delineating an entity: its goal is “to detail, chart, describe, or depict an entity and its relationship to other entities” (MacInnis 2011). In a conceptual article, creative scope is unfettered by data-related limitations, allowing the researcher to explore and model emerging phenomena where few empirical data are available (Yadav 2010). The model paper typically contributes by providing a roadmap for understanding the entity in question by delineating the focal concept, how it changes, the processes by which it operates, or the moderating conditions that may affect it (MacInnis 2011).

A model paper typically begins from a focal phenomenon or construct that warrants further explanation. For example, Huang and Rust (2018) sought to explain the process and mechanism by which artificial intelligence (AI) will replace humans in service jobs. They employed literature that tackles key variables associated with the target phenomenon: service research illuminates the focal phenomenon, technology-enabled services, and research across multiple disciplines discusses the likely impact of AI on human labor. By synthesizing this literature pool, they identified four types of intelligence and then built a theory that could predict the impact of AI on human service labor. This involved a particular kind of formal reasoning, supported by research from multiple disciplines and real-world applications (Huang and Rust 2018). In other words, the authors use method theories and deductive reasoning to explain relationships between key variables, facilitated by theories in use (MacInnis 2011).

Model papers typically summarize arguments in the form of a figure that depicts the salient constructs and their relationships, or as a set of formal propositions that are logical statements derived from the conceptual framework (Meredith 1993). For example, Payne et al. (2017) used resource-based theory to develop a conceptual model of the antecedents and outcomes of customer value propositions. While figures and propositions of this kind help the reader by condensing the paper’s main message, Delbridge and Fiss (2013) noted that they are also a double-edged sword. At their best, propositions distill the essence of an argument into a parsimonious and precise form, but by virtue of this very ability, they also put a spotlight on the weaknesses in the argument chain. According to Cornelissen (2017), the researcher should therefore be clear about the “causal agent” in any proposed relationship between constructs when developing propositions—in other words, the trigger or force that drives a particular outcome or effect. Careful consideration and justification of the choice of theories and the manner in which they are integrated to produce the arguments is hence pivotal in sharpening and clarifying the argumentation to convince reviewers and readers.

Conclusions

This paper highlights the role of methodological considerations in conceptual papers by discussing alternative types of research design, in the hope of encouraging researchers to critically assess and develop conceptual papers accordingly. Authors of conceptual papers should readily answer the following questions: What is the logic of creating new knowledge? Why are particular information sources selected, and how are they analyzed? What role does each theory play? For reviewers, assessing conceptual papers can be difficult not least because the generally accepted and readily available guidelines for evaluating empirical research seldom apply directly to non-empirical work. By asking these questions, reviewers and supervisors can evaluate whether the research design of a paper or thesis is carefully crafted and clearly communicated to the reader.

The paper identifies four types of conceptual papers—Theory Synthesis, Theory Adaptation, Typology, and Model—and discusses their aims, methods of theory use, and potential contributions. Although this list is not exhaustive, these types offer basic templates for designing conceptual research and determining its intended contribution (cf. MacInnis 2011). Careful consideration of these alternative types can facilitate more conscious selection of approach and structure for a conceptual paper. Researchers can also consider opportunities for combining types. In many cases, mixing two types can be an attractive option. For example, after distinguishing types of service innovation in terms of their conceptual underpinnings, Helkkula et al. (2018) synthesized a novel conceptualization of service innovation that exploited the strengths of each type and mitigated their limitations. Typologies can also provide the basis for models, and synthesis can lead to theory adaptation.

This paper highlights the many alternative routes along which conceptual papers can advance extant knowledge. We should consider conceptual papers not just as a means to take stock, but to break new ground. Empirical research takes time to accumulate, and the scope for generalization is relatively narrow. In contrast, conceptual papers can strive to advance understanding of a concept or phenomenon in big leaps rather than incremental steps. To be taken seriously, any such leap must be grounded in thorough consideration and justification of an appropriate research design.

Funding Information

Open access funding provided by University of Turku (UTU) including Turku University Central Hospital.

A discussion of how different theoretical lenses can be integrated is beyond the scope of this paper, but see for example Okhuysen and Bonardi (2011) and Gioia and Pitre (1990).

Publisher’s note

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As a powerful means of theory building, conceptual articles are increasingly called for in marketing academia. However, researchers struggle to design and write non-empirical articles because of the lack of commonly accepted templates to guide their development. The aim of this paper is to highlight methodological considerations for conceptual papers: it is argued that such papers must be grounded in a clear research design, and that the choice of theories and their role in the analysis must be explicated and justified. The paper discusses four potential templates for conceptual papers – Theory Synthesis, Theory Adaptation, Typology, and Model – and their respective aims, approach for using theories, and contribution potential. Supported by illustrative examples, these templates codify some of the tacit knowledge that underpins the design of non-empirical papers and will be of use to anyone undertaking, supervising, or reviewing conceptual research.

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Writing the Conceptual Article: A Practical Guide (available open-access)

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Organizing Your Social Sciences Research Paper

• 6. The Methodology
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

The methods section describes actions taken to investigate a research problem and the rationale for the application of specific procedures or techniques used to identify, select, process, and analyze information applied to understanding the problem, thereby, allowing the reader to critically evaluate a study’s overall validity and reliability. The methodology section of a research paper answers two main questions: How was the data collected or generated? And, how was it analyzed? The writing should be direct and precise and always written in the past tense.

Kallet, Richard H. "How to Write the Methods Section of a Research Paper." Respiratory Care 49 (October 2004): 1229-1232.

Importance of a Good Methodology Section

You must explain how you obtained and analyzed your results for the following reasons:

• Readers need to know how the data was obtained because the method you chose affects the results and, by extension, how you interpreted their significance in the discussion section of your paper.
• Methodology is crucial for any branch of scholarship because an unreliable method produces unreliable results and, as a consequence, undermines the value of your analysis of the findings.
• In most cases, there are a variety of different methods you can choose to investigate a research problem. The methodology section of your paper should clearly articulate the reasons why you have chosen a particular procedure or technique.
• The reader wants to know that the data was collected or generated in a way that is consistent with accepted practice in the field of study. For example, if you are using a multiple choice questionnaire, readers need to know that it offered your respondents a reasonable range of answers to choose from.
• The method must be appropriate to fulfilling the overall aims of the study. For example, you need to ensure that you have a large enough sample size to be able to generalize and make recommendations based upon the findings.
• The methodology should discuss the problems that were anticipated and the steps you took to prevent them from occurring. For any problems that do arise, you must describe the ways in which they were minimized or why these problems do not impact in any meaningful way your interpretation of the findings.
• In the social and behavioral sciences, it is important to always provide sufficient information to allow other researchers to adopt or replicate your methodology. This information is particularly important when a new method has been developed or an innovative use of an existing method is utilized.

Bem, Daryl J. Writing the Empirical Journal Article. Psychology Writing Center. University of Washington; Denscombe, Martyn. The Good Research Guide: For Small-Scale Social Research Projects . 5th edition. Buckingham, UK: Open University Press, 2014; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008.

Structure and Writing Style

I.  Groups of Research Methods

There are two main groups of research methods in the social sciences:

• The e mpirical-analytical group approaches the study of social sciences in a similar manner that researchers study the natural sciences . This type of research focuses on objective knowledge, research questions that can be answered yes or no, and operational definitions of variables to be measured. The empirical-analytical group employs deductive reasoning that uses existing theory as a foundation for formulating hypotheses that need to be tested. This approach is focused on explanation.
• The i nterpretative group of methods is focused on understanding phenomenon in a comprehensive, holistic way . Interpretive methods focus on analytically disclosing the meaning-making practices of human subjects [the why, how, or by what means people do what they do], while showing how those practices arrange so that it can be used to generate observable outcomes. Interpretive methods allow you to recognize your connection to the phenomena under investigation. However, the interpretative group requires careful examination of variables because it focuses more on subjective knowledge.

II.  Content

The introduction to your methodology section should begin by restating the research problem and underlying assumptions underpinning your study. This is followed by situating the methods you used to gather, analyze, and process information within the overall “tradition” of your field of study and within the particular research design you have chosen to study the problem. If the method you choose lies outside of the tradition of your field [i.e., your review of the literature demonstrates that the method is not commonly used], provide a justification for how your choice of methods specifically addresses the research problem in ways that have not been utilized in prior studies.

The remainder of your methodology section should describe the following:

• Decisions made in selecting the data you have analyzed or, in the case of qualitative research, the subjects and research setting you have examined,
• Tools and methods used to identify and collect information, and how you identified relevant variables,
• The ways in which you processed the data and the procedures you used to analyze that data, and
• The specific research tools or strategies that you utilized to study the underlying hypothesis and research questions.

In addition, an effectively written methodology section should:

• Introduce the overall methodological approach for investigating your research problem . Is your study qualitative or quantitative or a combination of both (mixed method)? Are you going to take a special approach, such as action research, or a more neutral stance?
• Indicate how the approach fits the overall research design . Your methods for gathering data should have a clear connection to your research problem. In other words, make sure that your methods will actually address the problem. One of the most common deficiencies found in research papers is that the proposed methodology is not suitable to achieving the stated objective of your paper.
• Describe the specific methods of data collection you are going to use , such as, surveys, interviews, questionnaires, observation, archival research. If you are analyzing existing data, such as a data set or archival documents, describe how it was originally created or gathered and by whom. Also be sure to explain how older data is still relevant to investigating the current research problem.
• Explain how you intend to analyze your results . Will you use statistical analysis? Will you use specific theoretical perspectives to help you analyze a text or explain observed behaviors? Describe how you plan to obtain an accurate assessment of relationships, patterns, trends, distributions, and possible contradictions found in the data.
• Provide background and a rationale for methodologies that are unfamiliar for your readers . Very often in the social sciences, research problems and the methods for investigating them require more explanation/rationale than widely accepted rules governing the natural and physical sciences. Be clear and concise in your explanation.
• Provide a justification for subject selection and sampling procedure . For instance, if you propose to conduct interviews, how do you intend to select the sample population? If you are analyzing texts, which texts have you chosen, and why? If you are using statistics, why is this set of data being used? If other data sources exist, explain why the data you chose is most appropriate to addressing the research problem.
• Provide a justification for case study selection . A common method of analyzing research problems in the social sciences is to analyze specific cases. These can be a person, place, event, phenomenon, or other type of subject of analysis that are either examined as a singular topic of in-depth investigation or multiple topics of investigation studied for the purpose of comparing or contrasting findings. In either method, you should explain why a case or cases were chosen and how they specifically relate to the research problem.
• Describe potential limitations . Are there any practical limitations that could affect your data collection? How will you attempt to control for potential confounding variables and errors? If your methodology may lead to problems you can anticipate, state this openly and show why pursuing this methodology outweighs the risk of these problems cropping up.

NOTE:   Once you have written all of the elements of the methods section, subsequent revisions should focus on how to present those elements as clearly and as logically as possibly. The description of how you prepared to study the research problem, how you gathered the data, and the protocol for analyzing the data should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic. If necessary, consider using appendices for raw data.

ANOTHER NOTE: If you are conducting a qualitative analysis of a research problem , the methodology section generally requires a more elaborate description of the methods used as well as an explanation of the processes applied to gathering and analyzing of data than is generally required for studies using quantitative methods. Because you are the primary instrument for generating the data [e.g., through interviews or observations], the process for collecting that data has a significantly greater impact on producing the findings. Therefore, qualitative research requires a more detailed description of the methods used.

YET ANOTHER NOTE:   If your study involves interviews, observations, or other qualitative techniques involving human subjects , you may be required to obtain approval from the university's Office for the Protection of Research Subjects before beginning your research. This is not a common procedure for most undergraduate level student research assignments. However, i f your professor states you need approval, you must include a statement in your methods section that you received official endorsement and adequate informed consent from the office and that there was a clear assessment and minimization of risks to participants and to the university. This statement informs the reader that your study was conducted in an ethical and responsible manner. In some cases, the approval notice is included as an appendix to your paper.

III.  Problems to Avoid

Irrelevant Detail The methodology section of your paper should be thorough but concise. Do not provide any background information that does not directly help the reader understand why a particular method was chosen, how the data was gathered or obtained, and how the data was analyzed in relation to the research problem [note: analyzed, not interpreted! Save how you interpreted the findings for the discussion section]. With this in mind, the page length of your methods section will generally be less than any other section of your paper except the conclusion.

Unnecessary Explanation of Basic Procedures Remember that you are not writing a how-to guide about a particular method. You should make the assumption that readers possess a basic understanding of how to investigate the research problem on their own and, therefore, you do not have to go into great detail about specific methodological procedures. The focus should be on how you applied a method , not on the mechanics of doing a method. An exception to this rule is if you select an unconventional methodological approach; if this is the case, be sure to explain why this approach was chosen and how it enhances the overall process of discovery.

Problem Blindness It is almost a given that you will encounter problems when collecting or generating your data, or, gaps will exist in existing data or archival materials. Do not ignore these problems or pretend they did not occur. Often, documenting how you overcame obstacles can form an interesting part of the methodology. It demonstrates to the reader that you can provide a cogent rationale for the decisions you made to minimize the impact of any problems that arose.

Literature Review Just as the literature review section of your paper provides an overview of sources you have examined while researching a particular topic, the methodology section should cite any sources that informed your choice and application of a particular method [i.e., the choice of a survey should include any citations to the works you used to help construct the survey].

It’s More than Sources of Information! A description of a research study's method should not be confused with a description of the sources of information. Such a list of sources is useful in and of itself, especially if it is accompanied by an explanation about the selection and use of the sources. The description of the project's methodology complements a list of sources in that it sets forth the organization and interpretation of information emanating from those sources.

Azevedo, L.F. et al. "How to Write a Scientific Paper: Writing the Methods Section." Revista Portuguesa de Pneumologia 17 (2011): 232-238; Blair Lorrie. “Choosing a Methodology.” In Writing a Graduate Thesis or Dissertation , Teaching Writing Series. (Rotterdam: Sense Publishers 2016), pp. 49-72; Butin, Dan W. The Education Dissertation A Guide for Practitioner Scholars . Thousand Oaks, CA: Corwin, 2010; Carter, Susan. Structuring Your Research Thesis . New York: Palgrave Macmillan, 2012; Kallet, Richard H. “How to Write the Methods Section of a Research Paper.” Respiratory Care 49 (October 2004):1229-1232; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008. Methods Section. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Rudestam, Kjell Erik and Rae R. Newton. “The Method Chapter: Describing Your Research Plan.” In Surviving Your Dissertation: A Comprehensive Guide to Content and Process . (Thousand Oaks, Sage Publications, 2015), pp. 87-115; What is Interpretive Research. Institute of Public and International Affairs, University of Utah; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University; Methods and Materials. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College.

Writing Tip

Statistical Designs and Tests? Do Not Fear Them!

Don't avoid using a quantitative approach to analyzing your research problem just because you fear the idea of applying statistical designs and tests. A qualitative approach, such as conducting interviews or content analysis of archival texts, can yield exciting new insights about a research problem, but it should not be undertaken simply because you have a disdain for running a simple regression. A well designed quantitative research study can often be accomplished in very clear and direct ways, whereas, a similar study of a qualitative nature usually requires considerable time to analyze large volumes of data and a tremendous burden to create new paths for analysis where previously no path associated with your research problem had existed.

To locate data and statistics, GO HERE .

Another Writing Tip

Knowing the Relationship Between Theories and Methods

There can be multiple meaning associated with the term "theories" and the term "methods" in social sciences research. A helpful way to delineate between them is to understand "theories" as representing different ways of characterizing the social world when you research it and "methods" as representing different ways of generating and analyzing data about that social world. Framed in this way, all empirical social sciences research involves theories and methods, whether they are stated explicitly or not. However, while theories and methods are often related, it is important that, as a researcher, you deliberately separate them in order to avoid your theories playing a disproportionate role in shaping what outcomes your chosen methods produce.

Introspectively engage in an ongoing dialectic between the application of theories and methods to help enable you to use the outcomes from your methods to interrogate and develop new theories, or ways of framing conceptually the research problem. This is how scholarship grows and branches out into new intellectual territory.

Reynolds, R. Larry. Ways of Knowing. Alternative Microeconomics . Part 1, Chapter 3. Boise State University; The Theory-Method Relationship. S-Cool Revision. United Kingdom.

Yet Another Writing Tip

Methods and the Methodology

Do not confuse the terms "methods" and "methodology." As Schneider notes, a method refers to the technical steps taken to do research . Descriptions of methods usually include defining and stating why you have chosen specific techniques to investigate a research problem, followed by an outline of the procedures you used to systematically select, gather, and process the data [remember to always save the interpretation of data for the discussion section of your paper].

The methodology refers to a discussion of the underlying reasoning why particular methods were used . This discussion includes describing the theoretical concepts that inform the choice of methods to be applied, placing the choice of methods within the more general nature of academic work, and reviewing its relevance to examining the research problem. The methodology section also includes a thorough review of the methods other scholars have used to study the topic.

Bryman, Alan. "Of Methods and Methodology." Qualitative Research in Organizations and Management: An International Journal 3 (2008): 159-168; Schneider, Florian. “What's in a Methodology: The Difference between Method, Methodology, and Theory…and How to Get the Balance Right?” PoliticsEastAsia.com. Chinese Department, University of Leiden, Netherlands.

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