essay on online shopping a trend

IELTS Writing Task 2: Essay on online shopping/virtual shopping/e-shopping; with planning and model answer

This IELTS Writing Task 2 post is about ‘online shopping and its merits and demerits’ . Here, I’ve discussed the advantages and disadvantages of virtual/online/e-shopping and presented a model answer on this Task 2 question. This model answer can guide you to write an answer to any online shopping related essay.

Let’s have a look at the question we are going to discuss today.

IELTS Writing Task 2: Essay on online shopping/virtual shopping/e-shopping; with planning and model answer

The language of this task 2 question can be different in different exams.

Here’s another example of the same question:

An increasing number of people are buying what they need online.

What are the advantages and disadvantages for both individuals and companies to shopping online?

Nowadays, e-shopping or shopping online has an increasing trend among shoppers. It has both positive and negative sides. First, we need to make a plan for writing on this topic.

Here’s a short plan that may help you.

Planning and organisation:

Here is how I’ve planned the essay with a 4-paragraph structure:

Introduction: topic + thesis (2 sentences can be sufficient): Introduce the topic – ‘online shopping getting more popular’. Then write a thesis on how you are going to show that there are some positives and negatives of the issue.
Body paragraph on the reasons behind virtual shopping being so popular: You can write about straightforward ideas e.g. people get more convenience, and availability or choice of products. Give some real-life examples here.
Body paragraph on the negative sides of online shopping: Again, present some very general ideas e.g. customers get cheated and people become more isolated. Give some real-life examples here too
Conclusion: restate your ideas Online shopping has both advantages and disadvantages. You can give your personal opinion on how the disadvantages can be reduced.

Now let’s take a look at the model answer.

Model answer: expected band score – 7.5 to 8.0

In recent years, the rate of in-store shopping has plunged due to vast opportunities for buying different products including daily necessaries from hundreds of online stores. This essay will try to demonstrate chances such as convenience and product availability as the reasons behind the popularity of e-shopping whereas it will focus on swindling and isolation as the pitfalls of this issue.

Initially, the prime reason behind the popularity of e-shopping is convenience which can be easily understood from the thousands of virtual shops all over the world. To illustrate, people nowadays are busier than ever because of the fast pace of the world and they want to save as much time as they can for relaxation. Virtual shopping gives this magnificent prospect of time-saving and so people enjoy taking it. Besides, superstores sometimes run out of products in the precise moment when people need them which online shops rarely have this crisis. For instance, I needed a flat-screen monitor a few months ago but my local store had it out of stock. When I peeped into some online stores I found it easily on eBay.

Meanwhile, though shopping on the internet looks very promising, it is not without its setbacks. Many people, mostly the newcomers, regularly complain of getting tricked on virtual shopping and the rate of complaints is increasing at a faster rate. To explain, one of my friends has recently got swindled when he paid in advance for a smartwatch. Additionally, people often become isolated in their rooms through e-shopping which can affect their feelings and behaviour. As an example, a friend of mine started shopping online a couple of years ago even though the nearest superstore was only 500 metres away. His neighbours, nowadays, describe him as an ill-mannered and antisocial person which, needless to say, is the result of being home and becoming isolated from the outer world.

In brief, virtual shoppers obtain greater benefits if compared to in-store shoppers. Converting such shopping to a stress-free experience, it is turning out to be progressively more convenient. However, as clients may sometimes get deceived and become cut off from the social world, concerned authorities should look into the matter cautiously. (360 words)

Here are some other Task 2 questions which can be answered taking help from the given essay example on online shopping:

Some people support online shopping because it is convenient, while others argue that shopping on the internet poses threats. Discuss both views and give your opinions.
Nowadays on-line shopping has become more popular than in-store shopping. Is it a positive or a negative development?
Nowadays many people go shopping in their free time. Shopping has replaced many other activities that people used to choose as their hobby. What are the reasons for this? Is this a positive or negative development?

If you have written any answer to this question, you can post it in the comment box and we can discuss about it in details.

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9 thoughts on “ IELTS Writing Task 2: Essay on online shopping/virtual shopping/e-shopping; with planning and model answer ”

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Essay on Online Shopping in 100, 200, and 300 Words.

Updated on
Dec 23, 2023

Shopping is something that many people love. It is particularly cherished during festive occasions such as Diwali, Navratri, Christmas or New Year etc. The shopping world has changed and evolved majorly providing us with various options of the same. The convenience of online shopping platforms has now come into play. Those days when individuals have to take on a long journey of shopping are now past us, all thanks to the various online shopping platforms that are now at the tip of our fingers. This is just a brief introduction to how to write an essay on online shopping. Now let’s have a look at the samples of essay on online shopping.

Table of Contents

1 Essay on Online Shopping in 100 words
2 Essay on Online Shopping in 200 words
3 Essay on Online Shopping in 300 words
4 Advantages

Essay on Online Shopping in 100 words

The way of shopping has been revolutionized by online shopping. It has made it possible and convenient to shop virtually from literally anywhere.

The sheer convenience of shopping is one of the biggest advantages of online shopping. For those individuals who are busy and struggle to find time to visit stores, online shopping is a boon.

Payments are easy this way with the variety of options available such as debit card, cash on delivery, etc. However, there are some drawbacks to online shopping as well. One of them is the delivery of the wrong item or a different item than that seen online. So one should be cautious and should make informed decisions.

Essay on Online Shopping in 200 words

In today’s world, as science and technology are progressing, a lot of things have become more convenient for us. One such thing is online shopping. Over the years due to its high demand and convenience, it has become very popular. It involves virtually placing an order on any e-commerce website without the need to go to a physical store. Various items such as shoes, gadgets, household products, and even groceries can be ordered from the comfort of your couch.

Some of the key benefits of online shopping are mentioned below:-

Crowd Avoided:- since online shopping is virtual, going to crowded places is avoided.
Convenience:- we can shop from the convenience of our homes.
Variety in products:- on different platforms, a vast range of products is available.
Variety in payment options:- Debit card, cash on delivery, etc payment options make it all the more convenient.

Although there are many pros of online shopping, there are some drawbacks as well. There have been many instances where wrong or damaged goods got delivered. There can be instances where a product may not match its depiction when delivered in terms of color, etc.

Some websites even scam people and are fraudulent. Hence, it is important to take caution while shopping online.

Essay on Online Shopping in 300 words

During the 1990s, the concept of online shopping came into play and since then, it has grown exponentially. Its principle lies in the ease of browning a wide variety of products on various e-commerce platforms. The e-commerce platforms have played a central role in enabling different businesses to connect with a global audience.

There are various advantages of online shopping, one of them being the ease of online shopping. With virtual stores, you can shop whenever you want and from wherever you want. The limitations of time don’t apply to the online stores. They are accessible 24/7.

Wide Range of Products

When you shop online, you don’t have to limit yourself to only some products. Online shopping opens a portal to a wide range of products to select from.

Saves time and money

When you shop online, you don’t have to go to stores. You can shop from the comfort of your couch. That saves time. And generally, online stores have some kind of offers and discounts going on which saves you money.

Although online shopping has many advantages, there are also certain cons that it carries with it. Some of those cons are mentioned below:-

Shipping issues

There can issues with the shipping such as the product may get damaged during its shipping or it may get delivered to the wrong address.

Return Policies

If the product is different and the customer wants to return it or get a refund, there can be certain policies that prevent the same.

Different item Delivery

There can be instances where the product, when delivered, is different from the one shown in the images online. Returning the same can be a hassle too as it has to be repacked for some resellers.

Hence, when shopping online one should always be cautious and take calculated decisions.

Deepansh Gautam

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Online Shopping Essay

500+ words online shopping essay.

The trend of online shopping has increased in recent times with the increase of e-commerce and digital technology. With just a single click, you can shop for everything by sitting at your home as per your choice, convenience and budget. This essay on online shopping will help students learn about the pros and cons of online shopping. We have also compiled a list of CBSE Essays on different topics to help them improve their essay-writing skills. These essays will also help them improve their scores on the English exam.

What Does Online Shopping Mean?

Online shopping is the activity of buying products and services over the internet using a web browser or mobile app. It means buyers have to go online to reach a seller’s website and then select the product they want to purchase. The buyer can pay for the goods and services either online with a credit or debit card or upon delivery. Online shopping sites are also known by many other names such as e-shop, e-web-store, e-store, internet shop, web-store, web-shop, virtual store and online store. An online shop creates a physical analogy for buying products or services. Some of the famous online retailing corporations which facilitate the experience of online shopping are Amazon, eBay, Flipkart, Myntra, etc.

Online shopping is a growing area of the digital world and technology. Establishing a store on the Internet gives various options to consumers. With the growth of online shopping, most businesses have started selling their products online. Now, just having physical stores is not enough in this fast-paced world. Having online store interfaces for consumers has also become essential for running a business in the current scenario.

Benefits of Online Shopping

There are numerous advantages of online shopping. People feel more convenient while shopping online. They can shop from anywhere at their own convenient time through easy and safe payment methods. Online shopping has empowered consumers with various advantages such as convenience and time-saving, lower search costs, better product selection, lower prices, etc. One of the biggest benefits of online shopping is that you can buy the items you want with just a single click. Online stores are open 24 hours a day and are accessible from any location with an internet connection.

Online stores carry more variations and provide more varieties of a product as compared to traditional stores. This is because online stores don’t need to attractively display their items on shelves, and they can keep a larger amount of inventory on hand. They might also have small amounts of each item since they don’t need to display them and can order more from their supplier as needed.

Online shops tend to provide more information about items for sale than you would get in a physical store. Product descriptions most often include a description from the manufacturer, another description from the vendor, specific technical and size details, reviews from professional magazines and journals, and reviews from people who have bought the product. Having all this information available when you are considering a purchase makes you a more informed consumer without having to perform extra research by yourself.

Online stores are not burdened by the costs of running a physical store, such as the rent of the physical premises and wages of sales staff. The cost savings by online stores lead to lower pricing on the internet, passing on cost savings to shoppers. The internet encourages online vendors to compete with one another by lowering prices.

Disadvantages of Online Shopping

The benefits of shopping online also come with potential risks and dangers. When you shop online, you can’t touch or try out the product. You have to depend upon product pictures only. You can’t buy the product instantly. If you don’t get the product in hand immediately after payment, you have to wait for delivery, which can take days to weeks. There is no guarantee that you will get the product in its original shape; it might get damaged on the way. Sometimes, the product is very different from the pictures and description due to various reasons and also has poor quality. If, after receiving the package, expectations weren’t met, you need to go through a returns process which can be time-consuming. Apart from these, there is also a chance of security threats from online shopping. If the site is not secured, you have a risk of losing your card information.

Online shopping is one of the convenient ways of purchasing different products. However, there are some products which are better if they are purchased from physical stores. So, in the future, we can expect online stores to improve their technology, making way for a much easier and faster shopping experience.

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Essay on Online Shopping 1000+ Words

Online shopping has transformed the way we buy goods and services. With the advent of the internet, the world of commerce has shifted to digital platforms, making shopping easier, more convenient, and accessible to millions. In this essay, we will explore the many advantages of online shopping, from its convenience and affordability to its impact on traditional retail stores and its role in our modern lives.

Convenience at Your Fingertips

Online shopping offers unparalleled convenience. Shoppers can browse and buy products from the comfort of their homes, avoiding long queues and crowded stores. This convenience is especially valuable for people with busy schedules or limited mobility.

A Vast Selection of Products

Online stores provide a vast array of products that cater to diverse tastes and needs. Whether you’re searching for clothing, electronics, books, or specialty items, the internet offers an extensive selection with just a few clicks.

Competitive Prices and Discounts

Online retailers often offer competitive prices and frequent discounts. The ability to compare prices from different sellers allows shoppers to find the best deals, saving them money. Additionally, online coupons and promotions further enhance the affordability of online shopping.

Access to Customer Reviews

Before making a purchase, online shoppers can read customer reviews and ratings. This valuable information helps buyers make informed decisions, ensuring they select high-quality products that meet their expectations.

Convenient Payment Options

Online shopping platforms offer a variety of payment options, including credit cards, digital wallets, and online banking. This flexibility makes transactions convenient and secure for shoppers.

Doorstep Delivery

One of the most significant advantages of online shopping is doorstep delivery. Shoppers no longer need to travel to physical stores; instead, their purchases are delivered to their homes, saving time and effort.

Avoiding Impulse Buying

Online shopping can help shoppers avoid impulse buying. In physical stores, tempting displays and in-store promotions can lead to unplanned purchases. Online, buyers have more control over their choices and can stick to their budgets.

Accessibility for All

Online shopping breaks down geographical barriers. People in remote areas or those with limited access to physical stores can now access a wide range of products and services, leveling the playing field for all consumers.

Impact on Traditional Retail

The rise of online shopping has led to changes in the traditional retail landscape. Many brick-and-mortar stores have expanded their online presence to remain competitive. Additionally, some traditional retailers now offer online shopping options to meet the changing preferences of consumers.

Environmental Benefits

Online shopping can have environmental benefits. With fewer people driving to physical stores, there may be a reduction in carbon emissions. Additionally, some online retailers are committed to eco-friendly packaging and sustainable practices.

Conclusion of Essay on Online Shopping

In conclusion, online shopping has revolutionized the way we shop and has become an integral part of our modern lives. Its convenience, affordability, vast selection, and accessibility have made it a preferred choice for millions of consumers worldwide. As technology continues to advance, online shopping will likely become even more accessible and efficient.

While online shopping offers numerous advantages, it’s essential to exercise caution and practice responsible consumerism. Shoppers should be mindful of their budgets, protect their personal information, and support reputable online retailers.

Online shopping is not just a trend; it’s a reflection of our evolving society and the way we adapt to new technologies. As we embrace the convenience and benefits it offers, let us also be conscious consumers who make informed choices, ensuring that online shopping continues to enhance our lives while respecting the principles of responsible shopping and sustainability.

Also Check: The Essay on Essay: All you need to know

Home — Essay Samples — Business — Online Shopping — The Rise of Online Shopping in Society

The Rise of Online Shopping During The Pandemic: Benefits and Drawbacks

Categories: E Commerce Online Shopping

About this sample

Words: 1388 |

Published: Sep 25, 2018

Words: 1388 | Page: 1 | 7 min read

Introduction, online shopping panic, benefits of online shopping, drawbacks of online shopping.

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COVID-19 has changed online shopping forever, survey shows

The pandemic has accelerated the shift towards a more digital world and triggered changes in online shopping behaviours that are likely to have lasting effects.

Woman accepts shopping ordered online from delivery person in a mask and gloves.

The COVID-19 pandemic has forever changed online shopping behaviours, according to a survey of about 3,700 consumers in nine emerging and developed economies.

The survey, entitled “ COVID-19 and E-commerce ”, examined how the pandemic has changed the way consumers use e-commerce and digital solutions. It covered Brazil, China, Germany, Italy, the Republic of Korea, Russian Federation, South Africa, Switzerland and Turkey.

Following the pandemic, more than half of the survey’s respondents now shop online more frequently and rely on the internet more for news, health-related information and digital entertainment.

Consumers in emerging economies have made the greatest shift to online shopping, the survey shows.

“The COVID-19 pandemic has accelerated the shift towards a more digital world. The changes we make now will have lasting effects as the world economy begins to recover,” said UNCTAD Secretary-General Mukhisa Kituyi.

He said the acceleration of online shopping globally underscores the urgency of ensuring all countries can seize the opportunities offered by digitalization as the world moves from pandemic response to recovery.

Online purchases rise but consumer spending falls

The survey conducted by UNCTAD and Netcomm Suisse eCommerce Association, in collaboration with the Brazilian Network Information Center (NIC.br) and Inveon, shows that online purchases have increased by 6 to 10 percentage points across most product categories.

The biggest gainers are ICT/electronics, gardening/do-it-yourself, pharmaceuticals, education, furniture/household products and cosmetics/personal care categories ( Figure 1 ).

Figure 1: Percentage of online shoppers making at least one online purchase every two months

However, average online monthly spending per shopper has dropped markedly ( Figure 2). Consumers in both emerging and developed economies have postponed larger expenditures, with those in emerging economies focusing more on essential products.

Tourism and travel sectors have suffered the strongest decline, with average spending per online shopper dropping by 75%.

Figure 2: Fall of average online spending per month since COVID-19, per product category

“During the pandemic, online consumption habits in Brazil have changed significantly, with a greater proportion of internet users buying essential products, such as food and beverages, cosmetics and medicines,” said Alexandre Barbosa, manager of the Regional Center of Studies on the Development of Information Society (Cetic.br) at the Brazilian Network Information Center (NIC.br).

Increases in online shopping during COVID-19 differ between countries, with the strongest rise noted in China and Turkey and the weakest in Switzerland and Germany, where more people were already engaging in e-commerce.

The survey found that women and people with tertiary education increased their online purchases more than others. People aged 25 to 44 reported a stronger increase compared with younger ones. In the case of Brazil, the increase was highest among the most vulnerable population and women.

Also, according to survey responses, small merchants in China were most equipped to sell their products online and those in South Africa were least prepared.

“Companies that put e-commerce at the heart of their business strategies are prepared for the post-COVID-19 era,” said Yomi Kastro, founder and CEO of Inveon. “There is an enormous opportunity for industries that are still more used to physical shopping, such as fast-moving consumer goods and pharmaceuticals.”

“In the post-COVID-19 world, the unparalleled growth of e-commerce will disrupt national and international retail frameworks,” said Carlo Terreni, President, NetComm Suisse eCommerce Association.

“This is why policymakers should adopt concrete measures to facilitate e-commerce adoption among small and medium enterprises, create specialized talent pools and attract international e-commerce investors.”

Digital giants grow stronger

According to the survey, the most used communication platforms are WhatsApp, Instagram and Facebook Messenger, all owned by Facebook.

However, Zoom and Microsoft Teams have benefitted the most from increases in the use of video calling applications in workplaces.

In China, the top communication platforms are WeChat, DingTalk and Tencent Conference, the survey shows.

Changes are here to stay

The survey results suggest that changes in online activities are likely to outlast the COVID-19 pandemic.

Most respondents, especially those in China and Turkey, said they’d continue shopping online and focusing on essential products in the future.

They’d also continue to travel more locally, suggesting a lasting impact on international tourism.

The great consumer shift: Ten charts that show how US shopping behavior is changing

Anyone who has hosted a game night over video chat or ordered groceries to be delivered at home for the first time understands how profoundly the COVID-19 crisis has changed our behavior as consumers. But which of these changes will stick? We see several that are key:

Flight to online

Shock to loyalty, need for hygiene transparency, back to basics and value, rise of the homebody economy.

We’ve boiled down extensive McKinsey consumer research into ten exhibits to illustrate the trends and the consumer segments associated with each.

1. Digital shopping is here to stay

Physical distancing and stay-at-home orders have forced whole consumer segments to shop differently. A few months into COVID-19, consumer shopping online has increased significantly across many categories. Consumer intent to shop online continues to increase, especially in essentials and home-entertainment categories. More interestingly, these habits seem like they’re going to stick as US consumers report an intent to shop online even after the COVID-19 crisis. Categories where expected growth in online shoppers exceeds 35 percent include essentials such as over-the-counter (OTC) medicine, groceries, household supplies, and personal-care products. Even discretionary categories such as skin care and makeup, apparel, and jewelry and accessories show expected customer growth of more than 15 percent.

2. Millennials and high-income earners are in the lead when it comes to shopping online

While the shift to online shopping has been near universal across categories, high-income earners and millennials are leading the way in shifting spend online across both essential and nonessential items. Gen X has experienced a similar online shift, although not at the same scale as millennials. Gen Z has concentrated its shift online in particular categories: apparel and footwear, at-home entertainment, and food takeout/delivery.

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3. consumers are switching brands at unprecedented rates.

The crisis has prompted a surge of new activities, with an astonishing 75 percent of US consumers trying a new shopping behavior in response to economic pressures, store closings, and changing priorities. This general change in behavior has also been reflected in a shattering of brand loyalties, with 36 percent of consumers trying a new product brand and 25 percent incorporating a new private-label brand. Of consumers who have tried different brands, 73 percent intend to continue to incorporate the new brands into their routine. Gen Z and high earners are most prone to switching brands.

The beneficiaries of this shift include big, trusted brands, which are seeing 50 percent growth during the crisis, and private labels, which have outpaced the retail market. Some 80 percent of customers who started using a private brand during the pandemic indicate they intend to continue using it once the COVID-19 crisis subsides.

4. Brands need to ensure strong availability and also convey value

Shoppers have cited a number of reasons for switching brands, with availability (in-store and online), convenience, and value leading the pack.

For marketers, this highlights the need to quickly become aware of when shoppers are migrating brands or retailers and then to manage the logistics to ensure product and service availability. Looking at China, which is further along in its recovery cycle than most countries, the increase in promotional activity to cater to consumers’ focus on value in apparel is expected to continue.

5. US consumers are changing how they shop in response to health and safety concerns

As Americans contemplate going back out to shop, hygiene and hygiene transparency have emerged as important sources of concern. It is becoming increasingly important for stores and restaurants to not only follow hygiene protocols (thorough cleaning and masks for consumers and employees are top priorities) but also communicate effectively that they are following those procedures.

US consumers have already started to change their behavior in response to hygiene concerns. Technologies that enhance hygiene, particularly contactless activities such as food and grocery delivery and curbside pickup, are taking off. There is strong intent to continue contactless activities across the United States. As an example, 79 percent of consumers intend to continue or increase their usage of self-checkout in retail after COVID-19. Millennials and Gen Z are the widest adopters of contactless activities.

6. Consumer shopping intent is focused on essentials

Around 40 percent of US consumers have reduced spending in general, and they expect to continue to cut back on nonessentials specifically. This reality reflects profound discomfort about the state of the economy.

With overall consumer spending declining, intent to spend in essential categories is increasing. Even among those with higher incomes, we see that while essentials show spending momentum, intent to buy discretionary products still lags significantly. As the worst of the crisis abates, we do see online spending in nonessential categories such as apparel and footwear starting to come back. This effect is strongest among high-income earners, consumers in the Northeast, and Gen Z.

7. Consumers want value for their money—especially in essential categories

Tied to the concern about the state of the economy is an increasing consumer focus on value—especially for essential categories. For example, in shampoo on Amazon, value and mass products have experienced the greatest increase in share, at two- and five-percentage-points gains, respectively. Premium shampoo products have seen significantly less growth in comparison, losing more than five points of volume.

How marketing leaders can both manage the coronavirus and plan for the future

How marketing leaders can both manage the coronavirus crisis and plan for the future

8. americans are changing how they spend their time at home.

Americans are spending more of their at-home time on domestic activities, media, and news. Intent to eat more at home post-COVID-19 has strengthened significantly over the past three months. Usage of popular online entertainment platforms has skyrocketed. (The popular video game Fortnite recently hosted a concert that was “attended” by 12.3 million users. 1 Andrew Webster, “More than 12 million people attended Travis Scott’s Fortnite concert,” The Verge , April 23, 2020, theverge.com. ) Investment in at-home fitness through equipment purchases and online activity is growing. Consumers still expect to spend more time on at-home activities, even in less-restricted regions.

9. Americans are concerned about going back to regular activities outside the home

As economies reopen, 73 percent of consumers are still hesitant to resume regular activities outside the home. They are concerned about going to a hair salon, gym, or restaurant, but are especially worried about shared environments, such as public transportation, ride sharing, air travel, and being in crowded spaces, such as attending large indoor or outdoor events.

Behaviors vary by consumer segment

10. ‘great consumer shift’ trends vary by consumer segment.

US consumer-segment behavior varies significantly across the next-normal trends. We have identified five customer segments driven by optimism, health, and financial concerns, each of relatively similar size. These five segments exhibit the consumer trends to a different degree and have the following characteristics:

Affluent and unaffected: These consumers express general optimism about the future (~20 percent higher than the overall US consumer population), skew male (60 percent), and make more than $100,000 a year. They tend to be able to stay at home during the pandemic crisis, allowing them to shop more online. This group is slightly less price sensitive than other cohorts due to greater job stability.

Uprooted and underemployed: These consumers are feeling major impact on both their finances and health due to job insecurity. They are cautious about how they spend money, with low optimism about future economic conditions. Not surprisingly, this group is trading down to essentials and value, swapping out brands, and shopping online when possible.

Financially secure but anxious: This population is largely 65 years old and older and is generally pessimistic about economic conditions after COVID-19, which has had a major impact on their habits. This group has expressed the greatest need for hygiene transparency, with above-average concerns on safety and well-being and concerns about the ability to get necessary supplies.

Out trying to make ends meet: These consumers are being cautious about how they spend money and feel that their jobs and job security have been heavily impacted by COVID-19. This group has significant representation from minority groups and rural populations. They are less likely to be able to stay at home (hence their lower likelihood to be part of the homebody economy), but they are strongly moving toward shopping for essentials and value.

Disconnected and retired: This category denotes those who are retired, over 65, and have a lower income level than the financially-secure-but-anxious segment. They are broadly optimistic about economic conditions after COVID-19 and are less likely to display any of the next-normal characteristics. Predominantly from Southern and suburban areas of the country, this group has not exhibited significant changes in shopping behavior.

As retailers contemplate the changes in consumer behavior, they will need to adjust their strategies and execution to adapt to the new norms, including:

Adjusting mix and spend to where the consumer is now (go digital, ensure full coverage of bottom-funnel marketing and demand capture, think region-by-region)
Revamping messaging and creative to be in sync with the times, particularly in terms of hygiene and value
Ensuring the end-to-end journey meets the new hygiene and at-home needs
Managing corporate social-responsibility efforts to build brand strength authentically
Refocusing on online and pickup solutions and rebuilding real-time measurement plans, as traditional media-mix models won’t suffice

Further, it will be important for brands to reevaluate and reprioritize their target audience and consumer segments, as the emphasis on each of the next-normal trends will vary based on the target consumer.

Tamara Charm is a senior expert in McKinsey’s Boston office, where Jamie Wilkie is a partner; Becca Coggins is a senior partner in the Chicago office; and Kelsey Robinson is a partner in the San Francisco office.

The authors wish to thank Nidhi Aurora, Sarah Coury, Resil Das, and Salvador Tormo for their contributions to this article.

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UNDERSTANDING CONSUMER BEHAVIOUR IN THE DIGITAL AGE: A STUDY OF ONLINE SHOPPING HABITS

December 2023
48(3):84-93

Duke College of Management Bhopal

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Essay on Online Shopping

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In the digital age, the paradigm of shopping has undergone a transformative shift, moving from traditional brick-and-mortar stores to the vast, boundless expanse of the internet. Online shopping has not only redefined consumer behavior but has also reshaped the global retail landscape, offering a convenience and variety that were unimaginable just a few decades ago. This essay delves into the evolution, benefits, challenges, and future prospects of online shopping, providing a comprehensive overview for students interested in exploring this modern-day phenomenon.

The Advent and Growth of Online Shopping

The inception of online shopping can be traced back to the 1990s, with the launch of the first internet-based retailers. This novel concept leveraged the burgeoning power of the internet to offer consumers the ability to purchase goods without the need to physically visit a store. Over the years, the proliferation of e-commerce platforms and the advent of secure online payment methods have significantly fueled the growth of online shopping. Today, giants like Amazon and eBay, along with countless other e-commerce websites, dominate the digital marketplace, offering everything from books and electronics to groceries and clothing.

Benefits of Online Shopping

Convenience.

The paramount advantage of online shopping is convenience. Consumers can browse and purchase products at any time, from anywhere, without the constraints of store hours or geographical limitations. This 24/7 availability has made it possible for individuals to shop at their own pace and on their own terms.

Wide Range of Products

Online stores offer an unparalleled variety of products, surpassing the physical limits of conventional stores. Shoppers can access a global market, finding niche products that are not available locally. This diversity ensures that consumers can easily compare products, prices, and features, leading to more informed purchasing decisions.

Cost Savings

Online shopping can also lead to significant cost savings. E-commerce stores often offer lower prices than physical stores due to lower overhead costs. Additionally, the ability to compare prices across different platforms easily helps consumers find the best deals. Exclusive online discounts, coupons, and cashback offers further enhance the potential for savings.

Ease of Information

The digital marketplace provides consumers with extensive product information, reviews, and ratings, enabling them to research and evaluate products thoroughly before making a purchase. This level of transparency fosters consumer confidence and satisfaction.

Challenges of Online Shopping

Despite its many advantages, online shopping is not without its challenges.

Cybersecurity Concerns

One of the most pressing issues is cybersecurity. The risk of data breaches and identity theft is a significant concern for online shoppers, necessitating robust security measures to protect personal and financial information.

Lack of Physical Verification

The inability to physically inspect or try out products before purchase can lead to dissatisfaction. This is particularly relevant for categories like clothing and footwear, where fit and feel are important.

Dependence on Technology

Online shopping’s reliance on internet connectivity and digital payment systems can exclude those without access to such technologies, highlighting a digital divide.

Environmental Impact

The environmental footprint of online shopping, driven by packaging waste and carbon emissions from delivery logistics, is a growing concern. While efforts are being made to mitigate these impacts, sustainable practices are not yet widespread in the e-commerce industry.

The Future of Online Shopping

The future of online shopping promises further innovation and expansion. Advancements in technology, such as augmented reality (AR) and virtual reality (VR), are set to enhance the online shopping experience by allowing consumers to virtually try on clothes or visualize furniture in their homes before making a purchase. The integration of artificial intelligence (AI) and machine learning algorithms offers personalized shopping experiences, with recommendations tailored to individual preferences and browsing history.

Sustainability is also becoming a focal point, with more consumers demanding eco-friendly products and practices. E-commerce platforms are responding by adopting sustainable packaging, optimizing delivery routes to reduce carbon emissions, and showcasing environmentally responsible brands.

In conclusion, Online shopping has revolutionized the retail industry, offering convenience, variety, and cost-effectiveness. However, it also presents challenges that need to be addressed to ensure a secure, satisfying, and sustainable shopping experience. As technology advances and consumer expectations evolve, the digital marketplace will continue to adapt, offering new opportunities and solutions. For students participating in an essay writing competition, understanding the complexities of online shopping is crucial. It is not just about the convenience of purchasing goods from the comfort of one’s home but also about recognizing the broader implications on society, the economy, and the environment. As we navigate the digital marketplace, it is essential to be informed, cautious, and conscious of the choices we make, shaping the future of online shopping in a way that benefits all stakeholders.

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Online Shopping is Significantly Increasing IELTS Essay

Online shopping is significantly increasing. What impact does this have on people, what are the disadvantages and what are the job opportunities?

Online shopping is significantly increasing. What effects does this have on the environment and the types of jobs required?

Give reasons for your answer and include any relevant examples from your own knowledge or experience. You should write at least 250 words.

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Online Shopping is Significantly Increasing Essay

With the proliferation of the internet and smart phones, the trend of online shopping is growing rapidly. This positively impacts environment as it reduces the need of a shop which has a huge ecological footprint. This impacts society in a favourable way by reducing the cost of goods and in an adverse way by reducing employment.

Traditionally, the products are sold in a physical shop that requires lighting, air conditioning, and infrastructure. All these result in environment damage as these require a lot of electricity and raw materials that lead to emission of green house gases (GHG). Online shops, on the other hand, merely transport goods from a large regional warehouse whose ecological footprint, a measure of GHG emissions, is lower than local shops. Thus online shops contribute in environment preservation.

Online shops have better economies of scale and thus offer prices which are lesser than local shops. This reduces the financial burden on pockets of the citizens and enables them to spend more on education, culture, and entertainment. These activities promote social stability and harmony. However, they often lead to lower employment in a society. Various studies have proved that online shops employ fewer people and they result in shutting down of local businesses. For example, Amazon and Flipkart offer heavy discounts on various products that local stores can not provide. This shifts consumer choice to these websites and this results in loss of local jobs.

In conclusion, online shopping impacts a society and the environment in various positive and negative ways. While it reduces employment opportunities for some, it reduces the cost of goods for a large majority of people. It also reduces the impact of business on the environment. This builds environment sustainability, social stability and economic prosperity in a region.

IELTS Writing Task 2 Online Shopping

In recent years, online shopping has gained more and more popularity all over the world. This tendency has several impacts on the environment and on various jobs related to electronic commerce.

The rise of online shopping is both beneficial and harmful to the environment to some extent. One obvious benefit of this trend is that it can help reduce the number of private vehicles travelling to brick-and-mortar stores since orders of customers from different locations can be grouped and delivered to homes at once. This will eventually lessen a great deal of exhaust fumes which is one of the causes of air pollution. However, if people are encouraged to shop online more, more plastic wastes will be released to the environment, especially water body such as rivers and oceans. This, as a consequence, will do harm to natural habitats of numerous marine species and worsen the problem of environmental pollution.

The growth of e-shopping has also brought both negative and positive impacts on people’s employment. On the one hand, this trend has created a variety of work opportunities for people, especially for those who major in information technology. To maintain an e-store, there will be a need for many kinds of jobs such as database administrators, web designers, delivery drivers, etc. On the other hand, when e-shopping is becoming more and more popular, an influx of people working at traditional retail stores might lose their jobs and face unemployment. This will place a huge burden on the government to create alternative jobs for these individuals, which might take a long time and require a large amount of budget.

In conclusion, online shopping impacts the environment and the labour market in both positive and negative ways.

Online Shopping is Increasing Significantly IELTS Essay

Recently, online shopping has become a hot trend. Purchasing and selling online has become popular and the services are increasing manifold. eBay and Amazon offer a wide variety of products, which we can avail from the comfort of our home. Major disadvantages included in window shopping are time-consuming, traveling to faraway shops, parking the vehicles at a time of a rush hour, etc. Online shopping has reduced these inconveniences for consumers.

While shopping online or browsing the internet, people come across a wide range of products to choose from. They are able to compare the prices and features of their choices on different websites. This helps them to make a well-thought decision. Flipkart and Jabong are two famous online shops in India. They not only provide the product description and price information but also allow comparison of products of the same category, providing customers reviews and opinions and ratings. The ordered items can be altered or canceled as per the customers’ needs. You can return or exchange the items you bought if you are not satisfied with the quality.

Shopping is considered a social experience. Certain people enjoy shopping and lingering about in the markets at leisure. Popular websites often sell things at a cheaper rate than local stores, offering attractive discount rates. This is also another reason why online shops are being preferred recently.

Online shopping is much more beneficial for customers in comparison to in-store purchasing. Since it is hassle-free, online shopping is convenient. Thus, shopping over the internet is definitely a positive trend, and will grow more popular over the years.

Online Shopping Impact on Environment IELTS Essay

The world in which we live has seen significant changes due to the advent of modern technologies such as the internet. Shopping is not an exception. These days, thanks to the development of the internet, online shopping has dramatically flourished. This essay seeks to investigate the effects of this trend on the environment and society.

While the development of internet shopping has a cascade of effects on the environment, some of them are more significant. Firstly, the number of conventional shops has dropped due to the lack of their necessity; hence, the space needed for their construction remained undeveloped. Moreover, less traveling is needed by people in order to purchase a merchandise.

Consequently, less emission is produced because of the fewer number of the vehicles on the streets; therefore, the air is less polluted. As a tangible example, studies show that in the United States alone, the tendency toward online shopping has prevented 10 million cars from leaving garages during the first three months of 2017. One can only imagine how much pollution has been averted.

The society has also been affected by this trend. First and foremost, indolence is spread. People are less active because of online shopping. The only physical activity needed is to press a button on the computer. Secondly, local commerce is negatively suffered. People prefer to buy online due to its convenience; therefore, fewer patrons visit local shops to buy products; hence, local businesses are disappearing. For example, statistic shows that after the development of online shopping, the survival rate of small businesses has dropped from 61 percent to 23 percent.

To summarize, online shopping has a plethora of effects on both our environment and our society from changing the look of surroundings and cleaning the air to rendering people lazier and jeopardizing small businesses.

IELTS Essay on Online Shopping

Despite the fact that we know what time it is on the clock, what the weather is like outside or there is a pandemic, we can conveniently buy the things we need in online stores. Very few people feel the need to take risks in stores. It cannot be denied that online shopping has become more popular and less tedious than in-store shopping. This trend has positive and negative sides, which are discussed in the following essay.

To inaugurate with, the fact that online shopping brings more benefits than shopping in a store. Firstly, it saves time for both buyers and sellers, as buyers don’t have to travel and sellers don’t have to show their products one by one to each consumer. Furthermore, they can get a perfect knock on prices and can easily compare products before pressing the buy button, which can lead to significant cost benefits for the buyers. In this manner, so people can make smarter decisions after evaluating and considering size, price and models. Also, it allows them to easily shop from any part of the world. As a result, the number of job opportunities in the future will increase as demand grows.

On the other hand, online shopping does not allow you to touch or see the product, which in fact makes it difficult to check the quality of the product, which leads to the purchase of an inferior product, and sometimes it is impossible to return or exchange the product, which in turn leads to wasted money. Another problem is that online shopping has made people compulsive shoppers. In addition, there is always the risk of financial information being obtained for use by hackers for security reasons, since there is always news of data leaks even from well-known brands and websites.

In conclusion, it can be clearly seen that although product reliability and financial risk have a certain impact on people, employment opportunities for them, especially in the field of employment, should also be considered. However, one must be careful about fraud and misrepresentation when buying from different sites.

IELTS Writing Task 2 on Online Shopping

The ubiquity of online shopping has brought with it concerns about the environment and an evolving job market. In my opinion, online shopping increases fossil fuel emissions and requires a massive, unskilled workforce for both delivery and production.

Online shopping uses fossil fuels in the making and transportation of goods. In order to manufacture a given product, such as a television, book, or bag of muesli, there is an environmental cost from sourcing and transporting all the elements, powering the factory that assembles it, and creating the plastic packaging, which is also a petroleum byproduct. In the case of a large company like Amazon, the product must be driven or flown to various centers around the country in order to be available for next-day delivery. From the storage warehouse, it is then driven or flown to the consumer who ordered it, further burning fossil fuels. The net impact on the environment is self-evidently massive and hastens climate change.

Moreover, online shopping is such a sprawling business that it manipulates the labor market. First of all, there are the workers directly involved. Deliverymen must pack, unpack and ship products while the whole operation also requires a variety of managers, foremen, and office workers. These workers are notoriously underpaid and exploited when working for the largest online retailers, who also streamline the means of production in order to offer the lowest prices. Instead of sourcing from local businesses, which would be slightly more expensive, they opt for large factories largely based in China that can cheaply and quickly produce standardized products. This requires an army of factory workers, working at low wages in unsafe conditions.

In conclusion, online shopping contributes greatly to climate change and has created deep fissures in the job market. Governments should regulate these companies before their rampant profit-driven efficiency has unforeseen social and political implications.

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Essay on Online Shopping

Online shopping in simple words: The form of shopping in which people can easily purchase goods and services by using the internet is called online shopping. Online shopping gives us an idea of the availability of everything online at a cost of our data. Online shopping is a growing and trending aspect. It provides customers with buying various products and services, and sellers to carry on their business and transactions in an online mode. It is time saving and convenient way of shopping. It can be said that it is the development of traditional shopping ways to make shopping more accessible, relaxing, and flexible.

Essay on Advantages and Disadvantages of Online Shopping

Short and Long Online Shopping Essays in English

Find here number of essays on online shopping vs offline shopping under various words limit for the ease of students of different classes. These essays justify all the aspects of online shopping vs offline shopping, so, you can better understand the topic in all perspectives:

Online Shopping Essay 10 Lines (100 – 150 Words)

1) Shopping by making use of the internet is called online shopping.

2) Online shopping allows us to shop for anything from our phones.

3) With online shopping, the days are gone to go to physical markets to buy things.

4) People, who don’t know how to use smartphones, cannot do online shopping.

5) Through online shopping, you can order your favorite things at your doorstep.

6) In online shopping, you can compare the prices of products and can buy the cheaper ones.

7) Alibaba, Amazon, Flipkart, eBay, etc are some famous sites for online shopping.

8) While doing online shopping, you can only see the products virtually.

9) Online shopping does not provide you with the product instantly.

10) Online shopping is a modern and flexible way of buying goods.

Essay 1 (100 words – 150 words) – Challenges of Online Shopping

Introduction

Online shopping is the better way of buying several items of your own choice at one place and get it delivered wherever you do live itself. Therefore we can define online shopping as one of the convenient and interesting ways of shopping. It reduces market crowd and saves our money and time.

Challenges of Online Shopping

Instead of providing best ways to make choices without getting out of our comfort zone, online shopping has many negative aspects too.

It requires a good knowledge of using smart technologies as well as net surfing.
There are many sections of society that do not have easy access to the same and thus are dependent on traditional ways of shopping.
Old people need to specify the products after touching thus they prefer traditional shopping and have not much confidence in online shopping.

Online shopping has turned out to be an essential need of the time. Because, nowadays in the so competitive world, people are busy in their offices and do not have time to shop. And this technology is making their life easier and fast.

Essay 2 (200 – 250 Words) – Essay on Online Shopping is a Boon for or Against

With the emergence of the internet, people can now shop online using their mobile phones or other related electronic devices. Online shops are virtual stores from where people can order the stuff of their choice.

Online Shopping is a Boon : For many people, online shopping is a boon as it offers many advantages. It not only saves your time but also helps to save your money and energy. Instead of spending a whole day in the market, you can buy things by sitting at your home. The prices of products in online shops are comparatively lower than those available offline. One reason behind this is that there is no need of maintaining any physical stores. It also offers different methods of payment. During festive times, online shopping offers discounts on various products. Online shopping is a convenient way of shopping these days.

Online Shopping is a Bane : Everything has a dark side and so is online shopping. The major drawback of shopping online is to compromise with quality. Sometimes you may receive the wrong product and returning can be a headache. You can only check the quality when you receive the product. Even on ordering your product you can get it delivered after some days. No instant service is available in online shopping methods. When doing online shopping, you will miss out on the joy of shopping with your friends or family. Precautions are a must in Online paying, as it involves several risks.

So, we can say that Online Shopping is both, boon and bane, we have to choose and use them as per our interest and skill.

Essay 3 (300 Words) – Essay on Online Shopping vs Offline Shopping or Traditional Shopping

Today, customers have the option to shop either online or offline. Both the methods have some advantages, and they do show some disadvantages. Online shopping is a method of purchasing goods via the internet. Offline shopping is the traditional means of going to the market physically to buy goods. Before the advent of the internet, people only had the option to buy things offline.

Online Shopping

The biggest advantage of Online shopping is time saving. People need not physically go to various shops to purchase items. You can select items of your choice from your phone. Shopping online is a good way to save your energy and money. You need not burn fuel to go to the markets. Another advantage we can enjoy in online purchasing is availability. You can go for online shopping at any time that best suits you, irrespective of your location. The online stores are open 24 hours a day. You need not take a holiday to go shopping.

Offline Shopping or Traditional Shopping

There are many reasons for which people go for offline shopping or traditional shopping instead of shopping online. The major advantage of going to physical stores is that the quality of the product can be checked on the spot. You can even try the clothes for perfect fitting. This feature is lacking in the online market. In traditional shopping, you get the product directly in your hands. No waiting for long days to receive the product. For purchasing items of daily use, traditional stores are far better than online stores. In offline shopping, you can bargain for prices, while in online shopping prices are fixed. Offline shopping gives you the facility of easy return.

So, we can say, both modes of shopping have their own advantages and disadvantages; we have to use them as per our choice and safety.

Essay 4 (400 Words) – Online Shopping: A Positive Approach to Digitalization

Online shopping is an emerging e-commerce technology. What can be more soothing and easier than facing the rush and crowd of the markets offering a limited range of products at a time? Yes, it is online shopping, making the way to shop easier and more convenient. The sellers are making the product details online which can be easily seen while browsing the website. There are many websites that have easy access.

Pleasure of Online Shopping

We are well aware of this fact that most of the people find shopping as an interesting aspect. Generally, women and girls are addicted to shopping. Now, since technology is advancing day by day and letting newer ways to develop, we have been benefitted by a way of shopping by sitting at our places and browsing over the internet. We are able to get various range of products in a single place. Also, we can search for the product related to men, women, and kids by entering the categories in the spaces meant for the same. We search, select, and order for the products and services and get it delivered to our places.

This is helping the people in remote areas too. We could search and order for the latest apparel through online mode. Generally, the shops are taking the time to bring and present the same.

The most preferred online shopping sites are Snapdeal, Flipkart, Amazon, Myntra, Ajio, etc.

Online shopping – a Positive Approach to Digitalization

Online shopping involves transactions or business over the internet. The buyer purchases the products and services required, by means of choosing the same over the internet. Therefore the technology is leading towards the digitalization concept. The normal shopping has been given a new face by the addition of technological aids. Offline or traditional ways have been advanced by making it online. It is a successful change in the business strategy. The new ideas and methods have been implemented to make it flourish, and provide greater revenue or economical benefits.

Online shopping is the result of a change in business strategy therefore helping in competing. It is proving it to be an easier, convenient, and better option and therefore is the best example of the concept of digitalization.

We can say that online shopping is a trending business. We can search for our choices over the internet by sitting in one place. We can get our desired products and can also gift the same to our close ones. Online shopping successfully reduced the pressure on traditional shopping methods and is time-saving too.

Long Essay 5 (500 Words) – Advantages and Disadvantages of Online Shopping

Technological advancements are changing our standards and lifestyle. One of the fascinating aspects of technology has favored is Online shopping that is the best way to business and safe transactions over the internet. It provides us broader way to search, choose and delivered the desired products and services at our specified addresses.

People these days are tugged up with several work pressures. They are spending much of their time intervals in offices or other important works. Traditional ways of shopping require a larger time to be consumed by visiting different stores for different products. Therefore online shopping provides a way to tackle the same by saving time and effort.

Advantages and Disadvantages of Online Shopping

Everything in this world is connected with both positive and negative aspects. The same is with online shopping too. On one hand, it is benefitting, and on the other hand, it has disadvantages too.

Advantages of Online Shopping:

It provides us with a convenient way of shopping.
We can see different products and services just by one click. Different variants are available in the required size and shapes.
It saves us from the rush and crowd of the markets. Also, saves our time wasted in roaming from one shop to another and standing in queues for hours for billing purposes.
We get products in our price ranges and also at a lower price.
We can order dresses according to our choice and occasion requirements. As most of the time, we are unable to get the dress we want, in offline shopping.

Disadvantages of Online Shopping:

The products we buy, generally when delivered, do not match with one we have ordered.
If we require the product immediately, then we cannot have that option or we will have to pay extra charges.
Offline shopping has a benefit to buy the product and use it immediately, but when we opt for online shopping the same benefit is not granted.
Many of the times we save our card details for the transaction purpose, hackers use the same card details for the cybercrime.
The returning of any product may be chargeable and time taking too.
Most of the time, damaged goods are received.

Online Shopping – Best Option during Pandemic (Covid-19)

The outbreak of COVID-19, throughout the world was most devastating for us. During those times, moving outside was banned and different countries were under lockdown for several months. People, all over the world, preferred online mediums to get their products and services ordered and delivered.

Therefore it can be stated that online shopping has been the best choice or alternative. People have been provided with the option of getting delivered every product at their doorstep.

Online shopping is the love of youngsters of today’s generation. It is an interesting way of exploring several products with variety and different prices at the same portal or place. Online shopping has blessed us with emerging ideas to give surprises to our closed ones on their special days. But on other accounts, it has some of the impacts too.

FAQs: Frequently Asked Questions

Ans . Online shopping was invented by an entrepreneur Michael Aldrich in 1979.

Ans . The concept of online shopping begins in India in 1995.

Ans . The first online shopping site launched in India was Amazon.

Ans . The website through which customers can easily purchase goods and services is called an online store.

Ans . The world’s largest online shopping retailer is Amazon.

Buying things on the Internet (Corrected essay)

Buying things on the Internet, such as books, air tickets and groceries, is becoming more and more popular. Do the advantages of shopping in this way outweigh the disadvantages?

WRITING TASK 2

You should spend about 40 minutes on this task.

Write about the following topic.

Give reasons for your answer and include any relevant examples from your own knowledge or experience.

Write at least 250 words.

----------------------------

Sample essay written by Nguyen Yen

In recent years, there has been a growing trend that people tend to buy things on the Internet. This present both pros and cos, however, in my opinion, its benefits are much more significant than the drawbacks.

In recent years, there has been a growing trend that people tend to buy things on the Internet in online shopping . This present both pros and cos cons , however, in my opinion, its benefits are much more significant than the drawbacks.

The phrase “buy things on the Internet” is already used in the essay topic. Try to shorten it by using a suitable buzzword, such as “online shopping”

Words such as 'people' and 'ideas' have the potential to be vague. So, avoid saying “people tend to” if possible.

The second sentence in the introduction has too many commas. Break it into two simple sentences if necessary.

On the one hand, shopping online online shopping brings to the consumers some disadvatages. Initially, since people are unable to touch or to see the products they want to buy in reality, it is always hard for them to examine the quality of these products. As a result, they might purchase the items with poor quality. In addition to that, as the consumers do not feel happy with the items they had bought online, they tend to abandon these products or dont do not use them at all. This is definitely a watse waste of money. Moreover, buyings thing on the Internet often makes people confused since there are a great number of shops on the Internet. To be specific, the buyers might see the same products in several shops, but the prices for these items can be very different, ranging from reasonable to prohibitedly expensive price . Consequently, they will not know which products they should purchase.

The second sentence is too wordy, due to the fact that the words “ people ”, “ they ”, and “ them ” all have been used despite being unnecessary. Since the main focus here is the products, not the people using them, I suggest rewriting the whole sentence into passive voice .

Avoid using contraction (“ don’t ”) in an academic context.

The ideas and sentence structures being used here are kinda repetitive. Regarding of online shopping, there are many issues that are worth mentioning ( shipment delays, misleading online marketing, annoying advertises, etc)

On the other hand, I am of the opinion that shopping online online shopping brings people a number of benefits. First, shopping online online shopping allows the consumers to browse for products and checking comparing the prices between these online shops. In this way, people can make a better decision to buy what they like after taking prices, sizes and models of the products into consideration. To speak From my experience, I used to buy an elegant dress es at virtual shop s , which was cheaper compared to that of some shops near my houses. Second, buyings things on the Internet helps people save a great deal of time. That is to say, since people nowadays are often so caught up with work and study, shopping online online shopping is a wise choice which doesn’t does not require them to go the the stores. With a click of mouse With just a click , they can buy the things they need and the shippers will deliver their products to the customers as soon as possible. Third, since there is a high demand of buying things online, many people can realize their dream of starting up their own business and achieve success in the long rub run. This can be seen as a positive trend because it creates good job opportunities for the people and thereby help people to improve their income and well-being. This also contributes to boost ing the economy of a nation in general l .

While the second body paragraph is very long (216 words!), its quaility doesn’t appear much better than the first one. Try to write only 70 words, you will definitely see an improvement.

Many idioms are introduced in this paragraph: “a great deal of time”, “in the long run”, “to be caught up”, “to take in consideration”, “with just a click”. However, the attempt to use them isn’t really succesful, due to some spelling mistakes.

The vocabulary is kinda limitted here. However, there are a variety of connectives (“on the one hand”, , “first”, “in this way”, “thereby”, etc).

In conclusion, although buyings things on the Internet exerts some adverse aspects, the advantages can justify these.

Too short and unconvincing. Need to give more emphasis.

Words: 418 words

Overall: 6.5

Task Response: 7

✓ addresses all parts of the task (the essay has answer the required question, and write more than 250 words) ✓ presents a clear position throughout the response ✓ presents, extends and supports main ideas, but there may be a tendency to overgeneralise and/or supporting ideas may lack focus

Coherence and Cohesion: 7

✓ logically organises information and ideas; there is clear progression throughout ✓ uses a range of cohesive devices appropriately although there may be some under-/over-use ✓ presents a clear central topic within each paragraph

Lexical Resource: 6

✓ uses an adequate range of vocabulary for the task ✓ attempts to use less common vocabulary but with some inaccuracy (the writer uses very few topic-related words. And when they are used, mistakes are presented “shopping online” ) ✓ makes some errors in spelling and/or word formation, but they do not impede communication

Grammatical Range and Accuracy: 6

✓ uses a mix of simple and complex sentence forms ✓ makes some errors in grammar and punctuation but they rarely reduce communication (lots of the article “the” are missing, so I cannot give a 7 score here)

----------------------------------------------------------

This essay is corrected by Anh Tran - Let's Write Something Group .

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Other sample essay

With the advent of technological advancement, 21st century has witnessed a boom in e-commerce. The number of online shopping websites is increasing exponentially. Shopping online has its upsides and downsides but the positives of this technological blessing far outweighs its negatives.

Firstly, online shopping saves one from travel and traffic problems. I live in the outskirts of Karachi and commuting to the city for buying stuff is not an easy task for me. Further, Karachi is an overly-populated city with the worst traffic situation, all this makes it more difficult to travel. This problem is hugely resolved by the e-buying facility. Everything is simply a click away, whether it is groceries, air tickets, clothes or books. Whatever I order is duly received at my doorstep, without my having to embark on long, hectic shopping-trips.

Secondly, buying things on the internet provides you with a wide range of options. Consider yourself in a gigantic super-mart having access to every type of item you can imagine! On the internet there is no physical space limitation, therefore the variety available for a single item is endless. Also, there are countless websites where you can compare product prices, specifications, extra features, deals and a lot more. One such website is Compare.Pk, where you can select an item and compare it with similar items of other brands for specifications and prices. All this not only provides convenience to customers but also exposes them to a very huge market for buying the most appropriate item.

In conclusion, it can be unambiguously agreed upon that the advancement in e-buying has resulted in convenience for buyers. One only has to select and order an item and it arrives at his doorstep. Also, the available options for a single commodity are endless, so that a person can compare and buy the best.

(Written by Narmeen Habib )

Corrected Essay:

With the advent of technological advancement, 21st century has witnessed a boom in e-commerce the number of online shopping websites is increasing exponentially. Shopping online has its upsides and downsides but the positives of this technological blessing far outweighs its negatives . The positive impacts on online shopping undermine its negative sides because the advanced technology can save our time and give more options for purchasing .

The opening paragraph does not contain a clear thesis statement. It is important to tell what you are going to talk about and where you are positioning on the views.

Phrases ‘ a boom in e commerce’ and ‘ is increasing exponentially’ have similar meaning. It is better to keep it in short, but clear sentence.

Firstly, online shopping saves one from travel and traffic problems. Online shopping does not require people to travel . I live in the outskirts of Karachi and commuting to the city for buying stuff is not an easy task for me. Further, Karachi is an overly-populated city with the worst traffic situation, all this makes it more difficult to travel. As living in Karachi, an over-populated city with its congestion problems, many citizens like me have to overcome difficult situation only for buying stuff in the city centre . This problem is hugely resolved by the e-buying facility. Everything is simply a click away, whether it is groceries, air tickets, clothes or books. Whatever I order is duly received at my doorstep, without my having to embark on long, hectic shopping-trips . This platform enables consumers to experience shopping activities in simple ways. Take the biggest e-commerce in the word, eBay which provides wide varieties of products, for example. As a student, I often ordered books, air tickets, and fashion items. Likewise, many housewives in my neighbourhood prefer to purchase groceries through this website. If eBay was never exist before, buyers like us might have to spend longer times taking long trips to get our shopping lists. This example tells about how an effective shopping is advantageous as a time saver.

Firstly is ommited as the topic sentence is not too clear enough to represent the main idea.

The use of ‘I’ in your example does not cover people’ problems in general, so I have changed ‘I’ into ‘ many citizen like me’

Everything is simply a click away needs to be elaborated . Please see the changes.

You only mention groceries, air tickets, clothes or books without giving explanation. If you want to score higher, it is your task to present your ideas in details. I have made some detailed explanations with this.

Secondly, Another benefit is that buying things items on the internet serves unlimited choices provides you with a wide range of options . Consider yourself in a gigantic super-mart having access to every type of item you can imagine! On the internet there is no physical space limitation, therefore the variety available for a single item is endless. Also, there are countless websites where you can compare product prices, specifications, extra features, and deals and a lot more . One such website is Compare.Pk, where you can select an item and compare it with similar items of other brands for specifications and prices. All this not only provides convenience to customers but also exposes them to a very huge market for buying the most appropriate item.

You need to link both main ideas in the first sentence using transitional phrase. But remember, reliance too much on this will score you lower. Use them when necessary .

The word ‘ things’ is a weak lexical resource. It is better to use some alternative vocabs like stuff, items, daily needs , etc.

A wide range of options have been mentioned in the intro, you need to paraphase it. Serves unlimited choices.

You do not need to use exclamation mark. Present your sentence in a smooth way.

Consider yourself in a gigantic super-mart having access to every type of item you can imagine!. This sentence also does not make a sense.

And a lot more is vague. You’d better omit this phrase.

In conclusion, it can be unambiguously agreed upon it is true that the advancement in e-buying has resulted in convenience for buyers. One only has to select and order an item and it arrives at his doorstep. Also, the available options for a single commodity are endless, so that a person can compare and buy the best.

You have to summarise your main points and reiterate your opinion. Some ideas presented are sidetrack.

Your opinion does not state your opinion clearly.

It can be unambiguously agreed upon is counted as 6 words. It is always good to be succinct and keep straight to the point.

Let me give you an example of this: In conclusion, the disadvantages of e-commerce trend are overshadowed by the benefits resulting from modern technology. I am convinced that online shopping is one of great innovations of people doing transaction as it reduces time and provides more options.

Overall: 7.0

· Task Response: 7

✓ addresses all parts of the task (the author wrote 303 words)

✗ presents a clear position throughout the response (the way you present your idea in the intro is too generic)

✓ presents, extends and supports main ideas, but there may be a tendency to overgeneralise and/or supporting ideas may lack focus

· Coherence and Cohesion: 6

✓ arranges information and ideas coherently and there is a clear overall progression

✓ uses cohesive devices effectively, but cohesion within and/or between sentences may be faulty or mechanical

✓ may not always use referencing clearly or appropriately

✗ uses paragraphing, but not always logically ( missing links between intro and conclusion)

Lexical Resource: 7

✓ uses a sufficient range of vocabulary to allow some flexibility and precision

✓ uses less common lexical items with some awareness of style and collocation

✓ may produce occasional errors in word choice, spelling and/or word formation

Grammatical Range and Accuracy: 7

✓ uses a variety of complex structures

✓ has produces frequent error-free sentences

✓ has good control of grammar and punctuation but may make a few errors

-----------------------

This essay is corrected by Eddy Suaib .

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The future of e-commerce: trends to watch in 2024.

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Denis Sinelnikov is the CEO of Media Components and Curis Digital, an award-winning, full-service digital marketing agency.

E-commerce is a dynamic industry that has transformed the way we shop and conduct business. With rapid advancements in technology and changing consumer preferences, your business must stay ahead of the curve to remain competitive.

Several emerging trends are set to reshape e-commerce in 2024. I’ll focus on the ones that are worth keeping an eye on this year and then share some tips for taking advantage of them.

Which Trends To Watch

Augmented reality shopping experiences.

AR enables customers to have immersive shopping experiences from the comfort of their homes. It allows them to visualize products in a real-world context, making informed decisions before making a purchase. Ikea has been using AR technology with its app for a few years now , proving that it isn’t merely a short-lived fad.

Ikea doesn’t have to be an outlier. We have the frameworks to apply AR technology to e-commerce on a broader scale than we currently do. TikTok and Instagram filters alone prove that we can do this easily, and relatively inexpensively. What we need is for companies that can most benefit from this tech—salons, clothing retailers and more furniture and home improvement retailers—to provide this interactive and engaging shopping experience.

Blockchain For Supply Chain Transparency

Blockchain technology is not new to the e-commerce industry, but its application is evolving. While we tend to think of blockchain in terms of cryptocurrency and NFTs, it has more potential uses. A blockchain is an append-only ledger, meaning that data can be added to the chain but not removed. The accountants and security professionals among you undoubtedly recognize the term and can immediately see the transparency a blockchain ledger can provide.

Logistics companies could greatly benefit from a blockchain ledger. It would provide transparency to their shipping clients and improve communication with their contracted owner/operators. The benefits could even extend to the customers of their clients, who could use the blockchain to provide real-time updates for restocking and shipments.

Customized Loyalty Programs

Personalization has been a hallmark of e-commerce; however, its scope has been historically limited to cross-selling through product recommendations. In 2024, I want to see us bring personalization further as retailers harness data analytics and AI. This could involve large retailers offering more personalized content to users and allowing users to customize loyalty programs to meet their specific shopping habits and needs. Ultimately, increased personalization can forge stronger connections between brands and their customers.

Eco-Friendly E-Commerce

The focus on sustainability and eco-friendliness has gained momentum in recent years. In 2024, this trend will likely intensify in the e-commerce industry. Customers expect e-commerce platforms to offer eco-friendly options, reduce packaging waste and embrace sustainable practices. I want to see retailers align with these values to improve their businesses and gain a competitive edge in the market.

Stronger Security And Privacy Measures

In 2024, I see consumers gravitating toward platforms that prioritize their personal data security, and governments are likely to introduce more stringent regulations. Retailers must invest in advanced security technologies and adopt transparent practices to build trust with their customers.

More Personalized Subscription Models

Subscription services have become increasingly popular in the e-commerce industry, but in 2024, I expect retailers will offer subscriptions tailored to individual preferences, not only in terms of product selection but also in the frequency and timing of deliveries. These highly customized subscription models can enhance customer loyalty and supply a steady revenue stream for businesses.

Taking Advantage Of The 2024 Trends

Knowing the trends isn’t enough. The companies that will rise to the top in 2024 are the ones that position themselves to implement them successfully. We are well past the era of “move fast and break things.” This needs to be the year that you build consumer trust as you take advantage of these trends.

The Considerations

Before you begin jumping on these trends, you need to consider which ones fit your brand, your industry and your customer needs. Ask yourself questions before you start looking at bringing these trends into your e-commerce strategy. Here are some key questions to get you started:

• Who is our consistent customer base, and what keeps them loyal?

• What new markets do we want to expand into this year?

• What security measures do we have in place for customer data, financial data and company data?

• What weaknesses do we have in our security?

• How are we collecting data, and are we continuing to receive valuable information on customers and leads?

• Which trends match our company vision, goals and culture?

• What is our process for converting leads to customers, and how do these trends fit into this process?

The Technology

Once you have an idea of what trends you want to implement and what roadblocks may be ahead of you, let’s look at what you will need to have in place to make these trends work for you.

• Have a solid data collection strategy and software. Several of the strategies I’ve discussed revolve around customer data. If you don’t have a reliable program that can run reports, monitor customer activity and interpret data, you will fall behind on these trends. Tools like Qualtrics that use AI can help companies not only capture information but use it to create the personalized experiences consumers want.

• Improve your data encryption and security. No matter how good your current security is, you need to improve it this year. Because so many of these trends rely on consumer habits and customer data, it’s more important than ever that you can safeguard that data. Not only will the increased security improve consumer trust in your brand, but it will also protect that valuable data from competitors.

• Invest in AI technology. Investing in AI tools for security, data collection and analysis and customer service interactions is a vital step to help you take advantage of each trend we have looked at here.

E-commerce in 2024 is characterized by several trends that I expect to reshape the industry. From the integration of augmented reality and blockchain for transparency to subscription models with increased personalization and a heightened focus on sustainability, e-commerce is set to offer customers innovative and socially responsible shopping experiences. By figuring out which trends best fit their brand and then investing in technology to enable them, businesses can navigate the e-commerce world of 2024 with confidence and enthusiasm.

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Elsevier - PMC COVID-19 Collection

The impact of COVID-19 on the evolution of online retail: The pandemic as a window of opportunity

Levente szász.

a Faculty of Economics and Business Administration, Babeș-Bolyai University, 400591, Cluj-Napoca, Teodor Mihali str, 58-60, Romania

Csaba Bálint

b National Bank of Romania, 030031, Bucharest, Lipscani str. 25, sector 3, Romania

Ottó Csíki

Bálint zsolt nagy, béla-gergely rácz, dénes csala.

c Department of Engineering, Lancaster University, Engineering Building, Lancaster University, Lancaster, LA1 4YW, United Kingdom

d Economics Observatory, School of Economics, University of Bristol, Beacon House, Queens Road, Bristol, BS8 1QU, United Kingdom

Lloyd C. Harris

e Alliance Manchester Business School, University of Manchester, Booth St W, Manchester, M15 6PB, United Kingdom

Associated Data

Data will be made available on request.

Pandemic-related shocks have induced an unexpected volatility into the evolution of online sales, making it difficult for retailers to cope with frequently occurring, drastic changes in demand. Relying on a socio-technical approach, the purpose of this paper is to (a) offer a deeper insight into the driving forces of online sales during the pandemic, and (b) investigate whether pandemic-related shocks accelerate the long-term growth of online retail. Novel, high-frequency data on GPS-based population mobility and government stringency is used to demonstrate how time spent in residential areas and governmental restrictions drive the monthly evolution of online sales in 23 countries. We deconstruct these effects into three main phases: lure-in, lock-in, and phase-out. Lastly, using time series analysis, we show that the pandemic has induced a level shift into the long-term growth trend of the online retail sector in the majority of countries investigated.

1. Introduction

The outbreak of the pandemic caused by the spread of a novel type of coronavirus, SARS-CoV-2, has induced an unprecedented shock to the global economy in terms of its speed and encompassing nature, having a significant impact on virtually all countries and economic sectors. During the pandemic, businesses and consumers have been forced continuously to adapt to the immediate and drastic changes brought about by this crisis. Furthermore, there is a general consensus that there will be long lasting global effects and the world economy will return to a “ new normal ” ( Roggeveen and Sethuraman, 2020 ; Sneader and Singhal, 2021 ).

As with similar health-related and economic crises in the past, it is widely accepted that online retail represents a sector that plays a crucial role ( Li et al., 2020 ; Guthrie et al., 2021 ), providing vital access for customers to essential products ( Kirk and Rifkin, 2020 ; Martin-Neuninger and Ruby, 2020 ). Given its significant role, the present paper focuses on the evolution of online retail during the COVID-19 pandemic and analyses the short-term and potential long-lasting effects of this crisis.

Most of the existing papers studying the interaction between the early-stage of the pandemic and the online retail sector report that in several countries the outbreak of COVID-19 led to an unprecedented surge in online retail demand (e.g., Gao et al., 2020 ; Hobbs, 2020 ; Hwang et al., 2020 ). These observations are supported by commentators suggesting that in 2020 the “share of e-commerce in retail sales grew at two to five times the rate before COVID-19” ( Lund et al., 2021 ). However, only a few studies acknowledge that, beyond the general upswing, the pandemic has increased the volatility of online sales evolution. Furthermore, literature offers little guidance on which factors can explain these changes in online sales during a crisis when traditional market mechanisms do not function as usual. In response, therefore, this paper aims to use large-scale, longitudinal data covering 23 different countries and multiple waves of the pandemic to investigate the drivers of short-term online retail evolution during COVID-19 .

While some researchers have tentatively begun to explore these short-term effects (e.g., Chang and Meyerhoefer, 2021 ; Eger et al., 2021 ), the longer-lasting implications of the pandemic on the online retail sector have yet to be studied empirically. Most scholars emphasize the need to investigate whether the pandemic has truly altered the evolution trajectory of online retail or if the current crisis is merely a single shock after which the sector will return to its traditional evolutionary path as consumers and retail businesses return to their “old habits” in the post-pandemic period ( Sheth, 2020 ; Eger et al., 2021 ; Reardon et al., 2021 ; Schleper et al., 2021 ). Consequently, given the uncertainty of what the “ new normal ” might bring for the online retail market, this paper also intends to use the most recent time series to investigate whether the pandemic has altered the long-term evolution of the sector .

In pursuing the two objectives (investigation of short-term drivers and long-term trend implications), this paper adopts Geels’ (2002) multi-level perspective (MLP) as a theoretical lens to investigate technological transitions in a complex socio-technical context. We interpret the pandemic as a force capable of opening a “window of opportunity” ( Dannenberg et al., 2020 ). Such windows constitute powerful tensions created at the level of the socio-technical landscape that bring a unique possibility for a technological novelty to break through and become more dominant in mass markets ( Geels, 2004 ). Hence, we explore the interplay between the window of opportunity opened by COVID-19 and the growth of the online retail sector. More specifically, we aim to investigate (a) the short-term driving forces behind the exponential evolution of the online retail sector during the pandemic, and (b) whether the pandemic has truly created a window of opportunity for a positive shift in the long-term evolution of online retail. Along with pursuing these objectives we also aim to provide a theoretical contribution to the literature on windows of opportunity, a central concept that has received only limited attention in previous MLP studies ( Geels, 2011 ; Dannenberg et al., 2020 ). In this regard, our paper aims to offer a more detailed insight into how a technological transition path might behave during such a period and to provide a means to evaluate the potential long-term effect of windows of opportunity.

2. Literature review

2.1. the impact of covid-19 on online retail.

Given the crucial role of online retail channels during a pandemic, researchers have examined a variety of ways in which COVID-19 has influenced online shopping. As COVID-19 was first identified in China, initial studies investigated how the outbreak of the crisis has reshaped the retail landscape in China with emphasis on the increasing importance of online channels ( Gao et al., 2020 ; Guo et al., 2020 ; Hao et al., 2020 ; Li et al., 2020 ; Jiang and Stylos, 2021 ). These studies focused on how the outbreak of the pandemic influenced online shopping ( Gao et al., 2020 ; Guo et al., 2020 ), and how online channels helped the population to cope with the emerging health-crisis ( Li et al., 2020 ; Hao et al., 2020 ).

Given the narrow focus of initial studies, authors called for further research in other countries better to understand the global impact of the pandemic on online retail ( Gao et al., 2020 ; Li et al., 2020 ; Jiang and Stylos, 2021 ). Subsequent studies taking this research avenue offered a good cross-section globally by covering multiple different countries but investigated almost exclusively the short-term impacts of COVID-19 on online retail, using data from the first wave of the pandemic ( Table 1 ). Moreover, observers typically argued that the major driving forces behind the exponential proliferation of online channel use in the context of COVID-19, can be grouped in two distinct, but intertwined categories: (a) governmental regulations and restrictions, and (b) pandemic-induced changes in customer behavior. In line with this observation, Shankar et al. (2021) also contend that “many shoppers move a large portion of their business online during the COVID-19 outbreak either by choice or due to regulation …” . Therefore, the next two subsections review the studies that attribute the changes in online sales to one of these two factors.

Summary of the literature on the impact of COVID-19 on the evolution of online retail.

Author(s)	Country (retail branch)	Period	COVID-19 implications
Author(s)	Country (retail branch)	Period	Short-term drivers	Long-term implications
	China (various sectors)	First wave (Feb 2020)	(number of COVID-19 cases/day/city)	–
	China (food retail)	First wave (Feb 2020)	(reduce health risks, gain access to food products)	–
	China (food retail)	First wave (Feb 2020)	(food stockpile behavior associated with online channels; community-based ordering)	–
	China (food retail)	First wave	(securing food supply for the urban population)	–
	China (various sectors)	First wave (Feb–Mar 2020)	(digital engagement during lockdowns)
	Vietnam (various sectors)	First wave (Jan–Mar 2020)	(Fear of pandemic)	Depending on COVID-19 lifespan, consumer behavior might change in the long run.
	New Zealand (various sectors)	First wave (Feb–Mar 2020)	(travel restrictions and lockdown policies)	–
	New Zealand (grocery)	First wave (Feb–Apr, 2020)	(lockdown policies)	Negative online experience can have a long-term impact
	Czech Republic (various sectors)	First wave (Apr, 2020)	spread of COVID-19) (government restriction)	–
	India (food retail)	First wave (Apr, 2020)	(Fear for health)	–
	US (craft and art supplies)	First wave (until Apr, 2020)	(government-issued interventions)	–
	Taiwan (food retail)	First wave (Jan–Apr, 2020)	(number of new infections) (media consumption)	Customers trying the online channel for the first time might continue using this channel
	Belgium (various sectors)	First wave (Apr–Jun 2020)	(travel restrictions, social distancing rules)	The ad-hoc setup of local online retail channels threatens their post-covid sustainability
	France (para-pharmaceutical, healthcare, well-being and beauty)	First wave (until Jul 2020)	(panic buying, coping with and adapting to the pandemic context)	–
	Canada (food retail)	First wave	(panic buying) (stay-at-home and distancing orders)	Online food retail will receive a sustained upward shift in adoption
	US (various sectors)	First wave	(social distancing rules)	–
	n.a. (various sectors)	First wave	(lower accessibility of stores) (health concerns)	Further store closures or bankruptcy of major brick and mortar retailers
	Asia and Latin America (food retail)	First wave	(lockdown policies)	–
	n.a.	First wave	(impact of a disaster and crisis on shopping behavior)	–
	Czech Republic (various sectors)	Second wave (Sep 2020)	(fear for health)	Customers might change their shopping habits in the long run
	India (mobile shopping)	Second wave (Sep–Dec 2020)	(fear of Covid-19)	–

2.1.1. Studies highlighting the impact of changing customer behavior

Adopting a behavioral perspective, Chang and Meyerhoefer (2021) illustrated how the first wave in Taiwan (where no strict stay-at-home orders or business closures were imposed) has shifted consumers’ attention towards online channels. In the early weeks of the pandemic the surge in the number of confirmed cases increased both sales and the number of customers of online food commerce. The change in customer behavior was also induced by the media, as COVID-19 related press articles and Google searches also positively correlated with online food sales.

In a similar manner, Sheth (2020) argued that the pandemic had several powerful and immediate effects on consumer behavior: while facing constraints, consumers improvised and replaced old habits with new ones, such as switching to online retail channels, enabling thereby the “store to come home”. In line with this, Jiang and Stylos (2021) proposed that individual pressures during lockdowns force consumers to create a “new retail purchasing normality” involving higher digital engagement and increased online purchases. Consultancy papers also supported this view. A multi-country survey conducted by McKinsey & Company demonstrated that the pandemic induced a major shift in consumer behavior, at least two thirds of customers having tried new, mostly online forms of shopping ( Sneader and Singhal, 2021 ).

In terms of shifting consumer behavior, Tran (2021) proposed that fear of the pandemic can also drive online purchasing intentions aiming to improve the health safety of the consumer and the surrounding community. Researchers focusing on the second wave of the pandemic ( Chopdar et al., 2022 ; Eger et al., 2021 ) also connected the fear of the virus to increased online shopping. One exception is identified by Mehrolia et al. (2021) , concluding that a considerable majority of Indian customers decided not to order food through online channels during the first wave of the pandemic due to the fear connected to food delivery.

Hao et al. (2020) focused on a different aspect of customer behavior. Their study points out that panic buying (i.e., ordering more than the short-term necessity of the household due to fear), which is a common consumer response during disasters, is more associated with online food retail channels than with traditional channels. Following this idea, Guthrie et al. (2021) use the react-cope-adapt model ( Kirk and Rifkin, 2020 ) to illustrate that during the first month of the pandemic in France consumers reacted by panic buying, dramatically increasing the online purchasing of essential products. This period was followed by coping with the crisis which led to an increase of online orders related to non-essential products. The adapt phase was supposed to show a sustained modification of online purchasing behavior. However, due to limited data available, the authors concluded that long-term behavior changes require further investigation.

2.1.2. Studies highlighting the impact of government regulations

During the pandemic, several governmental restrictions had an immediate impact on online retail. For example, Martin-Neuninger and Ruby (2020) and Hall et al. (2021) identify government-related factors, namely the lockdown period and travel restrictions, as primary reasons behind the surge in online shopping in New Zealand. Hobbs (2020) also argued that initial stay-at-home and distancing orders issued in Canada led to an uptake of the online food retail: while online grocery deliveries were already used by early adopters in the pre-pandemic era, during the outbreak many late-adopter customers tried this channel for the first time. Jílková and Králová (2021) reported similar phenomena in the Czech Republic for all generational cohorts. In summary, unexpected regulations imposed by governments determined an immediate increase in demand for online shopping: existing customers started to use online channels more frequently, while new customers, including older and less tech-savvy generations, turned to online channels for the first time ( Hwang et al., 2020 ; Pantano et al., 2020 ).

From the retailer’s perspective, Reardon et al. (2021) provided several case examples of Asian and Latin American food industry firms strengthening their e-commerce business models or reconfiguring their entire food supply chains as a response to early-stage lockdown policies. Based on a survey among small Belgian retailers, Beckers et al. (2021) found that restrictions have doubled online orders during the first wave of the pandemic. To match the increase in demand, half of the retailers not using online channels before the pandemic opened one during the first months of COVID-19. Based on a literature review, Kirk and Rifkin (2020) also predicted that in order to conform to social distancing regulations, online retail coupled with contactless distribution methods would substantially gain ground during the pandemic. However, results related to the long-lasting effects of the pandemic on online retail are still “speculative in nature” ( Hobbs, 2020 ). Many of the customers who made the shift due to the restrictions might continue to utilize online channels in the long run. Other customers might return to traditional channels as soon as possible ( Beckers et al., 2021 ; Mehrolia et al., 2021 ). Thus, whether online retail can capitalize on the pandemic in the long run is still a subject of debate.

2.1.3. Summary and research questions

A summary of the key studies is provided in Table 1 in chronological order, highlighting the short-term drivers (i.e., government regulations and/or customer behavior, beside the papers narrowly focusing on the effect of the pandemic itself) and potential long-term implications related to the growth of the online retail sector.

Based on the literature, we derive two main conclusions that serve as basis for our research questions. First, as demonstrated in Table 1 , there is a plethora of mostly anecdotal, non-empirically-based evidence that during the pandemic (and beside the pandemic itself) two major factors, i.e., government restrictions and consumer behavior changes, drove a significant initial surge in online shopping. Second, extant studies failed to offer insights into how these factors drive online sales during the entire period of the current pandemic ( Schleper et al., 2021 ). Therefore, we cover the full period of COVID-19 to date and provide more conclusive empirical evidence on how these two factors influence the evolution of online retail.

RQ1. How do changes in customer behavior and government regulations drive the evolution of online retail during the pandemic?

Moreover, the long-term implications of this change in online retail use have remained, so far, a subject of anecdotal speculation ( Table 1 ). However, changes to the retail sector might become a constant in the “ new normal ”, and further research is needed “to understand the short-term and long-term impact of the pandemic on consumer behavior and provide guidance on how retailers should cope with those changes” ( Roggeveen and Sethuraman, 2020 ). Hobbs (2020) suggested that COVID-19 prompted sceptics and late-adopters to use online retail channels, and these new customers are likely to continue to shop online even after the pandemic. More cautious voices, however, asked the question whether the pandemic has “swung the pendulum too far and too fast towards online shopping” ( Gauri et al., 2021 ), which may potentially result in an unsustainable boost to online retail. Thus, the extent to which this shift will lead to a fundamental leap in the long-term role of online retailing is unknown.

RQ2. What trend-shifting impact does the pandemic have on the long-term evolution of online retail?

In answering RQ1 and RQ2 we also aim to extend the scope of existing research ( Table 1 ) in four different aspects. Given that COVID-19 is a global phenomenon, we aim to cover a larger geographical region compared to the majority of previous studies focusing on a single country. Second, in contrast with existing research mostly investigating a single branch of the online retail sector, we propose to analyze the online retail sector as a whole, covering the sales of all types of products. Third, we integrate novel measures into the analysis that have emerged during this pandemic (mobility indicators, government stringency index) to be able better to explain the evolution of the online retail sector during this crisis. Fourth, we investigate a longer period before and during the pandemic than previous studies to infer long-term implications.

2.2. A socio-technical approach to study the evolution of online retail during COVID-19

The multi-level perspective (MLP) has been established as insightful in studying COVID-19 related developments in the online retail sector ( Dannenberg et al., 2020 ). Consequently, we use the MLP as a theoretical lens to study the short and long-term evolution of online retail. Geels (2002) argues that the central tenet of MLP is that technological transitions are not only dependent on the development of the technology itself, but also pivot on the broader socio-technical context. In line with this view, technological transition represents a change from one socio-technical configuration (regime) to other: beyond the substitution of an older technology with a newer one, such transitions include changes in other socio-technical dimensions such as infrastructures, policies, user practices, and markets ( Geels, 2002 , 2004 ).

According to the MLP, technological transitions are shaped by the interaction between developments unfolding on three analytical levels ( Geels, 2002 , 2004 , 2011 ):

• Technological niches represent the micro-level of the MLP. Niches are quasi-protected spaces where radical innovations are developed (e.g., R&D laboratories, subsidized development projects, or specific user categories supporting emerging innovations). They are unstable socio-technical configurations where innovations are carried out by a limited number of actors. Processes in the niche are gradually linked together and stabilize in time into a dominant design that allows for the radical innovation to break through to the next level.
• Socio-technical regimes represent the meso-level of the MLP. Regimes refer to “the semi-coherent set of rules that orient and coordinate the activities of social groups” ( Geels, 2011 ) creating thereby a “deep structure” that ensures the stability of the current socio-technical system. Nevertheless, the semi-coherence of these rules allows for a dynamic stability which enables further incremental innovation, with small adjustments accumulating into stable technological transition paths. A socio-technical regime is formed by the co-evolution of different sub-regimes, each with its own set of rules and dynamics: user and market, technological, science, policy, and socio-cultural sub-regimes. According to Geels (2004) , the socio-technical regime can be understood as the meta-coordination of the different sub-regimes that determines technology adoption and use.
• The socio-technical landscape represents the macro-level of the MLP. The landscape provides a wider, technology-external context for the interactions of actors within the niche and the socio-technical regime. Actors cannot influence elements of the landscape on the short-run, and changes at the landscape level take place usually slowly, representing longer-term, deep structural tendencies (e.g., macroeconomic processes, cultural patterns, political trends).

An important implication of the MLP is that the future evolution of a (new) technology does not only depend on the processes within the niche, but also on the interactions between different levels; including the regime and landscape levels. Geels and Schot (2007) contend that the general pattern of technology transition involves all three levels: (1) niche innovations align and gain internal momentum, (2) landscape developments put pressure on existing regimes, and (3) regimes destabilize creating an opportunity for niche innovations to break through to mass markets.

In terms of the interplay between COVID-19 and online retailing, another important concept linked to the MLP is the “window of opportunity”. Geels (2002) argues that windows of opportunity are created when tensions appear in the current socio-technical regime or when landscape developments put a pressure on the current regime for internal restructuring. These tensions loosen the rules of the socio-technical regime and create opportunities for technologies to escape the niche-level and become more deeply embedded in the regime. Competition with the existing technology becomes more intensive, triggering wider changes in the regime, where the new technology may replace the old one in the long run ( Geels, 2004 ).

Dannenberg et al. (2020) conclude that COVID-19 represents a critical landscape development that puts pressure on the socio-technical configuration of the retail sector. In line with our literature review, they suggest that two sub-regimes were particularly affected: policy regime (government regulations) and, user and market regime (sudden change in customer behavior). The authors further argue that these two major changes have opened a window of opportunity for online grocery retail to gain substantial market share. In this regard, RQ1 aims to investigate how the developments within these two dimensions influence the evolution of the online retail sector during the opening up of a window of opportunity ( Fig. 1 ). Given that, to date, the MLP offers little insight into the evolution of a technology during a window of opportunity ( Dannenberg et al., 2020 ), answering RQ1 should enrich this theoretical framework by explicating the forces that drive technology transitions during tensions in the landscape and the socio-technical regime (i.e., during a window of opportunity).

COVID-19 and the trajectory of online retail evolution (adapted from: Geels, 2002 ; Dannenberg et al., 2020 ).

Concerning the long-term impact of this window of opportunity, we investigate whether it enables the online retail sector to gain a significantly higher share of the whole retail sector on the long run (technology trajectory in Fig. 1 ) to the detriment of offline channels ( Helm et al., 2020 ). However, in the long run, MLP is not necessarily about mapping “winning” technologies that entirely replace/reconfigure existing regimes: it is just as possible that the breakthrough of a new technology will lead to a symbiosis with incumbent socio-technical regimes ( Geels, 2002 ; Genus and Coles, 2008 ). Thus, in our case, the question is more about the relative share of online retail and physical retail within the retail sector (cf. omnichannel retailing, Gauri et al., 2021 ). Beside speculation, current literature offers little guidance in this regard. Dannenberg et al. (2020) suggest that even if the pandemic has led to an upswing of online shopping, there is no indication for a fundamental long-term shift from physical to online retail. The authors, however, base their assumptions on a limited set of data, both from a temporal (March–May 2020) and from a geographical/sectoral perspective (German grocery retail). On the other hand, many other authors advocate a breakthrough of online retail as a result of taking advantage of the window of opportunity created by the pandemic (e.g., Chang and Meyerhoefer, 2021 ; Hobbs, 2020 ; Tran, 2021 ). Answering RQ2 is designed to explicate and illuminate further this debate.

3. Data and variables

3.1. data used in short-term analysis (rq1).

To investigate RQ1, we use as dependent variable the monthly evolution of online retail sales during the pandemic (Feb 2020–Jan 2022) in European countries. We rely on Beckers et al. (2021) who define online retail channel use as the selling of goods via mail, phone, website, or social media. Therefore, we adopt NACE-level retail trade data published by Eurostat using the index of deflated turnover (i.e., turnover in real terms, 2015 = 100) for the “Retail sale via mail order houses or via Internet” sector. Seasonally and calendar adjusted time series data is used to assess the monthly changes during the pandemic in this sector, shortly denoted from now on “online retail” ( ΔOnline_retail ). In terms of countries, the Eurostat database was deemed the most suitable to study our research questions as it provides online retail data for 23 European countries (20 countries of the European Union, plus Norway, UK, and Turkey, covering thereby all major economies from Europe). This sample offers a rich variety of pandemic-related contexts: each of these countries was hit by the pandemic to a different extent and the reaction of authorities was also fairly diverse ( Hale et al., 2021 ). Fig. 2 illustrates the evolution of the ΔOnline_retail variable in these countries.

Monthly changes in online retail turnover during the pandemic in the countries investigated.

To investigate this volatile evolution, two novel measures are used as explanatory variables that have been introduced recently as a response to the need to track social phenomena more frequently and more precisely during the pandemic.

The first variable is a proxy of changes in general customer behavior: population mobility . Shankar et al. (2021) argue that during a period characterized by dramatic and frequent changes in shopping behaviors, high-frequency, mobile GPS data can offer better information for retailers. Therefore, we integrate into our analysis the mobility data provided by Google® through their Community Mobility Reports ( Google, 2021 ), comprising several types of mobilities grouped by the destination/location of the mobility. Based on Beckers et al. (2021) who argue that COVID-19 has temporarily put an end to hypermobility cutting short consumers’ physical range around their homes, we select the residential component ( ΔResidential ) from the different forms of mobility, arguing that the changes in residential mobility (i.e., amount of time spent at home) could be the strongest component to explain changes in online shopping. Given that there might be some time needed for online shopping behavior to adjust to changes in mobility, the one-month lagged version of the variable is also used in our model ( ΔResidential(-1) ).

The second explanatory variable incorporated in our analysis is related to government restrictions . We use data from the Oxford COVID-19 Government Response Tracker, more precisely the values of the COVID-19 Stringency Index which aggregates the stringency of lockdown-type governmental measures, such as school closures, travel restrictions, bans on public gatherings, workplace closures, etc. ( Hale et al., 2021 ). This represents the most suitable proxy to measure the type of regulations connected by previous literature to online channel use during the pandemic ( Table 1 ). The index provides a multi-country panel of daily frequency, measured as a percentage value; 100% representing the highest level of stringency. To match the frequency of the dependent variable, the monthly change of the index is computed as explanatory variable ( ΔGovernment_stringency ). The one-month lagged variant is also introduced in the analysis ( ΔGovernment_stringency(-1) ).

Beside the two novel explanatory variables generated during the pandemic, we integrate several control variables in our analysis. These variables assess the income and purchasing power of the population (GDP/capita and unemployment level in each country), the level of urbanization (density of the population in each country), the level of education (percentage of the population attending tertiary education), the pervasiveness of online channels (Internet penetration), and the actual pervasiveness of online shopping (Online retail share in the retail sector) ( Hortaçsu and Syverson, 2015 ). Data for all countries analyzed are retrieved from the Eurostat database. The unemployment variable has a monthly frequency ( Δ Unemployment ), while the other variables ( GDP/capita, Internet penetration, Tertiary education, Population density, Online retail share ) change on a yearly basis. Descriptive statistics for the monthly variables are provided in Table 2 . The correlation matrix is included in Appendix A.

Descriptive statistics of the main variables included in the short-term analysis.

	Variables
Statistics	Δ Online retail	Δ Unemployment	Δ Residential	Δ Residential (−1)	Δ Government stringency	Δ Government stringency (−1)
	0.0206	−0.0132	0.0039	0.0035	2.1595	2.1232
	0.0087	−0.1000	0.0027	0.0021	0.0000	0.0000
	0.5520	1.5000	0.2071	0.2071	58.0242	58.0242
	−0.2554	−2.0000	−0.1321	−0.1321	−31.4557	−31.4557
	0.0904	0.4170	0.0419	0.0426	13.5469	13.7702
	1.1902	0.1672	0.7464	0.7609	1.37032	1.36048
	7.1846	6.1327	5.3353	5.2217	5.8321	5.70269
	507	509	552	529	552	529

3.2. Data used in long-term analysis (RQ2)

To evaluate the trend-shifting potential of the pandemic in the online retail sector, the same retail trade data is used as for the short-term analysis, covering however a longer period of time between Jan 2000 and Jan 2022 ( Online_Retail ). To offer an overview of the long-term evolution of our focal variable, we present a boxplot containing data for all countries aggregated to annual averages, normalized on a 0–100 scale ( Fig. 3 , left). Primary visual inspection suggests that two periods can be distinguished in terms of the dynamism of the sector (2000–2010 characterized by slower growth pace versus 2011–2021 showing stronger momentum), while the relatively higher values of the last two boxplots indicate that it is beneficial to investigate whether the pandemic has induced a level shift into the evolution of online retail.

Long-term evolution of online retail turnover (left) and online retail market share (right) in the countries investigated (normalized: min = 0, max = 100).

Furthermore, to assess whether the online retail sector could exploit the window of opportunity opened by the pandemic, we compute another variable as a proxy measuring the share of online retail in total retail sales. For this purpose, we calculate the ratio between the indices of deflated turnover of online retail and the “Retail trade, except of motor vehicles and motorcycles” sector, this latter being a proxy for total retail sales ( Online_Retail_Ratio ≈ Online_Retail/Total_Retail ) ( Fig. 3 , right). The ratio approach is also consistent with theory (symbiotic technologies: Geels, 2002 ) and previous research ( Hortaçsu and Syverson, 2015 ).

4. Analysis and results

4.1. short-term analysis (rq1), 4.1.1. panel regression analysis.

To illuminate the impact of mobility and government restrictions on the monthly evolution of online sales, we have elected to implement a panel regression model. We have performed three random-effects and three cross-section fixed-effects panel regressions. We opted for the panel specification because it enables us to harness the rich structure of our data and to account for the unobserved heterogeneity present in the data. We perform 2 × 3 = 6 regressions because of the different methodology (fixed vs. random effects), and the 3 combinations resulting from including only the government stringency variables, only the residential mobility variables, and both. Five control variables were nearly collinear in the fixed effects case; therefore Table 3 presents only the estimates for these variables in the random effects case. Our main specification is the following:

where C i j t and β ( C ) j are the independent variables and their coefficients, i is the index of countries, t of time, and j of the equation variables.

Regression models.

Dependent variable: Δ Online retail
1	2	3	4	5	6
Fixed effects (FE)			Random effects (RE)
–	–	–	−0.000000 (−0.64)	−0.000000 (−0.39)	−0.000000 (−0.61)
–	–	–	−0.000656 (−0.47)	−0.000546 (−0.39)	−0.000554 (−0.40)
–	–	–	−0.000405 (−1.30)	−0.000485 (−1.55)	0.000428 (−1.38)
–	–	–	0.028760 (1.04)	0.031739 (1.15)	0.028319 (1.03)
–	–	–	−0.000011 (−0.01)	0.000033 (0.04)	−0.000011 (−0.01)
0.010779 (1.65)	0.001487 (0.15)	0.008275 (0.84)	0.007104 (0.61)	−0.007929 (−0.67)	−0.001937 (−0.16)

		0.283552 (1.72)			0.228287 (1.10)
		0.000801 (1.52)			0.000615 (1.01)
		0.001006 (1.94)
0.204	0.202	0.217	0.220	0.219	0.237
0.160	0.158	0.169	0.203	0.202	0.216
4.60	4.55	4.57	12.91	12.78	11.28
456	456	456	374	374	374

Notes: t-values in parentheses; *significant at 0.05; **significant at 0.01.

Results of the fixed effects specifications of our panel regression model (equations 1 to 3) indicate that our first variable of interest, residential mobility, and its one-period lag, have a significant impact on the monthly change in online retail sales, both variables having the expected positive sign. The same can be pointed out for the government stringency and lag variables. However, when we include both residential mobility and government stringency, only the first remains significant, due to high collinearity between the two explanatory variables. The results are similar in the random effects case (equations 4 to 6). The goodness-of-fit statistics (adjusted R-squared, F-statistic) are quite high for panel regressions, indicating that the explanatory variables introduced in the panel explain a large proportion of the variation of the monthly change in online retail sales.

Thus, results altogether indicate that both residential mobility and government stringency are significant predictors of online retail channel use: as residential mobility increases (i.e., people spend more time at home) and, alternatively, as government stringency increases (i.e., anti-COVID-19 measures become stricter) the use of online retail channels increases. Furthermore, the impact of all control variables is insignificant, meaning that mobility and government stringency indicators provide a better explanation for the variation of online retail sales during the pandemic than traditional variables that have been used to explain the evolution of the online retail sector in pre-pandemic periods.

4.1.2. Detailed analysis of short-term effects

While panel regression results show that both residential mobility and government stringency are good predictors of the evolution of online sales, relationships between variables are rarely perfectly linear. Therefore, we provide a more detailed analysis on the interplay between these variables. Fig. 4 illustrates the monthly evolution of online sales (vertical axis) together with the monthly percentage change in residential mobility (horizontal axis) for the entire period of the pandemic, each dot representing one country in one month.

Monthly evolution of online sales and residential mobility during the pandemic in the countries investigated.

Beside the general positive relationship between the two variables, the scatter plot also indicates that three different forces can be identified that shape the evolution of online retail sales during the pandemic. First, there are periods in which mobility is restricted more and more to residential areas, and consumers adapt by significantly increasing their monthly spending on online retail channels (as high as +30–50% during the first wave of the pandemic). This process is exactly what was expected during the pandemic: as the mobility range of people is restricted primarily to their homes, they turn to online retail channels more frequently. This process is termed the “lure-in” phase. Typical months during which the lure-in phase was dominant were Mar 2020, Apr 2020, Oct–Nov 2020, Nov 2021, and Jan 2022 ( Fig. 5 ).

Monthly evolution of online sales and residential mobility during different phases of the pandemic in the countries investigated.

However, it is also observable that when consumers are not confined to residential areas and start increasing their mobility outside their homes (i.e., residential mobility decreases), a decrease in online spending does not follow automatically, as people tend to continue to use, or even increase the usage of, online retail channels. Additionally, in many cases a large drop in residential mobility is paired with no significant change in online retail sales. These cases are labelled as the “lock-in” phase, which means that temporarily consumers remain users of online channels even if their mobility would allow them to use offline channels more intensively. Thus, mobility restrictions have an immediate (lure-in), but also a lagged (lock-in) impact on online retail channel use, in line with the significance of lagged variables in our panel regression model ( Table 3 ). The most typical months in which several European countries went through this lock-in phase were May 2020, Jun 2020, Feb 2021, Mar 2021 ( Fig. 5 ). This phase is not as consistent on a monthly basis as the lure-in phase, several countries experiencing a negative change in online channel use, concurrently with the decrease of residential mobility.

Lastly, there is also a “phase-out” period denoting cases where online retail use decreases, while time spent at home generally decreases. During these months a part of the former online shopping volume of customers is most probably replaced by (or allocated back to) offline channels. Furthermore, in some rare instances residential mobility has a slight increase, while consumers still decrease their online spending. Predominantly phase-out months include Jul 2020, May–Jul 2021, Dec 2021 ( Fig. 5 ).

The same three phases can be observed if the residential mobility indicator on the vertical axis is replaced by the government stringency index ( Fig. 6 , Fig. 7 ). In summary, there is a clear lure-in phase which was noticeable especially during the beginning of the first and second wave of the pandemic (Mar–Apr, 2020; Oct–Nov 2020): sudden drops in mobility and severe governmental restrictions clearly prompt customers to shop online. This effect has some “stickiness” (lock-in phase) because as governmental restrictions are eased, certain customers continue to use (or even increase the use of) online retail channels. Nevertheless, after a relatively short period the lock-in effect fades and customers drop their online shopping volume significantly (phase-out), countervailing to some extent the argument of the pandemic-induced upward boost of the online retail sector. Thus, while illuminating in other respects, this analysis, in itself, is unhelpful regarding the longer-term implications of the pandemic for the online retail sector. The next section aims to address this deficiency.

Monthly evolution of online sales and government stringency during the pandemic in the countries investigated.

Monthly evolution of online sales and government stringency during different phases of the pandemic in the countries investigated.

4.2. Long-term analysis (RQ2)

To investigate the potential trend-shifting impact of the pandemic in the online retail sector, a two-step approach is applied. First, to establish a basis for comparison, we analyze the 20-years trend of the sector without considering the specific effect of the pandemic. Second, based on the long-term trend established, we focus on the period of the pandemic, and use outlier detection methods to estimate whether the pandemic has induced a level shift in the long-term trend of the sector.

4.2.1. Long-term trend analysis

Online retail sales and online retail market shares show an increasing tendency during the last 20+ years ( Fig. 3 ). While the retail sector as a whole had a slight increasing tendency during this period, the average annual growth rate of the online retail sector was clearly higher. This difference is most visible during the last ten years when the online retail sector has been constantly on an increasing trajectory, thereby raising its market share within the total retail sector. Thus, the online retail sector has been benefitting from continuous market share gains with a relatively lower growth pace in the early period (2001–2010), and with rapid increases in the last period (2011–2021). These differences are illustrated in Fig. 8 .

Average annual growth rates in the retail sector in European countries (%).

Next, we use unit root tests to statistically demonstrate that there is an underlying long-term growth trend in the data ( Chatfield and Xing, 2019 ), both in terms of monthly online retail turnover ( Online_Retail ) and in terms of online retail market share ( Online_Retail_Ratio ). Applying the most widely used Augmented Dickey-Fuller (ADF) test, we aim to show that there is a systematic, persistent stochastic trend in the time series (i.e., an upward tendency in our case). Unit root test results confirm that in most of the countries investigated the null hypothesis of one unit root cannot be rejected: the p-values are above 0.05 in 23 cases out of 24 in case of the Online_Retail variable and in 21 cases out of 24 for Online_Retail_Ratio . Thus, for the vast majority of countries neither Online_Retail , nor Online_Retail_Ratio is stationary, indicating that there is an (upward) long-term stochastic trend in the time series. Furthermore, unit root test results also imply that any positive or negative shock (such as the pandemic) during the period investigated has a persistent effect on the trend. Nevertheless, further investigation is needed to determine whether this shock applies for the pandemic period as well.

4.2.2. Outlier detection during the pandemic

Outlier detection is used to determine whether the pandemic has caused a level shift in the Online_Retail , and especially in the Online_Retail_Ratio time series. For this purpose, we use ARIMA 1 models with specific dummy regressors on both time series, implemented in JDemetra+ which is a proprietary software developed by the National Bank of Belgium in cooperation with the Deutsche Bundesbank and Eurostat. The software has been officially recommended since 2015 to the members of the European Statistical System and the European System of Central Banks as a tool for seasonal adjustment and other connected time series issues, such as outlier detection. In general, outliers are represented by abrupt changes in a time series caused by unexpected natural or socioeconomic effects, such as the pandemic. Three main types of outliers can be identified ( Fig. 9 ): (a) additive outlier (AO), which changes the time series for one period only, returning to the original trend afterwards, (b) level shift (LS) that causes a permanent (upward or downward) change in the level of a time series, and (c) transitory change (TC) whose effect of changing the time series is faded out over a limited number of periods ( IMF, 2018 ). Here, we specifically look for LS type outliers: a positive LS would suggest that online retail turnover and its market share registered a sudden increase during the pandemic, and that therefore the pandemic has accelerated the underlying growth trend of online retail.

Level shift versus other outlier types (source: IMF, 2018 ).

JDemetra+ uses the traditional TRAMO 2 methodology ( Gómez and Maravall, 1996 ; Findley et al., 2017 ) where TRAMO is designed to perform outlier detection as well. 3 Although this is a widely used framework in economics and connected disciplines, its applications in retailing are quite scarce which offers us the possibility to shed additional light on the effect of the pandemic on the online retail sector. In particular, TRAMO uses regression models with ARIMA errors as follows:

where z t is the original data series, β = ( β 1 , … β n ) is a vector of regression coefficients, y t = ( y 1 t , … y n t ) represents n regression variables (in our case LS, AO and TC outliers), while x t is the disturbance that follows the general ARIMA process.

Using the TRAMO method, we analyze the full Jan 2000–Jan 2022 time period for outliers in each country involved in the analysis, complemented by the aggregated time series on the EU-27 level. Both Online_Retail and Online_Retail_Ratio time series were analyzed for all three types of outliers. However, in light of RQ2, only LS type outliers are listed in Table 4 that were identified during 2020. It should be noted that 2021 LS outliers are not (yet) taken into consideration here because they are situated at the end of our time series data (i.e., further data is needed by TRAMO to determine whether a 2021 LS will remain significant and persist in the long run). In contrast, LS outliers in 2020 have already proven that they induced a persistent upward shock into the long-term trend of the online retail sector. Table 4 lists all significant level shifts (p < .05) detected during 2020. Full results are presented in Appendix B .

Level shift (LS) detection during the pandemic.

Online_Retail		Online_Retail_Ratio
LS date	Magnitude (t-value)	LS date	Magnitude (t-value)
04–2020	+.161 (6.573)	03–2020	+.149 (5.667)
04–2020	+.266 (5.77)	–	–
–	–	–	–
–	–	03–2020	+.142 (12.52)
04–2020	+.214 (9.752)	–	–
04–2020	+.206 (6.138)	03–2020	+.183 (4.902)
–	–	–	–
–	–	–	–
04–2020	+.339 (8.350)	03–2020	+.201 (5.479)
04–2020	+.259 (10.479)	04–2020	+.259 (10.634)
05–2020	+.167 (10.036)	03–2020	+.151 (7.447)
–	–	–	–
–	–	–	–
05–2020 08–2020	+.011 (1.837) +.020 (3.615)	03–2020 06–2020 11–2020	+.247 (28.143) −.092 (−9.905) +.117 (11.338)
04–2020 11–2020	+90.59 (49.585) +27.01 (13.700)	11–2020	+25.291 (12.4)
04–2020	+.158 (6.298)	–	–
03–2020 11–2020	+.215 (7.412) +.138 (4.863)	03–2020 06–2020 11–2020	+.203 (7.08) −.112 (−3.904) +.149 (5.543)
–	–	–	–
–	–	–	–
–	–	–	–
04–2020	+.180 (9.191)	04–2020	+.203 (10.393)
–	–	–	–
04–2020	+.170 (5.772)	04–2020	+.349 (12.074)
04–2020	+.185 (12.005)	11–2020	+.131 (9.141)

The results of LS detection indicate that at the level of the EU-27, as well as in most of the countries investigated there was at least one positive LS in the online retail trend during the first year of the pandemic. This strongly suggests that COVID-19 has induced a boost both to online retail turnover and to its market share, supporting the window of opportunity concept. Out of the 23 countries analyzed, only 9 where had no significant LS. However, these cases represent smaller European countries, the largest ones (Germany, France, Italy, Spain, UK) all experiencing positive significant LSs. Furthermore, some of the countries (Italy, Lithuania, Norway) experienced multiple significant LSs during 2020 which further strengthens our conclusion related to the long-term implications of the pandemic. While there are two anomalous negative LSs in the Online_Retail_Ratio as well ( Table 4 ), we suggest that these do not contradict our results, as these are all overcompensated by multiple positive LSs in the same countries (Italy and Norway), the magnitude of which is significantly higher than that of the negative LSs. Nevertheless, these negative LSs could be a sign of a significant “phase-out” effect, as discussed in the short-term analysis.

5. Summary and discussion

Two important gaps were addressed in this paper: (RQ1) how can factors related to consumer behavior (mobility) and regulations (government stringency) explain the volatile evolution of online retail sales during the pandemic, and (RQ2) what long-term trend-shifting effects can be identified during the pandemic in the evolution trajectory of online retail.

First, our results confirm that the two indicators proposed to estimate changes in consumer behavior ( Residential mobility ) and in government regulations ( Government stringency ) can significantly explain the hectic short-term evolution of the online retail sector during the pandemic. Released for the first time during the pandemic, these two indicators are significantly above and beyond the explanatory power of traditional variables used to predict online channel use in pre-pandemic periods. The more people are confined to residential areas, and the stricter government restrictions are, the more customers turn to online channels. These results offer empirical support to previous studies that proposed that changes in mobility ( Shankar et al., 2021 ) and pandemic-related government regulations ( Hwang et al., 2020 ) could provide a better measure to estimate changes in online sales.

Second, using these newly introduced variables, our study goes beyond demonstrating the simple linear relationship between these variables and online retail turnover, to describe in more detail how online shopping habits change during the pandemic. This is a novel approach compared to existing studies that simply argue that the pandemic is linked to the increased use of online channels (e.g., Chang and Meyerhoefer, 2021 ; Hwang et al., 2020 ; Eger et al., 2021 ). Using government stringency and mobility data, we offer a more nuanced understanding of how online shopping behavior evolves during the different stages of the pandemic, an issue currently hotly debated in the literature ( Kirk and Rifkin, 2020 ; Guthrie et al., 2021 ; Schleper et al., 2021 ). Three different phases are distinguished in this paper: (1) a lure-in phase; (2) a temporary lock-in phase; and (3) a phase-out period. Furthermore, the same phases seem to repeat during different waves of the pandemic, starting with a strong lure-in phase, followed by a mix of lock-in and phase-out periods.

Third, using advanced outlier detection methods, we show that the faster growth trend that characterized online retail in the past decade has experienced a new positive level shift during 2020 in most of the countries investigated. In only a couple of months during the pandemic, online retail has gained extra market share against offline retail that in normal circumstances would have probably taken several years. Thus, our empirical findings confirm the predictions of some researchers (e.g., Chang and Meyerhoefer, 2021 ; Tran, 2021 ), and actively address the questions posed by other researchers (e.g., Sheth, 2020 ; Guthrie et al., 2021 ), by establishing that the pandemic has indeed induced a persistent upward shift into the growth trajectory of online retail. These level shifts were especially visible in the larger economies of Europe. Thus, our results are concordant with several other studies that suggest that many firms managed to quickly overcome infrastructural challenges and build up the necessary online capacities ( Guo et al., 2020 ; Beckers et al., 2021 ; Reardon et al., 2021 ), while customers will continue to use online retail channels more intensively in post-lockdown periods as well ( Hobbs, 2020 ; Eger et al., 2021 ; Hall et al., 2021 ). Even if some customers return to traditional shopping channels ( Hobbs, 2020 ; Sheth, 2020 ), our results indicate that for a large segment of customers the pandemic-induced shock outweighs the potential phase-out effect, shifting their long-term orientation towards online channels.

6. Conclusion

This paper analyzed short-term drivers (RQ1) and long-term implications of the pandemic (RQ2) in the online retail sector, relying on the MLP’s socio-technical approach as a theoretical lens. COVID-19 is operationalized within the MLP as an exogeneous landscape event that induced a shock on the regime level. This shock opened a window of opportunity for online retail to exponentially grow and significantly increase its share against traditional retail channels.

6.1. Theoretical implications

Our research shows that during a window of opportunity created by a landscape event, forces within the socio-technical regime that shape the long-term trajectory of a technology change radically. Geels and Schot (2007) argue that strong landscape pressures (such as a pandemic) destabilize actual socio-technical regimes creating tensions that open windows of opportunity for technologies to emerge. Our short-term analysis related to RQ1 offers additional insights into how these regime tensions function. Panel regression results indicate that during unstable periods (when windows of opportunity are created by landscape pressures), certain sub-regimes take over the force that shapes technological transitions, while other sub-regimes become negligible. In our study, the policy regime (strict government restrictions) and the user preferences and market regime (reorientation of shopping behaviors due to reduced mobility) were responsible for creating the tension on the regime-level. Conversely, other sub-regimes on the same level, such as technological regimes (e.g., technical infrastructure used in online retail), science regime (e.g., technical knowledge used to operate online transactions), and socio-cultural regimes (e.g., distrust of certain segments of the population in online retail), had no significant impact on the way online retail was evolving. Thus, we propose that windows of opportunity are created when one or more particular regimes exert pressures that take over the place of other regimes in creating the forces that shape technological transitions. When a window of opportunity is open, these new forces remain dominant and might even alter other regimes.

Second, our long-term analysis suggests that COVID-19 can be regarded as a shock-type landscape development that creates tension in the current socio-technical regime to create a window of opportunity for online retail. Results of our long-term analysis suggest that the quasi-stable socio-technical regime of the last decades enabled a gradual and constant growth of online retail in Europe, attaining continuously increasing market shares throughout the years. However, as the pandemic generated a window of opportunity for this sector, online retail was able to capitalize on this opportunity in most countries, receiving a significant boost to its previous growth tendency.

Third, as a more general research implication for retail, our study demonstrates that high-frequency indicators that emerged during the pandemic, such as data on population mobility and on government stringency can be used to better assess fundamental socio-economic processes during crises. These two types of indicators provide a more complex, real-time assessment of ongoing socio-economic processes, making them more suitable to make predictions or explain phenomena in a volatile context.

6.2. Practical implications

Through demonstrating that mobility and government stringency has a positive impact on the evolution of online sales, we offer an important tool to retail practitioners to monitor and anticipate potential large variations in online demand. While mobile GPS data has already been used to track retail store traffic, our analysis suggests that tracking customer movements outside brick-and-mortar stores can also provide an anchor during volatile times. Such high-frequency, near-real-time data could become the primary input for managers to keep up with sudden pandemic-related developments, and potentially with post-pandemic shopping behavior changes as well.

Online retailers that have already capitalized on this pandemic should also take into consideration that a sudden pandemic-related growth in sales could be followed by a temporary lock-in phase. However, retailers should continue to work on keeping (newly acquired) customers, as a phase-out period might rapidly occur. Conversely, our long-term analysis, suggests that actors in the online retail sector should expect that, on average, the phase-out effect is outweighed by the pandemic-induced boost in online sales, creating much potential on the long-run for online retailers to capture the benefits of the positive level shift in the growth trajectory of the sector.

6.3. Limitations and further research

A first set of limitations is related to the nature of data employed in our study. While Eurostat provides the most reliable macroeconomic data, comparable across countries, on the evolution of the (online) retail sector, aspects of the data were not ideal. Several countries had missing data on the most recent values of the online retail turnover index, and some European countries (e.g., Switzerland) could not be involved in our study at all. While all largest retail markets have been included in our sample, results of the study can nevertheless not be universally generalized beyond the 23 countries involved in the analysis.

In respect of GPS-based mobility and government stringency data, we have shown that these variables are suitable to explain the large variations in online retail sales during the pandemic. However, whether and to what extent these data can be used to keep up with developments in the online retail sector beyond the pandemic remains unknown but represents a promising direction for future research.

Another set of limitations stems from the results described in this paper. While our outlier detection could empirically demonstrate the pandemic-induced level shift in the long-term evolution of the online sector, statistically significant shifts were not observed in all the countries investigated. It remains an important future research avenue to explain why some countries, including the largest European economies, experienced level shifts during the pandemic, while others have not.

Lastly, this paper focused on the evolution of the online retail sector, explaining its volatile evolution during the pandemic and demonstrating how the sector could take advantage of the window of opportunity created by COVID-19. Our results could provide a starting point for investigating other technologies and solutions, such as video conferencing, home delivery or VR-solutions, to evaluate whether and to what extent they have capitalized on pandemic-induced opportunities, thereby shaping how the “ new normal ” might look like in a post-pandemic world.

Acknowledgement

This research was partially supported by the PN-III-P1-1.1-TE-2019-1773 research project for young independent research teams funded by UEFISCDI Romania.

1 Autoregressive Integrated Moving Average.

2 Time series Regression with ARIMA noise, Missing values and Outliers.

3 A comprehensive description of the procedure and its technical implementation in JDemetra+ is provided by Eurostat’s website .

Appendix A. – Correlation matrix

Δ Online retail	Δ Unemployment	Δ Residential	Δ Residential (−1)	Δ Government stringency	Δ Government stringency (−1)
1.0000
0.0682	1.0000
0.3406*	−0.0775	1.0000
0.3662*	0.0739	0.3323*	1.0000
0.3696*	0.0510	0.8244*	0.4035*	1.0000
0.3583*	0.2004*	0.2426*	0.8226*	0.3692*	1.0000

*significant at the p < .001 level.

Appendix B. Complete results of outlier detection

Outlier detection with TRAMO in the Online_Retail time series (Jan 2000–Jan 2022)

OUT (1)	OUT (2)	OUT (3)	OUT (4)	OUT (5)	OUT (6)	OUT (7)	OUT (8)	OUT (9)	OUT (10)
TC (7–2021): −0.114 [-6.265]	TC (7–2020): −0.105 [-6.765]	LS (4–2020): 0.185 [12.005]	LS (5–2015): 0.096 [6.315]	AO (8–2009): −0.059 [-3.58]	AO (12–2005): 0.061 [3.696]	AO (6–2000): −0.05 [-3.031]
LS (4–2020): 0.266 [5.77]	AO (11–2008): −0.313 [-6.097]	AO (7–2008): −0.46 [-9]	LS (1–2006): −0.54 [-11.719]	AO (5–2001): 0.501 [9.567]	AO (4–2001): 0.211 [4.054]
LS (1–2006): −0.269 [-4.574]
TC (4–2020): 0.19 [26.189]	TC (12–2019): 0.041 [5.591]	TC (8–2014): 0.136 [23.936]	LS (1–2013): 0.122 [19.92]	LS (12–2008): −0.144 [-23.536]	AO (5–2000): 0.454 [50.068]
LS (4–2020): 0.206 [6.138]	AO (5–2005): 0.155 [4.791]	AO (12–2004): −0.233 [-7.159]	AO (7–2004): 0.215 [6.429]	LS (1–2004): 0.218 [6.693]	AO (12–2001): 0.213 [6.548]	AO (8–2001): −0.195 [-5.809]	AO (7–2001): 0.253 [7.519]	AO (4–2001): 0.183 [5.625]	TC (2–2001): −0.299 [-8.764]
LS (7–2021): −0.149 [-6.325]	LS (4–2020): 0.214 [9.752]	LS (5–2015): 0.205 [10.089]	LS (1–2015): 0.05 [2.445]	AO (4–2008): 0.083 [3.917]	AO (9–2006): −0.096 [-4.46]	AO (12–2005): 0.114 [5.327]	AO (6–2000): −0.127 [-5.169]	AO (5–2000): 0.129 [5.24]
LS (1–2005): −0.391 [-4.776]	TC (8–2003): −0.308 [-3.892]	TC (8–2002): 0.31 [3.914]
AO (7–2015): −0.386 [-4.014]	AO (8–2008): −0.429 [-4.46]	LS (12–2004): −0.502 [-4.008]
AO (7–2021): −0.228 [-6.79]	AO (7–2020): −0.217 [-6.468]	LS (4–2020): 0.339 [8.35]	LS (5–2015): 0.225 [5.535]	LS (9–2012): −0.181 [-4.446]	AO (8–2001): 0.211 [6.289]	AO (2–2001): 0.401 [11.971]
TC (7–2021): −0.092 [-4.605]	TC (2–2021): 0.123 [6.796]	AO (7–2020): −0.219 [-14.341]	LS (5–2020): 0.167 [10.036]	AO (4–2017): −0.064 [-4.179]	LS (8–2015): 0.157 [9.461]	AO (8–2009): −0.06 [-3.929]	AO (4–2006): 0.07 [4.553]	AO (4–2005): 0.072 [4.705]	AO (11–2003): −0.09 [-5.91]
AO (8–2020): −0.251 [-4.267]	AO (3–2020): −0.246 [-4.195]	AO (8–2019): −0.329 [-5.61]	TC (10–2014): −0.372 [-6.038]	TC (8–2014): 0.506 [8.207]	AO (7–2005): −0.286 [-4.868]	AO (2–2004): 0.306 [5.172]	AO (12–2003): −0.271 [-4.57]	AO (8–2003): −0.289 [-4.903]	LS (5–2003): −0.247 [-4.195]
AO (5–2021): −0.173 [-19.32]	LS (8–2020): 0.02 [3.615]	LS (5–2020): 0.011 [1.837]	AO (12–2018): −0.143 [-28.913]	TC (1–2014): 0.154 [44.932]	AO (1–2010): 0.126 [33.284]
LS (7–2021): −30.487 [-13.656]	TC (3–2021): 25.141 [14.866]	LS (2–2021): 16.387 [7.689]	TC (12–2020): 111.835 [58.71]	LS (11–2020): 27.01 [13.7]	TC (6–2020): −14.646 [-8.642]	LS (4–2020): 90.59 [49.585]	TC (3–2020): 11.86 [6.659]	AO (11–2019): −14.275 [-12.237]	AO (4–2018): −9.764 [-8.765]
TC (4–2020): 0.393 [10.824]	LS (7–2011): 0.197 [9.63]	AO (12–2007): 0.123 [5.93]	AO (9–2006): −0.026 [-1.293]	AO (1–2005): −0.041 [-2.035]	AO (8–2004): −0.078 [-3.728]	AO (12–2002): −0.147 [-5.766]
TC (1–2021): 0.19 [6.623]	LS (4–2020): 0.158 [6.298]	TC (2–2005): 0.262 [9.231]	AO (12–2004): −0.162 [-5.848]	TC (9–2004): 0.216 [7.467]	TC (1–2004): 0.179 [6.556]	AO (8–2002): 0.162 [5.963]	TC (9–2001): 0.162 [5.904]	AO (10–2000): −0.144 [-5.064]	LS (4–2000): 0.156 [5.577]
TC (11–2020): 0.173 [5.619]	LS (4–2020): 0.161 [6.573]	AO (7–2005): −0.124 [-3.734]	TC (4–2004): 0.131 [4.318]
LS (10–2013): −0.225 [-3.898]	LS (1–2010): 0.327 [5.663]	LS (1–2008): 0.44 [7.604]	LS (1–2006): 0.578 [10.001]	TC (6–2001): −0.253 [-4.441]	TC (10–2000): −0.266 [-4.664]
TC (5–2019): 0.321 [4.498]	LS (1–2005): −0.587 [-8.939]	TC (1–2001): 0.387 [5.425]
TC (1–2008): −1.589 [-38.435]	LS (12–2005): 1.346 [29.719]	AO (6–2005): 0.738 [19.879]	AO (1–2005): −1.199 [-28.919]	TC (11–2004): 0.396 [8.765]	LS (7–2004): 0.617 [10.883]	AO (9–2003): −0.296 [-8.396]	LS (1–2002): 0.295 [5.523]	LS (1–2001): 0.678 [12.269]	LS (7–2000): −0.4 [-7.31]
LS (4–2020): 0.259 [10.479]
LS (4–2020): 0.18 [9.191]	AO (5–2019): −0.078 [-3.674]	LS (4–2018): −0.175 [-8.951]	LS (1–2018): −0.075 [-3.803]	TC (12–2013): 0.076 [3.688]	AO (4–2006): 0.089 [4.183]	AO (12–2003): −0.113 [-5.36]	AO (12–2002): −0.101 [-4.745]	AO (10–2002): 0.083 [3.908]	AO (6–2001): 0.103 [4.869]
LS (6–2021): −0.2 [-7.072]	LS (2–2021): 0.132 [4.606]	LS (11–2020): 0.138 [4.863]	AO (4–2020): 0.161 [5.189]	LS (3–2020): 0.215 [7.412]	TC (12–2018): −0.141 [-4.648]	AO (9–2004): 0.123 [4.133]	LS (6–2001): −0.123 [-4.405]
TC (5–2020): 0.147 [4.603]	LS (4–2020): 0.17 [5.772]	LS (12–2002): −0.139 [-5.252]	LS (2–2001): −0.178 [-6.737]
AO (11–2019): 0.143 [4.528]	AO (11–2018): 0.176 [5.586]	TC (2–2014): −0.207 [-5.546]

Content of cells: (a) type of outlier: LS – level shift, TC – transitory change, AO – Additive outlier; (b) month of occurrence in parentheses; (c) magnitude of outlier [t-value].

Outlier detection with TRAMO in the Online_Retail_Ratio time series (Jan 2000–Jan 2022)

OUT (1)	OUT (2)	OUT (3)	OUT (4)	OUT (5)	OUT (6)	OUT (7)	OUT (8)	OUT (9)	OUT (10)
LS (6–2021): −0.11 [-7.671]	LS (11–2020): 0.131 [9.141]	AO (7–2020): −0.085 [-5.169]	TC (4–2020): 0.271 [16.049]	TC (3–2020): 0.108 [6.457]	LS (5–2015): 0.091 [6.435]	AO (8–2009): −0.057 [-3.524]	LS (1–2006): −0.052 [-3.712]	AO (6–2000): −0.041 [-2.538]
LS (5–2015): 0.078 [6.023]	AO (12–2005): 0.052 [3.274]
TC (7–2021): −0.127 [-6.924]	TC (1–2021): 0.07 [4.287]	LS (11–2020): 0.124 [7.876]	TC (4–2020): 0.275 [15.286]	TC (3–2020): 0.108 [6.041]	AO (7–2020): −0.096 [-5.481]	LS (5–2015): 0.103 [6.897]	AO (8–2009): −0.06 [-3.459]	LS (1–2006): −0.056 [-3.716]
TC (11–2020): 0.237 [4.546]	TC (4–2020): 0.359 [6.913]	AO (11–2008): −0.248 [-4.722]	AO (7–2008): −0.374 [-7.144]	LS (1–2006): −0.559 [-11.922]	AO (5–2001): 0.523 [9.812]	AO (4–2001): 0.231 [4.333]
LS (1–2021): −0.24 [-4.114]
LS (5–2021): −0.073 [-5.852]	AO (12–2020): −0.09 [-7.459]	AO (5–2020): 0.061 [6.656]	AO (4–2020): 0.178 [18.193]	LS (3–2020): 0.142 [12.52]	TC (8–2014): 0.121 [16.184]	LS (1–2013): 0.111 [13.906]	LS (12–2008): −0.151 [-18.944]	LS (1–2004): 0.045 [5.568]	AO (5–2000): 0.452 [44.191]
LS (3–2021): −0.161 [-4.311]	LS (3–2020): 0.183 [4.902]	AO (12–2004): −0.231 [-4.983]	LS (1–2004): 0.194 [5.204]	AO (12–2001): 0.182 [3.912]	AO (8–2001): −0.192 [-4.08]	AO (7–2001): 0.253 [5.387]	TC (2–2001): −0.272 [-6.217]
TC (1–2021): 0.194 [7.337]	TC (4–2020): 0.265 [10.23]	LS (5–2015): 0.196 [8.446]	AO (12–2005): 0.099 [3.894]	AO (6–2000): −0.123 [-4.484]	AO (5–2000): 0.112 [4.074]
TC (4–2020): 0.374 [4.984]	LS (1–2005): −0.381 [-5.052]	TC (8–2003): −0.306 [-4.088]	LS (4–2001): 0.291 [3.859]
LS (12–2004): −0.546 [-4.184]
AO (9–2021): −0.181 [-4.587]	AO (7–2021): −0.255 [-7.796]	AO (7–2020): −0.198 [-6.431]	TC (4–2020): 0.519 [14.508]	LS (3–2020): 0.201 [5.479]	LS (5–2015): 0.219 [6.275]	AO (8–2001): 0.183 [6.349]	AO (2–2001): 0.382 [13.215]
LS (6–2021): −0.141 [-7.295]	LS (2–2021): 0.1 [5.292]	AO (11–2020): 0.206 [10.403]	TC (7–2020): −0.214 [-10.419]	TC (4–2020): 0.172 [7.808]	LS (3–2020): 0.151 [7.447]	LS (8–2015): 0.157 [8.545]	AO (4–2005): 0.082 [4.25]
AO (4–2020): 0.409 [6.357]	AO (8–2019): −0.322 [-4.998]	TC (10–2014): −0.366 [-5.359]	TC (8–2014): 0.48 [7.019]	AO (7–2005): −0.275 [-4.266]	AO (2–2004): 0.315 [4.891]	AO (12–2003): −0.25 [-3.882]	AO (8–2003): −0.315 [-4.896]
AO (5–2021): −0.192 [-17.094]	AO (1–2021): 0.048 [4.718]	LS (11–2020): 0.117 [11.338]	LS (6–2020): −0.092 [-9.905]	AO (4–2020): 0.114 [12.281]	LS (3–2020): 0.247 [28.143]	TC (5–2019): −0.032 [-4.527]	AO (12–2018): −0.135 [-19.603]	TC (1–2014): 0.157 [29.273]	AO (1–2010): 0.128 [21.782]
AO (3–2021): 8.777 [5.57]	TC (1–2021): 27.845 [16.032]	TC (12–2020): 106.929 [58.167]	LS (11–2020): 25.291 [12.4]	TC (6–2020): −10.686 [-5.922]	TC (5–2020): −25.697 [-15.036]	TC (4–2020): 105.011 [58.766]	TC (3–2020): 27.288 [15.714]	AO (11–2019): −12.908 [-8.995]	TC (4–2018): −8.16 [-5.004]
TC (4–2020): 0.543 [14.62]	LS (7–2011): 0.206 [8.35]	LS (1–2008): −0.123 [-4.806]	AO (8–2006): 0.082 [3.077]	AO (11–2004): −0.142 [-6.156]	AO (8–2004): −0.16 [-5.844]	AO (10–2003): −0.108 [-4.615]	AO (12–2002): −0.167 [-6.749]
TC (1–2021): 0.292 [7.055]	TC (4–2020): 0.181 [4.419]	TC (2–2005): 0.237 [5.78]	AO (9–2004): 0.186 [5.309]	AO (8–2002): 0.183 [5.22]	AO (9–2001): 0.152 [4.305]
AO (1–2021): 0.184 [5.52]	TC (11–2020): 0.267 [8.561]	AO (4–2020): 0.284 [8.321]	LS (3–2020): 0.149 [5.667]
TC (4–2020): 0.254 [4.295]	LS (1–2010): 0.295 [4.886]	LS (1–2008): 0.445 [7.39]	LS (1–2006): 0.546 [9.054]	AO (5–2001): 0.227 [4.415]	TC (10–2000): −0.267 [-4.521]
TC (12–2020): 0.259 [3.738]	AO (5–2019): 0.243 [4.099]	AO (4–2005): −0.228 [-3.844]	LS (1–2005): −0.692 [-11.59]	TC (1–2001): 0.384 [5.606]
TC (1–2008): −1.624 [-37.838]	LS (12–2005): 1.27 [26.899]	AO (6–2005): 0.69 [17.072]	AO (1–2005): −1.133 [-27.327]	LS (7–2004): 0.448 [7.743]	LS (2–2002): 0.462 [9.506]	LS (1–2001): 0.679 [14.441]	LS (7–2000): −0.38 [-6.528]	AO (5–2000): −0.402 [-7.998]	AO (2–2000): −0.427 [-7.646]
LS (4–2020): 0.259 [10.634]
LS (4–2020): 0.203 [10.393]	TC (4–2019): −0.077 [-3.712]	LS (4–2018): −0.182 [-9.294]	AO (12–2013): 0.083 [4.165]	AO (4–2006): 0.106 [5.175]	TC (2–2006): −0.087 [-4.303]	AO (12–2003): −0.099 [-4.77]	AO (12–2002): −0.104 [-5.003]	AO (10–2002): 0.085 [4.255]	AO (6–2001): 0.116 [5.773]
LS (6–2021): −0.203 [-7.624]	LS (2–2021): 0.146 [5.378]	LS (11–2020): 0.149 [5.543]	LS (6–2020): −0.112 [-3.904]	AO (4–2020): 0.138 [4.22]	LS (3–2020): 0.203 [7.08]	TC (12–2018): −0.131 [-4.498]	AO (9–2004): 0.116 [3.93]	LS (6–2001): −0.139 [-5.283]
LS (4–2020): 0.349 [12.074]	TC (3–2020): 0.129 [4.453]	LS (12–2002): −0.133 [-4.705]	LS (2–2001): −0.204 [-7.186]	TC (1–2001): −0.113 [-3.931]
AO (5–2021): 0.124 [3.641]	TC (4–2020): 0.343 [8.118]	AO (11–2019): 0.141 [4.16]	AO (11–2018): 0.183 [5.392]	TC (2–2014): −0.166 [-3.94]

Data availability

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Traditional vs. Online Shopping Essay

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Introduction

Shopping constitutes a compulsory function for humans in all walks of life. For a majority of people, shopping is an activity that has transcended from being merely a necessity to one that has become a favorite pastime that brings happiness, recreation, and ‘quality time with friends and members of the family. There are basically 3 kinds of shopping where we buy things we require, things we convince ourselves we require, and things we look at (window shopping) just for pleasure. In the modern world of today, it is possible to indulge in all 3 kinds of shopping by utilizing 2 methods: Traditional shopping and ‘Online’ shopping.

Traditional shopping involves shoppers physically entering a brick-and-mortar store or shopping mall to select items of their choice, pay for them in cash or by credit card, and either take delivery personally or have them delivered to their homes by the retailer. ‘Online shopping is a relatively new method of shopping that involves the shopper sitting in front of a Personal Computer at any location (it could be at home, in the office, in friends’ apartments or in internet cafes), browsing through different categories of products at selected websites either alone or with the assistance of family members and/or friends, choosing items, paying for the purchases by credit card or by electronically transferring money from a bank account (from personal experience, I have noticed there is usually no other payment option).

The selected goods are delivered within a period ranging from a day to a week or even longer. In almost all cases, due to the fact that while selecting an item its availability is also clearly mentioned, the entire selection is delivered; if for some unforeseen reason some items are not delivered, then the value of those items is refunded to the customer by the ‘Online’ seller.

Traditional and ‘Online’ shopping are similar in two ways. Firstly, both forms of shopping follow the general concept of commerce; in both cases, there is a buyer and a seller, both of whom share a specific understanding of how the commercial transaction is expected to unfold, run its course and reach its satisfactory conclusion. Secondly, the prominent method of payment in both forms of shopping is credit card payment; although traditional shoppers can opt for check or cash payment, and although ‘Online’ shoppers can opt for electronic transfer of funds from their bank accounts, credit card purchases are preferred in both cases.

Traditional and ‘Online’ shopping is different in several ways. In one group of differences, Traditional shopping holds ‘absolute’ superiority: Firstly, shoppers experience the physical thrill of shopping. Shopping is commonly seen as a way of unwinding after a hard day’s work, or (especially in the case of housewives), escaping from the monotonous routine of everyday life (cooking, cleaning, and looking after the kids). Then there is festival shopping, which usually involves the entire family shopping for decorations and gifts for such occasions as Christmas, Easter, and Thanksgiving (personally, I have several fond memories of this).

Secondly, Traditional shoppers are brought face-to-face with an item that they can touch, feel and examine at close proximity – this goes a long way towards making up their mind to buy it. Thirdly, Traditional shoppers are able to talk with the salespersons or merchants of the store or mall upfront, and freely seek clarification or additional information about products that interest them. Fourthly, Traditional shoppers are able to bargain and obtain a better price for their purchases.

Although people in the United States do not usually engage in energetic bargaining, there are people of several other international cultures (such as Italians, Greeks, and Indians), to whom bargaining forms the essence of the shopping experience, and without which they would end up with the uncomfortable feeling of being cheated. Fifthly, Traditional shoppers are able to judge the merchant’s reputation (and by association, the products being sold in that store) by interacting with other customers. Sixthly, Traditional shoppers are able to take home their purchases immediately, or at the most have them delivered to their homes on the same or the next day.

They, therefore, save time as do not have to wait for days or weeks to receive their purchases as is the usual case in ‘Online’ shopping (there is also the distinct possibility of some items not being ultimately delivered due to some reason such as shortages caused due to improper inventory management). Lastly, almost everyone is well aware that today’s world is blemished by an increasing number of cybercrimes.

These have grown at an alarming rate with increasingly ingenious methods being adopted by computer-savvy criminals. A very large number of innocent people have been, and are being fleeced of their hard-earned money over the Internet – their only crime being that they had to give their personal and bank details while shopping online. On the other hand, Traditional shoppers do not need to give their names, address, and (most importantly) bank account information which are all ‘must-do’s in the case of ‘Online’ shopping.

In the second group of differences, ‘Online’ shopping holds the ‘absolute’ superiority. The first difference involves selection. ‘Online shoppers can browse through a wide selection of products from different retailers and place a single order involving products from different retailers, rather than otherwise embark on the tedious exercise of visiting several stores or malls physically to pick up a few items here and a few items there.

Secondly, ‘Online’ shoppers are benefited by a significant reduction in prices as ‘Online’ sellers have vastly reduced overheads to contend with (especially store/mall rent/maintenance and salaries/perks for salespersons) and are able to comfortably pass on a sizeable part of this benefit to customers in the form of reduced prices for the products sold. Lastly, ‘Online’ shoppers have the luxury of doing their shopping at leisure from the comfort of their home, without having to drive to far-away shopping destinations and being traumatized by rash drivers and difficult car parking situations.

In the third group of differences, both types of shopping score nearly equal points. The first difference involves the time element. In Traditional shopping, customers save time as don’t have to wait for days or weeks to receive their purchases. ‘Online’ shoppers choose the time and place to shop, thus saving valuable time and problems associated with traveling to and from the store.

Secondly, while admitting that the ‘sight and touch’ factor is important, ‘Online’ shoppers find it is irrelevant in the case of items like computers, consumer electronic items, cosmetics, perfumes, and jewelry, where ‘Online’ specifications are clear-cut, very detailed and imminently satisfactory. Lastly, while Traditional shoppers can get clarification and further information about a product from the salesperson or merchant, ‘Online’ shoppers have access to clarifying the information in the form of Frequently Asked Questions (FAQ) and ‘Online’ customer service for the products they intend to purchase.

From a fair and impartial judgment of both cases, it is my contention that Traditional shopping is definitely better than ‘Online’ shopping simply because the comparative number and weight of its advantages vis-à-vis ‘Online shopping is much more significant as compared to ‘Online’ shopping own unique advantages. As a result, while agreeing that ‘Online’ shopping continues to grow in the United States, it will not overtake Traditional shopping mainly because of the two greatest ‘arrows in the quiver’ of the latter – Firstly, it involves the formidably unique ‘sight and touches’ advantage that Traditional shoppers enjoy.

And secondly, it gives people an opportunity to mingle with others, interact with acquaintances, friends, and relatives and spend ‘quality time with them – in our increasingly busy and modern world of today comprising people increasingly cocooned in their own lives and problems, this pleasurable human interaction afforded by Traditional shopping is literally priceless.

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Online shopping is increasing dramatically. How could this trend affect our environment and the kinds of jobs required?

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Ielts essay # 1178 - buying things on the internet is becoming more and more popular, ielts writing task 2/ ielts essay:, buying things on the internet, such as books, air tickets and groceries, is becoming more and more popular., do the advantages of shopping in this way outweigh the disadvantages.

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Essay on Online Shopping 1000+ Words

Convenience at Your Fingertips

A Vast Selection of Products

Competitive Prices and Discounts

Access to Customer Reviews

Convenient Payment Options

Doorstep Delivery

Avoiding Impulse Buying

Accessibility for All

Impact on Traditional Retail

Environmental Benefits

Conclusion of Essay on Online Shopping

The Rise of Online Shopping During The Pandemic: Benefits and Drawbacks

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