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Online Shopping Is Amazing. Or Is It?

So many shower curtains! But with the endless choice comes the risk of being fooled.

By Shira Ovide

This article is part of the On Tech newsletter. You can sign up here to receive it weekdays.

In our pandemic-altered 2020, it’s felt essential for many of us to be able to buy almost anything from home. One thousand varieties of shower curtains at our fingertips!

But being a truly informed online shopper now requires us to have an advanced degree in internet scams and the business of how products are marketed, sold and transported around the world.

This is a pattern with online news, entertainment, merchandise and more. Seemingly endless choice is amazing, but it has also introduced more confusion and the risk of being fooled.

I still think the benefits outweigh the drawbacks, but I’m also tired from thinking so hard about buying a pressure cooker or whether that photo from a political protest is real or forged.

My exhaustion reached a peak in the last few weeks. I wrote last month about bogus reviews on Amazon , and now I find myself eyeballing every online review for clues that it was bought off. I’ve always been skeptical, but now I don’t trust anything.

Then this weekend, I listened to this podcast about the Chinese mystery seeds. Remember all those news articles months ago about Americans who received plant seeds they didn’t order that arrived from China or other foreign countries?

It turns out that it was probably not a nefarious plot but rather the result of a surge in online ordering, paranoia about China and a common internet scam known as “brushing.”

Brushing essentially involves a seller fabricating online orders to make a product appear more popular, and then trying to avoid detection by shipping a cheap and low-weight product, such as plant seeds, to a real person. Here is a more detailed explanation .

Not long ago I also had to explain to a family member why an item he bought on Amazon arrived on his doorstep in a Walmart shipping box. Short answer: The merchant on Amazon probably took the order, bought the same item for less on Walmart’s website, had it shipped directly to my relative, and pocketed the price difference as profit. This is another common e-commerce moneymaking tactic in the sea of complicated ways to game the system.

Online shopping is a massive industry, complete with consulting companies that advise on fake reviews , software sold for people to spot and take advantage of price differences and towns filled with warehouses to repackage online orders. This is how shopping works now.

You can, of course, just click buy and be blissfully unaware of any of this. That’s fine! I know I’m that annoying person who screams “THAT’S A TRICK” when you’re just trying to order dish soap.

But also know that there’s a risk we might be persuaded by bogus online reviews into buying a bad product, or we might believe we’re buying something from Amazon and instead purchase a dangerous toy from a no-name seller . Or maybe we freak out about seeds arriving at home out of seemingly nowhere.

The risk of going astray isn’t confined to shopping. Behind the Facebook post at the top of my feed , the series that Netflix recommends and the headphones that appear in Amazon’s one-click ordering are often elaborate, financially motivated games to influence what we do .

This system of internet persuasion is not inherently bad, but it is helpful to understand how it works. It’s just that doing so is utterly exhausting.

Remember: Elected officials make laws

It is the job of our elected officials to tell companies what they should or shouldn’t do.

We know that banks help draft financial regulations and automakers advise on car safety rules, but somewhere in there lawmakers must make laws.

Remember that. My colleague David McCabe wrote that Google, Facebook, Twitter and some other companies suddenly seem open to tweaking a bedrock law of the internet that limits companies’ legal exposure for the material that people post on their sites.

This rule, Section 230 of the Communications Decency Act, made possible YouTube, Amazon’s sea of merchants and the comments sections of The New York Times, but both Republicans and Democrats say the law must change — although they’re divided on why and how .

David wrote that the new posture of internet companies “could change the dynamics of an increasingly heated debate over how to handle hate speech, extremist content and child pornography online.”

But again, lawmakers must decide on new rules. Changing Section 230 requires elected officials to thoughtfully balance freedom of online expression with our safety. And here I get discouraged.

Reading David’s article I had a flashback to 2018, when Mark Zuckerberg — in response to Facebook’s gazillionth scandal — said that government regulation might be needed to disclose who is behind paid online political messages, similar to the rules for TV advertising. This was after Facebook for years sought to be excluded from the political ad disclosure rules that apply to conventional media.

Members of Congress had pending bills to mandate more transparency for online ads. And then … nothing. The rules didn’t pass, at least not yet. (To be fair, online companies fought against some of the proposed internet political ad restrictions.)

Facebook on its own started an online hub that discloses who pays for ads about political and hot-button social issues. Facebook’s ad transparency efforts are seriously flawed , but they’re still more helpful than the nothing from America’s elected officials.

So yes, it’s notable when major internet companies say they’re open to revised regulation. But the next step — government rule makers deciding on thoughtful rules and actually making them — is the hard part.

(Meanwhile in Europe, in an effort to regulate the tech industry there, lawmakers wrote laws .)

Before we go …

The U.S. government hack was bigger than we thought: Software used by many companies and government agencies to monitor their computer networks was found to have been compromised by Russian hackers , my colleagues reported. That appeared to be the origin of a large and sophisticated cyberattack that struck parts of the Pentagon, the Department of Homeland Security and other government agencies.

Dying of “overwork”: More than a dozen package-delivery couriers have died in South Korea this year, some after complaining of unbearable work loads, my colleague Choe Sang-Hun wrote. The revelations have made South Koreans reflect on worker protections in the country and the expectations for online orders to arrive with “bullet speed.”

Can technology help people remember us? A Wall Street Journal video documentary discusses technologies that can preserve people’s voices, photos and memories for our loved ones after we die. I always thought technologies like chatbots of dead people were creepy, but this video made me reconsider.

Hugs to this

I love it when pets attack whatever is happening on a TV screen. Here is a cat who is really into a “Star Wars” scene . Pets are so weird.

We want to hear from you. Tell us what you think of this newsletter and what else you’d like us to explore. You can reach us at [email protected].

If you don’t already get this newsletter in your inbox, please sign up here .

Shira Ovide writes the On Tech newsletter, a guide to how technology is reshaping our lives and world. More about Shira Ovide

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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The Pros and Cons of Online Shopping

6 Benefits and Drawbacks To Keep in Mind When You Shop Online

Pros of Online Shopping

Cons of online shopping, how to make the most of online shopping, money-saving tips for online shopping, frequently asked questions (faqs).

The Balance / Jiaqi Zhou

Online shopping is more popular today than ever before. A report from the U.S. Census Bureau found that in the first quarter of 2022, an estimated $250 billion was spent in retail e-commerce sales. In the second quarter of 2011, for comparison, retail e-commerce sales were $47.5 billion.

Due in part to new and growing technology, online shopping has become incredibly easy and convenient. It also offers a greater selection than one storefront, opening the doors to products and services that may not be available at a nearby brick-and-mortar store .

While online shopping comes with a number of benefits, there are drawbacks to know about, too. Let's dive deeper into the pros and cons of shopping online.

Key Takeaways

Online shopping is convenient and offers a variety of products you may not be able to find at your local stores.
It's easier to comparison shop online, where you can access prices, reviews, and product details with a click.
When you shop online, you need to wait for your product to be delivered to you, and you might spend more than you would if you went to a brick-and-mortar store.
There's also a risk of fraud when you shop online, which you can combat by choosing trusted stores and paying with a card that offers fraud protection.

Convenience

Greater selection

Easy access to information

Can be more expensive

Increases risk of fraud

Leads to longer wait times

Using your computer or another digital device for your shopping needs can be convenient, offer more options, and provide insight you might not find in person at a store.

The greatest benefit of online shopping is its convenience. Through the digital space, you can buy anything you want from the comfort of your own home. Since online stores are open 24/7 and accessible from anywhere with internet access, it's easy to fit online shopping into your life no matter how busy you are. You don't have to plan your purchases based on when a brick-and-mortar store is open and available to serve you.

Greater Selection

Because products online live within the digital space, online retailers are not restricted to shelves and often have more inventory on hand with a wider selection of products. Also, online shopping gives you the chance to buy anything from any retailer, no matter where you're located. If you're in the market for a new lamp, for example, you'll have more options available to you than you would if you only shopped at stores in your local area.

Easy Access to Information

When shopping online, you will often find more details about a business's products than you would get in physical stores. Instead of speaking to one or two sales associates in person, you can peruse product descriptions, recommendations of similar products, and reviews from other shoppers online that may help you make a more informed purchasing decision.

Online retailers also tend to have membership options, typically via email or newsletters, that give shoppers early access to sales, seasonal releases , and other events. This way, you can be one of the first to know of offerings from your favorite brands.

Shopping for items online can also have its pitfalls, including hidden price mark-ups, an increased risk of fraud, and the inability to use or wear the item you purchased right away.

Can Be More Expensive

Online purchases can cost you more for several reasons. Even though many major online retailers offer free shipping, they generally require you to meet a minimum to qualify for it. In addition, online retailers may use several strategies to encourage you to buy more items or more expensive items than if you were shopping in person.

Depending on the state you live in, you may be required to pay an internet sales tax , too. In Texas, for example, you may have to pay a tax on out-of-state purchases delivered into Texas or purchases made from online-only sellers.

Many online retailers take part in digital tactics to convince shoppers to make more purchases, often considered impulse buys . Some include using "limited time" sale pop-ups that reset every time users reload the page, fake customer testimonials, or messages that promote higher-cost items.

Increases Risk of Fraud

Unfortunately, online shopping scams do exist. According to the Federal Trade Commission (FTC), online shopping was the fourth most common fraud category for consumers as of February 2022. Some scammers pretend to be legitimate online sellers with fake websites or create fake ads on real sites.

Always pay by credit card rather than a debit card, as you can easily report fraud to your credit card company. Also, it is best to avoid online sellers that only accept payment via money transfers, gift cards, or cryptocurrency. Scammers may encourage you to pay through these methods so they can access your money faster.

Leads to Longer Wait Times

When you shop at a brick-and-mortar store, you can walk away with the product you bought and use or wear it right away. Online shopping forces you to wait days, weeks, or even longer for your order to arrive. If you're in a time crunch and need a product right away, such as a gift, going to an in-person shop may be a better option for you.

These tips can allow you to enhance your online shopping experience.

Know Which Products To Buy Online

Some items are better to buy online than others because you can find countless consumer reviews, discounts, or other deals pertaining to them. For items you regularly use (such as a laptop, phone charger, luggage, or textbook), the internet may be the best place to compare offers. For things you require to have long-lasting value (like a car) or must get right away (such as groceries), shopping in person may be best.

Read Reviews

Before you check out, read reviews on the retailer's website as well as third-party sites like Google and Facebook. This can help you find out if the retailer is legitimate and whether there may be any potential issues with the product you're about to invest in. Reviews are beneficial for small businesses , too. Ninety-eight percent of consumers read online reviews of local businesses, according to marketing consultancy BrightLocal's 2022 Local Consumer Review Survey.

Some companies have more nuanced review options than others. Clothing rental service Nuuly, for example, lets its customers add photos of themselves wearing products with written reviews, enabling future customers to make empowered, smart purchasing decisions.

Examine Product Details

If you’re interested in a product, read its description. Make sure you know what it’s made out of, whether it comes with a warranty, what sizes are available, and so on. By doing so, you can avoid unwanted surprises that cost you time, money, and headaches when the product arrives.

There are many ways to save some money while making online purchases. Consider these tips to improve your online shopping experience.

Comparison Shop

If you have a specific product in mind, it's in your best interest to comparison shop, similar to how you would when looking for life insurance. Look at various online stores that offer what you want. Then, compare prices so you can find the best deal.

As you comparison shop, read product descriptions very closely. The FTC recommends looking out for words like "refurbished" or "vintage," as this could mean a product will arrive at your door in less-than-perfect condition.

Follow Online Retailers on Social Media

Online retailers often promote their sales and discounted items on Facebook, Instagram, and other social media channels. If you follow some of your favorite companies on social media, you may be one of the first to see and purchase the latest offers.

Use Money-Saving Apps or Plug-ins

There is no shortage of apps or plug-ins that can allow you to save money online without the hassle. Some examples are Honey, Swagbucks, Capital One Shopping, and Rakuten. You can also look for coupon codes online on sites like RetailMeNot.com and Coupons.com.

How do you get your money back from an online purchase?

This process varies by retailer. Some may automatically refund your money when you report a problem with your purchase; others may require you to return the product first. You may not be able to get your money back at all, especially if it's after the retailer's return window. If you're buying something that may not work for you, like clothing, check the retailer's refund policy before you buy.

How has the internet changed shopping?

The internet has completely changed the shopping experience. People have access to products from around the globe. Payments are instant, and recommendations are tailored to your shopping and browsing habits. Brick-and-mortar retailers have had to respond by launching websites and improving their in-person customer experience.

U.S. Census Bureau. " Quarterly Retail E-Commerce Sales 1st Quarter 2022 ," Page 1.

U.S. Census Bureau. " Quarterly Retail E-Commerce Sales 2nd Quarter 2011 ," Page 2.

Texas Comptroller's Office. " Taxes: Online Orders - Texas Purchasers and Sellers ."

University of Michigan. " Impulse Buying: Design Practices and Consumer Needs ," Pages 6, 9, and 11.

Federal Trade Commission. " Consumer Sentinel Network ," Page 7.

BrightLocal. " Local Consumer Review Survey 2022 ."

Nuuly. " Forget Me Not Mini Dress ."

Federal Trade Commission. " Online Shopping ," See "Comparison Shopping."

A study on factors limiting online shopping behaviour of consumers

Rajagiri Management Journal

ISSN : 0972-9968

Article publication date: 4 March 2021

Issue publication date: 12 April 2021

This study aims to investigate consumer behaviour towards online shopping, which further examines various factors limiting consumers for online shopping behaviour. The purpose of the research was to find out the problems that consumers face during their shopping through online stores.

Design/methodology/approach

A quantitative research method was adopted for this research in which a survey was conducted among the users of online shopping sites.

As per the results total six factors came out from the study that restrains consumers to buy from online sites – fear of bank transaction and faith, traditional shopping more convenient than online shopping, reputation and services provided, experience, insecurity and insufficient product information and lack of trust.

Research limitations/implications

This study is beneficial for e-tailers involved in e-commerce activities that may be customer-to-customer or customer-to-the business. Managerial implications are suggested for improving marketing strategies for generating consumer trust in online shopping.

Originality/value

In contrast to previous research, this study aims to focus on identifying those factors that restrict consumers from online shopping.

Online shopping

Daroch, B. , Nagrath, G. and Gupta, A. (2021), "A study on factors limiting online shopping behaviour of consumers", Rajagiri Management Journal , Vol. 15 No. 1, pp. 39-52. https://doi.org/10.1108/RAMJ-07-2020-0038

Emerald Publishing Limited

Published in Rajagiri Management Journal . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

Today, people are living in the digital environment. Earlier, internet was used as the source for information sharing, but now life is somewhat impossible without it. Everything is linked with the World Wide Web, whether it is business, social interaction or shopping. Moreover, the changed lifestyle of individuals has changed their way of doing things from traditional to the digital way in which shopping is also being shifted to online shopping.

Online shopping is the process of purchasing goods directly from a seller without any intermediary, or it can be referred to as the activity of buying and selling goods over the internet. Online shopping deals provide the customer with a variety of products and services, wherein customers can compare them with deals of other intermediaries also and choose one of the best deals for them ( Sivanesan, 2017 ).

As per Statista-The Statistics Portal, the digital population worldwide as of April 2020 is almost 4.57 billion people who are active internet users, and 3.81 billion are social media users. In terms of internet usage, China, India and the USA are ahead of all other countries ( Clement, 2020 ).

The number of consumers buying online and the amount of time people spend online has risen ( Monsuwe et al. , 2004 ). It has become more popular among customers to buy online, as it is handier and time-saving ( Huseynov and Yildirim, 2016 ; Mittal, 2013 ). Convenience, fun and quickness are the prominent factors that have increased the consumer’s interest in online shopping ( Lennon et al. , 2008 ). Moreover, busy lifestyles and long working hours also make online shopping a convenient and time-saving solution over traditional shopping. Consumers have the comfort of shopping from home, reduced traveling time and cost and easy payment ( Akroush and Al-Debei, 2015 ). Furthermore, price comparisons can be easily done while shopping through online mode ( Aziz and Wahid, 2018 ; Martin et al. , 2015 ). According to another study, the main influencing factors for online shopping are availability, low prices, promotions, comparisons, customer service, user friendly, time and variety to choose from ( Jadhav and Khanna, 2016 ). Moreover, website design and features also encourage shoppers to shop on a particular website that excite them to make the purchase.

Online retailers have started giving plenty of offers that have increased the online traffic to much extent. Regularly online giants like Amazon, Flipkart, AliExpress, etc. are advertising huge discounts and offers that are luring a large number of customers to shop from their websites. Companies like Nykaa, MakeMyTrip, Snapdeal, Jabong, etc. are offering attractive promotional deals that are enticing the customers.

Despite so many advantages, some customers may feel online shopping risky and not trustworthy. The research proposed that there is a strong relationship between trust and loyalty, and most often, customers trust brands far more than a retailer selling that brand ( Bilgihan, 2016 ; Chaturvedi et al. , 2016 ). In the case of online shopping, there is no face-to-face interaction between seller and buyer, which makes it non-socialize, and the buyer is sometimes unable to develop the trust ( George et al. , 2015 ). Trust in the e-commerce retailer is crucial to convert potential customer to actual customer. However, the internet provides unlimited products and services, but along with those unlimited services, there is perceived risk in digital shopping such as mobile application shopping, catalogue or mail order ( Tsiakis, 2012 ; Forsythe et al. , 2006 ; Aziz and Wahid, 2018 ).

Literature review

A marketer has to look for different approaches to sell their products and in the current scenario, e-commerce has become the popular way of selling the goods. Whether it is durable or non-durable, everything is available from A to Z on websites. Some websites are specifically designed for specific product categories only, and some are selling everything.

The prominent factors like detailed information, comfort and relaxed shopping, less time consumption and easy price comparison influence consumers towards online shopping ( Agift et al. , 2014 ). Furthermore, factors like variety, quick service and discounted prices, feedback from previous customers make customers prefer online shopping over traditional shopping ( Jayasubramanian et al. , 2015 ). It is more preferred by youth, as during festival and holiday season online retailers give ample offers and discounts, which increases the online traffic to a great extent ( Karthikeyan, 2016 ). Moreover, services like free shipping, cash on delivery, exchange and returns are also luring customers towards online purchases.

More and more people are preferring online shopping over traditional shopping because of their ease and comfort. A customer may have both positive and negative experiences while using an online medium for their purchase. Some of the past studies have shown that although there are so many benefits still some customers do not prefer online as their basic medium of shopping.

While making online purchase, customers cannot see, touch, feel, smell or try the products that they want to purchase ( Katawetawaraks and Wang, 2011 ; Al-Debei et al. , 2015 ), due to which product is difficult to examine, and it becomes hard for customers to make purchase decision. In addition, some products are required to be tried like apparels and shoes, but in case of online shopping, it is not possible to examine and feel the goods and assess its quality before making a purchase due to which customers are hesitant to buy ( Katawetawaraks and Wang, 2011 ; Comegys et al. , 2009 ). Alam and Elaasi (2016) in their study found product quality is the main factor, which worries consumer to make online purchase. Moreover, some customers have reported fake products and imitated items in their delivered orders ( Jun and Jaafar, 2011 ). A low quality of merchandise never generates consumer trust on online vendor. A consumer’s lack of trust on the online vendor is the most common reason to avoid e-commerce transactions ( Lee and Turban, 2001 ). Fear of online theft and non-reliability is another reason to escape from online shopping ( Karthikeyan, 2016 ). Likewise, there is a risk of incorrect information on the website, which may lead to a wrong purchase, or in some cases, the information is incomplete for the customer to make a purchase decision ( Liu and Guo, 2008 ). Moreover, in some cases, the return and exchange policies are also not clear on the website. According to Wei et al. (2010) , the reliability and credibility of e-retailer have direct impact on consumer decision with regards to online shopping.

Limbu et al. (2011) revealed that when it comes to online retailers, some websites provide very little information about their companies and sellers, due to which consumers feel insecure to purchase from these sites. According to other research, consumers are hesitant, due to scams and feel anxious to share their personal information with online vendors ( Miyazaki and Fernandez, 2001 ; Limbu et al. , 2011 ). Online buyers expect websites to provide secure payment and maintain privacy. Consumers avoid online purchases because of the various risks involved with it and do not find internet shopping secured ( Cheung and Lee, 2003 ; George et al. , 2015 ; Banerjee et al. , 2010 ). Consumers perceive the internet as an unsecured channel to share their personal information like emails, phone and mailing address, debit card or credit card numbers, etc. because of the possibility of misuse of that information by other vendors or any other person ( Lim and Yazdanifard, 2014 ; Kumar, 2016 ; Alam and Yasin, 2010 ; Nazir et al. , 2012 ). Some sites make it vital and important to share personal details of shoppers before shopping, due to which people abandon their shopping carts (Yazdanifard and Godwin, 2011). About 75% of online shoppers leave their shopping carts before they make their final decision to purchase or sometimes just before making the payments ( Cho et al. , 2006 ; Gong et al. , 2013 ).

Moreover, some of the customers who have used online shopping confronted with issues like damaged products and fake deliveries, delivery problems or products not received ( Karthikeyan, 2016 ; Kuriachan, 2014 ). Sometimes consumers face problems while making the return or exchange the product that they have purchased from online vendors ( Liang and Lai, 2002 ), as some sites gave an option of picking from where it was delivered, but some online retailers do not give such services to consumer and consumer him/herself has to courier the product for return or exchange, which becomes inopportune. Furthermore, shoppers had also faced issues with unnecessary delays ( Muthumani et al. , 2017 ). Sometimes, slow websites, improper navigations or fear of viruses may drop the customer’s willingness to purchase from online stores ( Katawetawaraks and Wang, 2011 ). As per an empirical study done by Liang and Lai (2002) , design of the e-store or website navigation has an impact on the purchase decision of the consumer. An online shopping experience that a consumer may have and consumer skills that consumers may use while purchasing such as website knowledge, product knowledge or functioning of online shopping influences consumer behaviour ( Laudon and Traver, 2009 ).

From the various findings and viewpoints of the previous researchers, the present study identifies the complications online shoppers face during online transactions, as shown in Figure 1 . Consumers do not have faith, and there is lack of confidence on online retailers due to incomplete information on website related to product and service, which they wish to purchase. Buyers are hesitant due to fear of online theft of their personal and financial information, which makes them feel there will be insecure transaction and uncertain errors may occur while making online payment. Some shoppers are reluctant due to the little internet knowledge. Furthermore, as per the study done by Nikhashem et al. (2011), consumers unwilling to use internet for their shopping prefer traditional mode of shopping, as it gives roaming experience and involves outgoing activity.

Several studies have been conducted earlier that identify the factors influencing consumer towards online shopping but few have concluded the factors that restricts the consumers from online shopping. The current study is concerned with the factors that may lead to hesitation by the customer to purchase from e-retailers. This knowledge will be useful for online retailers to develop customer driven strategies and to add more value product and services and further will change their ways of promoting and advertising the goods and enhance services for customers.

Research methodology

This study aimed to find out the problems that are generally faced by a customer during online purchase and the relevant factors due to which customers do not prefer online shopping. Descriptive research design has been used for the study. Descriptive research studies are those that are concerned with describing the characteristics of a particular individual or group. This study targets the population drawn from customers who have purchased from online stores. Most of the respondents participated were post graduate students and and educators. The total population size was indefinite and the sample size used for the study was 158. A total of 170 questionnaires were distributed among various online users, out of which 12 questionnaires were received with incomplete responses and were excluded from the analysis. The respondents were selected based on the convenient sampling technique. The primary data were collected from Surveys with the help of self-administered questionnaires. The close-ended questionnaire was used for data collection so as to reduce the non-response rate and errors. The questionnaire consists of two different sections, in which the first section consists of the introductory questions that gives the details of socio-economic profile of the consumers as well as their behaviour towards usage of internet, time spent on the Web, shopping sites preferred while making the purchase, and the second section consist of the questions related to the research question. To investigate the factors restraining consumer purchase, five-point Likert scale with response ranges from “Strongly agree” to “Strongly disagree”, with following equivalencies, “strongly disagree” = 1, “disagree” = 2, “neutral” = 3, “agree” = 4 and “strongly agree” = 5 was used in the questionnaire with total of 28 items. After collecting the data, it was manually recorded on the Excel sheet. For analysis socio-economic profile descriptive statistics was used and factors analysis was performed on SPSS for factor reduction.

Data analysis and interpretation

The primary data collected from the questionnaires was completely quantified and analysed by using Statistical Package for Social Science (SPSS) version 20. This statistical program enables accuracy and makes it relatively easy to interpret data. A descriptive and inferential analysis was performed. Table 1 represents the results of socio-economic status of the respondents along with some introductory questions related to usage of internet, shopping sites used by the respondents, amount of money spent by the respondents and products mostly purchased through online shopping sites.

According to the results, most (68.4%) of the respondents were belonging to the age between 21 and 30 years followed by respondents who were below the age of 20 years (16.4%) and the elderly people above 50 were very few (2.6%) only. Most of the respondents who participated in the study were females (65.8)% who shop online as compared to males (34.2%). The respondents who participated in the study were students (71.5%), and some of them were private as well as government employees. As per the results, most (50.5%) of the people having income below INR15,000 per month who spend on e-commerce websites. The results also showed that most of the respondents (30.9%) spent less than 5 h per week on internet, but up to (30.3%) spend 6–10 h per week on internet either on online shopping or social media. Majority (97.5%) of them have shopped through online websites and had both positive and negative experiences, whereas 38% of the people shopped 2–5 times and 36.7% shopped more than ten times. Very few people (12%), shopped only once. Most of the respondents spent between INR1,000–INR5,000 for online shopping, and few have spent more than INR5,000 also.

As per the results, the most visited online shopping sites was amazon.com (71.5%), followed by flipkart.com (53.2%). Few respondents have also visited other e-commerce sites like eBay, makemytrip.com and myntra.com. Most (46.2%) of the time people purchase apparels followed by electronics and daily need items from the ecommerce platform. Some of the respondents have purchased books as well as cosmetics, and some were preferring online sites for travel tickets, movie tickets, hotel bookings and payments also.

Factor analysis

To explore the factors that restrict consumers from using e-commerce websites factor analysis was done, as shown in Table 3 . A total of 28 items were used to find out the factors that may restrain consumers to buy from online shopping sites, and the results were six factors. The Kaiser–Meyer–Olkin (KMO) measure, as shown in Table 2 , in this study was 0.862 (>0.60), which states that values are adequate, and factor analysis can be proceeded. The Bartlett’s test of sphericity is related to the significance of the study and the significant value is 0.000 (<0.05) as shown in Table 2 .

The analysis produced six factors with eigenvalue more than 1, and factor loadings that exceeded 0.30. Moreover, reliability test of the scale was performed through Cronbach’s α test. The range of Cronbach’s α test came out to be between 0.747 and 0.825, as shown in Table 3 , which means ( α > 0.7) the high level of internal consistency of the items used in survey ( Table 4 ).

Factor 1 – The results revealed that the “fear of bank transaction and faith” was the most significant factor, with 29.431% of the total variance and higher eigenvalue, i.e. 8.241. The six statements loaded on Factor 1 highly correlate with each other. The analysis shows that some people do not prefer online shopping because they are scared to pay online through credit or debit cards, and they do not have faith over online vendors.

Factor 2 – “Traditional shopping is convenient than online shopping” has emerged as a second factor which explicates 9.958% of total variance. It has five statements and clearly specifies that most of the people prefer traditional shopping than online shopping because online shopping is complex and time-consuming.

Factor 3 – Third crucial factor emerged in the factor analysis was “reputation and service provided”. It was found that 7.013% of variations described for the factor. Five statements have been found on this factor, all of which were interlinked. It clearly depicts that people only buy from reputed online stores after comparing prices and who provide guarantee or warrantee on goods.

Factor 4 – “Experience” was another vital factor, with 4.640% of the total variance. It has three statements that clearly specifies that people do not go for online shopping due to lack of knowledge and their past experience was not good and some online stores do not provide EMI facilities.

Factor 5 – Fifth important factor arisen in the factor analysis was “Insecurity and Insufficient Product Information” with 4.251% of the total variance, and it has laden five statements, which were closely intertwined. This factor explored that online shopping is not secure as traditional shopping. The information of products provided on online stores is not sufficient to make the buying decision.

Factor 6 – “Lack of trust” occurred as the last factor of the study, which clarifies 3.920% of the total variance. It has four statements that clearly state that some people hesitate to give their personal information, as they believe online shopping is risky than traditional shopping. Without touching the product, people hesitate to shop from online stores.

The study aimed to determine the problems faced by consumers during online purchase. The result showed that most of the respondents have both positive and negative experience while shopping online. There were many problems or issues that consumer’s face while using e-commerce platform. Total six factors came out from the study that limits consumers to buy from online sites like fear of bank transaction and no faith, traditional shopping more convenient than online shopping, reputation and services provided, experience, insecurity and insufficient product information and lack of trust.

The research might be useful for the e-tailers to plan out future strategies so as to serve customer as per their needs and generate customer loyalty. As per the investigation done by Casalo et al. (2008) , there is strong relationship between reputation and satisfaction, which further is linked to customer loyalty. If the online retailer has built his brand name, or image of the company, the customer is more likely to prefer that retailer as compared to new entrant. The online retailer that seeks less information from customers are more preferred as compared to those require complete personal information ( Lawler, 2003 ).

Online retailers can adopt various strategies to persuade those who hesitate to shop online such that retailer need to find those negative aspects to solve the problems of customers so that non-online shopper or irregular online consumer may become regular customer. An online vendor has to pay attention to product quality, variety, design and brands they are offering. Firstly, the retailer must enhance product quality so as to generate consumer trust. For this, they can provide complete seller information and history of the seller, which will preferably enhance consumer trust towards that seller.

Furthermore, they can adopt marketing strategies such as user-friendly and secure website, which can enhance customers’ shopping experience and easy product search and proper navigation system on website. Moreover, complete product and service information such as feature and usage information, description and dimensions of items can help consumer decide which product to purchase. The experience can be enhanced by adding more pictures, product videos and three-dimensional (3D), images which will further help consumer in the decision-making process. Moreover, user-friendly payment systems like cash on deliveries, return and exchange facilities as per customer needs, fast and speedy deliveries, etc. ( Chaturvedi et al. , 2016 ; Muthumani et al. , 2017 ) will also enhance the probability of purchase from e-commerce platform. Customers are concerned about not sharing their financial details on any website ( Roman, 2007 ; Limbu et al. , 2011 ). Online retailers can ensure payment security by offering numerous payment options such as cash on delivery, delivery after inspection, Google Pay or Paytm or other payment gateways, etc. so as to increase consumer trust towards website, and customer will not hesitate for financial transaction during shopping. Customers can trust any website depending upon its privacy policy, so retailers can provide customers with transparent security policy, privacy policy and secure transaction server so that customers will not feel anxious while making online payments ( Pan and Zinkhan, 2006 ). Moreover, customers not only purchase basic goods from the online stores but also heed augmented level of goods. Therefore, if vendors can provide quick and necessary support, answer all their queries within 24-hour service availability, customers may find it convenient to buy from those websites ( Martin et al. , 2015 ). Sellers must ensure to provide products and services that are suitable for internet. Retailers can consider risk lessening strategies such as easy return and exchange policies to influence consumers ( Bianchi and Andrews, 2012 ). Furthermore, sellers can offer after-sales services as given by traditional shoppers to attract more customers and generate unique shopping experience.

Although nowadays, most of the vendors do give plenty of offers in form of discounts, gifts and cashbacks, but most of them are as per the needs of e-retailers and not customers. Beside this, trust needs to be generated in the customer’s mind, which can be done by modifying privacy and security policies. By adopting such practices, the marketer can generate customers’ interest towards online shopping.

Conceptual framework of the study

Socioeconomic status of respondents

KMO and Bartlett’s test

Cronbach’s α

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Original Article
Published: 07 February 2022
Volume 11 , pages 82–94, ( 2023 )

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João Coelho Soares ORCID: orcid.org/0000-0002-3278-0844 1 ,
Ricardo Limongi ORCID: orcid.org/0000-0003-3231-7515 2 ,
João Henriques De Sousa Júnior ORCID: orcid.org/0000-0001-8589-8101 1 ,
Weverson Soares Santos ORCID: orcid.org/0000-0003-1358-401X 1 ,
Michele Raasch ORCID: orcid.org/0000-0002-8885-8540 1 &
Lenoir Hoeckesfeld ORCID: orcid.org/0000-0002-1339-1157 3

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Introduction

The growing number of internet users worldwide emphasizes its importance in the various aspects of society, transforming it into a relevant communication tool and a support platform for creating new businesses. Currently, 4.57 billion people are using the internet worldwide, representing an annual increase of more than 7% compared to previous years (Kemp 2020 ).

Furthermore, the potential of the online environment for companies and the insertion of organizations in this environment have become a constant practice that seeks to differentiate themselves in the market (Kietzmann et al. 2011 ). However, by defining the allocation of resources and investment in developing and adopting information technologies, organizations face risky investment in decisions that can affect their competitive position (Davis and Venkatesh 1996 ; Sun 2017 ). These decisions will certainly affect the company and its audience. So, it is salutary to understand that consumer purchasing decisions can be affected by several factors, such as, for example, in public health emergencies (Yan et al. 2020 ; Wang et al. 2020 ).

The COVID-19 pandemic affected the daily life of all (Kim 2020 ) and brought direct and indirect consequences not only in the field of public health but also in public safety, education, logistics, and economics, for example. It is perceived that, and all over the world, people have used more time in digital activity because of the restrictive measures imposed as ways of containing the exponential curve of contamination of COVID-19, especially in countries that have suffered from lockdown and decreased social interaction (Kemp 2020 ).

Although online purchases have certain risks, such as privacy issues and product delivery, their benefits eventually outperform and lead people to make this type of purchase (Chiu et al. 2014 ; Sheth 2020 ). The pandemic has accelerated the pace of growth in online sales, causing companies in and across diverse segments to invest in making digital selling more effective and accessible (Kim 2020 ). Thus, as a large portion of the population has found restrictions on activities and remained isolated or distanced within their homes, this public ended up being exposed to a more significant advertising appeal. Thus, it is crucial to understand this trend in the search for online commerce motivated by the blocking of physical stores and restrictions on human contacts and social interaction (Addo et al. 2020 ).

To better attract consumer attention in the online environment, companies must know the attitudes and behaviors of their consumers to online shopping and their background (Chiu et al. 2005 ). Latin America is an emerging market with a growth in the number of people buying online (Ventre and Kolbe 2020 ). As data from the first quarter of 2020 presented in the Kantar report ( 2020 ), in Brazil, e-commerce had already attracted more than 1.2 million new homes. It reached a frequency three times higher in 2020, indicating that the market is transitioning to e-commerce. In the second quarter of the same year, according to Kemp's study ( 2020 ), half of those surveyed mentioned buying online for longer, reaffirming the exponential growth of this consumer profile. The rise of online shopping offers new opportunities for businesses during and after COVID-19 (Kim 2020 ).

Kim ( 2020 ) pointed out recently, the pandemic was an accelerator of structural change in consumption and digital transformation in the market, to the point that companies that have not made such a transition to digital have already drastically reduced access to their customers and thus are less likely to survive the pandemic.

Despite the exponential growth in the number of infected worldwide throughout the first half, a slowdown in the rate of contagions in some places led to the relaxation of specific restrictive measures, causing people to return to leave home to resume some of their activities (WHO 2020 ). However, the return to work and exposure to the risk of COVID-19 infection may contribute to the ad's resumption of mobility (Yan et al. 2020 ). Given this risk exposure, studies such as Kim ( 2020 ), Yan et al. ( 2020 ), and Sheth ( 2020 ) indicate that the pandemic could leave lasting impacts on consumer culture, may have transformed the structure of the market for the post-pandemic period, influenced consumer purchasing decisions, and even created new real and lasting buying habits and behaviors.

In this sense, the pandemic’s impacts and reflexes on consumer behavior and market dynamics show the relevance and need for academic deepening of the theme (Kim 2020 ). It is imperative to understand the trend and impacts of the COVID-19 pandemic on consumer buying behavior (Addo et al. 2020 ) and how to expand the understanding of the effect of COVID-19 on consumers and consumer crops (Kim 2020 ). There is a need for more studies on the effect of risk perception toward epidemics on consumer behavior and decision making (Shim et al. 2021 ).

The concern of researchers in understanding the consumer behavior in the face of changes imposed by the pandemic scenario, hitherto unknown, within the time limit of one year of pandemic, can be seen. A review of research related to consumer behavior in the COVID-19 pandemic is presented by Silva et al. ( 2021 ). The authors identified a focus on research on changes in consumption habits and behaviors in the face of social isolation, focusing on the food context, with most of the studies occurring in the United States and China (Silva et al. 2021 ). Among the research identified on consumer behavior in the context of the COVID-19 pandemic, Troise et al. ( 2021 ) used the combination of TAM and TPM to understand the adoption of online food delivery behavior among Italians. Their results point to greater perceived usefulness with deliveries due to their convenience. The perceived risks of COVID-19 affect behavioral intentions negatively and showed a significant relationship with the perception of ease of use for online food delivery (Troise et al. 2021 ). The study by Kim et al. ( 2021 ) analyzes the perceived risk of contamination of North American hotel guests and uses technology (robots) to reduce this risk. Through four experiments, they identified that contrary to what occurred before COVID-19, consumers had positive attitudes toward hotels that used this technology.

These results show that there is still room for empirical research exploring the relationship between the pandemic and consumer behavior in different contexts, like in Brazilian e-commerce. Thus, the present study aims to analyze the influence of the COVID-19 pandemic on online shopping behavior through a proposed model and data collected from Brazilian online consumers.

In this context, it is salutary to highlight that this study contributed positively to the advancement of studies investigating online shopping behavior during the pandemic, identifying that the pandemic scenario influences online purchasing behavior and that one of the possible causes for the growth of online shopping is due to the higher exposure of people to the internet, enhancing their perception of usefulness and ease of purchase-related to online shopping.

Literature review

The technology acceptance model (TAM) investigates the impacts of usefulness and perceived ease of use in attitudes toward internet use, behavioral intentions, and actual use (Law et al. 2016 ). The model was designed to understand the causal chain that links external variables to their acceptance by the user and their actual use, and use proved to be among the most effective models to predict user acceptance and use behavior (Davis and Venkatesh 1996 ). However, changes in TAM have already been made since the model was created for a general explanation of the determinants of acceptance of computer technology and not for specific topics, such as behavioral intentions of online shopping (Chiu et al. 2005 ). The original TAM or a modified/extended version has already been used to analyze online purchase behavior in different contexts.

Fayad and Paper ( 2015 ) point out the need to study behavioral expectations, in addition to behavioral intentions, when predicting purchasing behavior using the TAM; the research carried out by the authors sought to support TAM's robustness in consumer research. The TAM model is one of the most used models in research that aims to identify the perceived usefulness and simplicity of use in consumption decisions (Fedorko et al. 2018 ).

In this sense, TAM can be applied in different contexts of online consumer behavior (Koufaris 2002 ; Chi 2018 ). TAM has been previously used in the literature to understand the online shopping process, such as the research by Tong ( 2010 ) and Ishfaq and Mengxing ( 2021 ). In Tong ( 2010 ), the TAM model was used to understand the online shopping behavior of consumers in the USA and China, to examine the main factors influencing the purchase decision of online shoppers in the retail sector. Recently, Ishfaq and Mengxing ( 2021 ) used the TAM model to predict users’ behavioral intention regarding the purchase of services during the COVID-19 pandemic.

Thus, the research model and hypotheses were elaborated based on the literature on the subject.

Perceived Risk of COVID-19

Consumer purchasing decisions and behaviors are complex processes affected by internal and external factors (Chu 2018 ). In TAM, the external variables are theorized to influence the behavioral intention of use indirectly and, later, its use through its influence on the usefulness and perceived ease of use (Davis and Venkatesh 1996 ). External factors act through external contextual events/factors, such as unexpected public health emergencies (Yan et al. 2020 ), such as the perceived pandemic-related risk of COVID-19.

Perceived risk can be understood as the subjective assessment of the probability of encountering a threat and the consequences and dangers of this threat (Zhang et al. 2018 ; Yan et al. 2020 ). In the present study, this dimension seeks to identify the perceived risk of COVID-19, defined through a person's subjective evaluation about the probability and severity of becoming infected by COVID-19 while making purchases in person in commercial establishments. Perceived risk can influence utilitarian value in purchase intention (Chiu et al. 2014 ). Most consumers are concerned about the situation of the COVID-19 pandemic (Nguyen et al. 2020 ); consequently, this concern affects their way of consuming (Sheth 2020 ).

The perceived risks of COVID-19 can negatively influence the behavioral intentions of consumers (Troise et al. 2021 ) and lead to changes in people's behavior and consumption patterns (Brewer and Sebby 2021 ). In a pandemic context, the perceived risk and the threat of contagion influenced consumer behavior changes, emerging a greater preference for the use of technologies to socially distance themselves from humans (Kim et al. 2021 ).

For many consumers, buying in face-to-face stores can pose a health risk, encouraging them to look for online alternatives to their purchases. Since buying in physical stores and buying online are two different activities (Chiu et al. 2005 ), the pandemic influences the transition in the consumer culture from face-to-face to online shopping (Kim 2020 ).

Previous research has indicated that perceived risk determines purchase intention (Chiu et al. 2014 ; Zhang et al. 2018 ; Yan et al. 2020 ). The study of Yan et al. ( 2020 ) analyzes the changes in intentions of buying cars before and after the outbreak of COVID-19 in China. The results revealed that the outbreak of this epidemic strongly influenced the intentions of buying cars of some consumers. In addition, they also observed that the probability of being infected by the virus during a trip motivates consumers to adopt various protective behaviors (Yan et al. 2020 ).

Nguyen et al. ( 2020 ) revealed that the COVID-19 pandemic has a positive and significant impact on consumers' intention to buy books online, i.e., consumers have adopted new online consumption habits, such as books, during the pandemic. This study also pointed out that consumers have a strong concern about the health risks associated with going to these stores in person, choosing to buy in e-commerce. Recently, the COVID-19 risk perception has been positively associated with consumers' perception of convenience and purchase intentions when ordering food online (Brewer and Sebby 2021 ).

Given what has been presented in the literature and believing that the perceived risk of making purchases in person during the pandemic favors the search for online shopping, the first three research hypotheses are as follows:

The perceived risk of being infected by COVID-19 when buying in person positively affects the perceived usefulness.

The perceived risk of being infected by COVID-19 when buying in person positively affects the perceived ease of purchase.

The perceived risk of being infected by COVID-19 when buying in person positively affects online purchase intention.

Perceived usefulness

As TAM suggests, perceived usefulness determines the intention to adopt a specific technology (Fortes and Rita 2016 ). The perceived usefulness for online shopping can be defined as the subjective probability of the potential consumer that the internet will provide their purchases more efficiently than face-to-face purchases (Koufaris 2002 ; Chiu et al. 2014 ; Law et al. 2016 ). In the present study, perceived use is understood as the individual's perception of the degree to which internet use will improve their purchasing performance (e.g., convenience, agility, timesaving).

The literature suggests that perceived usefulness is positively related to purchasing intention (Law et al. 2016 ). E-commerce is seen as more economical and convenient than face-to-face purchases (Ventre and Kolbe 2020 ). When the consumer believes that the use and specific site is helpful to carry out their purchases, they will probably have a better attitude toward the site and will return to use it (Koufaris 2002 ; Moslehpour et al. 2018 ). E-commerce generally offers a wide variety of products, increasing the likelihood of consumers finding the desired product than offline purchases, providing a more effective shopping experience (Chiu et al. 2014 ). When users understand the internet as a helpful tool, this increases its frequency, duration, and use, changing consumers’ purchasing platform (Isaac et al. 2017 ).

The perceived usefulness has a positive effect on internet use (Isaac et al. 2017 ), and previous studies have already observed significant and positive relationships between perceived usefulness and online purchase intention (Chiu et al. 2005 ; Law et al. 2016 ; Moslehpour et al. 2018 ; Sukno and Riquelme 2019 ) and attitudes toward e-shopping (Çelik and Yilmaz 2011 ). Moslehpour et al. ( 2018 ) identified that Taiwanese online consumers who perceive technology as a valuable tool for shopping online tend to make more online purchases. Sukno and Riquelme ( 2019 ) found similar results in C2C e-commerce in Chile. Ventre and Kolbe ( 2020 ) identify the perceived usefulness of online reviews as the essential factor in online shopping intention for Mexican consumers aged 18 to 50 years old who use e-commerce. In this sense, based on the existing literature and research objectives, the hypothesis four of the study is as follows:

Perceived usefulness positively affects online purchase intention.

Perceived ease of purchase

In TAM, the dimension that corresponds to the degree to which a person believes that using a specific system would be effort-free is called "perceived ease of use" (Davis and Venkatesh 1996 ). The literature suggests that ease of use positively influences the attitude and intention to use a given technology (Law et al. 2016 ). The literature also points out that the perceived ease of use positively affects the perceived usefulness, stating that the more accessible the user perceives a specific technology (e.g., internet), the more valuable, for the user, the technology will be perceived (Isaac et al. 2017 ).

However, as in other studies (Chiu et al. 2005 ; Law et al. 2016 ), this research changes the focus of the dimension because this is something more general to technology, directing its scope and denomination of what format the ease of purchase is perceived. Thus, the perceived ease of purchase is conceptualized as the individual’s expectation that online purchase will require less effort than a face-to-face purchase (Koufaris 2002 ; Law et al. 2016 ). When focusing on consumer efforts about online shopping issues, the dimension can be seen as an evolution of the old construct (perceived ease of use) because the ease of use of the internet has become increasingly common among its users. In contrast, the ease of online shopping is not yet familiar to everyone (Chiu et al. 2005 ).

According to Çelik and Yilmaz ( 2011 ), the internet and e-commerce rapidly spread new and effective ways to shop online, such as smartphone apps (Wang et al. 2020 ). The user perceives the more ease of use to some technology, the greater the perception of the usefulness of this technology and predisposes to use it more often (Sukno and Riquelme 2019 ). The perceived ease of use is also relevant to the online shopping experience, strongly associated with the purchase intention (Moslehpour et al. 2018 ). In a study related to the purchase intention of a particular brand of coffee, it was possible to observe that the ease of App (software application) use positively affects the purchase intention in coffee services (Shim et al. 2021 ).

Previous research also suggested a positive relationship between perceived ease of use and perceived usefulness (e.g., Çelik and Yilmaz 2011 ; Kim 2012 ; Manis and Choi 2019 ; Sukno and Riquelme 2019 ). However, the empirical results may differ, suggesting that the effect of perceived ease of use on perceived usefulness and purchase intention may be different according to the context and technology researched (Isaac et al. 2017 ). For instance, the perceived ease of use positively influenced the perceived usefulness but did not significantly affect the purchase intention in the Chilean context (Sukno and Riquelme 2019 ). The perceived ease of use did not statistically affect perceived usefulness in a study related to YouTube for procedural learning (Lee and Lehto 2013 ).

Specifically related to the perceived ease of purchase dimension, previous literature showed that this dimension positively influences online purchase intentions when analyzed in the context of customers of Taiwan's largest internet service provider (ISP) (Chiu et al. 2005 ) and among adults aged from 31 to 60 years old in Hong Kong (Law et al. 2016 ). Thus, the fifth and sixth hypotheses of the study are as follows:

Perceived ease of purchase positively affects perceived usefulness.

Perceived ease of purchase positively affects online purchase intention.

Online purchase intention

The intention is the cognitive representation of a person's readiness to perform a given behavior, and intention is the best predictor of actual behavior (Wee et al. 2014 ). Online purchase intention can be defined as measuring a consumer's intention to perform a specific internet buying behavior (Chiu et al. 2005 ). As the literature suggests (Wang and Herrando 2019 ), the present study investigates consumers’ actual buying behavior rather than just examining the purchase intention.

Customer loyalty or repeated consumer buying is critical to the survival and success of any business (Chiu et al. 2014 ). Consumers spend their time in e-commerce looking for information and evaluating product options so that they progressively build an intention to buy that could become an actual purchase (Wang and Herrando 2019 ). Individual attitudes affect users' behavioral intentions, which influence their actual behavior.

A recent survey published by We Are Social showed a trend of behavior change regarding online shopping (Kemp 2020 ). Data showed that 47% of internet users said they spent more time shopping online during the pandemic. Some sectors and product categories have seen a significant increase in sales. There was a 251% increase in visits to supermarket websites, while purchases increased by 76%. Sheth's ( 2020 ) survey also pointed out a significant increase in food retail and bar online shopping. Previous research has also observed that consumer buying intention is positively associated with their actual buying behavior (Çelik and Yilmaz 2011 ; Wee et al. 2014 ; Wang and Herrando 2019 ). There’s a link between the intention to use e-commerce and online purchases (Çelik and Yilmaz 2011 ). Thus, it was decided to formulate the seventh and final hypothesis of the present study:

The intention of online shopping positively affects online shopping behavior.

Thus, Fig. 1 presents the study research model and summarizes the five dimensions and the seven established research hypotheses.

Study framework

Table 1 summarizes some relevant insights and findings of the literature reviewed.

We apply a quantitative, exploratory approach, with data collected via an online survey and analyzed through descriptive statistics and the partial least squares structural equation modeling (PLS-SEM) technique. For the survey, a questionnaire was used for data collection. The dimensions and items of the questionnaire were identified from existing literature, translated (reverse translation), analyzed, and adapted, aiming for compatibility with the current research theme and local context. Table 2 presents the five dimensions surveyed, descriptions, and primary references.

The items related to dimension perceived risk of COVID-19 are based on Zhang et al. ( 2018 ) and Yan et al. ( 2020 ), and the three dimensions related to the technology acceptance model (perceived usefulness, perceived ease of purchase, and online purchase intention) were adapted from Chiu et al. ( 2005 ), Çelik and Yilmaz ( 2011 ), and Law et al. ( 2016 ). The items relating to "online purchase" are based on Çelik and Yilmaz ( 2011 ).

After adapting the items to the research context, we sought to validate the instrument before collecting the data. Content validity and face validity were performed to reduce possible errors resulting from the use of irrelevant or insufficient measures and improve the understanding of the instrument. At first, a group of experts (composed of researchers and marketing professionals) reviewed the initial questionnaire and forwarded feedback on the ease of understanding of the instrument, the adequacy of the terms used, and the consistency of the sequence of items. The order of the items was changed, and the translation of the terms used was adapted for the Portuguese. Subsequently, the instrument underwent a pre-test process with the target audience. 12 Brazilian online consumers (who did not participate in the final sample) answered the questionnaire in this situation. It provided feedback on semantic adequacy (ease of understanding of instructions, items, and response options) and the survey format (online tool used, colors, size, and font type). The feedback led to some specific changes in text and terms used in certain items, aiming at a better understanding by the respondents.

The final instrument used to collect the survey data has 30 items, starting with a request for authorization of the respondent to participate in the study, five questions related to identifying the respondents' profile and socio-demographic data, and 24 items related to the five dimensions present in the research model. The complete instrument and its articles are available in the Online Appendix.

The non-probabilistic convenience sampling technique selected the sample. The data collection period (between June 15 and 21, 2020) coincides with the change of season: from autumn to winter on June 20th, the first winter during the pandemic in Brazil. During data collection, the country had registered 1 million cases related to COVID-19. Data were collected with an online form (Google Forms), whose link was made available through email (to groups of students, professors, researchers, and university workers) and disclosure on digital social media (Facebook and WhatsApp). The sample was selected due to the greater ease of online access for individuals, given the mobility restrictions present at data collection. Such people are part of the target audience for being present online and purchasing through this channel.

The sample selection was carried out with no age limit for the respondents, given that previous studies based on TAM were carried out with different age groups, such as with people aged from 31 to 60 years old (Law et al. 2016 ), from 16 to 74 years old (Fortes and Rita 2016 ), from 16 to 45 years old (Moslehpour et al. 2018 ), below 30 years old (Wei et al. 2018), or with average age around 27 years old (Sukno and Riquelme 2019 ). Based on these studies, it’s suggested that TAM can be used in research involving purchasing behavior with consumers of all ages. At the end of that data collection period, a total number of 1053 questionnaires were answered.

The initial analysis of the data was verified by verifying the completion and validation of the questionnaires received. Of the total of 1053 questionnaires received, only one person indicated, in the first question, not wanting to participate in the survey and therefore excluded from the final sample, which results in 1052 valid and duly completed questionnaires. It is observed that this number of respondents is higher than the minimum estimate of the sample size, recommended by the "ten times rule,” which consists of a method of estimating minimum sample size widely used in studies with PLS-SEM (Hair et al. 2011 ; 2012 ).

Following the data analysis, we used the PLS-SEM (partial least squares structural equation modeling) technique through the SmartPLS software, version 3, to test the proposed model and the seven hypotheses. This technique has been chosen for being indicated for research in consumer behavior (Hair Jr et al. 2011 ) and has already been used by several studies (e.g., Chiu et al. 2014 ; Law et al. 2016 ; Arora and Sahney 2018 ; Wang and Herrando 2019 ; Ventre and Kolbe 2020 ).

Analysis of results

Sample profile.

This section presents the profile of the study participants. Table 3 shows the main characteristics of the respondents' profiles.

Among the 1,052 respondents, it is noteworthy that the majority (74.8%) declared themselves as female, while 25.2% as male, 0.4% preferred not to answer, and 0.1% were classified with "Other.” Concerning the age group, 35.6% of participants were between 25 and31 years old, 29.6% were up to 24 years old , 17.3% were between 32 and 38 years old , 9.9% were over 45 years old , 7.1% were between 39 and 45 years old , and 0.6% preferred not to answer. Related to marital status, the sample is predominantly single/bachelor (62.5%) or in a stable union or married (33.4%), while only 3.8% reported being divorced or widow, and 0.4% preferred not to answer. As far as education level is concerned, a little more than half (50.5%) participants were with a postgraduate degree (MBA and Ph.D.), 28.7% with complete graduation, 20.4% completed elementary or high school, and 0.4% preferred not to answer.

PLS analysis (partial least squares)

This section presents the analysis of partial least squares (partial least squares) through two stages: evaluation of the model of measurement and analysis of the structural model, both presented in the sequence.

Model evaluation—validity and reliability

From the export of the primary data collected for the SmartPLS software, the report of the preliminary data obtained was generated. The evaluation of the model was initiated through its convergent validity (via average variance extracted—AVE), discriminant validity (via cross-loadings, HTMT, and Fornell–Larcker criterion), and reliability of the model/Internal consistency reliability (via composite reliability), as recommended by Hair Jr et al. ( 2017 ).

AVEs for the latent variables are greater than zero, indicating a convergence validity of 0.50, acceptable according to Hair Jr et al. ( 2012 ) and Ringle et al. ( 2014 ). Only the C/L AVE dimension < 0.5(0.339) and, according to Ringle et al. ( 2014 ), in these situations, observed variables of the dimensions presenting < 0.50 should be eliminated. Thus, the two items that showed factor loadings of lower values were eliminated (COV1 and COV2). Later, the data were recalculated, reaching values higher than 0.5 in all the AVE, according to Table 4 .

After ensuring convergent validity, the next step consisted of evaluating the discriminant validity of the model, which indicates whether constructs or variables are independent of each other (Hair Jr et al. 2017 ). According to Ringle et al. ( 2014 ) and Hair Jr et al. ( 2012 ), the convergent validity can be ascertained through the Fornell–Lacker criterion, in which the square roots of the AVE must be greater than the correlations between the constructs (Fornell and Larcker 1981 ) and by observing cross-loadings, where each indicator must be higher in the construct intended to measure (Chin 1998 ). We evaluate, first, the criterion of Fornell–Larcker, which, according to Hair Jr et al. ( 2017 ), is considered more conservative. Table 4 presents the values of the correlations between dimensions and square roots of the AVE values on the main diagonal (boldunderline).

In Table 4 , the values of the correlations are higher than the square roots of their AVE; therefore, the Fornell–Larcker criterion was confirmed. Subsequently, cross-loading scans were analyzed according to Chin's ( 1998 ) criterion, which proved to be adequate, as set out in Table 5 :

Analyzing Table 5 , it is verified that the factor loadings of the observed variables are higher when compared to the other constructs. The correlations’ heterotrait–monotrait ratio (HTMT) also measured the discriminant validity. The HTMT is the mean value of the item correlations across constructs relative to the mean of the average correlations for the items measuring the same construct (Hair Jr et al. 2019 ). HTMT is expected to be lower than 0.85 (for conceptually different constructs) or lower than 0.90 (for conceptually similar constructs) (Hair Jr et al. 2019 ). The Online Appendix shows that HTMT is significantly lower than the threshold value (HTMT < 0.85).

Thus, the model has discriminant validity. Finally, the values of internal consistency were evaluated through composite reliability. In Table 4 , the composite reliability index was higher than 0.7 (Ringle et al. 2014 ; Hair Jr et al. 2012 , 2017 ) for COV (0. 779), EOP (0.885), OP (0.809), PI (0.866), and PU AQ7 (0.894). Also, we tested model fit by using the standardized root mean square residual (SRMR). Henseler et al. ( 2014 ) suggest the SRMR as a goodness-of-fit measure for PLS-SEM that can be used to avoid model misspecification. It is expected that SRMR is < 0.08, which was the case in the data analysis in the present study (SRMR = 0.079).

Therefore, by validating the measurement model based on the criteria described above, the next section will analyze the structural model.

Structural model assessment

The first evaluation performed at this stage analyzed collinearity through the variance inflation factor (VIF). According to Hair Jr et al. (2009), non-compliance with this assumption may make inferences based on the model erroneous or unreliable. It is stressed that, in the context of PLS-SEM, when the VIF values are higher, the level of collinearity is higher, and ideally fetched a VIF value of less than three since the value equal to or greater than five indicates a potential problem of collinearity (Hair Jr et al. 2017 ). Table 6 shows the values of our study:

As values are less than three, we continue with all variables. Subsequently, Pearson's coefficients of determination ( R 2 ) were evaluated. According to Ringle et al. ( 2014 , p . 67), R 2 "evaluates the variance of endogenous variables, which the structural model explains.” According to Cohen ( 2013 ), for social and behavioral sciences, the coefficient usually varies between 2 and 26%, being R 2 = 0.02 considered a small effect; R 2 = 0.13, average effect; and R 2 = 0.26, large effect.

The values observed were perceived usefulness ( R 2 = 0.518), perceived ease of purchase ( R 2 = 0.015), online purchase intentions ( R 2 = 0.485), and online purchase ( R 2 = 0.420). It is verified that the endogenous latent variables result in R 2 above the percentage suggested as a large effect (Cohen 2013 ) and high (Hair Jr et al. 2011 ), except for dimension perceived ease of purchase (1.5%). The model explained a substantial part of the variation of endogenous variables, specifically 42%, 48.5%, and 51.8% of the variation of online purchase, online purchase intentions, and usefulness. Thus, Fig. 2 presents the study research model and summarizes the observed R 2 .

Study framework and R 2

Subsequently, to test the significance of the relationships mentioned, the bootstrapping technique was used to evaluate the significance (p value) of the correlations (measurement models) and the regressions (structural model). Thus, a procedure and analysis of bootstrapping resampling were performed with 5000 samples. Table 7 summarizes the results of the hypothesis tests performed.

As shown in Table 7 , the results are above the reference value (1.96), except for Hypothesis 3 ( T = 1. 383; p value > 0.05). In the other cases, H 0 was rejected so that the correlations and regression coefficients are significant, providing support for the proposed model. Therefore, six hypotheses were supported with a p value < 0.001. A figure with the bootstrapping results is available in the Online Appendix.

Discussion of results

The perceived risk of being infected by COVID-19 when making purchases was positively related to perceived usefulness ( T = 5352; p < 0.001) and perceived ease of purchase ( T = 3706; p < 0.001), supporting Hypotheses 1 and 2. These results suggest that as they realize the possible risks related to face-to-face purchases, consumers come to understand that online shopping is safer/more useful and provides them with greater ease/convenience.

However, the perceived risk of being infected by COVID-19 when buying in person had no statistically significant influence on online purchase intention ( T = 1383; p > 0.05), not supporting Hypotheses 3. The discovery is based on the evidence observed in previous studies, such as Nguyen et al. ( 2020 ) and Yan et al. ( 2020 ), who observed the COVID-19 pandemic as an influencer of online purchase intention. The dissonance may be explained in part by the research context where Nguyen et al. ( 2020 ) observed the consumption of books and Yan et al. ( 2020 ) observed automobiles and possible cultural differences between Brazilian respondents and studies on Asian cultures. This result is also out of previous research that observed the perceived risk as an important determinant of purchase intention (Chiu et al. 2014 ; Zhang et al. 2018 ; Yan et al. 2020 ).

The results of assessing Hypothesis 4 suggest that perceived usefulness is positively related to online purchase intention ( T = 10,818; p < 0.001), supporting the hypothesis. Previous studies also found this behavior (e.g., Chiu et al. 2005 ; Law et al. 2016 ; Moslehpour et al. 2018 ; Sukno and Riquelme 2019 ). Thus, realizing that online purchases will provide greater efficiency than face-to-face purchases, consumers will be more interested in making such purchases.

Empirical evidence also supported Hypothesis 5, related to the positive relationship between perceived ease of purchase and perceived usefulness ( T = 36,684; p < 0.001). It is in line with the previous studies that also observed that perceived ease of use positively affected perceived usefulness (Çelik and Yilmaz 2011 ; Isaac et al. 2017 ; Arora and Sahney 2018 ; Moslehpour et al. 2018 ; Manis and Choi 2019 ; Sukno and Riquelme 2019 ). Hypothesis 6 was supported, having seen the significant positive association between perceived ease of purchase and the intention of online purchase ( T = 9,648; p < 0.001), corroborating the findings in the literature (Chiu et al. 2005 ; Law et al. 2016 ). The results suggest that by understanding that online shopping will require less effort than a face-to-face purchase, consumers perceive online shopping will improve their buying performance and have greater intention to make purchases in this way.

Finally, there was a significant positive association between intention and purchase intention ( T = 36,666; p < 0.001), supporting Hypothesis 7. This result is in line with the literature (Çelik and Yilmaz 2011 ; Wang and Herrando 2019 ), where consumer purchase intent is positively associated with your actual online purchase. Most respondents claimed to have made more than five purchases in the last three months (during the pandemic), staying more than 15 min per week performing their online shopping. In this way, the acceptance of these hypotheses meets the idea that the more companies can demonstrate to their consumers that online shopping will bring them benefits, such as ease of use and time savings, the greater their purchase intention and, consequently, makes them buy more online. Companies can further exploit such benefits in times of health emergencies, showing how buying online will bring fewer risks than a face-to-face purchase (at the company itself or its competitor).

Final considerations

This study aimed to analyze the influence of COVID-19 on online shopping behavior. The results reveal a significant impact of the perceived risk of being infected by COVID-19 when buying in person to perceived usefulness and ease of online purchase, which, in turn, influence online purchase intention. The intention to purchase online has also positively influenced online shopping. Such findings are essentially in harmony with the previous research.

That said, it can be concluded that the findings of this study indicate that the COVID-19 pandemic influences online shopping behavior, since, at this time, people fear being infected when accessing physical retail environments and find in the online environment the ease of being able to access this purchase without having to leave the comfort of their homes and expose themselves to risk. Furthermore, it is also possible to note that this moment of greater exposure to digital media favors the growth of online shopping because the consumer who has an intention to buy online most likely decides to make such a purchase.

Implications of the study

The study presents theoretical, managerial, and social contributions. From a theoretical point of view, this article contributes to the body of literature on online purchasing decisions. The findings of the study also contributed to corroborate the results of studies and theoretical propositions of authors such as Chiu et al. ( 2005 ), Çelik and Yilmaz ( 2011 ), Law et al. ( 2016 ), Arora and Sahney ( 2018 ), Moslehpour et al. ( 2018 ), Zhang et al. ( 2018 ), Sukno and Riquelme ( 2019 ), and Wang and Herrando ( 2019 ).

From the point of view of management contributions, the understanding of consumer buying behavior in the use of the virtual environment to the detriment of face-to-face, especially in this pandemic scenario, to make their purchases, it is crucial for companies and marketing professionals to rethink their strategic actions focusing on better conducting, planning and realignment of their products and services primarily the omnichannel perspective.

The study presents social contributions; from the moment that companies understand the behavior of online buying, they can improve the experience, access, and usability that will be socially useful in the day-to-day of the population and especially in a crisis. The study also contributes to the guidance of authorities and policymakers and economic recovery plans, suggesting that perceived risk when shopping in physical stores influences consumers to make their purchases online.

Research limitations and future research directions

Like any scientific study, this also presents some methodological limitations. The sample is composed only of Brazilian consumers and, since this is a non-probabilistic sample, inference to the rest of the population is not possible. Therefore, future studies can be conducted in the Brazilian and international context with the proposed model, with a more representative sampling process, and a random selection of respondents.

The proposed model does not consider all possible variables influencing consumers’ online purchase behavior. The data collection occurred at the beginning of winter and a few months in the pandemic when there were more mobility restrictions, influencing the decision to buy online. Thus, it is suggested to improve the theoretical model tested here, including other variables and dimensions not considered in the present study or the use of the current model at different moments of the pandemic. It is also recommended to use the model proposed herein studies on online shopping in specific segments, such as food and clothing.

However, although it is recognized that the results and implications of the present study are limited and require caution in its extrapolation and generalization, it is evident that these limitations do not compromise the analyses performed and the contributions presented by the same to academia, the market, and society.

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Soares, J.C., Limongi, R., De Sousa Júnior, J.H. et al. Assessing the effects of COVID-19-related risk on online shopping behavior. J Market Anal 11 , 82–94 (2023). https://doi.org/10.1057/s41270-022-00156-9

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ORIGINAL RESEARCH

The impact of risk factors on South African consumers' attitude towards online shopping

Khathutshelo M. Makhitha; Kate M. Ngobeni

Department of Marketing and Retail Management, College of Economics and Management Sciences, University of South Africa, Pretoria, South Africa

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ORIENTATION : The advances in technology have resulted in an increasing number of people choosing to shop online, globally. Despite the growing number of those shopping online and online retailers, most customers continue to avoid shopping online. This could be because of risks inherent in online shopping that have resulted in some consumers opting not to shop online RESEARCH PURPOSE : The main aim of the research study is to identify the risks influencing consumers' attitude towards online purchases MOTIVATION FOR THE STUDY: The study was driven by the need to determine the risks associated with online shopping that influence whether consumers will shop online or not. RESEARCH DESIGN, APPROACH AND METHOD: A survey, using the non-probability convenience sampling method, was used to reach respondents (207 consumers in South Africa who visited two shopping malls) in Gauteng, South Africa. Data were collected from consumers at the two shopping malls from March 2019 to April 2019. Structural equation modelling (SEM) was used to test the conceptual model for the study. MAIN FINDINGS : The results showed that product risk and privacy risk influence consumer attitude in online shopping positively and that delivery risk does not to have a great influence on attitude towards online shopping. The attitude towards online shopping was also found to positively influence their intention to shop online PRACTICAL/MANAGERIAL IMPLICATIONS: The practical implications for this study would be that retail owners and marketers would understand and manage product and privacy as risks that inhibit consumers from shopping online. Retailers should formulate appropriate marketing and retail strategies that address these risks to change consumers' perceptions about online shopping and reduce the level of risks related to online shopping. CONTRIBUTION/VALUE-ADD: Marketing and retail strategies should include strategies on how product risk and privacy risks will be managed and reduced to ensure they do not influence consumer's attitude against online shopping.

Keywords : online shopping; purchase intention; risk factors; attitude, consumer behaviour.

Introduction

Online shopping has been an increasing trend worldwide, especially in countries with a well-developed infrastructure for online marketing activities. Online shopping involves purchasing goods and services over the internet (Malapane 2019:1). Consumers can now conveniently purchase products from anywhere, at any time (Arora & Sahney 2018:1040), with an abundance of information. Given the benefits of online shopping, online transactions' high cart abandonment rates remain a concern (Statista 2020). This is because consumers often prefer to shop at physical retailers because of the ability to touch and feel products physically, instant possession, online distrust and the perceived risk associated with online purchases (Arora & Sahney 2018:1040). Because of these concerns, online shopping is used to make price and product feature comparisons; however, the decision and actual purchases are made in store, after the physical evaluation (Wolny & Charoensuksai 2014:324). This challenge presents an opportunity for online retailers and marketing practitioners to evaluate further the impact that perceived risk has on online buying behaviour and to comprehend online shopping through consumers' eyes. This is supported by Yang, Sarathy and Lee (2016:75), who stated that future research should take a more consumer-centric approach and try to understand better the impact of online shopping risk factors on consumers' purchasing behaviour.

Perceived risk factors that affect online shopping behaviour have been identified in previous studies (Bhatti, Saad & Gbadebo 2018; Orubu 2016; Tandon, Kiran & Sah 2018). However, future researchers should focus on other potential online shopping risk factors that could have an impact on consumers' attitudes and their purchasing behaviour (Hong, Zulkiffli & Hamsani 2016:20). Bhatti et al. (2018:8-9) further suggested that future researchers should investigate online shopping adoption, purchase intention and behaviour in relation to the perceived risks in developing and developed countries. To ensure universal applicability, the impact of risk factors on consumers' attitudes and intention to purchase online should be examined in other environments and segments (Marza, Idris & Arbor 2019:594).

The advent of online shopping has evoked some concerns for consumers, including product quality assurance, insufficient information disclosure, security of payment methods and private information vulnerability (Ariff et al. 2014:309). These challenges have evolved because of online retailers' lack of understanding of the main risk factors influencing consumers' attitude and online shopping behaviour in South Africa. Moreover, limited research was performed regarding the perceived risk factors influencing consumers' attitudes and the effect of attitude on consumers' online shopping intention. Investigating this is important, as it will help marketing practitioners and online retailers to understand better how they can improve their online sales. It will also provide online retailers with useful information to formulate strategies and to help curb the risks faced in the online shopping environment. This study was conducted to achieve the following three objectives:

To determine perceived risk factors affecting consumers' attitude towards online shopping intentions in South Africa.

To determine the influence that perceived risk factors have on attitude towards online shopping in South Africa.

To determine the effect of online shoppers' attitude towards their intention to shop online in South Africa.

Literature review

The South Africa online shopping development

The South African e-commerce market is composed of 19.9 million users, with 4.9 million more anticipated in 2021 (Statista 2018). Currently, the market contributes 1% in value of the total retail sector, indicating an exponential growth opportunity (export.gov 2018). E-commerce is expanding at a rapid pace in the South African retail industry, especially in remote rural areas where traditional distribution channels are extremely expensive for retailers to reach consumers, which increase the cost of purchase for consumers (export.gov 2018). The shopping behaviour of South African consumers is also changing, with many consumers now doing research online before completing the transaction in-store, whilst others do research in the store, but make the actual purchase online (Smith 2020).

According to Businesstech (2018), the South African online retail business is being reshaped by mobile e-commerce (m-commerce). This is driven by the proliferation of smartphones, improvements in network services (export.gov 2018; Payfast 2019) and the growing demand for flexibility and accessibility (Itnewsafrica 2017). Ease of use, convenience and instantaneous purchases have been identified as important determinants for satisfying South African consumers' needs and maintaining customer loyalty online (Itnewsafrica 2017). This has led Visa to realise that it must facilitate consumers' online purchasing process by implementing secure and trustworthy payment systems, which make it convenient to shop online (Smith 2020). However, online consumers in South Africa are still sceptical about shopping online, because of perceived risks, such as financial loss because of fraudulent retailers, product non-delivery, risk to privacy and the lack of product evaluation before the purchase (Malapane 2019:1, 5).

Risk as a factor influencing online purchasing intentions

Understanding consumers' perceptions of risk in online shopping is an important factor because it affects consumers' buying decisions in an online shopping environment. This suggests that if the risk is perceived to be high, consumers are less likely to buy a product online (Rosillo-Díaz, Blanco-Encomienda & Crespo-Almendros 2019:152). 'Perceived risk is referred to as consumers' perception of the uncertainty and adverse consequences of engaging in a purchase activity' (Pathak & Pathak 2017:33). Previous studies have examined the influence of perceived risks on consumers' online shopping intentions, with some findings indicating that perceived risk has no effect on consumers' online shopping intentions (Bhatti et al. 2018:7-8). Other researches, on the other hand, indicate that consumers' perceptions of risk have no effect on their purchase decisions online (Lin et al. 2019:1198), which indicates that the effect of perceived risks on consumers' online shopping intention differs across consumers. The effect of perceived risks on consumers' online shopping intention also differs across types of risks (Nawi et al. 2019:9). There are various types of risks that serve as deterrents to conducting online transactions. The risk factors that affect consumers' online shopping behaviour are depicted ( Table 1 ).

Previous studies have identified product risk (Masoud 2013:76; Orubu 2016:14), delivery risk (Masoud 2013:76; Tanadi et al. 2015:226) and security and privacy risk (Masoud 2013:76) as the factors that have most impact in online shopping behaviour. Given that these are the most important factors affecting consumers' online buying decisions, this study examines the impact of product risk, delivery risk, privacy risk and security risk on South African consumers' attitudes and, consequently, their online shopping intentions as depicted in Figure 1 .

Product risk

Consumers experience difficulties in evaluating the quality of products online, as they must rely on limited information and images to make a purchase decision. Product risk is primarily caused by the incapability to inspect products thoroughly prior to purchase by touching, smelling and feeling them (Ariff et al. 2014:3). Therefore, consumers perceive an elevated risk, because of the lack of a physical sense. According to Ariff et al. (2014:313), product risk is regarded as the risk of loss suffered by consumers should the product fall short of their expectations. This suggests that product risk is closely linked to the product's performance, relative to the consumers' expectation (Tandon et al. 2018:68). Consumers who want to purchase products online face a significant deterrent in the form of product risk (Aghekyan-Simonian et al. 2012:329). According to Bhatti et al. (2018:7-8), attitude has a significant moderating influence on product risk and online shopping behaviour. Consumers' attitude towards online shopping is negatively influenced by product risk (Ariff et al. 2014:7). Furthermore, consumers' attitude towards their online shopping intentions was found to be influenced more by product risk than by delivery risk (Hong et al. 2016:18). Therefore, the first hypothesis was formulated as follows:

H 1 : Product risk has a significant influence on consumers' attitude.

Delivery risk

Consumers, who purchase products online, are generally concerned with the product's delivery. Delivery risks include the product being damaged whilst in transit, the product being delivered to a wrong address or even a delay in delivery. Delivery risk is a prevalent factor that influences online shopping behaviour of consumers (Tanadi et al. 2015:226). Delivery risk is defined as consumers' concerns about products not being delivered on time, product loss or damaged during transit (Ariff et al. 2014:3; Tanadi et al. 2015:227). Previous researchers have found several conflicting results regarding delivery risk. According to Masoud (2013:83), consumers' online purchasing intentions are not affected by delivery risk. However, consumers' attitude towards online purchasing intent has been shown to be negatively influenced by delivery risk (Hong et al. 2016:18). Moreover, Tanadi et al. (2015:227) reported that consumers' attitude towards online purchases is significantly influenced by delivery risk. Subsequently, the following hypothesis was formulated:

H 2 : Delivery risk has a significant influence on consumers' attitude.

Privacy risk

In this regard, consumers avoid purchasing products online to avoid sharing personal information online and consumers cannot verify the retailers' credibility before purchasing especially in instances where the reputation of the retailer is unknown. Privacy concerns become prevalent, especially during the check-out process, which leads to consumers aborting their shopping carts (Kukar-Kinney & Close 2010:244). Having to share personal information on online payment systems leads to consumers feeling uneasy and vulnerable (Tanadi et al. 2015:228). The possibility of retailers misusing consumers' personal information discourages consumers from purchasing online (Thakur & Srivastava 2015:153). Privacy risk is the possibility of losing sensitive information and becoming vulnerable to fraudulent activity in an online environment (Fortes & Rita 2016:168).

Several factors affect consumers' online shopping behaviour, including privacy and security risks (Farhana et al. 2017 :225). Privacy risk has been identified as one of the most common factors preventing consumers from successfully completing online purchases that require digital wallets (Fortes & Rita 2016:168). Furthermore, Orubu (2016:17) discovered that consumers' attitude towards online shopping is significantly influenced by privacy risk.

As a result, the following hypotheses were developed:

H 3 : Privacy risk has a significant influence on consumers' attitude.

Security risk

Dai and Chen (2015:44) defined security as involving consumers' concern about information safety regarding the confidentiality, integrity and authentication of such information. Security risk is the possibility of financial loss when transacting online (Thakur & Srivastava 2015:153). According to Ariffin, Mohan and Goh (2018:322), the most significant factor influencing consumers' online shopping behaviour is security risk. Jun and Jaafar (2011:122) established a correlation between consumers' attitude towards online shopping and their perception of security risks. This was confirmed by Keisidou et al. (2011:31) and Dai and Chen (2015:51), who found that consumers' attitude towards online shopping is influenced by perceived security risk although the influence was found to be negative by Ariffin et al. (2018:322). On the contrary, Tandon et al. (2018:82) found security to have no significant influence in online shopping. The fourth hypothesis was formulated as follows:

H 4 : Security risk has a significant influence on consumers' attitude.

Risk as a factor influencing attitude and online shopping intentions

Consumers' perceived risk in online shopping context has an influence on purchase intention, indirectly, through attitude (Chang & Wu 2012:387), suggesting that, if the perceived risk is high, then consumers will have a negative attitude and, therefore, their intention to purchase will be reduced (Chang & Wu 2012:393).

Arora and Rahul (2018) examined the key factors of perceived risk that influence online shopping and found perceived risk not to have a substantial influence on the attitude of women in India (Arora & Rahul 2018:108). This was supported by previous studies that found perceived risk has no significant effect towards online shopping (Bhatti et al. 2018:7-8; Marza et al. 2019:591).

In contrast, a study by Hsu and Luan (2017) revealed that perceived risk has an impact on attitudes. Attitude was found to have an impact on purchasing intent when it comes to online shopping platforms (Hsu & Luan 2017:27). This was supported by Yang et al. (2016:74) who found a significant relationship between perceived risk and consumer attitude towards online shopping. Consequently, the following hypothesis was formulated:

H 5 : Attitude has a significant influence on consumers' intention to shop online.

Research methods and design

Study design and sample

A quantitative research methodology using a survey data collection research method was regarded as the most appropriate method for the study. Prior online shopping studies adopted a survey to determine factors influencing online shopping of products (Orubu 2016; Tandon et al. 2018). The purpose for adopting a survey was to determine the risk factors influencing consumers' attitudes when shopping online and to determine the influence of consumers' demographic factors on online shopping.

The population targeted for this research was consumers in South Africa comprising of those who either have shopped or have not shopped online. The sample population for the study was shoppers in South Africa, who visited two malls: Cresta Shopping Centre, in Johannesburg and Sunnypark Shopping Centre, in Sunnyside, Pretoria, regardless of whether they have access to internet or not. The study adopted a convenience, non-probability sampling method.

Data collection and research instrument

The questionnaire items of prior research studies were used to design a questionnaire instrument to achieve the objectives of this study (Yang & Lester 2004). The questionnaire consisted of 13 demographic questions and 21 statements linked to risk factors influencing consumers when shopping online. The product risk factor was measured using seven risk statements with five statements measuring privacy risk, another five statements measuring delivery risk and four statements measuring security risk. There were four statements linked to attitude towards online shopping and another four statements measuring intention to shop online. Risk factors in online shopping were measured using the Likert scale, from 1 to 5 - with 1 measuring 'highly disagree' and 5 measuring 'highly agree'.

Data were collected from consumers at the two shopping malls from March 2019 to April 2019. Shoppers, who visited the malls during this period, were intercepted by fieldworkers and were asked to participate in the research study by voluntarily completing the self-completion questionnaire provided as a hard copy. A company specialising in fieldwork services was hired to render the services and was responsible for training the fieldworkers prior to data collection. There was no compensation offered to consumers who completed the questionnaires. The questionnaire was ethically approved by the academic institution prior to data collection. It took 20 min for consumers to complete the questionnaire. A total of 207 people responded, culminating in a response rate of 98%, which is a high response rate. Similar studies investigating risks in online shopping targeted 200 respondents (Hong et al. 2016; Mudaa, Mohd & Hassan 2016).

Analysis of data

The SAS JMP version 15 for Mac and the R language version 3.5.2 were used to analyse data. The following statistical tests were conducted to achieve the objectives of the study: descriptive analyses, exploratory factor analysis and structural equation modelling (SEM).

Ethical considerations

Approval for the study was obtained from the Department of Marketing and Retail Management Ethics Committee, University of South Africa (MRM_2019_001).

Results and findings

This section will present the results of the study starting with the profile of respondents.

The respondents' profile

The respondents consisted of more females (60.4%, n = 125) than males (39.6%, n = 82). Almost one-third of the respondents were 18-21 years old (31.6%, n = 65), with almost two-thirds of them being 18-25 years old (60.2%, n = 124). Respondents older than 45 years were not well represented in the sample. Less than 10% (9.2%, n = 19) of the respondents did not complete Grade 12. Over 90% of the respondents ( n = 188) completed Grade 12 and more than half (56.6%, n = 117) of the respondents have some tertiary qualification. Most of the respondents (70.9%, n = 146) have a monthly income of below $666.66 (R10 000.00).

All the respondents (100%, n = 207) had access to the internet with three-quarters (74.9%, n = 155) purchasing products or services online whilst a quarter 25 (25%, n = 52) of respondents do not buy products or services online. More than 90% (93.7%, n = 194) of the respondents use their cellphones to access the internet. The more popular method for connecting to the internet is from a computer at home (45.9%, n = 95). More than 70% (72.8%, n = 150) of the respondents use the internet for communication, social websites, etc. The more popular reason for accessing the internet is finding information (57.3%, n = 118), followed by research, homework and study (48.1%, n = 99).

Most of the respondents (83.1%, n = 172) possess a credit and/or debit card and buy clothing and accessories online (61.1%, n = 118). The next most popular type of purchase is books (32.6%, n = 63), followed by electronic goods (30.6%, n = 59). Almost 60% (58.5%, n = 121) of the respondents do not buy electronic products online. Of those respondents who do not buy electronic goods online, almost one-third (32.5%, n = 40) indicated that they may buy electronic goods online in the next 12 months. Of those respondents that currently buy electronic goods online, more than 40% (43.2 n = 38) do so once a year. Of those respondents who currently buy electronic goods online, 36.8% ( n = 75) visit one to three online stores, before making their purchase. Takealot is the most popular online shop to purchase electronic goods (70.4%, n = 119), followed by Makro (38.5%, n = 65).

Factor analysis

The purpose for conducting the factor analysis was to determine whether variables developed from a literature review could, in fact, be grouped into meaningful variables describing the risk factors influencing consumer intention to shop online. Therefore, the exploratory factor analysis was applied to responses on the 21 risk items with the intention to group risk items into meaningful groups of risk items. To extract the risk factors, the principal axis factoring was used, followed by a quartimin (oblique) rotation. Five of the factors had eigenvalues greater than 1. For the five-factor solution, the 5th factor showed three items with between 0.3 and 0.38 factor loadings, which were too low; therefore, the four-factor solution was considered. The total variance for the combined four factors accounted for 56%. The factor loadings for each scale item are presented ( Table 2 ).

Although items with factor loadings of 0.3 can be accepted (Hair et al. 2010:117), Stevens in Field and Miles (2010:557), recommended a factor loading of 0.364 for a sample of 200. For this study, items loading 0.40 or greater were considered for further analysis. Four items were dropped because of either loading lower than 0.40 or cross loading, thus retaining 17 items as shown ( Table 2 ). The first factor therefore loaded seven items and was named 'product risk'. The mean score for product risk is 2.166 - standard deviation (SD) of 0.828, lower than for other risk factors, which shows that product risk is of less importance for consumers when shopping online. The SD for 0.828 for this factor shows that the respondents varied in their perception of the product factor having less importance on consumers when shopping online. The second factor loaded three items and was named 'privacy risk'. Loaded on the third factor were four items named 'delivery risk' and the fourth factor was named 'security risk' with three items loading on the factor. The privacy risk and delivery risk had high mean scores of 3.11 (SD = 0.994) and 3.05 (SD = 0.880), respectively, which implied that these risks are more important to consumers when shopping online; however, the SD for all were high at 0.99 and 0.88, respectively, showing variation in the respondents' perceptions of these risks factor in online shopping environment. According to Field and Miles (2010:37), the SD closer to 1 indicates that there is variation in the response.

The exploratory principal factor analysis with axis factoring was carried out in SAS JMP version 15, which is considered appropriate for the correlation patterns between the questions used to determine the respondents' perceptions towards online shopping risks in South Africa. The Pearson's product-moment correlation coefficient was used to determine the factorability of the correlation matrix. The assumptions of normality, linearity and homoscedasticity were not violated as indicated by the preliminary distribution analyses. The correlation matrix demonstrated several coefficients of 0.3 and above.

According to Yayar and Karaca (2017:55), the Kaiser-Meyer-Olkin (KMO) value must be 0.6 or more. The KMO value for the study was 0.846 and satisfactory, which indicated that data were suitable for factor analysis. This was also supported by the Bartlett's test of sphericity, which reached statistical significance, p < 0.0001, then, the correlation matrix was deemed factorable. According to Hair et al. (2010:463), small values of less than 0.05 of the significance level indicate that a factor analysis is useful with the data.

Validity and reliability

To determine if the individual questions load onto the constructs as intended in the questionnaire and to determine the construct validity of the study, the exploratory factor analysis was performed. According to Child (2006), a threshold minimum of 0.2 must be maintained on the communalities to further determine the construct validity of the instrument, which was performed in this study. One of the items (item 21) had a lower communality of 0.11 and was kept as part of the validation but was just observed. Table 1 was developed to ensure that both the study and the questionnaire are aligned with existing studies, thus achieving construct validity (see Table 1 ). To further ensure the validity of the questionnaire, it was also pre-tested with 10 respondents and approved by two academics, experts in the field based on the comments from the respondents and the two academics, several minor modifications of the wording and the question item sequence were performed.

Cronbach's alpha ( α ) coefficient is calculated to assess the reliability of the different constructs in the questionnaire. The overall α for the constructs was 0.96 and the individual α was 0.88 (product risk), 0.78 (privacy risk), 0.74 (delivery risk) and 0.42 (security risk). According to Malhotra (2010), a Cronbach's alpha coefficient must be above 0.70 to be acceptable and that those less than 0.50 are deemed unacceptable whilst those between 0.50 and 0.69 are considered adequate. The more closer to one the value is, the more acceptable it becomes. However, a Cronbach's alpha of 0.60 is considered acceptable for exploratory study, which implies that the acceptability for Cronbach's alpha differs across types of research study. As this study is not an exploratory study, the Cronbach's alpha for security risk of 0.42 was unacceptable and security risk will, therefore, not be used for further analysis.

Model testing

The model testing was carried out using the lavaan version 0.6-1 (Rosseel 2012) in R version 3.5.2 (R Core Team 2018). A maximum likelihood estimation with robust standard errors (maximum likelihood mean [MLM]), which produce a robust (scaled) test statistic, was used. The MLM chi-square test statistic is also referred to as the Satorra-Bentler chi-square with robust standard errors. The latent factors were standardised, allowing free estimation of all factor loadings - the R version 3.5.2 with the lavaan library. The purpose of this phase is to assess causative relationships amongst latent constructs (Nusair & Hua 2010). The measures of model fit of this study were performed using the following indices: chi-square value over degree of freedom, normed fit index (NFI), the incremental fit index (IFI), Tucker Lewis index (TLI), comparative fit index (CFI) and standard root mean residual (root mean square error of approximation [RMSEA]). As a result of security being excluded from further analysis based on an unacceptable Cronbach's alpha, the model tested whether the three risk factors: product, privacy and delivery influence consumer attitude towards online shopping and whether consumer attitude towards online shopping influences their intention to shop online. Therefore, H4 was not tested further because of low Cronbach's alpha.

The results of model fit testing are shown ( Table 3 ). The goodness-of-fit index (GFI), CFI, TLI, IFI, relative fit index (RFI) and NFI, must be greater than or equal to 0.9 in order to show model fit; however, a value greater than 0.8 can marginally be accepted (Hair et al. 2006). As appears here, the model fit was good with the following indices: a chi-square (178) = 238.69; p = 0.002, the relative chi-square = 1.34, RMSEA of 0.045 90% CI (0.029, 0.059), standardised root mean squared residual (SRMSR) = 0.079, CFI = 0.96 (robust) and TLI of 0.95 (robust). The 90% confidence interval for the RMSEA statistics ranged from 0.029 to 0.059, meaning that it is plausible that the population RMSEA statistic might be as low as 0.029 and as high as 0.059.

The RMSEA of 0.045 is less than the required 0.05 (< 0.05), signifying the model fit. An SRMSR of 0.079 was attained in this study. According to Hu and Bentler (1999), a cut-off value close to 0.08 for standardised root mean residual (SRMR) signifies good fit between the model and the data under observation.

The structural model is shown with standardised coefficients of the three risk factors-product risk, delivery risk and privacy risk that were tested to determine if they influence consumer attitude towards online shopping ( Figure 2 ). The figure also shows the effect of attitude towards consumer intention to shop online.

Hypothesis testing results

Two regressions were performed as part of the structural part of the SEM model. The first regression tested the influence of privacy, product and delivery risk on attitude towards online shopping and then the second regression tested the effect of attitude on intention to shop online (refer to Table 4 and Table 5 ).

The z -values with Wald tests were used for testing statistical significance in the SEM model. The privacy risk factors have a stronger effect on attitude towards online shopping with a beta coefficient of 0.33 ( z = 3.22) followed by product risk with a beta coefficient of 0.24 ( z = 5.43). The delivery risk has a negative and weak effect on attitude towards online shopping with a beta coefficient of -0.16 and the z value of -1.79, which shows that the hypothesis was not significant as shown ( Table 3 ). The findings by Thakur and Srivastava (2015) reported that privacy risk weighs lower than product risk with less effect on attitude towards online shopping, which contradict findings of this study.

Attitude has a stronger effect on intention to shop online with a beta coefficient of 0.81 ( z = 7.87) ( Table 4 ).

From Table 6 , the following hypotheses were supported or rejected:

Product risk has a statistically significant influence on users' perceived attitude (standardised coefficient = 0.296, p = 0.001) (refer to Table 4 and Table 6 ). The path coefficient of H 1 ( product risk influences attitude towards online shopping ) is 0.296. This shows the effect that product risk has on attitude towards online shopping. The p -value of 0.001 signifies that the hypothesis is supported. The findings of this study are similar to those of existing studies that reported that product risk is a barrier to consumers' online shopping (Panwar 2018:2489). However, other studies found product risk to have no significant influence on online shopping (Bhatti et al. 2018:7; Tariq et al. 2016:98), which shows that the influence of product risk on attitude towards online shopping differs across consumers.

Privacy risk has a statistically significant influence on users' perceived attitude (standardised coefficient = 0.553, p < 0.001) (refer to Table 4 and Table 6 ). The path coefficient of H 2 ( privacy risk influences attitude towards online shopping ) is 0.553. This implies a strong and significant relationship between privacy risk and attitude towards online shopping. The p -value 0.001 proves that the hypothesis is supported. According to Orubu (2016:17), perceived privacy risks are major barriers for consumer adoption of online shopping, which support the findings of this study.

Delivery risk does not have a statistically significant influence on users' attitude towards online shopping (standardised coefficient = -0.203, p = 0.07). The path coefficient of H 3 ( delivery risk influences attitude towards online shopping ) is -0.203. This indicates that the delivery risk has no influence on attitude towards online shopping. The p -value 0.072 signifies that the hypothesis is not supported. The results of the study by Panwar (2018:2489) supported that delivery risk does not have a significant impact on consumers' attitude towards online shopping.

As a result of the Cronbach's alpha measuring the reliability for the security risk being low, H 4 was not tested further.

Attitude has a statistically significant influence on users' perceived intention (standardised coefficient = 0.81, p < 0.001) as shown ( Table 5 and Table 6 ). The path coefficient of H 5 ( attitude has a statistically significant influence on users' intention ) is 0.81, which denotes a strong relationship between attitude towards online shopping and intention to shop online. The p -value has a 0.001 confidence level ( p < 0.05), which signifies that the hypothesis is supported because it is significant. This implies that attitude influences consumers' intention to shop online, which is supported by Lin et al. (2018:1198).

Managerial implications

The findings of this study contribute to existing research on online shopping in South Africa. The findings confirm that some risk factors play a significant role in the online shopping environment by influencing consumers' attitude towards online shopping. It is important for policymakers and retailers to understand the risks and how they influence consumer's attitude towards online shopping. The implication for policymakers is that they must formulate policies that can help reduce the impact of the risks to increase online shopping adoption in South Africa. There are still a large number of consumers in South Africa who do not shop online; therefore, policymakers could also provide the necessary support to retailers selling online to ensure that risks in online shopping are minimised. Retailers should also find ways to minimise the impact of risks on consumers who are shopping online and more importantly protecting their online shopping activities.

The privacy risk was found to have influence on online shopping than the product factors. This implies that online retailers and markets must address these risk factors if they want to increase the number of people shopping online. For example, with privacy risk, consumers are not comfortable providing personal information. Consumers' personal information may include information about their debit or credit card details. Some online shops allow consumers to pay cash on delivery, which helps to overcome the fear of using debit or credit facilities online; this helps to reduce the privacy risk because consumers do not have to share debit or credit card details. Alternatively, e-tailers and marketers should constantly update the existing security measures in place to ensure that consumers' personal information does not end up in the wrong hands.

Delivery risk was found to have no influence on online shopping. However, retailers should still address this risk to ensure that consumers are happy with the delivery of products when shopping online.

To address the product risk, e-tailers and marketers could use advanced technologies that enable consumers to view or even to try products online, to avoid buying something that will not fit or look different to what they saw online. Online shops such as Spec Savers allow consumers to fit spectacles online before deciding whether to buy or not. This involves the use of augmented reality (AR) shopping. Augmented reality is defined as mixed reality systems that integrate and enhance virtual objects to real physical environments (Yuen, Yaoyuneyong & Johnson 2011). The systems provide consumers with the ability to navigate through rooms with staged furniture, in houses that are under construction, fit clothing and try on pairs of sunglasses, virtually, in the comfort of their own homes (Hilken et al. 2017:885); therefore, eliminating uncertainties during the purchasing process (Yuen et al. 2011).

Online marketers and e-tailers must still make sure that the product consumers buy are what they receive. They could make sure that the product performs as promised. In addition, they must make it easy for consumers to return products that are not functioning as expected.

Conclusions, limitations and recommendations for further study

This study found that product risk and privacy risk influence attitude towards online shopping. The delivery risk was found not to have influence on attitude towards online shopping. The study also found that attitude towards online shopping also influences the intention to shop online. Retailers in South Africa can learn from the results of this study and formulate appropriate retail and marketing strategies to manage the risks in online shopping.

The study targeted consumers in Gauteng, at the two malls in Pretoria and Johannesburg. The results cannot be generalised across cities and other areas in South Africa, which serve as a limitation for this study. Another limitation for the study is that fewer respondents (25%, n = 52) had not shopped online, future studies could investigate risk factors influencing those who do not shop online. Further studies could investigate online shoppers across South Africa and those outside our borders. Studies could also investigate the additional security risk factors because the factor was proven unreliable in this study. Adding more items on security factors could help researchers explore further if security as a factor could load satisfactorily and be reliable. The use of AR as a tool for reducing the impact of risk factors on online shopping could also be investigated. Studies could also investigate emerging consumers in South Africa, to determine if they have adopted online shopping and factors that influence them to shop online.

Acknowledgements

This article is based on the data collected for a Master's dissertation with permission from Miss A. Nhlapulo with permission at the University of South Africa, 2020, titled: 'Factors influencing consumers' behaviour towards online shopping for consumer electronics in Gauteng, South Africa', available here: http://hdl.handle.net/10500/27356 .

Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Authors' contributions

K.M.N. wrote literature sections. K.M.M. conceptualised the idea, asked permission to use data from a masters' graduate from the University of South Africa. K.M.M. also mentored K.M.N. and also wrote the empirical part of the article.

Funding information

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Data availability

Data are available on request from the corresponding author.

The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.

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Received: 19 Dec. 2020 Accepted: 27 May 2021 Published: 03 Aug. 2021

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Thomas Williams

Great topic. I think that the thesis and the connection to STS needs to be worked on. Citations could be stronger and they need to be linked in the chapter. Add links to keywords? Sections need to be labeled with topics. Your images need to be labeled and add alt text. Over all, the chapter could be more explicit and provide more examples.

Introduction

The COVID-19 pandemic has caused people to make many changes in their lives. One of these changes is a significant increase in shopping online instead of in physical stores. The pandemic has caused increased use of online shopping as an alternative to physical stores that will remain after the pandemic ends.

Connection to STS Theory

The shift from physical shopping to online shopping is related to the Theory of Path Dependence , which states that current decisions made by people are based on decisions made in the past due to a resistance to change. After the pandemic had taken off, customers stuck with shopping online because of past experiences with shopping during the pandemic. Since the ratio of online shoppers to in-store shoppers decreased during the pandemic, many people decided to continue the convenience of shopping online as opposed to changing their routine to travel to the store.

Online Shopping Is on the Rise

A shopping cart is covered by a large mask, which sits over the front of the cart, with the straps attached to the handlebars. This is to represent stores taking precautions and making changes for the pandemic. It does this by putting a mask on the symbol of shopping, just as we would put a mask on ourselves.

More people are shopping online after the pandemic than before. According to the United Nations Conference on Trade and Development (abbreviated UNCTAD), the number of purchases made online has risen by 6% – 10% since the beginning of the pandemic ( UNCTAD , 2020). This increase in online purchases shows that the pandemic has caused people to shop online more.

People do not feel comfortable or safe when they are shopping in person. Why are people shopping online more? People do not feel comfortable or safe when they are shopping in person. In decades prior, people would have had to take that risk, but in 2020, we have an alternative. According to a Morning Consult study, which was shared by Forbes, 24% of consumers said that they would be uncomfortable shopping for 6 months after March ( Meyers , 2020) ( Columbus , 2020). People are not comfortable shopping in person, so they are now shopping online.

Will This Go Back to Normal?

This change in behavior is likely here to stay.

Is this a permanent change? This change in behavior is likely here to stay. According to CNN Business, consumers are embracing these new changes with no sign of reverting to pre-Covid numbers ( Riley , 2020). This is consistent with the path-dependence theory, which states that humans will make choices based on previous choices. Behaviors do not change unless they have to.

People have begun shopping online as an alternative to in person shopping during the pandemic. They did this to feel safe. Even after the pandemic is over, people are likely to continue this behavior, as there will not be anything that forces them to change it. Online shopping is now more prevalent than ever and is here to stay.

UNCTAD. COVID-19 has changed online shopping forever, survey shows. (2020, October 08). Retrieved November 02, 2020, from https://unctad.org/news/covid-19-has-changed-online-shopping-forever-survey-shows

Columbus, L. (2020, April 28). How COVID-19 Is Transforming E-Commerce. Retrieved November 02, 2020, from https://www.forbes.com/sites/louiscolumbus/2020/04/28/how-covid-19-is-transforming-e-commerce/

Meyers, A. (2020, April 10). When Consumers Say They’ll Feel OK About Dining Out and Other Activities. Retrieved November 02, 2020, from https://morningconsult.com/2020/04/10/consumer-expectations-normal-activities-comfortable/

Riley, C. (2020, October 13). Online shopping has been turbocharged by the pandemic. There’s no going back. Retrieved November 02, 2020, from https://www.cnn.com/2020/10/11/investing/stocks-week-ahead/index.html

Path Dependence. (n.d.). Retrieved December 03, 2020, from https://www.britannica.com/topic/path-dependence

“Shopping trolley with medical mask.” by focusonmore.com is licensed under CC BY 2.0

To the extent possible under law, Thomas Williams has waived all copyright and related or neighboring rights to COVID 19: A Student Perspective , except where otherwise noted.

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Essay on Online Shopping

Students are often asked to write an essay on Online Shopping in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Online Shopping

Introduction to online shopping.

Online shopping is a popular way to buy goods and services. It involves using the internet to visit websites of stores and buying items digitally.

Benefits of Online Shopping

Online shopping has many advantages. It’s convenient, as you can shop anytime, anywhere. It also offers a wider variety of products than physical stores.

Disadvantages of Online Shopping

Despite its benefits, online shopping has downsides. There’s the risk of fraud, and you can’t physically check the product before buying.

Online shopping is a significant part of our lives. It’s important to be aware of its pros and cons to shop wisely.

Also check:

Advantages and Disadvantages of Online Shopping
Speech on Online Shopping

250 Words Essay on Online Shopping

Introduction.

Online shopping, a digital revolution, has transformed the traditional shopping experience. It provides a platform where consumers can purchase goods and services from the comfort of their homes, eliminating geographical boundaries.

Convenience and Variety

One of the primary advantages of online shopping is the convenience it offers. Consumers can shop at any time, from anywhere, without the need to queue in stores. Additionally, it provides a wide variety of products, from electronics to groceries, all under one digital roof.

Price Comparison and Reviews

Online shopping platforms allow consumers to compare prices and read product reviews before making a purchase. This transparency fosters informed decision-making, leading to enhanced customer satisfaction.

Economic and Environmental Impact

E-commerce has significant economic implications. It has created a global marketplace, boosting competition, and driving down prices. However, it also poses challenges to small, local businesses. Environmentally, while it reduces the carbon footprint associated with physical shopping trips, it increases packaging waste and carbon emissions from delivery vehicles.

Security Concerns

Despite its numerous benefits, online shopping is not without risks. Cybersecurity threats, such as identity theft and fraud, are significant concerns. Therefore, it’s crucial for consumers to shop on secure websites and avoid sharing sensitive information.

In conclusion, online shopping has revolutionized the retail landscape, offering convenience, variety, and transparency. However, consumers must be vigilant about cybersecurity threats. As the digital age progresses, it’s crucial to find a balance between the convenience of online shopping and its economic, environmental, and security implications.

500 Words Essay on Online Shopping

Online shopping, a term synonymous with the digital age, has revolutionized the way consumers interact with the marketplace. It denotes the act of purchasing products or services over the Internet, a practice that has seen exponential growth due to technological advancements and changing consumer behavior.

The Evolution of Online Shopping

The genesis of online shopping can be traced back to the 1990s with the advent of the World Wide Web. The first secure retail transaction over the Web was either by NetMarket or Internet Shopping Network in 1994. Today, it has evolved into a multi-billion dollar industry, with companies like Amazon, Alibaba, and eBay leading the charge. This evolution has been catalyzed by the proliferation of smartphones and high-speed internet access, making online shopping a convenient and time-saving activity.

Advantages of Online Shopping

Online shopping offers numerous advantages. Firstly, it provides consumers with a wider range of products than traditional brick-and-mortar stores. This is because online stores are not limited by physical space, allowing them to offer a more diverse selection of goods.

Secondly, online shopping allows for price comparisons. Consumers can compare prices from different online stores to ensure they are getting the best deal. This is a significant advantage over traditional shopping, where price comparison is more time-consuming and less efficient.

Lastly, online shopping offers unparalleled convenience. Consumers can shop from the comfort of their homes at any time, thus eliminating the need to travel, saving both time and energy.

Challenges of Online Shopping

Despite its numerous advantages, online shopping is not without its challenges. The most significant of these is the lack of physical interaction with the product before purchase. This can lead to dissatisfaction if the product does not meet the consumer’s expectations upon delivery.

Additionally, online shopping is susceptible to cybercrime. Consumers’ personal and financial information can be at risk if the online store’s security systems are not robust enough.

The Future of Online Shopping

The future of online shopping looks promising, with advancements in technology poised to further enhance the online shopping experience. For instance, augmented reality (AR) is expected to play a significant role in online shopping, allowing consumers to virtually try on products before purchasing them.

Furthermore, the integration of artificial intelligence (AI) will enable more personalized shopping experiences. AI can analyze consumers’ shopping habits and preferences to provide tailored product recommendations.

In conclusion, online shopping has transformed the retail landscape, offering consumers unparalleled convenience and a wide range of products. While it does pose certain challenges, the continuous advancements in technology promise to mitigate these issues and enhance the overall online shopping experience. As we move further into the digital age, online shopping will continue to evolve and shape consumer behavior.

That’s it! I hope the essay helped you.

If you’re looking for more, here are essays on other interesting topics:

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Apart from these, you can look at all the essays by clicking here .

Happy studying!

The Dangers of Online Shopping and How to Stay Safe [Video]

This past Cyber Monday, consumers spent nearly $8 billion online, with over 54% of purchases made directly from smartphones. Two days prior, on Black Friday, online sales surpassed $6 billion.

The holidays are, of course, prime time for purchases in general, and are an extreme example of the amount of shopping we do online.

But if you’re like most of us, you do plenty of your regular, day-to-day shopping online too. Why go to a store and wait in line when, with a few taps of our finger, we can have the same item shipped right to our door in a day or two?

Online shopping is extremely convenient. But here’s the catch: if we don’t take proper precautions, it can also be extremely dangerous.

The risks of shopping online

Every time we make purchases over the internet, we are potentially opening the door to:

Viruses. A malicious link, site, or ad could easily infect your machine with viruses and malware.
Scams. Bogus “sales” can trick you into paying for something you’ll never receive, or into buying fake/counterfeit items.
Stolen account credentials . The email account and password associated with your purchase could be compromised. (And if you use those same credentials elsewhere, hackers can gain access to those accounts, too.)
Stolen financial information. Credit card information and bank information could give hackers full access to your finances.
Stolen identity. If more personal information is breached, you could fall victim to identity theft.

Fortunately, there are some security best practices you can follow to help minimize your risk.

Top 7 tips on how to shop online safely

Before making any purchase online, please consider the following.

1. Use the right card

Only use a credit card that has fraud protection to make your purchase. If you use a debit card and your information is compromised, the hacker would have direct access to your entire bank account.

You can also check to see if your bank offers temporary credit cards that you can set to expire, or a reloadable prepaid credit card.

Regardless, keep record of all your transactions, and check your statements for unfamiliar activity regularly.

2. Buy from trusted, secure sites only.

Amazon and all the major retailer sites are, for the most part, a safe bet. Make sure any site you buy from has “http s ” in the address bar versus “http,” and has a padlock icon to show that it’s secure.

If you navigate to an unfamiliar site to make a purchase, do an internet search with the site name and the word “security” to see what comes up.

3. Use a secure internet connection.

Avoid making purchases over public WiFi whenever possible – bad actors can intercept your connection and access your information. If you have to use public WiFi, use a VPN to connect.

4. Only submit information you absolutely have to.

Never give any online retailer your social security number or other personal information – it’s unnecessary and likely a scam. They need a name, credit card, and shipping address, but not much else.

5. Avoid using an important email account.

Consider setting up a separate email for all your online shopping accounts and product registrations. That way, if hackers ever obtain that email address from the site you bought from (an account they can try to phish or even breach), it won’t do them much good.

6. Use strong passwords and enable two-factor authentication.

This is a best practice across the board. If you have trouble remembering passwords, consider a password manager like LastPass or DashLane.

7. If it seems “too good to be true,” it probably is.

You may receive emails about outrageous deals, or even see ads for them on your social media feeds. Approach all of these with great caution, as they could be (1) laced with malware, or (2) a scam.

Stay safe out there!

More Insights

Scam tactics you need to know.

We’ve reached another inflection point in the ongoing evolution of cybersecurity. For years and years IT service providers like us have been talking about how

CNN: How to Recognize if You Are the Target of ‘Smishing’ Scam

Image Source: CNN Our CEO Heinan Landa was interviewed by CNN to explain the new “smishing” scam targeting version users CNN’s Joe Johns reports on

Chief Executive: The Key to Thriving Through the Great Resignation

As originally published in Chief Executive December 20, 2021 Retaining Talent Through Sustaining Momentum: Tech’s Starring Role in the Great Resignation by Heinan Landa |

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Advantages of Online Shopping Essay

The internet has opened up a wide range of knowledge that has made it possible for people to adopt to new things and new experiences. The increased use of the internet has opened up a channel for online marketing and shopping. Many businesses that have a vision to globalize their sales use the internet to advertise and sell their merchandise or services worldwide.

Physical stores are complemented by websites where the store owners list their produce to fetch more customers, while some businesses operate with just the online stores. Online stores have become a popular place for shopping, as opposed to previous nonphysical methods like ordering by phone or by mail.

Research on the popularity of online shopping indicated that about half of the United States population had purchased something online. In addition to this, the number of people adapting to online shopping is expected to grow, due to the numerous benefits associated with it.

While online shopping is an ideal option, first time customers observe a few factors before they can create their trust to online businesses. It is the responsibility of the online vendor to ensure that the customers feel comfortable making purchases, by adjusting their perception of risks associated with online shopping.

Other factors that potential online customers consider include the ease of finding appropriate items, the means of delivery, and the time taken for the item to reach you.

One of the advantages of online shopping over the traditional method of going to the store in person is convenience. In the traditional system, customers had to either go to the store or send a person with instructions about the purchase.

With online shopping, it is easy to find the exact product desired, within a short time frame and using minimal effort. Online shopping saves on time since it does not require the customer to travel to the retail shop, and move about looking for the desired items.

Shopping for products online does not require much effort, as one can do it in their own homes, and use online search components to locate specific items. In addition to this, most online shops have shopping carts, which allow customers to pick items and the quantity of each product, before proceeding to the payment option.

Another benefit of online shopping is confidentiality. Buyers can purchase items and remain anonymous, in cases where the public may question their choices. A survey conducted on online shoppers indicated that most of them prefer searching for information regarding new products online, as opposed to inquiring from personnel in the retail shops.

Another appealing factor to online shopping is the convenience of shopping hours. While products may not be available instantly, a person can purchase items at any time of the day or night. There is no time limitation to rush the shoppers, since the online stores do not close.

This is especially beneficial for customers who intend to purchase items that they have never used before, as they can go through reviews from other users of the product. Discussion forums and chat rooms are also helpful in providing relevant information to the use of new products, and in making decisions regarding various brands and designs.

Online shopping eliminates the need for vendors, and the customer deals directly with the store personnel. This is good for the shopper since there is no one to persuade them in to purchasing items, which makes their choices informed and decisive.

Online stores are ideal to most people because they have unlimited space. This is good since they can display a wider variety of products, and the consumers can, therefore, find the most suitable item without their options being limited by store space, or geographical location, for the items that are not locally available. People are also able to compare different products with ease online, which leads to informed purchases.

While online shopping is a favorable option for many people, there are still a few drawbacks associated with it. The first drawback involves the fun aspect of shopping. Most people consider shopping as a fun activity that is done with friends.

The excitement associated with physical interaction with products when shopping in retail shops is lost when purchases are made online. Another limitation to online shopping concerns both privacy and security. Most people are uncomfortable with providing personal information to web sites, due to the large number of phishing sites.

Privacy is a key factor in discouraging online shopping due to increasing crimes related to credit card frauds. Other privacy concerns are undesired solicitation and use of private information for a variety of unauthorized purposes.

The third limitation of online shopping is that it requires access to both a computer and the internet. This limits the use of online services to well off people who can afford computers, or at least, have access to one.

In addition to this, an individual needs to be skilled in using the internet, in order to access web sites with online stores, and to navigate with ease. As a result, older people who are not familiar with computers and the internet cannot make use of online shopping services, and have to travel to the retail shops to purchase their items.

The fourth concern with regard to online shopping is product category risk. It is risky to purchase some items such as electronics since one cannot verify that their functional operation is as required and desired.

Apparels and perfumes also exhibit low online purchases, since most customers prefer to buy the items once they have interacted with them, and are satisfied with the operations.

The demonstrations given when making the purchases in retail shops are significant in giving the buyers the confidence that they operate and fit well. Clothes too, need to be fitted on before purchasing, so that the customer examines the comfort level of the attire.

Another concern to online shopping is indecisiveness due to exposure to a wide variety of products. While having a large number of products to choose from may be a good thing, some people get confused on the best item to purchase, and end up making a random purchase which may not be the best option. To eliminate such challenges, the online stores should organize their products in a user friendly manner.

Online shopping has many advantages, and the few demerits associated with privacy and security can be eliminated by using appropriate website designs and integration of relevant security measures, especially with regard to online payments.

This will be effective in getting people to trust the online store and, therefore, attract more customers. The use of interactive tools such as 3D technology will also give the consumers more confidence when making particular purchases. In spite of the rapid growth of online stores, the traditional methods of shopping are unlikely to be entirely eliminated.

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The Pros and Cons of Online Shopping

Pros of Online Shopping

Key Takeaways

Convenience

Greater Selection

Easy Access to Information

Can Be More Expensive

Increases Risk of Fraud

Leads to Longer Wait Times

Know Which Products To Buy Online

Read Reviews

Examine Product Details

Comparison Shop

Follow Online Retailers on Social Media

Use Money-Saving Apps or Plug-ins

How do you get your money back from an online purchase?

How has the internet changed shopping?

A study on factors limiting online shopping behaviour of consumers

Design/methodology/approach

Research limitations/implications

Originality/value

Introduction

Literature review

Research methodology

Data analysis and interpretation

Further reading

Corresponding author

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Introduction

Literature review

Perceived Risk of COVID-19

Online purchase intention

Analysis of results

PLS analysis (partial least squares)

Model evaluation—validity and reliability

Structural model assessment

Discussion of results

Final considerations

Implications of the study

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