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A Systematic Literature Review on E-Commerce Success Factors

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• First Online: 10 March 2020
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• Konstantinos Fouskas 4 ,
• Olga Pachni-Tsitiridou 4 &
• Chrysa Chatziharistou 4  

Part of the book series: Springer Proceedings in Business and Economics ((SPBE))

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Purchases from online stores are preferred by the majority of European customers. Thus, it has stimulated both academic and business interest the identification of the factors that can affect their success. The objective of this article is to increase the understanding of the factors affecting the success of an online store. Thus, it can be a tool for online shop managers to have an overview of the factors that are important for an e-shop success. To achieve this, we contact a systematic literature review which tries to determine the success factors. In order to achieve this, we examine 24 articles published between 2013 and 2017 from peer-reviewed journals and conferences. Then we classify the factors in four main categories design and site presentation, e-marketing techniques, trading, delivery and customer support before and after the purchases and site’s reliability, safety and reputation.

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Konstantinos Fouskas, Olga Pachni-Tsitiridou & Chrysa Chatziharistou

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Fouskas, K., Pachni-Tsitiridou, O., Chatziharistou, C. (2020). A Systematic Literature Review on E-Commerce Success Factors. In: Kavoura, A., Kefallonitis, E., Theodoridis, P. (eds) Strategic Innovative Marketing and Tourism. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-36126-6_76

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After-sales attributes in e-commerce: a systematic literature review and future research agenda.

1. Introduction

2. methodological procedures, 2.1. first step: assembling, 2.2. second step: arranging, 2.3. third step: assessing, 3.1. structured review, 3.1.1. trends and thematic analysis: after-sales customer services, fulfillment, return and refund, customer support, ratings and comments, 3.1.2. world cloud, 3.1.3. typological analysis, 3.2. bibliometric review, 3.2.1. descriptive analysis of the corpus, 3.2.2. bibliographic coupling analysis, 4. discussion, 5. conclusions and future research agenda, 5.1. future research agenda, 5.1.1. exclusive after-sales studies, 5.1.2. longitudinal studies: detailing the after-sales journey, relationship between constructs and purchase recurrence, 5.1.3. post-purchase behavior, 5.1.4. application of the studies in different market contexts and geographical regions, 5.1.5. delving deeper into each of the clusters presented in this review, 5.1.6. ewom and disconfirmation and dissonance concepts, 5.1.7. the role of technology in the development of post-purchase e-commerce, 5.2. limitations, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Ferraz, R.M.; da Veiga, C.P.; da Veiga, C.R.P.; Furquim, T.S.G.; da Silva, W.V. After-Sales Attributes in E-Commerce: A Systematic Literature Review and Future Research Agenda. J. Theor. Appl. Electron. Commer. Res. 2023 , 18 , 475-500. https://doi.org/10.3390/jtaer18010025

Ferraz RM, da Veiga CP, da Veiga CRP, Furquim TSG, da Silva WV. After-Sales Attributes in E-Commerce: A Systematic Literature Review and Future Research Agenda. Journal of Theoretical and Applied Electronic Commerce Research . 2023; 18(1):475-500. https://doi.org/10.3390/jtaer18010025

Ferraz, Rodolfo Magalhães, Claudimar Pereira da Veiga, Cassia Rita Pereira da Veiga, Thales Stevan Guedes Furquim, and Wesley Vieira da Silva. 2023. "After-Sales Attributes in E-Commerce: A Systematic Literature Review and Future Research Agenda" Journal of Theoretical and Applied Electronic Commerce Research 18, no. 1: 475-500. https://doi.org/10.3390/jtaer18010025

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A systematic review of e-commerce websites literature in 2010-2020 period

Business & Management Studies: An International Journal

In parallel with the increasing e-commerce usage rates worldwide, academic papers on e-commerce have increased in the last decade. In this regard, in this study, the papers on e-commerce indexed in the Web of Science (WOS) database between 2010 and 2020 are examined and discussed by journals, published years, countries, sample size, main purposes, theories, variables and main findings. Therefore, 70 selected research articles were examined. The selection criteria of these articles are to be research articles and to collect data from consumers using e-commerce websites. Therefore, 70 selected articles were examined and evaluated by using the content analysis method. As a result of the analysis, selected articles are summarised in Appendix 1. The selected articles have some common inferences: the reputation of websites, size of websites, familiarity, perceived ease of use, recommendations, design, convenience, perceived usefulness, system quality, service quality and information quali...

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AN OVERVIEW OF RESEARCH ON E-COMMERCE ADOPTION: FUTURE TRENDS, 2021

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Sustainable and resilient e-commerce under COVID-19 pandemic: a hybrid grey decision-making approach

Saleh yahya alwan.

1 College of Economics and Management, Northeast Forestry University, Harbin, China

Ahmed Abdulwali Mohammed Haidar Al Asbahi

2 College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China

Yaser Khaled Al Harazi

Ahmed khaled al harazi.

3 School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan, China

Associated Data

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

E-commerce saw a paradigm shift during COVID. Consumers turned to online shopping when pandemic lockdowns caused brick-and-mortar stores to shut for extended periods. Although the pandemic drove more buyers online, it had negative impacts that affected e-commerce performance. This study assesses both positive and negative impacts and their relative significance. The findings are then used to prioritize different strategies for e-commerce development in four vibrant Middle Eastern economies: United Arab Emirates, Saudi Arabia, Qatar, and Kuwait. The study employs a hybrid approach incorporating grey analytical hierarchy process (GAHP) and grey relational analysis (GRA). The GAHP evaluates the relative significance of impacts, whereas the GRA ranks the strategies. The study is based on the responses from 36 local e-commerce specialists. The findings revealed that the supply chain disruption was a rather significant factor, and that “expanding supplier base” was a top-ranked strategy. The study suggests that increasing market share of e-commerce will necessitate the improvement of the supply chains, including the expansion of the supply base, as well as the establishment of sustainable supply chains. In addition to that, the moment has come to implement meaningful changes, such as digital transformation of supply chains, in order to fulfil customer expectations.

Introduction

Electronic commerce (or “e-commerce”) involves the buying and selling of goods and services through the Internet (Kitukutha et al. 2021 ). The payment for such a transaction can be performed online, eliminating the need for the seller and purchaser to meet in person. However, cash on delivery is still another alternative (Jaller and Pahwa 2020 ). E-commerce has grown in popularity since the emergence of the coronavirus disease (COVID-19). COVID-19’s spread boosted e-commerce as a platform for business between consumers and retailers and between enterprises (Myovella et al. 2020 ). People turned to online shopping since they were unable to leave their homes due to restrictions (Yuan et al. 2021 ). This made people keen to try new online shopping options for essential and non-essential goods. E-commerce platforms, on the other hand, delivered products and services to consumers’ doorsteps; sites that offered non-essentials before the pandemic began selling food, masks, sanitizers, and other essentials. (Ali Taha et al. 2021 ).

The growth of the e-commerce after the pandemic has been phenomenal. According to research conducted by Nint, Inc., sales in Japan’s three largest e-commerce marketplaces (Rakuten, Amazon, and Yahoo) grew by 7% in January, 13% in February, and 14% in March 2020 compared to the same month the year before. Specifically, online sales of medical products surged significantly. While global retail sales were forecasted to fall 3% in 2020, eMarketer predicted a 28% growth in retail e-commerce sales (Hayakawa et al. 2021 ). According to the most recent research, COVID-19-related business restrictions have triggered a global paradigm shift toward the digital economy, which has severely impacted conventional business models while simultaneously creating possibilities through the diversification of online sales. This clearly indicates the influence of the pandemic on worldwide e-commerce revenues, putting an extra 19% sales growth for 2020 and an additional 22% sales growth to the current 9% and 12% normal anticipated sales growth rates, respectively. Aside from providing secure shopping and access to critical supplies during COVID-19 shutdown, e-commerce is also recognized for benefiting farmers by building block chain technology, which allows them to sell their products directly to wholesale purchasers, bypassing intermediaries. This has aided farmers’ financial growth while also decreasing waste (Galhotra and Dewan 2020 ).

In addition to its positive effects, COVID-19 had detrimental impacts on e-commerce. The pandemic adversely influenced e-commerce in a number of locations, including America, Europe, Asia, and the rest of the world. In Europe, the most instances were documented in Italy, Spain, Germany, France, and China, whereas in Asia, the most cases were recorded in China. Alibaba, China’s largest supplier of e-commerce services, battled to sustain growth rates in its domestic market while dealing with the unpredictability of coronavirus. Amazon.com, Inc., Alibaba Group Holding Ltd., Qoo10 Pte. Ltd., Walmart Inc., eBay Inc., JD.com, Rakuten Group, and Shopify are among the major corporations affected by the market. Amazon, for example, made significant investments in a 1-day shipment that has yet to be repaid (Abdelrhim and Elsayed 2020 ). The lockdown had a significant impact on manufacturing, transportation, and distribution, resulting in unclear supply chain concerns for the e-commerce business. This impacted a wide range of firms, including older retailers such as Walmart, which saw a decrease in informal buying, shocks, and an increase in the purchase of essential necessities, food, basic toiletries, and other items. Other online firms found it extremely difficult to sell their items online and encountered significant difficulties while getting their products from China (Moosavi et al. 2022 ).

Despite the negative impacts, e-commerce has a bright future ahead of it. Traditional trade shares have become volatile and in sharp decline; this will be a powerful motivator for these traditional market traders to transfer to online trading to save the remainder of their shares and keep their commercial field and market success. To succeed in the post-pandemic era, e-commerce must adopt competitive strategies that make digital platforms resilient and sustainable. Numerous such measures to enhance resilience and sustainability in e-commerce have been documented in the literature. These measures should be prioritized depending on their ability to establish resilient and sustainable e-commerce after COVID-19. Before continuing with the prioritization process, it is necessary to understand the significance of the different COVID-19 impacts on e-commerce. The efficient way of comprehending the significance of the impacts is to quantify them. However, most studies have merely identified those impacts; studies that assess the relative importance of these impacts in the adoption of e-commerce in the post-pandemic era are lacking. Thus, this work addresses a research need. It starts with a review of current literature to assess the impacts and potential strategies; later, it measures the relative importance of impacts; and finally, it prioritizes the competitive strategies to make e-commerce resilient and sustainable.

For the analysis, multi-criteria decision-making (MCDM) methods were employed because analyzing impacts and strategies is a complicated and multifaceted subject, and no other approaches are as effective for such a task as MCDM methods (Solangi et al. 2019 ). Two well-known MCMD approaches, grey analytical hierarchy process (GAHP) and grey relational analysis (GRA), were used. The study is based on the experts’ opinions, which were gathered using a couple of questionnaires. The initial questionnaire collected data for comparing impacts; this data was then processed using GAHP to obtain weights of impacts. The second questionnaire asked experts to score each strategy in relation to each impacting factor; the resulting data was utilized in GRA for prioritizing.

The remainder of the paper is structured as follows: “ Literature review ” section is the literature review, which examines relevant papers and identifies research gaps. In addition, the section explores COVID’s influence on e-commerce and post-COVID digital platform strategies. “ Methodology ” section describes the methodological framework, which consists of two well-known MCDM methodologies (the grey analytical hierarchy process (GAHP) and the grey relational analysis (GRA)). The GAHP quantifies the relative magnitude of various impacts, while the GRA prioritizes strategic pathways. “ Case study ” section presents the findings and discusses them. “ Results ” section is the conclusion, which summarizes the work, discusses its limitations, and makes recommendations for further research.

Literature review

E-commerce occurs when a buyer and seller make commercial transactions through the Internet. E-commerce businesses are classified into the following categories: customer-to-customer (C2C), business-to-consumer (B2C), business-to-business (B2B), business-to-government (B2G), and mobile commerce (M-commerce). The terms “e-commerce” and “online shopping” are sometimes used interchangeably, although e-commerce is considerably larger than this—it encapsulates a notion for doing online business, integrating a variety of various services such as making electronic payments and booking tickets.

Three major factors driving the development of e-commerce include wider variety, lower pricing, and accessibility and convenience (Morrish 2015 ). More variety has been a major factor in the expansion of online buying over the last two decades. Because of almost limitless selection of brands and items to pick from, customers are not restricted by the availability of certain items in their local city or country. Goods may also be sourced and transported throughout the world. One recent study discovered that customers are becoming frustrated with e-commerce websites that provide excessive options. However, more options have almost certainly been a beneficial thing in the long run (Musaad et al. 2020 ).

Managing an Internet store is significantly less expensive than managing an offline, brick, and mortar shop. An online shop generally requires fewer staff because web-based management solutions enable owners to automate inventory control, whereas warehousing is not always required. As such, e-commerce companies can pass operational cost reductions on to customers by giving discounts on products and services while still maintaining their profit margin. Moreover, the increased availability of price comparison websites provides customers with better cost transparency, which typically drives customers to purchase from online shops rather of brick-and-mortar stores. E-commerce websites, unlike many conventional stores, are open 24 h a day. Customers may learn about services, browse for items, and place orders at any time. This makes Internet shopping extremely simple and gives buyers more control. Furthermore, people who reside in remote areas may order from home with the press of a button, saving them the time it takes to get to a shopping center.

Impacts of COVID-19 on e-commerce

Numerous latest studies have assessed the impact of COVID-19 on e-commerce. For instance, Galhotra and Dewan ( 2020 ) set out to investigate the impact of COVID-19 on e-commerce in India. The authors found remarkable dependability on China. Due to travel restriction, shipment from China hindered which ultimately reduced the growth of e-commerce in the country. The analysis in the study revealed that online businesses were critically impacted in India due to the pandemic.

Hasanat et al. ( 2020 ) assessed the effect of COVID-19 on Malaysian online businesses. The study assumed that the deadly virus had a significant impact on Malaysian e-commerce, particularly on Chinese items, because many e-commerce enterprises in Malaysia rely on China for half of their retail products. For this study, a survey was undertaken, as well as primary research, in order to obtain a better result. The findings demonstrated that the majority of the items originate from China, and the majority of the industries are locked down, implying that there is no product import or export. Kim ( 2020 ) looked at the pandemic as a catalyst for structural changes in consumer and market digitalization. According to the study, managers frequently take a wait-and-see strategy regarding COVID-19’s influence on sales. It is sometimes unknown whether or not consumers will return once the pandemic has ended. Furthermore, certain changes may linger even after the situation improves. The research suggested that managers react to the market’s digital change in order to recoup or perhaps increase sales following COVID-19. Shahzad et al. ( 2020 ) conducted a quantitative online survey-based study to investigate the influence of COVID-19 on e-commerce in Malaysian healthcare. The information was gathered mostly from hospital administration, doctors, medical assistant nurses, and medical suppliers in Peninsular Malaysia. The study found that organizational preparation, e-commerce competence, and supply chain integration all had a considerable favorable influence. In comparison, information technology infrastructure and external pressure have little impact on e-commerce adoption.

Dinesh and MuniRaju ( 2021 ) attempted to comprehend the characteristics that help e-commerce enterprises improve their operations throughout the pandemic. The research also sought to learn about consumer behavior during COVID-19. The study indicated that COVID-19 pandemic had a significant impact on individuals all around the world. The pandemic compelled customers to purchase online due to their concerns about safety. According to the findings, the rate of online buying has grown over the pandemic era. The study recommended that both physical and online shops must invest in intelligent technology in order to boost client engagement. Hoang et al. ( 2021 ) did empirical research on the use of e-commerce by small and medium enterprises (SMEs) to steer the economic recovery in Vietnam following COVID-19. The study underlined that COVID-19 triggered a significant economic catastrophe. It also emphasized how, despite the pandemic’s brief duration, various innovations were applied to ensure organizational survivability and revival in the digital era’s competitive market environment. The primary goal of the article was to identify major determinants and their effects on e-commerce adoption among SMEs in Vietnam, particularly during pandemic times. According to the findings, technological compatibility had the greatest influence on e-commerce adoption during COVID-19, preceded by managerial support and external pressure, with external support having the least impact. It can be seen that the review of the literature revealed both good and negative effects of COVID-19 on e-commerce. The most common impacts documented in the literature are discussed in the following sub-sections.

Increased online audience

When several major cities proclaimed self-isolation and implemented lockdowns and social isolation, the activities of Internet users skyrocketed. The data shows that the number of active and new users of online and mobile applications has increased significantly. This increase in online audience numbers can be seen as early as the first week of March, 2020 (Jebril 2020 ). A similar pattern may be seen in online mobile applications. Apps that provide food delivery services and facilities account for the most of new and active audiences in online mobile applications.

An increase in the online audience can be critical to the growth of e-commerce. The global Internet statistics show that more than half of the world’s population has Internet access (according to Nadanyiova et al. 2020 , 4.2 billion people have access to the Internet), with 58% adoption, and 85% of those use it for online shopping and information search. A survey of worldwide e-commerce activity finds that the overall number of users is 4.57 billion, or 59% of the entire population, with a + 7.1% or around 301 million individuals spending roughly 6 h each day on Internet shopping; 81% use the Internet to look for a product or service to purchase, 90% visit online shopping websites, 66% use a smartphone app to accomplish online shopping, 74% order a product or service online at least once a week, and 51% use social commerce and mobile commerce. Table ​ Table1 1 gives population estimates for global Internet penetration.

Global Internet penetration and usage based on population (Kitukutha et al. 2021 )

Increased online consumer demand

The pandemic has expedited the transition to a more digital society and spurred shifts in online buying patterns that seem to have long-term impacts. Before COVID-19, e-commerce was rapidly expanding, but the pandemic drove even more shoppers online. The pandemic is causing a dramatic and profound change in consumer behavior. As per the United Nations Trade and Development (UNCTAD), the e-commerce industry has seen an exceptional increase in its percentage of total retail sales. The Global Consumer Insights Pulse Survey demonstrates a significant shift to online shopping, as people were initially confined by lockdowns and then managed to work from home (Villa and Monzón 2021 ). Additional tendencies in this transition toward digital consumption involve online customers looking for the greatest deal, choosing healthier alternatives, and becoming more eco-friendly by purchasing locally wherever feasible.

Customer behavior was impacted by both COVID-19 and government constraints. Consumers of all generations reported buying more items and services online during the pandemic, but Baby Boomers were important drivers of e-commerce expansion. Overall, there has been a considerable shift toward digital purchase, with 43% of all respondents shopping online since the beginning of the crisis, up from 12% before the crisis. The frequency of purchases has also grown. Across all demographic groups, 25% of respondents acknowledged weekly Internet shopping, compared to 9.8% before the pandemic (Jílková and Králová 2021 ).

Ghandour and Woodford ( 2020 ) noted an exceptional increase in online customer demand in many product categories following the outbreak of COVID-19. For example, they claimed that demand for skincare items increased by 143.96%, with orders from new consumers accounting for 99.92% of the increase. Likewise, they noted a worldwide increase in healthcare items including masks, sanitizers, and medications. Global corporations have also faced a comparable spike in online demand, forcing them to make critical modifications to their business procedures. To accommodate the increased online demand, Amazon, for example, employs roughly 300,000 full-time staff and expects to add another 250,000.

Additionally, even late adopters who may not have previously shopped online have been compelled to do so since they have no other option while sheltering in place. Following COVID-19, a significant portion of such late adopters who had previously been reticent to buy online rushed into e-commerce (Kim 2020 ).

E-commerce surged in 2020 as a result of business closures and customers’ fear of contracting the coronavirus outside. Global traffic on retail platforms increased dramatically between January 2019 and June 2020. Retail websites generated approximately 22 billion visitors in June 2020, representing a 35.5% increase year on year (Villa and Monzón 2021 ). In the USA, e-commerce increased its percentage of overall retail sales from 11.8 to 16.1% during the first and second quarters, while in the UK, it increased from 20.3 to 31.3%. In the EU-27, retail sales over the Internet increased by 30% in April 2020 compared to April 2019, although total retail sales decreased by 17.9% (OECD 2020a ). The trend persisted until 2021, when immunizations were widely accessible. Furthermore, consumer demand for products increased, as people spent their stimulus cheques and reallocated cash that would have gone toward costs like travel and restaurants to house maintenance and furnishings, among other things.

Supply chain disruption

Without a question, the economic circumstances that have resulted from COVID-19 outbreak have been unparalleled. Never before have so many worldwide closures, shortages, and travel bans happened at the same time, wreaking havoc on both communities and businesses. One of the most serious consequences of these incidents is the disruption of the global supply chain.

According to Majumdar et al. ( 2020 ), Haak-Saheem ( 2020 ), and Karmaker et al. ( 2021 ), the latest pandemic is a rare incidence of supply chain disruption that is having a significant impact on the global economy. The majority of those impacted are supply chains for critical items like healthcare and food supplies, as well as other essentials like sanitizers and toilet papers. Sharma et al. ( 2020 ) observed serious disruptions in India’s healthcare supply chain as the infection worsened the situation. Barman et al. ( 2021 ) emphasized the economic ramifications of COVID-19, as well as the effects of the lockdowns on the food supply chain and agribusiness. According to the research, business operations and supply of various food items have been halted owing to a reduction in demand, the closure of food manufacturing facilities, and financial constraints. Mahajan and Tomar ( 2021 ) examined the food supply chain disruption caused by the pandemic-induced economic shutdown in India. The study found that product availability for vegetables, fruits, and edible oil decreased by 10%, but the price impact remained minor. It was mirrored by a 20% drop in vegetable and fruit arrivals at the farm gate. The analysis indicated that the major cause of the decrease was supply chain disruption. Paul and Chowdhury ( 2020 ) emphasized that COVID-19 has the greatest impact on manufacturing supply chains. This impact makes it more difficult for makers of high-demand, necessary goods like hand sanitizer and toilet paper. The authors noted that in a pandemic situation, the demand for vital items grows dramatically; yet, the availability of raw materials reduces significantly due to manufacturing capacity constraints. These two disturbances have a sudden influence on the manufacturing process, and it may collapse if urgent and appropriate steps are not taken.

Cross-border restrictions and city lockdowns have confounded and exacerbated the issue. The majority of suppliers kept items in their warehouses, causing shortages and panic in society. As a result, people are compelled to purchase as much as possible in order to stock up at home (Chakraborty and Maity 2020 ). Due to the influence of COVID19, the increased demand for items with limited availability led prices to rise. The most frequently purchased things online are masks, pain relievers, vitamin C template, sanitizers, aprons, and cleaning soaps. Hospitals, on the other hand, have a strong requirement for personal protective equipment (PPE) to prevent COVID-19 from spreading further.

According to the global e-commerce industry research, the impact of COVID-19 on these industries has been widespread owing to supply chain and customer demand uncertainties throughout the world. The majority of the time, e-commerce supply chains are hectic. Apart from China, the USA and other countries have shut down factories. Electronic items are the most affected by COVID-19 epidemic, as China accounts for the majority of COVID-19 infections and is the worlds largest producer of electronics and their parts (Ping and Shah 2022 ). A significant portion of China’s imports of electronic components that are integrated into finished products such as consumer electronics and computers are subsequently included. However, as a result of the plant closure, the electronics product supply chain is now on the verge of impacting the e-commerce electronics business (Fernandes 2020 ).

Extended delivery time

E-commerce needs an effective trade environment in order to match client expectations of quick and easy delivery. COVID-19, on the other hand, significantly slowed deliveries and extended delivery timeframes. This was most likely due to lockdowns in such locations and the shutdown or underutilization of local postal services. Some countries restricted the flow of post that entered their countries, resulting in significantly longer wait times for orders to be delivered. This increased delivery times in most locations by up to 30 working days, and much longer in more difficult-to-reach places (Bhatti et al. 2020 ). The longer delivery delays had an influence on online sales, emphasizing the complementarity of online and offline sales platforms. People began to shop at offline retailers once the lockdown was eased in order to avoid having to wait for delivery for extended periods of time. As a result, even if Amazon’s own sales were 26% higher in the first quarter of 2020 than the previous year, its proportion of overall e-commerce in the USA declined from 42.1% in January 2020 to 38.5% in June 2020. Amazon, in particular, lost 4.2 to 5% of its market share to Walmart and 2.2 to 3.5% of its market share to Target (OECD 2020b ). It may be assumed that these and related businesses undoubtedly benefited from extensive networks of physical stores, allowing for quick deliveries and curbside pickups.

Labor shortage

Last but not least, the business industry as a whole, including e-commerce, is experiencing a labor shortage. The pandemic increased digitization and e-commerce growth, necessitating the hiring of even more logistics workers. The rapid expansion of e-commerce makes order-picking highly labor-intensive, requiring warehouse and logistics corporations to hire more personnel than ever before. On the other hand, when more people call in sick, become infected with the virus, or struggle to find childcare, the already critical shortage of delivery personnel intensifies. In addition, e-commerce companies bracing for steps such as wage cutbacks and layoffs to reduce the effect of company losses add to the decline in e-commerce delivery (Suguna et al. 2021 ). In the warehouse, good employees have been prevented from working due to the pandemic because they are afraid of contracting the virus and have childcare obligations that prevent them from working full-time hours. In other instances, state and federal unemployment benefits act as a deterrent to returning to work (Shen and Sun 2021 ). As a result, warehouse labor is in limited supply to satisfy the present number of e-commerce orders.

The labor shortages caused by COVID-19 affect nearly every industry that interacts with customers; retailers are hard hit as well. Retailers faced a slew of challenges, including inventory shortages, manufacturing delays, and delivery limits, to mention a few (Larue 2020 ). The most noticeable shortfall, however, was in the work force. Retail employees interact often with customers. The rise of services such as buy online, pick up in store, curbside pickup, and home delivery has complicated their job even further. Grocery retailers, in particular, are facing new obligations in order fulfilment as more retail activity transitions to e-commerce (Hobbs 2020 ). The retailer now must pay a staff to do the same task that an in-store consumer formerly did for free. There are additional laborious tasks that must be completed. A growing number of unwell, exposed, or overworked personnel prompted retailers to adopt unusual measures as their labor difficulties increased. Macy’s reduced store hours in several regions. Walmart temporarily shuttered roughly 60 locations in coronavirus high regions. Other firms, such as Starbucks, Nike, and Chipotle had to close some of their locations due to a lack of employees.

Competitive strategies for digital platforms after COVID-19

COVID-19 has accelerated the digitization process across all ecosystems, ushering in a new retail experience as a future trend (Pahwa 2020 ). This sub-section overviews competitive strategies that can support digital platforms to keep up with the new trend of consumer demand through e-commerce mechanisms.

Digitalization of public and private sectors

Crucial platforms for digitalizing both the commercial and public sectors of the economy must be established as working remotely will need the establishment of such platforms. These platforms should validate users’ credentials and enable them to conduct transactions in a safe environment (Mahroum 2021 ). This might be one of the foundations for the effective digitalization of infrastructure, allowing the economy to develop and become more stable in the next years (Ghandour and Woodford 2020 ).

Collaboration with e-vendors

The interruption and collapse of the supply chain harmed retail and e-commerce. However, by collaborating with transporters and e-commerce sellers, it is possible to assure that products and services reach all locations (Dash and Chakraborty 2021 ).

Monitoring of customer preferences and tastes

Online businesses preserve a record of every consumer that visits their website, allowing them to track customer interests and tastes. As a consequence, merchants send email promotion alerts to customers. Special deals and promotions serve to entice the majority of potential consumers, converting them into real buyers (Kang et al. 2020 ). These tendencies readily switch clients to online buying (Bigorra et al. 2020 ).

Modification to regulatory frameworks

Changes and modifications to regulatory frameworks are critical to supporting the growth of e-commerce. Prior to the coronavirus, there had been an upsurge in remote workers throughout the world. Coronavirus, according to leading market participants, will fundamentally alter the nature and dynamics of occupations and employment. Remote employees are expected to make up about 73% of all departments by 2038 (Haak-Saheem 2020 ). As a result, it is not advantageous to struggle against changing market conditions. Rather, there is a need to remain solid and adapt to various developments, as well as amend legislation and frameworks to encourage the growth of online commerce.

Expansion of the supply base

The disruption of supply chain networks continues to be the most significant impact on the e-commerce business. As illnesses spread, a huge number of nations ceased exporting products and services to other countries. Workers were victims of COVID-19, which harmed supplier dependability and reduced their operations to a halt. Therefore, as research produced in the context of the global economy suggests (Ranney et al. 2020 ), expanding supplier base has become critical for the economies.

Development of an effective risk management system

Assess all related risks early on to prevent a financial crisis from impeding e-commerce growth. Countries who are unable to create an adequate risk management system in their e-commerce activities are expected to lag behind by 5 to 10 years. To avoid the failure of the e-commerce business, appropriate risk management mechanisms should be set up, as either supply will outnumber demand or vice versa (Woong and Goh 2021 ).

Implementation of extended payments or payments at regular intervals

Customers should be prioritized in this situation, taking into consideration their existing financial limits. This may be accomplished by providing consumers with payment invoices that can be extended or payments made at regular intervals (Babenko et al. 2019 ). Through this, firms or stores can reestablish consumer confidence, which has been eroded as a result of the decline in jobs and income.

Integration of cutting-edge technologies

Retailers all over the world have begun to integrate new technology into their workflow in order to better serve their customers using virtual reality systems and artificial intelligence (Ghandour and Woodford 2020 ). They gather cognitive data and analytics in order to give a more tailored and individualized experience to their customers. To improve sales and maximize the decreased customer quantity, the user’s product preferences are tracked, and only related or related goods are offered. Furthermore, retailers have gone a step further and provided consumers with a virtual reality system so that they may examine the goods more precisely and appropriately.

Methodology

Identifying the most consequential impacts and pertinent strategies is a complex endeavor requiring analysis across several dimensions (Longsheng and Shah 2022 ). Although there is no commonly acknowledged method to analyze such problems, most studies have used multi-criteria decision-making (MCDM) strategies for a multidimensional analysis (Xu et al. 2019b ; Jiskani et al. 2020 ; Muhammad et al. 2020 ; Solangi et al. 2020 , 2021 ; Ali et al. 2021 ; Shah et al. 2021 ). The present research also used an integrated MCDM framework to evaluate impacts and prioritize measures. There are a variety of MCDM methods including Delphi, AHP (Shah et al. 2019a ), data envelopment analysis (DEA) (Mohsin et al. 2018 ; Shah et al. 2019b ), analytical network process (ANP), the technique for order of preference by similarity to ideal solution (TOPSIS), decision-making trial and evaluation laboratory (DEMATEL), and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). These methods have been extensively combined to build hybrid decision support systems. For instance, a recent study conducted by Kamranfar et al ( 2022 ) integrated DEMATEL, Delphi, and ANP to build a hybrid decision-making tool for analyzing green construction development barriers. Gheibi et al ( 2022 ) designed a hybrid decision support system based on the Gaussian model and genetic algorithm in order to examine strategies for removing cyanide contamination from drinking water systems through chlorination. Shahsavar et al ( 2022 ) designed an efficient and comprehensive decision-making framework for a green city and sustainable development goals to manage municipal plastic waste. The study modeled the bio-recovery of municipal plastic wastes using a unique integrated MCDM technique that intelligently combines Shannon Entropy, Ordered Weighted Aggregation, AHP, TOPSIS, and ELimination Et Choice Translating REality (ELECTRE) systems.

The current study integrates AHP and GRA methodologies since, among the MCDM approaches, they are the ones that are the most appropriate for the problem at hand and also the ones that are the simplest and most efficient (Jiskani et al. 2021b ). The research integrates grey system theory with the proposed models for coping with ambiguity and uncertainty in decision-making. The theory is determined to be the most effective in removing ambiguity and uncertainty from the data (Zhuo et al. 2020 ). As a result, the models are better equipped to handle the ambiguity included in the experts’ comments.

Figure  1 displays the study’s research framework, which involves three steps. In the first step, a thorough literature analysis is conducted to examine the impact of COVID-19 on e-commerce. Grey AHP is then used to analyze and quantify the relative significance of the impacts. In the final step, GRA is used to prioritize strategies based on their success in the development and smooth operation of e-commerce in normal days, as well as to adequately prepare for potential emergencies. The subsections that follow offer a brief description of the methodologies, which include computational steps used in the study.

Hybrid research framework

Grey system theory

Julong presented grey theory in 1989 as a mathematical technique to dealing with situations requiring unclear decision making (Julong 1989 ). The theory has five major components: grey relational analysis, grey programming, grey forecasting, grey control, and grey decision-making. In comparison to typical statistical techniques, grey models use less data to assess the function of ambiguous systems and generate a reliable and impartial point estimate (Liu and Forrest 2010 ). In grey systems, items like function, process, structure, and behavior are not predictable or fully unknown, but they are known in part. The grey system separates information into three groups: “white,” “grey,” and “black,” corresponding to information that is “totally-known,” “partially-known,” and “completely unknown.” The sign ⊗ is frequently used to represent grey numbers. In the Appendix of this article, the procedures for performing arithmetic operations on grey numbers are detailed.

Grey numbers are used in this study to represent subjectivity and lessen variance in decision-makers’ judgments. The linguistic scale with grey number notation used in this study is shown in Table ​ Table2. 2 . The assessment values must be converted to grey numbers in the appropriate way.

Grey linguistic scales

Analytical hierarchy process (AHP) is a structural MCDM methodology for organizing and evaluating complex decision-making operations (Shah 2019 ). Since its inception by Saaty in 1977, AHP has grown in popularity (Saaty 1977 ). In AHP, both numerical and subjective data may be utilized to make judgments based on a range of criteria (Xu et al. 2019a ). Pairwise comparisons are used to derive the priorities of alternatives in respect of stated criteria (Longsheng et al. 2022 ). AHP has served as a foundation for several MCDM techniques and has also been combined with other methods (Alshehri et al. 2022 ). Grey AHP (GAHP) integrates AHP with grey system theory to reduce evaluative judgments in decision making. The essential approach of GAHP is the same as that of AHP, with the distinction that GAHP employs grey numbers instead of crisp numbers (Jiskani et al. 2021a ). The representation of grey numbers and the linguistic phrases employed in GAHP are shown in Table ​ Table2, 2 , while the steps of the approach (Shah and Longsheng 2022 ) are given in the Appendix.

Grey relational analysis

Grey relational analysis (GRA) is a crucial technique of grey theory that serves as the basis for grey theory modelling, analysis, forecasting, and decision-making. Grey relation is an indeterminate relationship formed by two variables. The basic concept of GRA is to examine the geometric proximity of distinct curves to determine their connection; the greater the similarity in form, the stronger the correlation between two variables. Assessing the degree of correlation between numerous variables and identical reference sequence yields dominant factors. GRA can compute the fundamental connection even when there is limited or poor information (Kuo et al. 2008 ). It is regarded as one of the most significant contributions to the subject of uncertainty system research. GRA eliminates the shortcomings of fuzzy or stochastic approaches. The advantage of GRA over fuzzy and scholastic approaches is that GRA can deal with fuzzy internal information, whereas both fuzzy and stochastic need accurate internal information (Akay et al. 2011 ). Therefore, this study employs GRA to evaluate digital platform strategies for coping with the impacts of COVID-19—the process shall reveal how important each strategy is in addressing the impacts. The method is applied according to the steps detailed in the Appendix.

The vibrant metropolis that emerged from the Gulf’s deserts in recent decades are now significant global hubs for investment and innovation. Saudi Arabia, the UAE, Qatar, and Kuwait are now among wealthiest countries with highest GDP per capita in the world. And, as government and the private sector actors continue to invest in startups, and emerging technologies with the potential to stimulate economies and transform society, the Middle East is resolved to be a role model of business rather than a follower (Wilson 2021 ). When COVID-19 began to have an impact on global markets, it became apparent that it would put the endurance and effectiveness of the Middle East’s rapidly growing e-commerce sector to the test (Charbel et al. 2020 ). This is notably true in the four main markets of the research, which are the United Arab Emirates (UAE), the Kingdom of Saudi Arabia (KSA), Qatar, and Kuwait.

Despite making up only 2% of the region’s retail industry, e-commerce increased from $4.2 billion in 2015 to $8.3 billion in 2017 (Mohammed et al. 2021 ). This was brought on by the rapid expansion of the Internet, the introduction of 4G, and a young population that felt comfortable making transactions online. In 2020, 80% of young Arabs shopped online on a regular basis, up from 71 in 2019. Furthermore, following the pandemic, 50% of people aged 18–24 in the region are purchasing more online. Because of this, the sector was worth $22 billion to the end of year 2020. The UAE, Saudi Arabia, Qatar, and Kuwait drove the majority of the sector’s development, accounting for 80% of the region’s entire e-commerce industry (Alkhaldi 2020 ; Sindakis and Aggarwal 2022 ). Before COVID-19, the digital sector of UAE accounted for 4.3% of national GDP. Furthermore, according to the Dubai Future Foundation, the country’s e-commerce market is anticipated to hit $62.8 billion by 2023. The industry in Saudi Arabia predicted a trade volume of $8.2 billion to the end of year 2024 (Alflayyeh et al. 2020 ).

COVID-19 marked a turning point in the year 2020. Global efforts to mitigate the pandemic’s impact have interrupted, modified, and reconfigured both commercial and consumer behaviors. The retail industry was among the most hurt by the global lockdowns. Footfall in the Middle East fell significantly, and border restrictions were tightened. Unfortunately, because many stores were unable to withstand such significant economic upheavals, their “closed shop” signs became “permanently closed.” This created an opportunity for e-commerce in the region, as people began purchasing items online (Salem and Nor 2020 ). The pandemic accelerated this anticipated increase since early reports showed that e-commerce in the region was outpacing the pandemic.

This study investigates how the pandemic influenced the e-commerce business in order to prioritize solutions to capitalize on this momentum. The report examines how the pandemic affected the development and endurance of the e-commerce landscape in these four countries. By changing consumer choices and logistical patterns, e-commerce has the ability to fundamentally transform how economies function (Alshehri et al. 2022 ). This tech-driven shift can create ecosystems that welcome small and local enterprises into the value chain, while the impetus of e-commerce can fuel the region’s growth. The research involved 36 industry experts, yielding some critical findings and recommendations on how e-commerce may continue to develop in the present and future landscapes.

Assessment of impact and prioritization of e-commerce competitive strategies is a MCDM problem that needs consideration of both qualitative and quantitative attributes. E-commerce firms should be able to devise strategic responses to possible disruptions. In this research, an integrated GAHP and GRA methodology is applied to calculate the exact closeness of each competitive strategies with the ideal referential strategies. Also, critical attributes contributing toward e-commerce resilience have been determined.

Initially, a committee consisting of 36 experts was formed. The number of experts was divided in a way that the experts from all the countries under investigation can be participated. As such, nine experts were selected from each country totaling 36 experts. As a real-life case study, a survey is conducted with 36 evaluators as the total sample, where the participants come from four different emerging Arab e-commerce countries. The sample is further divided into three groups (i.e., junior, middle, and senior) of the e-commerce businesses. Those juniors whose experience is less than 5 years are considered as junior-level managers, managers with 5–10 years of experience are considered as mid-distance commuters, and the managers with more than 10 years are considered as senior managers. The experts’ basic characteristics can be found in Table ​ Table3 3 .

Composition of expert panel

After the experts’ panel was finalized, the hierarchical structure of the problem is constructed by using the goal, the criteria, and the alternative of the problem. In this case, there are exclusively those alternatives that are related to the aim. Thus, the hierarchical structure has two levels (see Fig.  2 ). The first level consists of impacts (5) and the second level comprises of strategies (8). To solve the first level, GAHP was employed in which relative weights of impacts were determined.

Hierarchical structure

Having determined the structure of the problem, the next step includes the pairwise comparisons for each node of the structure thus combining them and obtaining the weights of impacting factors by using the calculation procedures given in the methodology section for the grey AHP. The combined pairwise matrices of UAE, Saudi Arabia, Kuwait, and Qatar are given in Tables ​ Tables4, 4 , ​ ,5, 5 , ​ ,6, 6 , and ​ and7, 7 , respectively. Later, these tables are normalized by using Eqs. ( 6 )–( 8 ). Afterward, the final weights are obtained. Table ​ Table8 8 shows the comparison of the weights of the impacting factors for all the four countries.

Integrated grey pairwise matrix—UAE

Integrated grey pairwise matrix—Saudi Arabia

Integrated grey pairwise matrix—Kuwait

Integrated grey pairwise matrix—Qatar

Final weights of impacts

Figure  3 shows ranking of countries under different impacts. It can be seen that the impact of increased online audience is greater in UAE followed respectively by Saudi Arabia, Kuwait, and Qatar. Figure  4 demonstrates the weights of each impact for different countries. In can be seen that in UAE, the highest weight of 0.224 is received by supply chain disruption, which is followed by increased online consumer demand (0.208), increased online audience (0.198), extended delivery time (0.187), and labor shortage (0.182). The results of Saudi Arabia are only slightly different than the UAE since both have similar top three impacts with similar ranking; however, in Saudi Arabia, labor shortage gets the second position while extended delivery time gets the fifth position. The ranking of impacts in Kuwait and Qatar remained the same as Saudi Arabia; however, the weightage obtained is different. For instance, weights of impacts in Kuwait were supply chain disruption (0.225), increased online consumer demand (0.219), increased online audience (0.194), labor shortage (0.182), and extended delivery time (0.18); whereas, weights obtained by factors in Qatar were supply chain disruption (0.226), increased online consumer demand (0.212), increased online audience (0.193), labor shortage (0.189), and extended delivery time (0.18).

Countries under each impact

Impacts in each country

By conducting the AHP method in a grey environment, not solely a weight and ranking of impacts for individual countries can be obtained but it can also be combined to get the collective scores of impacts in whole countries can be combined. The final results of weights that shall be used for analyzing and prioritizing the competitive strategies are shown in Fig.  5 . Moreover, successfully representing subjective judgements and including the bias caused by personal judgements when minimizing it during the estimation process are part of the current study.

The weights obtained using GAHP were entered into GRA to prioritize competing strategies. A group of 12 e-commerce experts was tasked with prioritizing the strategies under consideration. These e-commerce analysts were professionals in their area, having worked in the e-commerce business for over 15 years. A total of eight strategies had to be prioritized. The experts were requested to score each strategy in relation to each COVID-19 impact. The significance of strategies was graded on linguistic measures ranging from None to Very High, namely None (N), Very Low [VL], Low [L], High [H], and Very High [VH] (Al Harazi et al. 2022 ). The grey number sets that corresponded to the ratings were chosen. Table ​ Table2 2 was used to transform the experts’ verbal judgments of strategies into grey numbers.

The converted input was then utilized to create the grey decision matrix depicted in Table ​ Table9. 9 . After that, the grey decision matrix was normalized using Eq.  19 to provide a grey number value ranging from 0 to 1. Table ​ Table10 10 displays the normalized matrix. Later, the fuzzy grade relationship coefficient was calculated, as shown in Table ​ Table11. 11 . Table ​ Table12 12 shows the grey weights of the impacts that were determined using GAHP. The weighted grey decision matrix was then created by grey multiplication of GAHP weights with the appropriate values of the fuzzy grade relational coefficient matrix using Eqs. 23 and 24 . Table ​ Table13 13 displays the weighted normalized grey decision matrix calculated values. Microsoft Excel was used to complete all computations.

Decision matrix

Fuzzy grade relational coefficient

Grey weights

Weighted matrix

The GRA method’s final results are reported in Table ​ Table14. 14 . The following is the ranking order of the techniques based on the white grey relationship degrees: Expansion of the supply base (S-5) ≻ Integration of cutting-edge technologies (S-8) ≻ Digitalization of public and private sectors (S-1) ≻ Development of an effective risk management system (S-6) ≻ Extended payments or payments at regular intervals (S-7) ≻ Collaboration with e-vendors (S-2) ≻ Monitoring of customer preferences and tastes (S-3) ≻ Modification to regulatory frameworks (S-4).

Final ranking

Discussion and implications

As a result of COVID-19, people are increasingly turning to e-commerce sites to shop. More such e-commerce websites are being developed; however, more marketing efforts and novel solutions are required to capture the attention of customers in order to boost competitiveness of e-commerce in the post-pandemic age. As such, it is critical to devise and implement strategies to maintain the gains earned in the e-commerce market and to convert this influx of people into regular customers. Such strategies must address the effects of COVID-19 while also boosting e-commerce so that it does not fold under the stress of crises and can continue to operate efficiently throughout and after the pandemic. Therefore, the strategies must be assessed and prioritized in terms of their ability to mitigate the effects of COVID-19. Prior to the prioritization, it is necessary to first understand the effects of COVID on the industry and how much they influenced industry performance. As a result, the process of prioritizing strategies becomes complex and difficult. Because the impacts are multifaceted in nature, an intuitive approach may provide erroneous findings. This sort of problem is addressed by MCDA methods.

This paper presents a novel concept based on MCDA methodologies, including a hybrid approach combining GAHP and GRA, that may be used to prioritize competitive strategies for e-commerce. The approach described in this study includes a quantitative assessment of COVID-19’s impacts, which may be used to develop an evaluation mechanism for e-commerce competitive strategies. The framework can especially give e-commerce managers in emerging nations with a better grasp of how to establish resilience in e-commerce businesses. The study indicate that quantitative evaluations of COVID-19 consequences are rarely considered by e-commerce decisionmakers when developing strategies mainly due to the intricacy of the computations involved. This study emphasizes the need of conducting quantitative analyses like the ones produced with GAHP in the current study. The results indicate that the proposed framework has potentially promising applicability and appropriateness in e-commerce evaluations.

According to the findings, the most significant impact of COVID-19 on e-commerce is supply chain disruption. The second most significant consequence is shown to be “increased online demand,” which, unlike “supply chain disruption,” contributed favorably to e-commerce. The third in the sequence is “increasing online audience,” which has also benefited e-commerce. The fourth and fifth factors in the ranking are “labor shortage” and “extended delivery time,” both of which have a negative impact on e-commerce.

Now that the quantitative significance of impacts has been determined, the goal is to prioritize strategies based on their potential for minimizing negative impacts and maximizing good impacts in order to boost the resilience and effectiveness of e-commerce. The findings of the prioritization suggested that “expansion of the supply base” was the most effective strategy for boosting e-commerce in the post-pandemic era. The “integration of cutting-edge technologies” and the “digitalization of public and private sectors” are found to be the second and third most important strategies.

The e-commerce business was rapidly growing prior to COVID-19, but COVID-19 has accelerated the process and elevated the e-commerce business to new heights (Beckers et al. 2021 ). The supply network, on the other hand, is a whole different story, and significant upgrades are necessary (Moosavi et al. 2022 ). Despite the coronavirus’s spread, supply networks remain typically traditional. Suppliers have taken no measures to digitalize their operations or remotely replenish stores and small businesses (Pujawan and Bah 2022 ).

If emerging markets want to become global leaders in the e-commerce business, they must carefully increase their supply base by initiating trade with new foreign partners. This will not only broaden their participation in global value portfolio, but will also aid in mitigating potential challenges caused by supply chain bottlenecks (Butt 2021 ). Enhancing supply quantity and quality will increase competitiveness among e-commerce vendors since failing to fulfil consumer needs will result in client loss. Likewise, customers will have a plethora of alternatives in the shape of various merchants and e-commerce platforms. As a result, merchants and retailers must be primarily client focused. Furthermore, the governments of these countries should develop a thorough system of rules to act as a blueprint for supply throughout their respective countries.

Covid-19 prompted customers to alter their shopping habits, with many preferring to purchase online rather than in-store, particularly toward the onset of the pandemic. Even older generations, who have historically relied on in-store purchases, are increasingly resorting to Internet shopping. As people get more comfortable with the conveniences of digital purchasing, this channel is projected to become their preferred form of shopping once the pandemic has passed. Similarly, the pandemic prompted several smaller retailers to enter the market by launching their own online services. If this transition becomes the normal state of affairs, as we anticipate, now is the time to identify strategies and put the necessary structures in place to sustain it.

Despite the fact that the pandemic pushed more buyers online, it had negative consequences that severely harmed e-commerce. Thus, it is vital to consider both the positive and negative repercussions of COVID-19 while positioning competing e-commerce initiatives. This research accomplishes both; it first examines consequences and then prioritizes strategies depending on the relevance of those impacts. The study identifies and evaluates five key impacts, two positive and three negatives. Positive impacts include increased online audience and increased online consumer demand; while negative impacts include supply chain disruption, extended delivery time, and labor shortage. The findings indicated that supply chain disruption, which is a negative impact, outranked all other consequences in terms of significance. Hence, while prioritizing strategies, the supply chain was given more weight. As a result, the strategy of expansion of the supply base received the highest ranking out of the eight possible strategies. Integrating cutting-edge technology and digitalizing the public and private sectors are the second and third most highly ranked strategies, respectively.

The findings suggest that increasing market share will necessitate the improvement of the supply chains, including the expansion of the supply base, as well as the establishment of sustainable supply chains. In addition to that, the moment has come to implement meaningful change, such as digital transformation of supply chains, in order to fulfil customer expectations. The supply chain model must also contain competitive delivery alternatives, a working pricing mechanism, and novel techniques to increasing value, such as cooperative distribution channels. The progressive adoption of technology throughout the pandemic will also lead to the acceptance of newly designed solutions in the e-commerce industry. A high demand has resulted in the creation of numerous new payment methods, and effective delivery systems, including improved methods of investigating the sustainability of drone-based delivery development systems, are anticipated to emerge in the long term. The fact that there is not much of a disparity in the overall weights of the consequences is one of the limitations of the research. This is particularly true when comparing the impacts of “increased online consumer demand” and “supply chain disruption.” This seems to imply that all of the impacts are about equal in weight, but obviously some are more important than others. Moreover, the validity of this analysis is also contingent on the assumption that the changes caused by COVID-19 would continue. For instance, “increased online audience” may not be a durable or long-lasting trend.

Acknowledgements

The authors are grateful to the experts who volunteered to participate in the survey and for their informative comments, which helped to improve the analysis.

Arithmetic operations on grey numbers

Let us define a grey number ⊗ a as ⊗ a = a _ , a ¯ , with a _ being the lower bound and a ¯ being the upper bound.

Basic arithmetic operations on two grey numbers ⊗ a 1 = a _ 1 , a 1 ¯ and ⊗ a 2 = a _ 2 , a 2 ¯ can be performed as follows:

Grey AHP procedural steps

Phase 1: To define the problem, create a hierarchical structure that includes the goal, criteria, and alternatives.

Phase 2: Collect input from professionals using the grey linguistic scale shown in Table ​ Table2 2 .

Phase 3: Develop integrated decision matrix G as follows:

where ⊗ x ij z = x _ ij z , x ¯ ij z and z ∈ 1 , 2 , 3 , ⋯ , Z . All pairwise comparisons employ the upper component of major diagonals, similar as standard AHP; the lower components are calculated using Eq.  8 ; and components on the primary diagonal are identical to 1 as stated in Eq.  9 .

Phase 4: Aggregate expert feedback by applying Eq.  10 (geometric mean formulation), which is not influenced by exceptionally high and significantly lower values of pairwise comparison matrices. According to Barzilai ( 1997 ), the geometric mean is the only method for generating weights from several pairwise matrices that satisfies fundamental consistency requirements. Moreover, in the additive case, the geometric mean is the only option that retains the problem’s complex mathematical structure while being fundamentally consistent with the arithmetic mean. Traditional AHP employs the geometric mean formula as well, therefore, the calculation is similar. But, the lower and upper bounds of the grey numbers are computed differently. Once all comparison matrices are integrated, the consolidated matrix may be stated as G y = ⊗ x ij mn without the number of decision makers.

Phase 5: Normalize the integrated pairwise matrix as stated in Eqs. 11 and 12 (Wu and Lee 2007 ):

where Δ min max = max ⊗ x ¯ ij z - min ⊗ x _ ij z .

Phase 6: As illustrated in Eq.  13 , calculate the grey weight for each criterion by averaging the rows.

where n = { 1 , 2 , ⋯ , N } is the criterion set.

Phase 7: Transform grey weights into white by employing Eq.  14 , making interpretations simpler and more precise. As seen below, the white values are crisp integers with a conceivable number between the lower and upper boundaries of an intermediate grey weight:

where λ represents whitening coefficient, whose value ranges between 0 and 1.

To handle only consistent feedback, the consistency ratio ( CR ) of all paired matrices was calculated. The replies were collected again if the ( CR ) was larger than 10%. Equation  15 was used to calculate the ( CR ).

GRA procedural steps

Create an initial matrix to assess each strategy with respect to each impact. Assume ⊗ A is an initial matrix:

where n and m respectively represent number of indices, and comparative sequence. The matrix ⊗ A ∗ is referred to as the “initial connection matrix.” and the ⊗ a ij ∗ is referred to as the “reference sequence.”

Because the impacts of COVID-19 on e-commerce are both positive and negative, they are calculated independently. Equation  17 is used to compute the positive impact, whereas Eq.  18 is used to determine the negative impact.

These impacts, however, have varied implications on strategies. To be more exact, the differences between comparative and reference sequences have a positive correlation connection for the positive impacts, thus, a greater difference signifies a larger normalized outcome. On the other hand, a bigger difference suggests a smaller normalized outcome for the negative impacts. To ensure that the strategies are effective, larger positive and lesser negative impacts are desired. Thus, all components are normalized into positive impact using Eq.  19 :

From the matrix ⊗ R , the reference sequence is retrieved and defined as follows:

where ⊗ R denotes normalized results.

The grey relational coefficient, which illustrates the proximity between ⊗ a 1 j and ⊗ a ij , is determined from Eq.  21 .

where ξ denotes the distinguishing coefficient, which has a range of 0 to 1, and the difference matrices are as follows:

The grey relational degree indicates how closely the comparative sequences are related. The reference sequence may then be produced by applying the absolute and weighted relational grades; they are as follows:

where w j is the weight of the j ‐ rh impact obtained using GAHP.

Author contribution

All of the studies, authors have contributed to it. Saleh Yahya Alwan and Yanying Hu established the original study. Yanying Hu also offered direction and oversight. Ahmed Abdulwali Mohammed Haidar Al Asbahi developed the methodological framework and obtained the results. Yaser Khaled Al Harazi and Ahmed Khaled Al Harazi revised and improved the manuscript.

Data availability

Declarations.

Not applicable

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Saleh Yahya Alwan, Email: moc.kooltuo@1111nawla_s .

Yanying Hu, Email: moc.anis@8357narix .

Ahmed Abdulwali Mohammed Haidar Al Asbahi, Email: [email protected] .

Yaser Khaled Al Harazi, Email: [email protected] .

Ahmed Khaled Al Harazi, Email: [email protected] .

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Electronic Commerce Research and Applications

Ecra executive article how extended reality influences e-commerce consumers: a literature review.

• • This study elaborates on how XR use affects individual B2C e-commerce consumers via a literature review.
• • This study identifies the factors affecting consumers’ reactions to XR-based online shopping.
• • This study also identifies consumers’ reactions to XR-based online shopping.
• • An integrated framework is proposed to explain how XR influences B2C e-commerce consumers.
• • Research gaps are identified, and potential research directions are proposed for future research.
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