Keywords

E commerce, TAM, SMEs, Technology Adoption, Covid, User Experience.

Introduction

This study examines users’ e commerce adoption and its impact on small and medium sized enterprises (SMEs) during the novel Coronavirus crisis in Kuwait. In Kuwait, small businesses are those identified to employ 1 50 employees; while medium sized businesses are those identified to employ 51 150 employees (The national fund for small and medium enterprise development). The boom of the SME generation was initiated in 2013 with the establishment of the national fund for SME development that motivated youth entrepreneurs to implement their ideas. However, most SMEs also faced some challenges like bureaucratic and time consuming government policies and regulations, while other start up owners were inexperienced in how to manage a business.

With the recent spread of the Covid pandemic, consumers shopping behavior has been widely affected and economies have been hardly hit (Hasanat et al., 2020). Covid has become the main concern of every country and citizen on earth with at total number of people infected worldwide is more than a million and several hundreds of thousands of deaths (Yeung & Renton, 2020). Coronavirus is recognized as the fourth group of human viruses descendent from the severe acute respiratory syndrome (SARS COV) (Van Der Hoek et al., 2004). Around 81% of the people that contract the Covid have mild symptoms which light look like a common flu (Surveillances, 2020) and can be good and bad at the same time (Wang, 2020). This has been specifically witnessed in the rapid shift of consumer buying behavior driven by strict government quarantine regulations to slow the spread of Covid.

The Coronavirus pandemic has pushed the country towards an e transformation phase of development across all sectors of the economy in an unprecedented time. This has been specifically witnessed in small and medium sized businesses that have implemented an e commerce model and were able to take the lead of the rapid shift of consumer buying behavior driven by strict government quarantine regulations to slow the spread of Covid, unlike other SME’s that have not previously implemented an e commerce model. Recent research has examined the effect of quarantine on users’ e commerce activity in a pandemic situation, however this study is unique by employing the technology acceptance model (TAM) to such concept, as it is a prominent model in technology adoption. Therefore, this paper employs the TAM to explore users’ e commerce adoption and shopping behavior during the Coronavirus pandemic.

Objectives

The objectives of this research are to examine how the Covid pandemic has impacted users’ E commerce shopping behavior in Kuwait. This research specifically explores the following:

• User’s E commerce shopping behavior during Covid 19.

• Prominent methods of shopping during Covid 19.

• The level of E commerce adoption among users.

• Users’ shopping priorities during Covid 19.

• Frequency of online shopping during Covid 19.

• Key reasons for user adoption of E commerce.

• Perceived usefulness of E commerce adoption during Covid 19.

• Perceived ease of using E commerce during Covid 19.

• Perceived benefits and barriers of users E commerce adoption.

• Level of user satisfaction in E commerce adoption.

• Users’ future E commerce adoption intentions.

Review of Literature

Theoretical Grounding

This research employs the technology acceptance model (TAM) (Davis, 1985) to examine user’s adoption of e commerce and its impact on SME performance considering the COVID 19 pandemic. The model examines the relationship between users’ perceived benefits and perceived barriers when using e commerce and perceived usefulness (PU) and perceived ease of use (PEOU). The TAM is a prevalent model in the field of technology adoption that has recurrently been used to examine the adoption and use of several new and developing technologies. Perceived Usefulness and Perceived Ease of Use are important predictors that affect a user’s decision to adopt or reject a technology (Davis, 1985; & Davis, 1989). Perceived Ease of Use is how easy and effortless a system is for a person to use, while Perceived Usefulness is the degree of usefulness a person feels when using a certain system (Davis, 1989).

AS the TAM has been updated to TAM2 highlighting a theoretical extension explaining perceived usefulness and intentions from a social influence perspective of the TAM (Venkatesh & Davis, 2000). In addition, to the latest update to the TAM the TAM3, which tests the adoption and use of technology (Venkatesh & Bala, 2008). A recent study examined the TAM3 and e commerce to understand Malaysian SMEs e commerce adoption (Salimon et. al, 2021).

E Commerce Generation

The Internet has dramatically changed people’s lives in the way they do business driving modern organizations to follow the force of e commerce to meet the evolving demands of modern consumers. In return, this powerful demand has driven businesses to either transform into e business models or face the threat of demolition. E commerce is “the use of the Internet to facilitate, execute, and process business transactions (Kim & Malhotra, 2005)”. E commerce involves business transactions that deal with the exchange of goods and services between the buyers and sellers for money and profit online. E commerce has been specifically adopted by customers during the Covid 19 pandemic. Retail sales show that COVID had a significant influence on e commerce and is expected to reach $6.5 trillion by 2023 (Jones, 2020). In the countries of Southeast Asia, for example, Singapore, Malaysia, Thailand, and Hong Kong, online traffic on food delivery websites has increased (Jebril, 2020). Similarly, an increase in the number of potential customers has been observed since the first week of March of 2020 (Karimi Zarchi et al., 2020). Hasanat et al. (2020) conducted a survey in Malaysia to understand how small and medium online businesses were affected by the Covid crises. The results illustrated that e commerce businesses were severely affected especially since most of the products are imported from China. A survey that involved more than 5,750 people was performed to investigate the economic impact of COVID on small businesses (Bartik et al., 2020). The results revealed that small businesses suffered financially after weeks of closure. Respondents that had temporarily closed referred that to the reductions in demand and to the employee health concerns. The study also provided negative evidence on business expectations for long term impact of COVID 19, as well as their perceptions of the support offered by their governments (Bartik et al., 2020).

Customers E commerce Adoption Behavior

Considering the Covid, the reaction of the population’s purchasing behavior is expected to change due to the precautionary instructions of the government such as the enforced lockdown and curfew regulations. Customer’s purchasing behavior is also likely to transform due to the shopping time limitations and limited availability of goods (Liang & Litscher, 2020). Crisis related to the circumstances, that the entire world and country is facing, is projected to radically alter customers’ method of purchasing and routine shopping trends. Purchasing behavior is expected to transform to online shopping creating a heavy reliance on e commerce during lockdown and curfew times, placing increased pressures on SME’s that have implemented e commerce (Hasanat et al., 2020).

From the customers’ point of view, in terms of benefits, a strong relationship has been evident between the users’ effort and e commerce, meaning the easier the website or application the more customers will adopt and use e commerce (Shahzad et al., 2020). Social media is a cost effective tool that has been evident to be a major driver of e commerce because it is an effective and preferred method of shopping among customers (Amornkitvikai & Lee, 2020). As social media has been previously recognized as a very important communication medium, this paper aims to examine customers’ use of social media and its effect on e commerce adoption during the Covid pandemic.

However, in terms of users’ perceived barriers, although e commerce has been recognized as a convenient method of shopping, consumers continue to face uncertainties when using e commerce, identified as risks such as the privacy risk which relates to how companies deal with customers’ personal information. Security risks relate to the level of website security when undergoing a transaction.

Functional risk is the customer’s perception that the product will not perform as expected and financial risk is customers’ perception that the product is not worth the price paid for. Time loss is all the time the customer spent preparing and making the order (reading previous customer reviews, seeking information, comparing prices, and waiting for the delivery (Park et al., 2004). Therefore, to examine the effect of the Coronavirus pandemic on customers’ e commerce shopping behavior the following questions will be examined.

1. How did users’ shopping behavior change during Covid?

2. What sectors of SMEs did users E commerce adoption mostly impact during Covid?

3. What were the perceived benefits and barriers of E commerce adoption that users experienced during Covid?

4. What are the important factors that users perceived as easy to use (PEOU) during their E commerce shopping experience?

5. What are the important factors that users perceived as usefulness (PU) during their E commerce shopping experience?

Methodology

The purpose of the study is to examine user’s adoption of e commerce and its impact on SME considering the Covid pandemic. The study adopts a quantitative approach, based on an electronically generated and distributed questionnaire using the survey monkey website to the public to achieve to reach the mass majority and collect different viewpoints of the phenomena from diverse user categories. The questionnaire was divided into three sections. The first section tests collect demographic data.

The second section examines users’ shopping behavior during Covid. The third section tests the TAM based on three core constructs, perceived usefulness (PU), perceived ease of use (PEOU), and intention to shop online in the future. The TAM is a prominent model that is used to test users’ adoption of new and existing technologies (Davis, 1985; & Davis, 1989). All the dependent variables were measured using the 5 Point ‘Likert Scale’, where 1 represents ‘strongly disagree’, 2 represents ‘disagree’, 3 represents ‘not sure’, 4 represents ‘agree’, and 5 represents ‘strongly agree’. Data will be analyzed using SPSS data analysis software to identify and highlight relationships.

Research Design and Data Collection

A questionnaire was designed and distributed to a specific audience, students, academic staff, and the public. They were asked to complete the questionnaire. The questionnaire was distributed to about 500 participants. Only those questionnaires were selected which were fully completed by the participants. Thus, a total of 402 questionnaires were selected for this study.

The Validity and Reliability of the questionnaire were measured. To measure the validity of the questionnaire, it was circulated to 10 university professors to get their feedback. Based on their suggestions and recommendations, the questionnaire was modified and electronically circulated using the Survey Monkey website to various participants.

Findings and Discussion

The reliability of the questionnaire was measured by using Cronbach’s Alpha of SPSS 20 software program. All results are shown in Table (1). All the results show very strong reliability for all the groups of variables.

Table 1 Reliability Of The Questionnaire Was Measured By Using Cronbach’s Alpha Of Spss-20 Software Program
Variable reliability testing	No. of Cases	No. of Items	Cronbach’s Alpha
‘The fears when you do on-line shopping’	402	7	.756
‘PU: how useful is shopping on-line during Coronavirus’	402	5	.835
‘PEOU: how easy is to shop on-line’	402	5	.830
‘what do you think about on-line shopping after your experience’	402	4	.819
‘overall economic impact of e-commerce on SME’s during the Coronavirus Pandemic’	402	21	.840

The frequency distribution and demographic data of 402 participants was the male participants in the study were 156 (38.8%) and female participants were 246 (61.2%). The number of participants who were in the age group of ‘18 24’ years were 135 (33.6%), ‘25 34’ years were 82 (20.4%), ‘35 44’ years were 77 (19.2%), ‘45 54’ years were 65 (16.2%), and ‘55 and above’ years were 43 (10.7%).

The academic qualification of ‘43 (10.7%)’ participants were ‘high school’, ‘158 (39.3%)’ participants were ‘college’, ‘156 (38.8%)’ participants were ‘university’, ‘26 (6.5%)’ participants were ‘masters’ and 19 (4.7%) participants were ‘Ph.D.’. All participants were divided in to two groups, based on their qualifications. The participants who were ‘up to college’ were 201 (50.0%) and the participants who were ‘university and above’ were 201 (50.0%).

Testing the Location of Residence

The participants who answered the questionnaire from different areas of Kuwait were as follows. Participants, living in ‘Capital City’ areas were 158 (39.3%), ‘Hawalli’ areas were 58 (14.4%), ‘Al Ahmadi’ areas were 57 (14.2%), ‘Mubarak Al Kabir’ areas were 30 (7.5%), ‘Jahra’ areas were 49 (12.2%), and ‘Farwania’ areas were 50 (12.4%). Later, all the participants were divided in to only two groups as per their living in ‘urban’ areas and ‘rural’ areas. The participants living in urban areas (Capital, Mubarak Al Kabir and Al Farwania), were 238 (59.2%) and participants living in rural areas (Hawalli, Al Ahmadi, and Jahra) were 164 (40.8%).

In terms of frequency of on line shopping during Covid, participants were asked about ‘how often do you shop on line during the coronavirus’: 11 (2.7%) participants said that they ‘never’ did on line shopping, 70 (17.4%) participants said that they ‘rarely’ did on line shopping, 143 (35.6%) participants said that they ‘sometimes’ did on line shopping, 102 (25.4 %) participants said that they ‘usually’ did on line shopping, and 76 (18.9%) participants said that they ‘always’ did on line shopping.

Participants were asked if they changed their shopping habits during coronavirus. Interestingly about 300 (74.6%) participants said that they changed their shopping habits during coronavirus whereas 102 (25.4%) participants say that they did not change their shopping habit during corona virus time. It is very interesting to note that about 75% of participants changed their shopping habit during coronavirus time.

The participants always prefer to go physically to shopping centres and do shopping but during the pandemic and quarantine they were forced by the circumstances to change their shopping habits and adopt new methods of shopping which was a unique experience for them. Findings of this study support previous studies that indicate coronavirus had pushed people to do online shopping and will they continue doing online shopping when this plague is over. The data for this paper was collected by circulating questionnaires on the social media as the situation was unsuitable to go for physical surveys.

This report is comprehensive in knowing whether coronavirus is triggering people to do online shopping, or they are still managing to buy products physically. Investigation has brought on the conclusion that people are not doing more online shopping during coronavirus and people also disagreed that they will be continuing doing online shopping with the same rate in future when this pandemic is over (Kashif & Aziz Ur Rehman, 2020).

Participants were asked about ‘how frequently did you shop on line during the coronavirus’: 16 (4.0%) participants said that they did on line shopping ‘every day’, 88 (21.9%) participants said that they did on line shopping ‘a few times a week’, 77 (19.2%) participants said that they did on line shopping ‘about once a week’, 92 (22.9%) participants said that they did on line shopping ‘a few times a month’, and 129 (32.1%) participants said that they did on line shopping ‘once a month’.

Participants were asked about their shopping methods during coronavirus time. It is a multiple answer question and participants can choose more than one method. 188 (46.8%) participants say that ‘they shop out of curfew times or ask for an exit permit.

• 87 (21.6%) participants say that ‘they order by phone’ • 230 (57.2%) participants say that ‘they shop on line’ and • 28 (7.0%) participants say that they did shopping by ‘other ways’.

It is to be noted that 57.2% participants (about 60%) were doing on line shopping during coronavirus time. It means that they learned and also enjoyed doing on line shopping. Also (46.8%) participants (about 50%) participants used to shop during curfew times by taking exit permit by concerned authorities. Thus, even the corona virus time was not a bottle neck for users to do their day to day activities.

Participants were asked ‘what did you shop on line during the coronavirus’ it is a multiple answer question and participants can choose more than one item.

Table shows the items, participants shop on line during the coronavirus. Items have been sorted out in the descending order of their on line shopping needs & requirements.

The table (2) shows that top three priorities of the participants for their on line shopping during the coronavirus were ‘supermarket’, then ‘pharmacy’ and then ‘electronics’ and the last priority of the participants for their on line shopping during the coronavirus was ‘jewelry and other accessories’.

Table 2 Top Three Priorities Of The Participants For Their On-Line Shopping During The Coronavirus
where did you shop on-line during the coronavirus	Number of participants who have done shopping for the item	Percentage of participants who have done shopping for the item
Supermarket	263	65.4%
Pharmacy	194	48.3%
Electronics	191	47.5%
Apparel / shoes	152	37.8%
Beauty makeup	92	22.9%
Restaurants	89	22.1%
Furniture	34	8.5%
Others	29	7.2%
Jewelry / accessories	20	5.0%

Participants were asked ‘During the quarantine did you need to shop at a store that did not have online ordering services’: 222 (55.2%) said that they did shopping at a store that did not have online ordering services whereas 180 (44.8%) participants did not do online shopping.

Testing User Fears

Participants were asked about their various fears when they do online shopping. The responses of all the participants about their various fears are shown in the following table (3) in the descending order of their mean values.

Table 3 The Participants Fears When They Do Online Shopping
where did you shop on-line during the coronavirus	Number of participants who have done shopping for the item	Percentage of participants who have done shopping for the item
Supermarket	263	65.4%
Pharmacy	194	48.3%
Electronics	191	47.5%
Apparel / shoes	152	37.8%
Beauty makeup	92	22.9%
Restaurants	89	22.1%
Furniture	34	8.5%
Others	29	7.2%
Jewelry / accessories	20	5.0%

Table (3) shows the participants fears when they do online shopping. The values of cells show the number of cases and their percentages. Responses of the participants have been sorted out in the descending order of their mean values.

The results from the table (3) show the various fears of the participants when they do on line shopping. All the fears have been sorted out and put in the descending order.

The first highest fear of the participants, when they do online shopping, is that ‘they think about the safety of the website before shopping online’. The second highest fear of the participants, when they do online shopping, is that ‘they fear a delay in the delivery time’. The third highest fear of the participants, when they do online shopping, is that ‘they fear that the product is not as expected when ordering’. The lowest fear of the participants, when they do online shopping, is that ‘they fear that entering the bank card details online is not secured.

Testing The TAM

Users shopping experience in relation to the TAM, testing the PU and PEOU. Testing PU: How useful is shopping on line during Coronavirus? Participants were asked about their opinion on usefulness of on line shopping during coronavirus. The responses of all the participants on usefulness of on line shopping during corona virus are shown in the following table (4) in the descending order of their mean values.

Table 4 Participants’ Opinion On Usefulness Of On-Line Shopping During Corona Virus
Variables	Strongly Disagree N, %	Disagree N, %	Not Sure N, %	Agree N, %	Strongly Agree N, %	Mean	Standard Deviation
Shopping online is convenient for me.	3 0.7%	14 3.5%	125 31.1%	130 32.3%	130 32.3%	3.92	0.915
Shopping online saves my time.	7 1.7%	19 4.7%	116 28.9%	127 31.6%	133 33.1%	3.90	0.978
Shopping online is useful.	3 0.7%	17 4.2%	133 33.1%	118 29.4%	131 32.6%	3.89	0.940
Shopping online is handy in respect to my location	11 2.7%	31 7.7%	158 39.3%	117 29.1%	85 21.1%	3.58	0.993
Shopping online is important in my daily life.	21 5.2%	57 14.2%	178 44.3%	83 20.6%	63 15.7%	3.27	1.055

Table (4) shows participants’ opinion on usefulness of on line shopping during corona virus. The values of cells show the number of cases and their percentages. Responses of the participants have been sorted out in the descending order of their mean values.

The results from the table (4) show the various uses the participants feel when they do on line shopping. All the results have been sorted out and put in the descending order.

The first highest usefulness of the online shopping that the participants feel is that ‘it is convenient for them’. The second highest usefulness of the online shopping that the participants feel is that ‘it saves their time’. The third highest usefulness of the online shopping that the participants feel is that ‘it is useful for them’. The next usefulness of the online shopping that the participants feel is that ‘Shopping online is handy in respect to their location’. The last usefulness of the online shopping that the participants feel is that ‘Shopping online is important in their daily life’.

PEOU: How easy is to shop online during Coronavirus?

Participants were asked about their opinion as how much on line shopping was easy during coronavirus.

The responses of all the participants about their opinion as how much on line shopping was easy during corona virus are shown in the following table (5) in the descending order of their mean values.

Table (5) shows Participants’ opinion as how much on line shopping was easy during corona virus. The values of cells show the number of cases and their percentages. Responses of the participants have been sorted out in the descending order of their mean values.

The results from the table (5) show Participants’ opinion as how much on line shopping was easy during corona virus. All the results have been sorted out and put in the descending order.

Table 5 Participants’ Opinion As How Much On-Line Shopping Was Easy During Corona Virus
Variables	Strongly Disagree N, %	Disagree N, %	Not Sure N, %	Agree N, %	Strongly Agree N, %	Mean	Standard Deviation
Online transaction and payment is understandable.	3 0.7%	8 2.0%	123 30.6%	188 46.8%	80 19.9%	3.83	0.790
Online shopping is easy.	2 0.5%	10 2.5%	157 39.1%	149 37.1%	84 20.9%	3.75	0.828
Browsing products online is clear.	5 1.2%	19 4.7%	200 49.8%	127 31.6%	51 12.7%	3.50	0.821
Order tracking does not require a lot of efforts.	17 4.2%	34 8.5%	172 42.8%	121 30.1%	58 14.4%	3.42	0.979
Communication with the shops online does not require a lot of efforts	13 3.2%	42 10.4%	177 44.0%	119 29.6%	51 12.7%	3.38	0.946

The first highest opinion about the ease of the online shopping, that the participants feel is that ‘Online transaction and payment is understandable’. The second highest opinion about the ease of the online shopping, that the participants feel is that ‘Online shopping is easy’. The third highest opinion about the ease of the online shopping, that the participants feel is that ‘Browsing products online is clear’. The next highest opinion about the ease of the online shopping, that the participants feel is that ‘Order tracking does not require a lot of efforts. The lowest opinion about the ease of the online shopping, that the participants feel is that ‘Communication with the shops online does not require a lot of efforts.

Post COVID E commerce Shopping Intention

This variable shows users intentions of shopping online based on their experience if they intend to continue shopping online or not in the future and after the pandemic has ended.

A special question was asked from these participants to know their intention to shop on line in future. The response of all the 402 participants was as follows.

129 (32.1%) participants say that they will continue to shop online on a regular basis even after Coronavirus.

101 (25.1%) participants say that they will shop less online after Coronavirus.

172 (42.8%) participants say that they do not think that they will shop online after Coronavirus.

What do you think about online shopping after your experience?

Participants were asked their opinion about online shopping after their experience of online shopping.

The responses of all the participants about online shopping after their experience of online shopping during corona virus are shown in the following table (6) in the descending order of their mean values.

Table (6) shows Participants’ opinion about online shopping after their experience of online shopping during corona virus. The values of cells show the number of cases and their percentages. Responses of the participants have been sorted out in the descending order of their mean values.

The results from the table (6) show Participants’ opinion about online shopping after their experience of online shopping during corona virus. All the results have been sorted out and put in the descending order.

Table 6 Participants’ Opinion About Online Shopping After Their Experience Of Online Shopping During Corona Virus
Variables	Strongly Disagree N, %	Disagree N, %	Not Sure N, %	Agree N, %	Strongly Agree N, %	Mean	Standard Deviation
My knowledge of online shopping has increased.	4 1.0%	15 3.7%	129 32.1%	159 39.6%	95 23.6%	3.81	0.873
I am more aware of how easy online shopping is.	3 0.7%	23 5.7%	130 32.3%	160 39.8%	86 21.4%	3.75	0.880
I am more aware of the negatives of online shopping	3 0.7%	27 6.7%	137 34.1%	163 40.5%	72 17.9%	3.68	0.870
My confidence in online shopping has increased.	10 2.5%	34 8.5%	187 46.5%	127 31.6%	44 10.9%	3.40	0.883

The first highest opinion about online shopping after their experience of online shopping is that the participants feel is that ‘their knowledge of online shopping has increased. “The second highest opinion about online shopping after their experience of online shopping is, that the participants feel that ‘they are more aware of how easy online shopping is”. The third highest opinion about online shopping after their experience of online shopping is that the participants feel that ‘their confidence of online shopping has increased. The last highest opinion about online shopping after their experience of online shopping is that the participants feel that ‘they are more aware of the negatives of online shopping’.

Results show that users have fears when shopping on line, mean value (M=3.82, SD=0.63).

The mean value (M=3.71, SD=0.76) for the variable in relation to PU users Overall Perceived Usefulness of online shopping during coronavirus shows that overall, all the participants feel online shopping is useful during Covid. The mean value (M=3.58, SD=0.68) for the variable Overall about Perceived Ease of Use when you shop online shows that overall, all the participants feel that it was very easy for them to shop online. The mean value (M=3.66, SD=0.71) for the variable Overall opinion of online shopping after your experience of online shopping shows that overall, all the participants have positive opinion of on line shopping after their experience of shopping on line.

The mean value (M=3.71, SD=0.50) for Overall about your opinion of shopping on line during corona virus shows that overall, all the participants have positive opinion of on line shopping during corona virus. They feel that they have gained some very special kind of experience while doing on line shopping during corona virus time.

Conclsion

This study presented a clear understanding of users shopping behavior and the level of e commerce adoption during the Coronavirus pandemic. The paper specifically explored users’ perceived benefits and barriers of e commerce adoption, which is very beneficial to understand for businesses and decision makers to improve their online systems to address better customer satisfaction. The study showed important results that showed users top three e commerce shopping experience reflecting their priorities were from the supermarket 65.4%, pharmacy 48.3%, and third is electronics 47.5%. Results show the most important factor for users was the perceived usefulness (PU) of e commerce shopping, and the second most important was the perceived ease of use (PEOU) of e commerce platform, and the third most important was users’ e commerce experience that made users excited about shopping online. And lastly ranked the fears of shopping through e commerce.

Implications

The study presents important theoretical and managerial implications that will build on existing literature involving Covid and assist decision makers and small businesses to meet the rapidly changing user requirements in crisis situations. Anticipated research outcomes will offer important facts and figures about user technology adoption trends during crisis situations.

Theoretical Implications

The study presented important empirical findings on the TAM model and user’s adoption of E commerce during the Covid pandemic. The TAM was effective and useful in testing users’ e commerce shopping behavior during Covid. Results displayed theoretical implications to build on existing literature in relation to testing TAM constructs during the Covid pandemic in Kuwait which has not been examined before.

Managerial Implications

The study presents practical recommendation to assist SMEs and decision makers on how to adapt their companies and change their business models to meet the fast passed requirements of the changing environment in a crisis as the one we are currently witnessing. The study effectively highlighted users’ online shopping preferences considering the novel coronavirus and provided key points of strengths that SMEs should focus on and key weaknesses for any e commerce businesses to learn from, resolve and avoid. The study shows users’ adoption rate of e commerce and key benefits and barriers that can assist businesses and decision makers in rearranging priorities and restructuring their business models to meet users’ changes in shopping behavior in light of the unpredictive and changing worldwide health situation. Mangers should carefully study the barriers that users faced as they represent key indicators of consistent ecommerce adoption.

Limitations

While this study highlights important findings about e commerce user experience during pandemic situations, it remains limited to understating user purchasing behavior in such urgent situations. To address this limitation future studies should explore user e commerce purchasing behavior in lessened pandemic restrictions where customers have the choice to purchase online or offline.

Second, although this study was performed in Kuwait and can be applied to other Gulf countries in the region that share similar economic and cultural backgrounds, it has not been tested in other western or European countries. Therefore, it would be interesting to study such phenomenon in other countries and backgrounds.

References

Amornkitvikai, Y., & Lee, C. (2020). Determinants of E-Commerce Adoption and Utilisation by SMEs in Thailand.

Indexed at, Google Scholar

Bartik, A.W., Bertrand, M., Cullen, Z., Glaeser, E.L., Luca, M., & Stanton, C. (2020). The impact of COVID-19 on small business outcomes and expectations. Proceedings of the National Academy of Sciences, 117(30):17656-17666.

Indexed at, Google Scholar, CrossRef

Davis, F.D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results.

Indexed at, Google Scholar

Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly,  319-340.

Indexed at, Google Scholar, CrossRef

Hasanat, M.W., Hoque, A., Shikha, F.A., Anwar, M., Hamid, A.B.A., & Tat, H.H. (2020). The impact of coronavirus (COVID-19) on e-business in Malaysia. Asian Journal of Multidisciplinary Studies, 3(1), 85-90.

Google Scholar

Jebril, N. (2020). World Health Organization declared a pandemic public health menace: a systematic review of the coronavirus disease 2019 “COVID-19.  Available at SSRN 3566298,

Indexed at, Google Scholar, CrossRef

Jones, K. (2020). The pandemic economy: What are shoppers buying online during COVID-19.

Google Scholar

Karimi-Zarchi, M., Neamatzadeh, H., Dastgheib, S.A., Abbasi, H., Mirjalili, S.R., Behforouz, A., Ferdosian, F., & Bahrami, R. (2020). Vertical transmission of coronavirus disease 19 (COVID-19) from infected pregnant mothers to neonates: a review. Fetal and Pediatric Pathology, 39(3), pp.246-250.

Indexed at, Google Scholar, CrossRef

Kashif, M., & Aziz-Ur-Rehman, M. (2020). COVID-19 impact on online shopping. International Journal of Medical Science in Clinical Research and Review, 3(04), pp.325-330.

Google Scholar

Kim, S.S., & Malhotra, N.K. (2005). A longitudinal model of continued IS use: An integrative view of four mechanisms underlying postadoption phenomena. Management Science, 51(5), pp.741-755.

Google Scholar, CrossRef

Liang, F., & Litscher, G. (2020). (Coronavirus Disease-19): Traditional Chinese Medicine Including Acupuncture for alleviation–A Report from Wuhan, Hubei Province in China. OBM Integrative and Complementary Medicine, 5(1), 1-1.

Google Scholar, CrossRef

The national fund for small and medium enterprise development.

Park, J., Lee, D., & Ahn, J. (2004). Risk-focused e-commerce adoption model: A cross-country study. Journal of Global Information Technology Management, 7(2), pp.6-30.

Indexed at, Google Scholar, CrossRef

Salimon, M.G., Kareem, O., Mokhtar, S.S.M., Aliyu, O.A., Bamgbade, J.A., & Adeleke, A.Q. (2021). Malaysian SMEs m-commerce adoption: TAM 3, UTAUT 2 and TOE approach. Journal of Science and Technology Policy Management.

Indexed at, Google Scholar, CrossRef

Shahzad, A., Chin, H.K., Altaf, M., & Bajwa, F.A. (2020). Malaysian SME's performance and the use of e-commerce: A multi-group analysis of click-and-mortar and pure-play e-retailers. Pakistan Journal of Commerce and Social Sciences, 14(1), pp.1-33.

Indexed at, Google Scholar

Surveillances, V. (2020). The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19)—China, 2020. China CDC Weekly, 2(8), pp.113-122.

Indexed at, Google Scholar, CrossRef

Van Der Hoek, L., Pyrc, K., Jebbink, M.F., Vermeulen-Oost, W., Berkhout, R.J., Wolthers, K.C., Wertheim-van Dillen, P.M., Kaandorp, J., Spaargaren, J., & Berkhout, B. (2004). Identification of a new human coronavirus. Nature Medicine, 10(4), 368-373.

Indexed at, Google Scholar, CrossRef

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 273-315.

Indexed at, Google Scholar, CrossRef

Venkatesh, V., & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.

Indexed at, Google Scholar, CrossRef

Wang, V. (2020). Most Coronavirus Cases Are Mild That’s Good and Bad News. The New York Times, 5.

Google Scholar

Yeung, J., Renton, A. (2020). Coronavirus pandemic: Updates from around the world.

Received: 04-Jun-2022, Manuscript No. IJE-22-12130; Editor assigned: 07-Jun-2022, Pre QC No. IJE-22-12130 (PQ); Reviewed: 21-Jun- 2022, QC No. IJE-22-12130; Revised: 28-Jun-2022, Manuscript No. IJE-22-12130 (R); Published: 05-Jul-2022