KMO and Bartlett’s test
KMO measure of sampling adequacy | 0.862 | |
---|---|---|
Bartlett’s test of sphericity | Approximate | 1,812.156 |
df | 378 | |
Sig | 0.000 |
Cronbach’s α
Research variables | Cronbach’s |
---|---|
Fear of bank transaction and no faith | 0.747 |
Traditional shopping is convenient than online shopping | 0.797 |
Reputation and service provided | 0.825 |
Bad experience | 0.816 |
Insecurity and insufficient product information | 0.784 |
Lack of trust | 0.760 |
Factors | Name of the factor | Statements | Eigenvalue | % of variance | Loadings |
---|---|---|---|---|---|
1 | Fear of bank transaction and faith | − The fact that only those with a credit card or bank account can shop on the internet is a drawback | 29.431 | 0.789 | |
−While shopping online, I hesitate to give my credit card number | 0.642 | ||||
−I do not prefer online shopping because of lack of trust over vendors | 8.241 | 0.601 | |||
−I do not prefer to buy online because of bad returning policy | 0.580 | ||||
−The fear of wrong product delivery stops me to buy through online | 0.552 | ||||
−I do not prefer to purchase from online stores if they do not provide cash on delivery facilities | 0.394 | ||||
2 | Traditional shopping is convenient than online shopping | − I think shopping on the internet takes lot of time | 2.788 | 9.958 | 0.713 |
−Online shopping is complex as compared to traditional shopping | 0.706 | ||||
−It is more difficult to shop on the internet | 0.698 | ||||
−I believe online shopping cannot overtake the traditional shopping | 0.658 | ||||
−I prefer traditional shopping than online shopping | 0.614 | ||||
3 | Reputation and service provided | −I prefer to purchase from reputed online websites | 1.964 | 7.013 | 0.775 |
−I generally prefer to buy after comparing prices with all other websites | 0.732 | ||||
−I prefer to purchase online if website is secure and genuine | 0.726 | ||||
−I prefer those websites only that deliver the goods as soon as possible | 0.638 | ||||
−If there is no guarantee and warrantee of the product, I will never prefer to buy through online stores | 0.550 | ||||
4 | Experience | −I do not prefer to purchase from online stores if they do not provide every month instalment (EMI) facilities | 1.299 | 4.640 | 0.776 |
−I hesitate to shop online because my past experience was not good | 0.663 | ||||
−I do not prefer to buy online because of little knowledge of internet | 0.606 | ||||
5 | Insecurity and insufficient product information | −I will not prefer online shopping if the description of products shown on the online websites are not accurate | 1.190 | 4.251 | 0.665 |
−I will not prefer online shopping if online prices are high | 0.614 | ||||
−The information given about the products and services on the internet is not sufficient to make purchase | 0.548 | ||||
−If variety of goods available on the online stores are less, I will not prefer online shopping | 0.539 | ||||
−Online shopping is not secure as traditional shopping | 0.416 | ||||
6 | Lack of trust | − I hesitate to give my personal information on online websites | 1.098 | 3.920 | 0.552 |
−Without touching products, it is difficult to make buying decision | 0.521 | ||||
−Shopping online is risky | 0.511 | ||||
−I would be frustrated about what to do if I am dissatisfied with a purchase made from the internet | 0.488 |
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Proceedings of 10th International Conference on Digital Strategies for Organizational Success
8 Pages Posted: 3 Jan 2019 Last revised: 19 Mar 2019
Uka Tarsadia University, Students; Pranveer Singh Institute of Technology
Independent
Date Written: January 5, 2019
Purpose – To investigate the factors affecting consumer’s online shopping behavior. Design/methodology/approach – A descriptive type of study using judgmental sampling for selecting the samples from online shopping users of Kanpur city. The data has been collecting with the help of questionnaire. The factor analysis is performed for identifying the factors, the nonparametric test has been used for hypothesis testing. Findings – The study results suggest that consumers’ online shopping behavior is being affected by several factors like demographic factors, social factors, consumer online shopping experience, knowledge of using internet and computer, website design, social media, situational factors, facilitating conditions, product characteristics, sales promotional scheme, payment option, delivery of goods and after sales services plays an important role in online shopping. Research limitations/implications – The study results cannot be generalized to the all online shopping users because of small sample size and geographical location from where data is collected. Future studies may also apply some more statistical techniques to improve the conclusiveness of the findings reported in this study. Practical implications – The results should be of interest to the online retailers in deciding their marketing program. Originality/value – The paper is based on original work, the questionnaire has been found reliable after checking the cronback Alpha value. The KMO values supports the adequacy of sample size. It will help the academicians and scholars in their research work in the form of a literature on online shopping. It will also provide guidelines to online retailers in making their marketing program.
Keywords: Consumer behaviour, online shopping, Internet shopping, Electronic commerce
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As Guest Editors for the special issue of Electronic Commerce Research on “Online Grocery Shopping – Current and Future Challenges and Opportunities”, we are delighted to announce its release. Online grocery shopping (OGS) has surged in popularity and significance in recent years, with the COVID-19 pandemic accelerating this trend. Although OGS offers numerous benefits, such as convenience and flexibility, many questions remain about its impact on the retail industry and consumer behavior. The rise of OGS necessitates new insights for retailers and manufacturers, as they may need to adapt their marketing strategies and analytics to this new sales channel. To reduce the current uncertainty in the field of OGS, this special issue is dedicated to presenting new research on this broad topic.
This special issue features numerous high-quality research papers covering a wide spectrum of electronic commerce research. Kumar et al. [ 1 ] provide a comprehensive literature review on OGS, offering readers a holistic overview of the developments in OGS research within the scientific literature. Other publications in this special issue focus on technology in the context of OGS. For instance, Bruni et al. [ 2 ] examine how the metaverse impacts marketing and competition in both offline and online retail. Upadhyay et al. [ 3 ] analyze the influence of customer experience in mobile food ordering applications on reuse intention. Additionally, Rohden and Espartel [ 4 ] investigate consumer reactions to recommendation agents in their research on technology related to OGS.
In addition to technology-related topics, this special issue delves into consumer reactions to various settings and situations in OGS. Lima et al. [ 5 ] conduct an empirical study on how to enhance customer satisfaction in online subscription-based services. Their findings offer valuable insights for improving user experience in such services. Acknowledging the detrimental impact of negative reviews in OGS, Kim et al. [ 6 ] employ scenario-based experiments to investigate how the responses of online store managers to negative reviews influence potential shoppers’ perceptions and behaviors.
Further research in this issue introduces an intelligent retail system centered on the consumer, leveraging the Internet of Things (Ala et al. [ 7 ]). Building on analyses focused on improving the value chain, Ekren et al. [ 8 ] propose strategies to enhance fulfillment in OGS. Additionally, a crucial factor for the long-term success of OGS, especially beyond the initial surge prompted by the COVID-19 pandemic, is customer loyalty. Against this background, Kuikka et al. [ 9 ] investigate the drivers of customer loyalty toward grocery retailers before, during, and after the pandemic.
Moreover, this special issue explores various consumer-related differences in OGS. Wang et al. [ 10 ] investigate how emotions, gender, and immersion impact impulse behavior in OGS. Braun and Osman [ 11 ] conduct an empirical study examining the factors that influence the adoption and non-adoption of OGS among individuals over 50.
We believe this special issue will greatly enhance the understanding and development of OGS, providing valuable insights for researchers, practitioners, and policymakers alike.
Shroff, A., Kumar, S., Martinez, L. M., & Pandey, N. (2024). From clicks to consequences: A multi-method review of online grocery shopping. Electronic Commerce Research , 24 (2), 1–40.
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Bruni, R., Colamatteo, A., & Mladenović, D. (2024). How the metaverse influences marketing and competitive advantage of retailers: Predictions and key marketing research priorities. Electronic Commerce Research , 24 (2), 1–18.
Upadhyay, Y., Baber, R., Paul, J., Baber, P., & Cain, L. (2024). Beyond the first bite: Understanding how online experience shapes user loyalty in the mobile food app market. Electronic Commerce Research , 24 (2), 1–25.
Rohden, S. F., & Espartel, L. B. (2024). Consumer reactions to technology in retail: Choice uncertainty and reduced perceived control in decisions assisted by recommendation agents. Electronic Commerce Research , 24 (2), 1–23.
Lima, D., Ramos, R. F., & Oliveira, P. M. (2024). Customer satisfaction in the pet food subscription-based online services. Electronic Commerce Research , 24 (2), 1–25.
Kim, E., Lee, C. C., & An, J. (2024). Examining how online store managers’ responses to negative reviews affect potential shoppers. Electronic Commerce Research , 24 (2), 1–38.
Ala, A., Sadeghi, A. H., Deveci, M., & Pamucar, D. (2023). Improving smart deals system to secure human-centric consumer applications: Internet of things and Markov logic network approaches. Electronic Commerce Research , 24 (2), 1–27.
Ekren, B. Y., Perotti, S., Foresti, L., & Prataviera, L. (2024). Enhancing e-grocery order fulfillment: Improving product availability, cost, and emissions in last-mile delivery. Electronic Commerce Research , 24 (2), 1–39.
Kuikka, A., Hallikainen, H., Tuominen, S., & Laukkanen, T. (2024). What drives customer loyalty in a pandemic? Semantic analysis of grocery retailers. Electronic Commerce Research , 24 (2), 1–36.
Wang, K. Y., Ashraf, A., Thongpapanl, N., Ferreira, C., Selcuk, C., & Green, T. (2024). Acting on impulse: The role of emotion, gender identity and immersion in driving impulse behavior. Electronic Commerce Research , 24 (2), 1–41.
Braun, S., & Osman, D. (2024). Online grocery shopping adoption versus non-adoption among the over-50s in Germany. Electronic Commerce Research , 24 (2), 1–38.
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Koen Pauwels
University of Illinois, Chicago, IL, USA
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Brüggemann, P., Martinez, L.F., Pauwels, K. et al. Introduction: online grocery shopping – current and future challenges and opportunities. Electron Commer Res (2024). https://doi.org/10.1007/s10660-024-09875-w
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Abstract. We offer a structured vision of the main research contributions made on a wide set of issues compounding the online consumer behaviour area. We present a wide view of research topics, analyzed from the marketing perspective, from the early nineties till now. This approach may be useful, not only to better structure or reinforce the ...
Consumer activity in online commerce plays a crucial role in modern business functions, impacting market trends and guiding approaches for digital merchants. This research utilizes the weighted sum technique to assess consumer actions among different age brackets, emphasizing significant indicators like Average Order Value, Satisfaction with Customer Support, Timeliness of Delivery, and Rate ...
The results showed that the main reason for making purchases through e-commerce was due to several things, namely practicality, the absence of products or goods sought directly in the store, many choices and considerations. This study aims to determine the influence of digital media and changes in consumer mindsets in online shopping or e-commerce. E-commerce (electronic commerce) is an ...
only used a quantitative research design, which may not capture the nuances of consumer behavior towards online shopping. Future research can use a larger sample size and a mixed-methods approach to understand consumer behavior towards online shopping in India better. Additionally, future research can explore the impact of trust and security on ...
Consumer behavior is the study of individuals, groups, or organizations and the. processes they use to select, secure, and dispose of products, services, experiences, or ideas to satisfy needs ...
The study also identifies the key drivers that influenced the consumer online purchasing intention during COVID. The results also suggest that preference towards e-commerce platforms remains uniform across the various zones. Extending this study to pan-India level can get better insights of the online shopping patterns of the consumers.
The main aim of the research is: To find out consumer behaviour towards online shopping in Vadodara city. The secondary objectives of the reseach are To identify consumers perception towards online purchasing To identify consumers online buying behaviour To identify consumers prefference towards different websites
The author found that the main factors that affect online shopping are convenience and attractive pricing/discount. Advertising and recommendations were among the least effective. In the study by Lian and Yen (2014), authors tested the two dimensions (drivers and barriers) that might affect intention to purchase online.
The factor analysis is performed for identifying the factors, the nonparametric test has been used for hypothesis testing. Findings - The study results suggest that consumers' online shopping behavior is being affected by several factors like demographic factors, social factors, consumer online shopping experience, knowledge of using ...
1. Introduction. Global retail sales through all channels were valued at $21 trillion in 2019. The retail e-commerce market size and share report (Grand View Research Inc., Citation 2020) show that the global retail e-commerce market size accounted for 20% of the total retail sales value or $4.25 trillion in 2019 and is expected to grow by 9.4% for 2020-2027.
consumer. I. INTRODUCTION. "Consumer behavior is the study of individuals, groups, or organizations and the processes they use to select, secure, and dispose of products, services, experiences, or ideas to satisfy needs and the impacts that these processes have on the consumer and society."" (Kuester, 2012)Shopping has changed as a result ...
Further research in this issue introduces an intelligent retail system centered on the consumer, leveraging the Internet of Things (Ala et al. []).Building on analyses focused on improving the value chain, Ekren et al. [] propose strategies to enhance fulfillment in OGS.Additionally, a crucial factor for the long-term success of OGS, especially beyond the initial surge prompted by the COVID-19 ...
1.5 lakh) have Internet access, and 6 percent are engaged in commercial activity online, the report said. The report also showed that. only 30 per cent of online buyers were drawn to Internet ...