Volume 10, Issue 1 (6-2023)
Human Information Interaction 2023, 10(1): 43-67 |
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Shakouri yadegari S, Hosseini M H, Khademi S M, forouzandeh L. Presenting the model of consumer behavior in e-commerce with an exploratory approach. Human Information Interaction 2023; 10 (1)
URL: http://hii.khu.ac.ir/article-1-3116-en.html
URL: http://hii.khu.ac.ir/article-1-3116-en.html
Assistant professer, Tama headquarters, Department of Business Administration, Payam Noor University, Tehran, Iran
Abstract: (2723 Views)
purpose: consumer behavior in the field of e-commerce and web-based services has different dimensions, including psychological, cultural, economic, personality, etc. components. Since the e-commerce market is constantly growing, it creates a good development opportunity for businesses, so business opportunities should be more adapted to the characteristics and behavioral characteristics of consumers to better meet customer needs. fulfill and facilitate business success. The current research was conducted with the aim of presenting the pattern of consumer behavior in electronic commerce with an exploratory approach.
Methodology: In terms of its fundamental purpose, this research is a survey descriptive research that was conducted in a mixed exploratory manner.
Findings: The results showed that the model of consumer behavior in e-commerce includes: causal conditions, categories, platforms, intervening factors, strategies and consequences. Also, in the quantitative part, the results of the research indicated the approval of most of the components of the qualitative part of the research by the experts.
Conclusion: Examining patterns and models of consumer behavior in e-commerce is necessary for institutions, and in this regard, the results of this research model and other models presented in the field of study should be used in order to create fields for predicting consumer behavior.
Methodology: In terms of its fundamental purpose, this research is a survey descriptive research that was conducted in a mixed exploratory manner.
Findings: The results showed that the model of consumer behavior in e-commerce includes: causal conditions, categories, platforms, intervening factors, strategies and consequences. Also, in the quantitative part, the results of the research indicated the approval of most of the components of the qualitative part of the research by the experts.
Conclusion: Examining patterns and models of consumer behavior in e-commerce is necessary for institutions, and in this regard, the results of this research model and other models presented in the field of study should be used in order to create fields for predicting consumer behavior.
References
1. Adib Haj Bagheri, M. (2006). Grounded theory research method: theorizing method in humanities and health sciences. Publisher: Tehran: Bushra: Tohfe.
2. Akyuz, E., Celik, E. (2015). A fuzzy DEMATEL method to evaluate critical operational hazards during gas freeing process in crude oil tankers. Journal of Loss Prevention in the Process Industries. 38: 243-253. [DOI:10.1016/j.jlp.2015.10.006]
3. Bahrini, R., & Qaffas, A. A. (2019). Impact of information and communication technology on economic growth: Evidence from developing countries. Economies, 7(1), 21. [DOI:10.3390/economies7010021]
4. Bawack, R. E., Wamba, S. F., Carillo, K. D. A., & Akter, S. (2022). Artificial intelligence in E-Commerce: a bibliometric study and literature review. Electronic Markets, 1-42. [DOI:10.1007/s12525-022-00537-z] [PMID] []
5. Cheba, K., Kiba-Janiak, M., Baraniecka, A., & Kołakowski, T. (2021). Impact of external factors on e-commerce market in cities and its implications on environment. Sustainable Cities and Society, 72, 103032. [DOI:10.1016/j.scs.2021.103032]
6. Cheng C, Lin Y. (2002). Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation. European Journal of Operational Research; 142(1): 174-186. [DOI:10.1016/S0377-2217(01)00280-6]
7. Fedushko, S., & Ustyianovych, T. (2022). E-commerce customers behavior research using cohort analysis: A case study of COVID-19. Journal of Open Innovation: Technology, Market, and Complexity, 8(1), 12. [DOI:10.3390/joitmc8010012]
8. Gajda, K. (2020). Factors shaping inter-organizational trust in e-commerce based on literature review. Management. Vol. 24, No. 1 [DOI:10.2478/manment-2019-0034]
9. Gielens, K., & Steenkamp, J. B. E. (2019). Branding in the era of digital (dis) intermediation. International Journal of Research in Marketing, 36(3), 367-384. [DOI:10.1016/j.ijresmar.2019.01.005]
10. Guthrie, C., Fosso-Wamba, S., & Arnaud, J. B. (2021). Online consumer resilience during a pandemic: An exploratory study of e-commerce behavior before, during and after a COVID-19 lockdown. Journal of Retailing and Consumer Services, 61, 102570. [DOI:10.1016/j.jretconser.2021.102570] []
11. Habibi, A., Jahantigh, F. F., & Sarafrazi, A. (2015). Fuzzy Delphi Technique for Forecasting and Screening Items. Asian Journal of Research in Business Economics and Management, 5(2), 130- 143. [DOI:10.5958/2249-7307.2015.00036.5]
12. Hamed, A., Ball, D., Berger, H., & Cleary, P. (2008). The threequarter moon: A new model for E-Commerce adoption. Communications of the IBIMA, 4(11), 88-96.
13. Han, H. (2021). Consumer behavior and environmental sustainability in tourism and hospitality: A review of theories, concepts, and latest research. Journal of Sustainable Tourism, 29(7), 1021-1042. [DOI:10.1080/09669582.2021.1903019]
14. Hasslinger, A., Hodzic, S., & Opazo, C. (2007). Online consumer behavior in online shopping. Kristianstad university.
15. Khoo, V., Ahmi, A., & Saad, R. A. J. (2018, September). A comprehensive review on e-commerce research. In AIP Conference Proceedings (Vol. 2016, No. 1, p. 020069). AIP Publishing LLC. [DOI:10.1063/1.5055471]
16. Kim, R.Y., (2020). The impact of COVID-19 on consumers: preparing for digital sales. IEEE Eng. Manag. Rev. 1, 1. [DOI:10.1109/EMR.2020.2990115]
17. Kuswanto, A. (2016). Perception of factors influence on intention of adopting e-commerce with the business value as intervening variable. Advanced Science Letters, 22(5-6), 1614-1617. [DOI:10.1166/asl.2016.6704]
18. Li, Z., Luan, D., Zhang, Y., & Guo, P. (2018). The evaluation of e-commerce efficiency in China using DEA-tobit model: Evidence from taobao data. WHICEB, Proceedings, 73 http://aisel.aisnet.org/whiceb2018/73.
19. Mojaddam, K., Nadaf, M., Mohammadi, S. (2019). Examining Factors affecting Consumer Use Behavior from Online Shopping Technology based on the Unified Theory of Acceptance and Use of Technology2 (UTAUT2) Case Study: Digikala Customers in Khuzestan Province, New Marketing Research Journal, 9(4), 115-135. magiran.com/p2171019
20. Mahmoodi , M,. karbalaee mehdi,F. (2018). An Investigation of the Effect of Electronic Sales on Consumer Behavior Reactions (The Case of RighTel Company's Customer), Journal of Psychological Research in Management, 4(6), 61-77. magiran.com/p1988547
21. Montazer, G.A., Jafari, N. (2008). Application of Fuzzy Delphi Method in Designing Tax Policy in Iran, The Economic Reseach, 8(1), 91-114. magiran.com/p713427
22. Rohani, S., Zare, A. (2013). Identification and Classification of Affecting Factors on E-Tourism in Iran, Journal of Tourism Planning and Development, 2(5), 184-206. magiran.com/p1194315
23. Rita, P., & Ramos, R. F. (2022). Global research trends in consumer behavior and sustainability in E-Commerce: A bibliometric analysis of the knowledge structure. Sustainability, 14(15), 9455. [DOI:10.3390/su14159455]
24. Shafizadeh, H. Seyedi, S. I. Ghasemi Dalarsetaghi, I. (2013). Presentation of Integrated Model of Consumer Behavior in Electronic Shopping, Journal of Marketing Management, 8(19), 13-28. magiran.com/p1160627
25. Sheth, J. (2020). Impact of Covid-19 on consumer behavior: Will the old habits return or die?. Journal of business research, 117, 280-283. [DOI:10.1016/j.jbusres.2020.05.059] [PMID] []
26. Tran, L. T. T. (2021). Managing the effectiveness of e-commerce platforms in a pandemic. Journal of Retailing and Consumer Services, 58, 102287. [DOI:10.1016/j.jretconser.2020.102287] []
27. Trudel, R. (2019). Sustainable consumer behavior. Consumer psychology review, 2(1), 85-96. [DOI:10.1002/arcp.1045]
28. Wigand, R. T., Benjamin, R. I., & Birkland, J. L. (2008, August). Web 2.0 and beyond: implications for electronic commerce. In Proceedings of the 10th international conference on Electronic commerce (pp. 1-5). [DOI:10.1145/1409540.1409550]
29. Wigand, R. T., Benjamin, R. I., & Birkland, J. L. (2008, August). Web 2.0 and beyond: implications for electronic commerce. In Proceedings of the 10th international conference on Electronic commerce (pp. 1-5). [DOI:10.1145/1409540.1409550]
30. Wu, C. H., and Fang, W. C, (2011), Combining the Fuzzy Analytic Hierarchy Process and the fuzzy Delphi method for developing crit-ical competences of electronic commerce professional managers. Qual Quant, 45(7): 751-768. [DOI:10.1007/s11135-010-9425-6]
31. Zhang, C., & Tan, T. (2020, May). The Impact of Big Data Analysis on Consumer Behavior. In Journal of Physics: Conference Series (Vol. 1544, No. 1, p. 012165). IOP Publishing. [DOI:10.1088/1742-6596/1544/1/012165]
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