ELEKTRON TIJORATNI RIVOJLANTIRISHDA XORIJIY TAJRIBALARDAN FOYDALANISH MASALALARI
DOI:
https://doi.org/10.5281/zenodo.20258044Keywords:
elektron tijorat, Big Data, sun’iy intellekt, text-mining, mijozlar qoniqishi, risklar tahlili, raqamli logistikaAbstract
Mazkur maqolada global va milliy miqyosda elektron tijorat bozorining rivojlanish dinamikasi eMarketer va
UNCTAD ma’lumotlari asosida tahlil qilingan. Tadqiqot natijalari elektron savdo hajmining barqaror o‘sishi bilan bir qatorda
infratuzilmaviy nomutanosibliklar mavjudligini ko‘rsatadi. Shuningdek, O‘zbekiston misolida elektron tijorat bozorining
kengayish tendensiyalari hamda uning rivojlanishini cheklovchi omillar aniqlangan
References
1. Alrawad, M., Lutfi, A., Alyatama, S., Al Khattab, A., Alsoboa, S. S., Almaiah, M. A., Ramadan, M. H., Arafa, H. M.,
Ahmed, N. A., Alsyouf, A., & Al-Khasawneh, A. L. (2023). Assessing customers’ perception of online shopping risks:
A structural equation modeling-based multigroup analysis. Journal of Retailing and Consumer Services, 71, 103188.
DOI: 10.1016/j.jretconser.2022.103188.
2. Ariffin, S. K., Mohan, T., & Goh, Y.-N. (2018). Influence of consumers’ perceived risk on consumers’ online purchase
intention. Journal of Research in Interactive Marketing, 12(3), 309–327. DOI: 10.1108/JRIM-11-2017-0100.
3. Chen, X., Long, J., Lin, L., & Lin, B. (2023). E-commerce enterprises financial risk prediction based on FA-PSO-LSTM
neural network deep learning model. Sustainability, 15(7), 5882. DOI: 10.3390/su15075882.
4. Cong, X. (2021). Research on financial risk management of e-commerce enterprises in the era of big data. Proceedings of
the 7th International Conference on Frontiers of Educational Technologies, 195–199. DOI: 10.1145/3473141.3473248.
5. Dai, Y. N., Viken, G., Joo, E., & Bente, G. (2018). Risk assessment in e-commerce: How sellers’ photos, reputation
scores, and the stake of a transaction influence buyers’ purchase behavior and information processing. Computers in
Human Behavior, 84, 342–351. DOI: 10.1016/j.chb.2018.02.038.
6. Forsythe, S., Liu, C., Shannon, D., & Gardner, L. C. (2006). Development of a scale to measure the perceived benefits
and risks of online shopping. Journal of Interactive Marketing, 20(2), 55–75. DOI: 10.1002/dir.20061.
7. Guru, S., Nenavani, J., Patel, V., & Bhatt, N. (2020). Ranking of perceived risks in online shopping. DECISION, 47(2),
137–152. DOI: 10.1007/s40622-020-00241-x.
8. Huang, Z. (2017). A study of e-commerce transaction risk assessment model in mobile internet. Journal of Electronic
Commerce in Organizations, 15(4), 1–10. DOI: 10.4018/JECO.2017100101.
9. Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce:
The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544–564. DOI: 10.1016/j.
dss.2007.07.001.
10. Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology
acceptance model. International Journal of Electronic Commerce, 7(3), 101–134. DOI: 10.1080/10864415.2003.1104
4275.
11. Kim, C., Tao, W., Shin, N., & Kim, K. S. (2010). An empirical study of customers’ perceptions of security and trust in
e-payment systems. Electronic Commerce Research and Applications, 9(1), 84–95. DOI: 10.1016/j.elerap.2009.04.014.
12. Zhang, T., Lu, C., & Kizildag, M. (2018). Banking “on-the-go”: Examining consumers’ adoption of mobile banking
services. International Journal of Quality and Service Sciences, 10(3), 279–295. DOI: 10.1108/IJQSS-07-2017-0067.
13. eMarketer. (2025). E-commerce to account for more than 20% of worldwide retail sales despite slowdown. Manba:
eMarketer official website
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