EXPLORING MOBILE TECHNOLOGY ADOPTION IN THE REPUBLIC OF SERBIA: IDENTIFYING CONSUMER SEGMENTS

Eighth International Scientific Conference Contemporary Issues in Economics, Business and Management [EBM 2024], [pp. 143-151]

AUTHOR(S) / AUTOR(I): Julija Vidosavljević

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DOI: 10.46793/EBM24.143V

ABSTRACT / SAŽETAK:

Mobile commerce is rapidly becoming a major driver of global commerce, with the potential to surpass traditional purchasing methods. As technology adoption expands, various models have emerged to explain user acceptance. While models like TAM offer foundational insights into user acceptance, they often lack the depth to address the complexity of modern consumer behavior. The UTAUT2 model expands on this by integrating factors such as hedonic motivation, price value, and habit, providing a more comprehensive framework for understanding mobile commerce adoption. Segmentation plays a critical role in this dynamic industry, helping businesses tailor strategies to diverse consumer needs. Considering the above mentioned, the aim of the paper is to identify distinct consumer segments regarding the acceptance and usage of mobile technologies, with UTAUT2 determinants serving as the foundation for segment classification. The sample consists of 210 respondents. The research was conducted in the territory of Central Serbia, from April to May 2023. Descriptive statistical analysis and cluster analysis were applied in the paper. The findings highlight the importance of customizing mobile commerce platforms for specific consumer groups. For lower- income users, strategies should focus on affordability, including discounts, flexible payment options, and easy-to-use interfaces. Educational campaigns addressing barriers like security concerns and limited technical knowledge, along with regular feedback, can further enhance offerings. This approach enables businesses to optimize platforms, ensuring they meet the needs of diverse consumer groups and improve overall user satisfaction.

KEYWORDS / KLJUČNE REČI:

m-commerce, UTAUT2, consumer segments

REFERENCES / LITERATURA:

  • Bhatnagar, A., & Ghose, S. (2004). A latent class segmentation analysis of e-shoppers. Journal of Business Research, 57(7), 758-767. https://doi.org/10.1016/S0148-2963(02)00357-0
  • Chong, A.Y.L. (2013). Predicting m-commerce adoption determinants: A neural network approach. Expert Systems with Applications, 40(2), 523-530. https://doi.org/10.1016/j.eswa.2012.07.068
  • Cui, Z. (2023). Clustering-Based Analysis of E- in the Post-epidemic Period, In book: 4th International Conference on E-Commerce and Internet Technology (ECIT 2023), 30-35. https://doi.org/10.2991/978-94-6463-210-1_5
  • Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS   Quarterly, 13 (3), 319-340. https://doi.org/10.2307/249008
  • Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35 (8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982
  • Huang, E. Y., Lin, S.-W., & Fan, Y.-C. (2015). M-S-QUAL: Mobile service quality measurement. Electronic Commerce Research and Applications, 14(2), 126142. https://doi.org/10.1016/j.elerap.2015.01
  • Humbani, M., & Wiese, M. (2019). An integrated framework for the adoption and continuance intention to use mobile payment apps. International Journal of Bank Marketing, 37(2), 646-664. https://doi.org/10.1108/IJBM-03-2018-0072
  • Kargin, B., Basoglu, N., & Turgul, B. (2009). Exploring Mobile Service Adoption: Customer Preferences, 42st Hawaii International International Conference on Systems Science (HICSS-42 2009), Proceedings (CD-ROM and online), 5-8 January 2009, Waikoloa, Big Island, HI, USA, 1-8. https://doi.org/10.1109/HICSS.2009.211
  • Lamberton, C., & Stephen, A. T. (2016). A Thematic Exploration of Digital, Social Media, and Mobile Marketing: Research Evolution from 2000 to 2015 and an Agenda for Future Inquiry. Journal of Marketing, 80(6), 146-172.  https://doi.org/10.1509/jm.15.0415
  • Ma, Q., & Liu, L. (2005). The Technology Acceptance Model: A Meta-Analysis of Empirical Findings. In M. Mahmood (Ed.), Advanced Topics in End User Computing, Volume 4 (pp. 112-128). IGI Global. https://doi.org/10.4018/978-1-59140-474-3.ch006
  • Marić, D. (2024). Understanding the determinants of continuous intention to use m-commerce: Application of the adapted UTAUT model. Marketing, 55(1), 5-16. https://doi.org/10.5937/mkng2401005M
  • Nunnally, J. C. (1978). Introduction to psychological measurement, New York: McGraw-Hill Omar, S., Mohsen, K., Tsimonis, G., Oozeerally, A., & Hsu, J.-H. (2021). M-commerce: The nexus between mobile shopping service quality and loyalty. Journal of Retailing and Consumer Services, 60, 1-15. https://doi.org/10.1016/j.jretconser.2021.102468
  • Payne, A.F., Storbacka, K., & Frow, P. (2008). Managing the co-creation of value. Journal of the Academy Market Sciences, 36, 83 – 96. https://doi.org/10.1007/s11747-007-0070-0
  • Quinn, L. (2009). Market segmentation in managerial practice: a qualitative examination. Journal of Marketing Management, 25, (3-4), 253-272.  https://doi.org/10.1362/026725709X429746
  • Sarkar, D. (2012). A Noble Approach of Clustering the Users in M-Commerce for Providing Segmented Promotion of Goods & Services Using K-means Algorithm. International Conference on Computer Technology and Science (ICCTS 2012) IPCSIT, IACSIT Press, Singapore, 96-100. https://doi.org/10.7763/IPCSIT.2012.V47.19
  • Social Serbia (2024). Istraživanje stanja društvenih mreža u Srbiji  https://pioniri.com/sr/socialserbia2024// datum pristupa: 05.09.2024.
  • Tak, P., & Panwar, S. (2017) Using UTAUT 2 model to predict mobile app based shopping: evidences from India. Journal of Indian Business Research, 9 (3), 248 264. https://doi.org/10.1108/JIBR-11-2016-0132
  • Venkatesh, V., Morris, M., Gordon B. Davis, G., & Davis, F. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27 (3), 425-478. https://doi.org/10.2307/30036540
  • Venkatesh, V., Thong, J.Y.L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412
  • Zhao, B. (2022). Research on Using Market Segmentation to do Recommendation in E- commerce. BT – Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022), 3017-3022. https://doi.org/10.2991/aebmr.k.220307.492