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Determinants of users’ intention to adopt m-commerce: an empirical analysis

Author

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  • Zoran Kalinic

    (University of Kragujevac)

  • Veljko Marinkovic

    (University of Kragujevac)

Abstract

The fast-growing penetration of mobile devices and recent advances in mobile technologies have led to the development of increasingly sophisticated services such as m-shopping for goods or services and m-payment. However, although the number of mobile subscribers is increasing, levels of actual m-commerce activities in many cases remain low. Determining what influences users’ intention to use m-commerce is therefore of growing importance. The purpose of this study was to investigate possible factors. To this aim, we developed a conceptual user adoption model based on technology acceptance model variables and on specific factors such as social influence, personal innovativeness, customization, and individual mobility. The empirical results show that social influence and customization significantly affect perceived usefulness; mobility, customization, and personal innovativeness significantly affect perceived ease of use; and perceived usefulness and perceived ease of use have a direct positive effect on behavioral intention.

Suggested Citation

  • Zoran Kalinic & Veljko Marinkovic, 2016. "Determinants of users’ intention to adopt m-commerce: an empirical analysis," Information Systems and e-Business Management, Springer, vol. 14(2), pages 367-387, May.
    • Handle: RePEc:spr:infsem:v:14:y:2016:i:2:d:10.1007_s10257-015-0287-2
    DOI: 10.1007/s10257-015-0287-2
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    References listed on IDEAS

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    Cited by:

    1. Brusch, Ines & Rappel, Nina, 2020. "Exploring the acceptance of instant shopping – An empirical analysis of the determinants of user intention," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    2. Chen, Chia-Chen & Chang, Chin-Hsuan & Hsiao, Kuo-Lun, 2022. "Exploring the factors of using mobile ticketing applications: Perspectives from innovation resistance theory," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    3. Ajimon George & Prajod Sunny, 2021. "Developing a Research Model for Mobile Wallet Adoption and Usage," IIM Kozhikode Society & Management Review, , vol. 10(1), pages 82-98, January.
    4. Siyal, Abdul Waheed & Chen, Hongzhuan & Jamal Shah, Syed & Shahzad, Fakhar & Bano, Shaher, 2024. "Customization at a glance: Investigating consumer experiences in mobile commerce applications," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    5. Pillai, Rajasshrie & Sivathanu, Brijesh & Dwivedi, Yogesh K., 2020. "Shopping intention at AI-powered automated retail stores (AIPARS)," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    6. Liébana-Cabanillas, Francisco & Marinkovic, Veljko & Ramos de Luna, Iviane & Kalinic, Zoran, 2018. "Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 117-130.
    7. Hou, Jianwei & Elliott, Kevin, 2021. "Mobile shopping intensity: Consumer demographics and motivations," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    8. Casado-Aranda, Luis-Alberto & Liébana-Cabanillas, Francisco & Sánchez-Fernández, Juan, 2018. "A Neuropsychological Study on How Consumers Process Risky and Secure E-payments," Journal of Interactive Marketing, Elsevier, vol. 43(C), pages 151-164.
    9. Yong Liu & Meng Wang & Danyu Huang & Qiang Huang & Hua Yang & Zhigang Li, 2019. "The impact of mobility, risk, and cost on the users’ intention to adopt mobile payments," Information Systems and e-Business Management, Springer, vol. 17(2), pages 319-342, December.
    10. Heetae Yang & Hwansoo Lee, 2019. "Understanding user behavior of virtual personal assistant devices," Information Systems and e-Business Management, Springer, vol. 17(1), pages 65-87, March.
    11. Yang, Luming & Xu, Min & Xing, Lin, 2022. "Exploring the core factors of online purchase decisions by building an E-Commerce network evolution model," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    12. Ming Wang & Jaewon Choi, 2022. "How Web Content Types Improve Consumer Engagement through Scarcity and Interactivity of Mobile Commerce?," Sustainability, MDPI, vol. 14(9), pages 1-18, April.

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