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

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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.

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Acknowledgments

This research was partially supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia, as a part of research project III-44010, titled: Intelligent Systems for Software Product Development and Business Support based on Models.

Author information

Authors and Affiliations

  1. Faculty of Economics, University of Kragujevac, Djure Pucara 3, Kragujevac, 34000, Serbia

    Zoran Kalinic & Veljko Marinkovic

Authors
  1. Zoran Kalinic
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  2. Veljko Marinkovic
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Corresponding author

Correspondence to Zoran Kalinic.

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Ethical statement

The authors declare that the manuscript has not been submitted to other journals for simultaneous consideration and it has not been published previously (partly or in full).

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Appendix: Questionnaire items (1–7-point Likert scale)

Appendix: Questionnaire items (1–7-point Likert scale)

1.1 Social influence

  1. 1.

    Relatives and friends have an influence on my decision to use m-commerce.

  2. 2.

    Mass media (e.g. TV, radio, newspapers) have an influence on my decision to use m-commerce.

  3. 3.

    I would use m-commerce more often if the service was widely used by people in my community.

  4. 4.

    It is the current trend to use m-commerce.

1.2 Innovativeness

  1. 1.

    I think I am one of the first in my community to have tried m-commerce.

  2. 2.

    I am eager to try new technologies.

  3. 3.

    I am eager to learn about new technologies.

  4. 4.

    My friends and neighbors often come to me for advice about new technologies and innovation.

1.3 Mobility

  1. 1.

    I can use m-commerce anytime.

  2. 2.

    I can use m-commerce anywhere

  3. 3.

    I can use m-commerce even while traveling.

  4. 4.

    Using m-commerce is suitable because my mobile phone is always within reach.

1.4 Customization

  1. 1.

    I think using m-commerce meets my needs.

  2. 2.

    I think m-commerce provides information and services according to my preferences.

  3. 3.

    I think the use of m-commerce is in accordance with my personal norms and values.

1.5 Perceived usefulness

  1. 1.

    Using m-commerce improves my work performance.

  2. 2.

    Using m-commerce improves my productivity.

  3. 3.

    Using m-commerce enhances my effectiveness in my work.

1.6 Perceived ease of use

  1. 1.

    I think it’s easy to use m-commerce.

  2. 2.

    I think m-commerce is understandable and clear.

  3. 3.

    I think using m-commerce requires minimum effort.

  4. 4.

    I think learning to use m-commerce is easy.

1.7 Behavioral intention

  1. 1.

    I intend to use m-commerce in the near future.

  2. 2.

    I believe my interest in m-commerce will increase in the future.

  3. 3.

    I will recommend others to use m-commerce.

  4. 4.

    I will encourage my friends and relatives to use m-commerce.

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Kalinic, Z., Marinkovic, V. Determinants of users’ intention to adopt m-commerce: an empirical analysis. Inf Syst E-Bus Manage 14, 367–387 (2016). https://doi.org/10.1007/s10257-015-0287-2

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  • DOI: https://doi.org/10.1007/s10257-015-0287-2

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