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The adoption of mobile payment services by consumers: an empirical analysis results

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  • Arkady Trachuk,
  • Natalia Linder

Abstract

This study considers the problems of distribution and adoption of mobile payment services in Russia and the factors of their perception by distribution network companies and consumers. To analyze the adoption of mobile payment services, in this article a model is suggested that includes both process-based and factor-based approaches. The model combines the user behavior analysis at different stages of the technology acceptance process and the analysis of the factors that influence this process. Factors are determined both by the features of the technologies themselves and by the characteristics of consumers. Within the framework of the process approach, the diffusion of innovation theory of Rogers (2003) and the technology acceptance model of Davis (1989) have been used. The factor analysis has been used to analyze the perception of mobile payment services by consumers and by distribution network companies. To analyze the factors influencing the decision-making by distribution network companies, the POER model, which allows analyzing internal factors, and the PEER model, which allows analyzing external factors, are used. The factors of perception of mobile payment services by consumers are analyzed using the Technology Acceptance Model (TAM) (Davis, 1989). When testing theoretical positions, the approach that comprises model testing at the qualitative stage of research (16 in-depth interviews with representatives of distribution network companies and 34 in-depth interviews with consumers) and subsequent empirical research (based on a sample of 128 distribution network companies and 429 consumer respondents) were applied. Based on the analysis results, conclusions were made about the impact of various factors on the acceptance of mobile payment services, and recommendations for companies that develop and implement mobile payment services have been worked out.This study considers the problems of distribution and adoption of mobile payment services in Russia and the factors of their perception by distribution network companies and consumers. To analyze the adoption of mobile payment services, in this article a model is suggested that includes both process- and factor-based approaches. The model combines the user behavior analysis at different stages of the technology acceptance process and the analysis of the factors that influence this process. Factors are determined both by the features of the technologies themselves and by the characteristics of consumers. Within the framework of the process approach, the diffusion of innovation theory of E. Rogers and the technology acceptance model of F. Davis have been used. The factor analysis has been used to analyze the perception of mobile payment services by consumers and by distribution network companies. To analyze the factors influencing the decision-making by distribution network companies, the POER model, which allows analyzing internal factors, and the PEER model, which allows analyzing external factors, are used. The factors of perception of mobile payment services by consumers are analyzed using the Technology Acceptance Model (TAM) (Davis, 1989). When testing theoretical positions, the approach that comprises model testing at the qualitative stage of research (16 in-depth interviews with representatives of distribution network companies and 34 in-depth interviews with consumers) and subsequent empirical research based on a sample of 128 distribution network companies and 429 consumer respondents were applied. Based on the analysis results, conclusions were made about the impact of various factors on the acceptance of mobile payment services, and recommendations for companies that develop and implement mobile payment services have been worked out.

Suggested Citation

  • Arkady Trachuk, & Natalia Linder, 2017. "The adoption of mobile payment services by consumers: an empirical analysis results," Business and Economic Horizons (BEH), Prague Development Center, vol. 13(3), pages 383-408, July.
    • Handle: RePEc:pdc:jrnbeh:v:13:y:2017:i:3:p:383-408
    DOI: 10.15208/beh.2017.28
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    References listed on IDEAS

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    1. Nicholas Economides, 1997. "The Economics of Networks," Brazilian Electronic Journal of Economics, Department of Economics, Universidade Federal de Pernambuco, vol. 1(0), December.
    2. Shaw, Norman, 2014. "The mediating influence of trust in the adoption of the mobile wallet," Journal of Retailing and Consumer Services, Elsevier, vol. 21(4), pages 449-459.
    3. Mahler, Alwin & Rogers, Everett M., 1999. "The diffusion of interactive communication innovations and the critical mass: the adoption of telecommunications services by German banks," Telecommunications Policy, Elsevier, vol. 23(10-11), pages 719-740, November.
    4. Lam, Shun Yin & Chiang, Jeongwen & Parasuraman, A., 2008. "The effects of the dimensions of technology readiness on technology acceptance: An empirical analysis," Journal of Interactive Marketing, Elsevier, vol. 22(4), pages 19-39.
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    Cited by:

    1. D. N. Savin, 2018. "Developing a new product development & launch process. Case: pharmaceutical market," Strategic decisions and risk management, Real Economy Publishing House, issue 2.
    2. Wei-Lun Chang & Li-Ming Chen & Takako Hashimoto, 2022. "Cashless Japan: Unlocking Influential Risk on Mobile Payment Service," Information Systems Frontiers, Springer, vol. 24(5), pages 1515-1528, October.
    3. A. V. Trachuk & N. V. Linder, 2018. "Fourth Industrial Revolution: How The Internet Of Things Influenceson Industrial Business Relationships?," Strategic decisions and risk management, Real Economy Publishing House, issue 3.
    4. V. L. Dostov & P. M. Shust & A. A. Khorkova, 2018. "Potential of decentralized interbank settlements using blockchain," Strategic decisions and risk management, Real Economy Publishing House, issue 2.

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    More about this item

    Keywords

    Mobile payment service; Models of innovations adoption; Perceived eReadiness model; Perceived external eReadiness;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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