Digital payment system innovations: A marketing perspective on intention and actual use in the retail sector

  • Received July 16, 2021;
    Accepted August 25, 2021;
    Published September 1, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.17(3).2021.09
  • Article Info
    Volume 17 2021, Issue #3, pp. 109-123
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This work is licensed under a Creative Commons Attribution 4.0 International License

This study empirically investigated the marketing perspectives of behavioral intention and the actual use of digital payment solutions as electronic innovation for retail purchases in Thailand. This is important as leveraging digital innovation can be applied to minimize physical contact between retailers and customers, especially in the COVID-19 era. The UTAUT model was used and extended to include attitude, social distancing, and perceived risk variables. The study was conducted using primary data collected from 467 Thai respondents who used digital payment systems as a means of payment in retail purchases. The study data were collected employing a structured questionnaire. Techniques used in data analysis include Confirmatory Factor Analysis and Structural Equation Modeling. The results from the data analysis highlighted that behavioral intention to use digital payment innovation in Thailand was influenced by Perceived Risk (PR), Facilitating Condition (FC), Performance Expectancy (PE), and Attitudes (AT) of people. The study also revealed that exploring the marketing perspectives, Behavioral Intention (BI) significantly influenced the Actual Use (AU) of digital payment systems. The implication is that stakeholders in retail and financial sectors, such as banks and other digital payment providers, should consider aspects of people’s attitudes and perceived risk as they influence the use and adoption of innovative digital payment solutions. Thus, it is, appropriate to propose policies and regulations that promote the effective use of digital payment systems in the Thai retail sector.

Acknowledgment
This work is supported by King Mongkut’s Institute of Technology Ladkrabang.

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    • Figure 1. Conceptual framework
    • Figure 2. Confirmatory factor analysis
    • Figure 3. Structural equation model analysis
    • Table 1. Demographics and respondent adoption of digital payments
    • Table 2. Reliability and validity statistics – Composite reliability and average variance extracted
    • Table 3. Evaluation of study hypotheses
    • Conceptualization
      Singha Chaveesuk, Bilal Khalid, Wornchanok Chaiyasoonthorn
    • Data curation
      Singha Chaveesuk, Bilal Khalid
    • Formal Analysis
      Singha Chaveesuk, Bilal Khalid
    • Investigation
      Singha Chaveesuk, Bilal Khalid, Wornchanok Chaiyasoonthorn
    • Methodology
      Singha Chaveesuk, Bilal Khalid, Wornchanok Chaiyasoonthorn
    • Resources
      Singha Chaveesuk, Bilal Khalid, Wornchanok Chaiyasoonthorn
    • Validation
      Singha Chaveesuk, Bilal Khalid, Wornchanok Chaiyasoonthorn
    • Writing – original draft
      Singha Chaveesuk, Bilal Khalid, Wornchanok Chaiyasoonthorn
    • Writing – review & editing
      Singha Chaveesuk, Bilal Khalid, Wornchanok Chaiyasoonthorn
    • Software
      Bilal Khalid