How chatbot e-services motivate communication credibility and lead to customer satisfaction: The perspective of Thai consumers in the apparel retailing context

  • Received April 26, 2022;
    Accepted June 21, 2022;
    Published July 8, 2022
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.18(3).2022.02
  • Article Info
    Volume 18 2022, Issue #3, pp. 15-27
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This work is licensed under a Creative Commons Attribution 4.0 International License

Correction to this article was published on 13 July 2023

Many apparel retailing brands use e-service marketing tools such as a chatbot (a system that is available 24 hours a day, 7 days a week) to increase their competitive advantage in today’s world of digitalization. During the COVID-19 pandemic, chatbots gained more power to serve as a communication tool that provides information and maintains customer experience. Therefore, this study is conducted to investigate the influence of chatbot e-service agents’ marketing efforts (involving interaction, entertainment, trendiness, and problem-solving) on Thai customers’ perceived communication credibility and satisfaction in apparel retailing, as research in this area is limited. In order to test the hypotheses, the paper employed structural equation modeling using Amos. In addition, an online survey of 400 Thai consumers who had previously used chatbots in the apparel retailing industry was conducted. The results showed that chatbot e-service marketing efforts, including interaction, trendiness, and problem-solving, affected customer satisfaction without entertainment elements. Beyond this, a chatbot, viewing interaction and entertainment, was found to have an insignificant effect on communication credibility. Thus, the coefficient value proved that information regarding communication credibility is more dominant in customer satisfaction. Therefore, the chatbot e-service marketing effort is essential in motivating communication credibility in customer satisfaction. These findings delivered managerial implications for understanding consumers in the field of digitalization.

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    • Figure 1. Conceptual framework
    • Table 1. Demographic characteristics
    • Table 2. Measuring sampling adequacy and Bartlett’s test of sphericity
    • Table 3. Reliability and validity result
    • Table 4. Structural model and hypothesis testing
    • Table A1. Factor analysis results
    • Conceptualization
      Akawut Jansom, Thaksaorn Srisangkhajorn, Wutticha Limarunothai
    • Data curation
      Akawut Jansom
    • Methodology
      Akawut Jansom, Thaksaorn Srisangkhajorn, Wutticha Limarunothai
    • Validation
      Akawut Jansom, Thaksaorn Srisangkhajorn, Wutticha Limarunothai
    • Writing – original draft
      Akawut Jansom
    • Supervision
      Thaksaorn Srisangkhajorn
    • Writing – review & editing
      Thaksaorn Srisangkhajorn, Wutticha Limarunothai
    • Software
      Wutticha Limarunothai