Scholarlink

<p>The adoption of mobile banking has become progressively more important for financial inclusion programs, particularly in rapidly digitalizing regions like Northern India. Chatbot-based m-banking services remain unpredictable despite the rise in smartphone penetration and internet availability. This study proposes an adapted Unified Theory of Acceptance and Use of Technology (UTAUT) model to examine users’ behavioral intention to adopt mobile banking, emphasizing the role of mobile banking chatbot customization. The study also contributes theoretically by validating an extended UTAUT model aligned with the mobile banking context to examine users’ behavioral intention with additional variables such as perceived epistemic value and the customization of mobile banking chatbots. It restructures traditional UTAUT paths by examining the mediating role of core constructs, thus enhancing contextual relevance. The research introduces perceived epistemic value as a novel construct and restructures traditional UTAUT paths by exploring the effects of performance expectancy, effort expectancy, and social influence. The study aims to assess the impact of customization of mobile banking chatbot on performance expectancy and effort expectancy, investigates the influence of customization of mobile banking chatbot and social influence on perceived epistemic value and its subsequent effect on behavioral intention, evaluates the mediating roles of performance expectancy, effort expectancy, and perceived epistemic value and enhances the contextual applicability of the UTAUT model in the m-banking domain. A quantitative, cross-sectional research design was adopted using a structured questionnaire administered to m-banking users in Northern India. The sample comprised 441 valid responses. Data analysis was conducted using Structural Equation Modeling via SmartPLS. The findings (R² = 0.701) reveal that customization enhances m-banking users’ knowledge and elevates the perceived value of knowledge gained during an interaction with the m-banking chatbot.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Comfort your mobile banking customer: An empirical study on customization of mobile banking chatbot using perceived epistemic value as a mediating variable

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月23日

查看全文
  • Vandana Chotani,
  • Rakesh Kumar Sharma,
  • Tarunpreet Bhatia

摘要

The adoption of mobile banking has become progressively more important for financial inclusion programs, particularly in rapidly digitalizing regions like Northern India. Chatbot-based m-banking services remain unpredictable despite the rise in smartphone penetration and internet availability. This study proposes an adapted Unified Theory of Acceptance and Use of Technology (UTAUT) model to examine users’ behavioral intention to adopt mobile banking, emphasizing the role of mobile banking chatbot customization. The study also contributes theoretically by validating an extended UTAUT model aligned with the mobile banking context to examine users’ behavioral intention with additional variables such as perceived epistemic value and the customization of mobile banking chatbots. It restructures traditional UTAUT paths by examining the mediating role of core constructs, thus enhancing contextual relevance. The research introduces perceived epistemic value as a novel construct and restructures traditional UTAUT paths by exploring the effects of performance expectancy, effort expectancy, and social influence. The study aims to assess the impact of customization of mobile banking chatbot on performance expectancy and effort expectancy, investigates the influence of customization of mobile banking chatbot and social influence on perceived epistemic value and its subsequent effect on behavioral intention, evaluates the mediating roles of performance expectancy, effort expectancy, and perceived epistemic value and enhances the contextual applicability of the UTAUT model in the m-banking domain. A quantitative, cross-sectional research design was adopted using a structured questionnaire administered to m-banking users in Northern India. The sample comprised 441 valid responses. Data analysis was conducted using Structural Equation Modeling via SmartPLS. The findings (R² = 0.701) reveal that customization enhances m-banking users’ knowledge and elevates the perceived value of knowledge gained during an interaction with the m-banking chatbot.