JOURNAL ARTICLE

Testing the Framework for Consumer Psychology in Green Gamified Banking: Does Artificial Intelligence in E-Banking Matter?

  • Published In: Journal of Macromarketing, 2025, v. 45, n. 4. P. 863 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Rehman, Obaid ul; Tang, Zhongjun; Arshad, Muhammad Usman 3 of 3

Abstract

This article investigates the psychological transformations involved in adopting green gamified banking (GGB), emphasizing the mediating role of Artificial Intelligence (AI) in e-banking on consumers' intentions to use such services. Using a Consumer Psychology of Brands (CPOB) framework combined with the Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM), the study surveyed 264 participants in mainland China and applied Structural Equation Modeling (SEM) and Fuzzy-Set Qualitative Comparative Analysis (FsQCA) to analyze relationships among brand identification, experience, integration, significance, connection, AI in e-banking, and intention to use GGB. Results indicate that AI fully mediates the effects of brand identification and brand significance on usage intention, while brand experience, integration, and connection are partially mediated; notably, brand integration and connection have strong direct effects on intention. The findings highlight AI’s critical role as a psychological enabler that enhances personalized, engaging, and sustainable banking experiences, offering theoretical extensions to TPB and TAM and practical guidance for banks to leverage AI-driven gamification to foster eco-conscious consumer behavior.

Additional Information

  • Source:Journal of Macromarketing. 2025/12, Vol. 45, Issue 4, p863
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2025
  • ISSN:0276-1467
  • DOI:10.1177/02761467251375915
  • Accession Number:189106471
  • Copyright Statement:Copyright of Journal of Macromarketing is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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