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AI-augmented customer-owned channels and relationship value

Paper Title: AI-augmented customer-owned channels and relationship value: a multi-mechanism model of engagement, trust, and loyalty

Authors: Jijin Yang, Haliyana Khalid, Xiaoli Xu, Youyu Xu

Corresponding Author: Jijin Yang (yyessayaply@163.com)/Malaysia

 

Abstract

This study explains the processes through which a relationship value in customer-owned channels is generated through AI-powered functionalities by focusing on the integrated psychological and behavioral processes. The basis of the work is large-scale text analysis of 18,456 market reviews of applications among 15-20 top customers in the areas of retail, finance, and life services, examining the entire value chain by semantic BERT analysis, hierarchical regression, and structural equation modeling with 5,000 bootstraps. Analysis of the results reveals the presence of function–dimension matching phenomena. These include intelligent recommendation, which has the maximum cognitive engagement (β = 0.41), chatbots, which have the peak affective engagement (β = 0.45), and predictive services, which are predominant in behavioral engagement with a β of 0.36. Customer-owned platforms produce 37.2% more overall effects than third-party platforms. The role of the overall chain mediating function of AI functions for relationship value creation is also supported by the study. The role that loyalty plays between trust and value is amplified by ownership of the channel. The results above present the objective assessment of the 37% boost that the ROI (Return on Investment) has on customer-owned communication channels. It also explains the role that development considerations play.
 
 

Keywords

Artificial intelligence enhancement, Customer-owned channels, Customer engagement, Dual trust, Loyalty mediation, Relationship value

 

Cite:

Yang, J., Khalid, H., Xu, X., & Xu, Y. (2026). AI-augmented customer-owned channels and relationship value: a multi-mechanism model of engagement, trust, and loyalty . Future Technology5(2), 38–48. Retrieved from https://fupubco.com/futech/article/view/695

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