October 12, 2025

The nexus between learning engagement, knowledge acquisition and valence of use: role of generative AI adoption in business context

Key Points

A positive relationship exists between performance expectancy and instrumentality of generative AI, leading to improved knowledge acquisition.
Business executives’ engagement in learning is enhanced through effective use of generative AI, which correlates positively with their valence.
Motivation acts as a moderator, influencing how executives' competence with generative AI boosts their learning and knowledge abilities.
The theoretical model developed from expectancy-value theory provides insight into the dynamics between generative AI use and executive engagement.

Abstract

Purpose This study aims to examine how generative artificial intelligence (Gen AI)-based knowledge acquisition and learning engagement relate to business executives’ valence for using Gen AI. Design/methodology/approach Based on expectancy-value theory and Vroom’s theory of motivation, this study developed a theoretical model to analyze how performance expectancy and instrumentality of Gen AI relate to business executives’ knowledge acquisition and learning engagement, which further influences their Gen AI valence. Motivation acts as a moderating variable to evaluate how business executives’ motivation and competence in utilizing Gen AI enhance their knowledge and learning abilities, complementing their valence for Gen AI. Findings The results indicate a positive relationship between performance expectancy and the instrumentality of Gen AI regarding business executives’ knowledge acquisition and learning engagement, which positively correlates with their outcome valence of Gen AI. Originality/value The results indicate a positive relationship between performance expectancy and the instrumentality of Gen AI regarding business executives’ knowledge acquisition and learning engagement, which positively correlates with their outcome valence of Gen AI.

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