ABSTRACT There is increasing engagement with AI tools; however, the extant literature needs a prominent tool to examine the factors that develop the attractiveness of AI tools to improve productivity. To this end, we developed an index of AI tool attractiveness (AI-ATT) based on the extended unified theory of acceptance and use of technology (UTAUT2). This study proposed performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and price value as potential formative constituents and enablers of AI-ATT. Based on 311 perceptual responses from Gen Zs and millennials residing in East India, and 224 from the West, this study developed a six-factor index for AI-ATT based on established best practices. Perceptual responses for the measurement and structural models using partial least squares. The contingent effect was evaluated using Process Macro in the SPSS 28. The developed index can also predict the behavioural intention of Gen Zs and millennials to use AI tools. Furthermore, the study underscores the significant contingent effect of generation (Gen Z vs. millennials) on each enabler’s role in AI ATT. The theoretical and practical implications are also discussed. This study is the first to develop a measurement scale for understanding the perceived attractiveness of AI tools.
Read full abstract