Antecedents of big data analytics and artificial intelligence adoption on operational performance: the ChatGPT platform

Abstract

PurposeThis study aims to measure the integrated impact of big data analytics and artificial intelligence (BDA-AI) adoption by using the ChatGPT generative AI online platform as a BDA-AI tool on the operational and environmental performance.Design/methodology/approachThis study considers Taiwanese professionals who engage with ChatGPT; the sample consists of 388 online users.FindingsThis study’s main finding is that the considered antecedents – including technological, organizational and environmental contexts, tangible resources and workforce skills – are significantly associated with BDA-AI adoption. Notably, BDA-AI adoption exhibits a significant relationship with operational performance, environmental performance and environmental process integration. Moreover, environmental process integration is significantly correlated with environmental performance. Lastly, operational performance is significantly correlated with environmental performance.Originality/valueThis study contributes to the heavily lacking but developing literature on the antecedents and consequences of BDA-AI adoption. Its theoretical foundation consists of the technological-organizational-environmental model, Roger’s diffusion of innovation theory and resource-based view theory.