PREDICTING COLLABORATIVE ARTIFICIAL INTELLIGENCE (AI) ADOPTION AMONG OPERATIONS MANAGERS IN MALAYSIA

Abstract

This study examines the factors influencing collaborative artificial intelligence (AI) adoption among operations managers. The study examines the importance of understanding the willingness and obstacles faced by operations managers in integrating collaborative artificial intelligence into their daily work processes. This study collects data from operations managers across Malaysia through online survey questionnaire to evaluate the hypotheses. The 183 valid responses were analyzed using structural equation modeling software SmartPLS v4.1.0.0. This empirical study identifies perceived ease of use (PEOU), perceived usefulness (PU), and perceived trust (PT) as salient independent variables influencing attitude (ATT) toward the adoption of collaborative artificial intelligence (AI). Furthermore, attitude (ATT) significantly mediated the relationship between these independent variables (PEOU, PU, and PT) and behavioral intention (BI) to adopt collaborative AI. However, the moderating effect of technology knowledge (KT) on the relationship between attitude (ATT) and behavioral intention (BI) was not statistically significant. This study contributes to the technology acceptance model (TAM) framework by examining the impact of perceived ease of use (PEOU), perceived usefulness (PU), perceived trust (PT), attitude (ATT), and knowledge in technology (KT) on operations managers' behavioral intention (BI) to collaborative AI adoption. Unlike prior research, this study specifically investigates the determinants of collaborative artificial intelligence adoption within operations management, a domain increasingly reliant on technological advancements for strategic planning and decision-making.