Knowledge management in metaverse: does knowledge storage matter as a factor affecting adoption and acceptance?

Abstract

Purpose This study aims to examine the behavioral intention of educators in higher education institutions regarding the adoption of knowledge management-driven metaverse technology (KM-D-MT). Grounded in unified theory of acceptance and use of technology 2 (UTAUT2), this research aims to enhance understanding of metaverse adoption factors, examining correlations among key constructs such as performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), perceived value (PV), hedonic motivation (HM), stability and knowledge storage. Design/methodology/approach Using a cross-sectional design and a quantitative approach, this study collects 278 responses from medical college educators and employs structural equation modeling-partial least squares to analyze the data, assessing the reliability and validity of research instruments. Findings The findings reveal significant positive impacts of PE, PE, SI, FC, PV and HM on the behavioral intention to adopt KM-D-MT. Stability is identified as a key factor positively influencing knowledge storage. In addition, knowledge storage shows positive correlations with behavioral intention. This study highlights the transformative potential of metaverse technology in reshaping knowledge management processes. Originality/value In terms of originality, this research contributes significantly to theoretical perspectives by advancing metaverse research, extending UTAUT2 frameworks in the medical education context and contributing to knowledge management paradigms. The study’s exploration of metaverse adoption in Iraqi medical colleges provides valuable insights for global research and practical applications.