The rapid evolution of immersive technologies (IMTs) underscores the need for food enterprises to adopt a flexible mindset, foster engagement, and embrace technological change to embark on a successful journey. This research employs an organizational change approach to empirically investigate the role of individual unlearning (IUNL) in enabling food sector organizations to navigate this transformation effectively. For this purpose, we utilized the AIDUA framework by interpreting the fundamental factors of employees' perceived autonomy, competence, and relatedness as catalysts for IUNL during the initial appraisal phase. In the ensuing secondary appraisal phase, the perceived performance expectation and effort expectancy of the IUNL approach were investigated, with the ultimate objective of influencing willingness to adopt or reject these IMTs in the final stage.
A mixed-methods approach, utilizing Partial Least Squares Structural Equation Modeling and Artificial Neural Networks, was employed to analyze data from 223 participants in China.
The results showed that fulfilling autonomy, competence, and relatedness has a positive impact on IUNL, which subsequently leads to a notable improvement in performance expectancy and effort expectancy. Furthermore, performance expectancy and effort expectancy have a positive and significant influence on the willingness to adopt IMTs in organizations, while demonstrating no considerable impact on the rejection of IMTs.
These findings highlight the crucial role of unlearning in facilitating IMT adoption and have far-reaching implications for shaping organizational strategy, fostering innovation, and facilitating a smooth transition to an increasingly dynamic technology environment.
