Exploring the Propensity of Adoption of Physiological Emotional Monitoring Technologies in Logistics Via TAM

The integration of emotional monitoring technologies in internal logistics processes might be a relevant driver in enhancing workers’ well-being and, therefore, their operational efficiency within a human-centric perspective. Since logistics industry continues to evolve, understanding the acceptance and adoption of such technologies is becoming crucial. This research proposes a Technology Acceptance Model (TAM) as a framework in order to explore relevant aspects that might impact logistics workers’ acceptance of emotional monitoring technologies, In particular, a bundle of physiological measures, Electromyography (EMG), Electrocardiography (ECG), and Galvanic Skin Conductance (GSC), is taken into account. The objective is to explore how perceived usefulness (PU) and perceived ease of use (PEOU), core constructs of TAM, along with external variables belonging to social, individual and system levels, could be related to this acceptance. The developed questionnaire has been administered to a sample of warehouse operators working on a logistics industry in Italy. The collected data was then analyzed by using Partial Least Squares Structural Equation Modeling (PLS-SEM) methodology, with SmartPLS4. The results show that the developed TAM model is able to explain the acceptance of these technologies in the examined working environment. Despite some different outcomes depending on the technologies, social (in particular, Subjective Norms and Social Influence) and system-related variables (in particular, Effort Expectancy) were more relevant to determine the behavioral intention to use.