Advancing Occupational Health and Safety with Wearable Technologies: An MCDM Framework for HR Strategies in the Manufacturing Sector

Abstract

This study develops a novel framework for prioritizing wearable technologies in Occupational Health and Safety (OHS) within the manufacturing sector, addressing both technical performance and workforce integration. The purpose of the framework is twofold: first, to identify the key criteria influencing the adoption and effectiveness of wearable technologies, such as safety impact, cost-effectiveness, reliability, ease of training, and employee adoption; and second, to create a structured decision-making approach that supports HR practitioners, stakeholders, and OHS managers in evaluating and selecting technologies. By integrating Fuzzy DEMATEL to analyze causal relationships among criteria and PROMETHEE to rank alternatives, the study reveals that cost-effectiveness and safety impact are the most influential drivers. The wearable technology alternatives, including Gas Detection Sensors, Fatigue-Monitoring Bands, Smart Helmets, and Exoskeletons, were selected as a simulation for the prioritization process, reflecting a diverse set of use cases and challenges. The findings highlight Gas Detection Sensors as the top-ranked technology due to their superior safety and reliability performance, followed by Fatigue-Monitoring Bands and Smart Helmets, while Exoskeletons rank lowest due to cost and training challenges. This framework emphasizes the alignment of technical solutions with workforce readiness, providing actionable insights for decision-makers, including strategies for enhancing employee adoption and targeted training programs. Grounded in the Technology Acceptance Model (TAM) to explain adoption behavior, the study bridges technical evaluation with human-centric criteria, offering a scalable, practical decision-making framework applicable to other industries aiming to enhance workplace safety through wearable technologies.