Group preference decision-making for the implementation of Industry 4.0 in food and beverage SMEs

This study aimed to model group preference decision-making to implement Industry 4.0 on food and beverage small- and medium-sized enterprises (SMEs). An ant colony optimisation was adopted to model the decision-making process based on the travelling salesman problem. The model was demonstrated on three preferences of Industry 4.0, namely, ergonomic work methods, machineries and tools, and e-commerce and promotion. The Likert-scale Kansei words data were obtained from 120 SMEs’ manager in Indonesia. The data were then plotted to Cartesian coordinates with the x and y-axes showing the mode and average values, respectively, and were simulated in a sequence using ACO. The results indicated that machinery and tools were the most preferred to implement Industry 4.0. Adaptiveness was the most preferred attribute in making the first decision. The benchmarking demonstrated ACO performed better than genetic algorithm in modelling group preference. The group preference was also compared to trust level and the finding showed a high correlation between both constructs. The high trust in the group preferences is expected to contribute for the sustainability of Industry 4.0. The method enriches various existing theoretical approaches for group preference decision-making and applicable to assist the SME’s management for implementation of Industry 4.0.