Conceptual Solution Decision Based on Rough Sets and Shapley Value for Product-Service System: Customer Value-Economic Objective Trade-Off Perspective

The product service system (PSS), as a design concept for integrated products and services, needs to be evaluated in the early design stage to maximize the value for stakeholders of the PSS concept, which is a crucial task for enterprises. However, existing methods focus on the ranking and value assessment of PSS evaluation criteria (e.g., quality, sustainability, cost), ignoring the needs conflict between customer value and economic objectives in PSS design, resulting in decision results that are not applicable to industrial enterprises. Furthermore, the influence of weight preference and uncertain information on solution evaluation is seldom considered when calculating the weight of each criterion. To fill this gap, integrating rough sets and the Shapley value decision approach for product-service system design considering customer value-economic objective trade-off is proposed, which mainly includes two parts: firstly, the best worst method (BWM) and the entropy weight method are integrated to obtain the comprehensive weight of evaluation criteria in the customer value and economic objectives; secondly, the Shapley value method in the coalition game is used to solve the optimal expectation allocation of the two objectives, so as to select the solution closest to the allocation, i.e., the optimal solution. In addition, rough set techniques are used to capture and integrate subjective assessment information originating from DMs under uncertainty. Finally, a case study of the electric forklift design is illustrated to verify the proposed decision model. The decision results show that this approach is more reliable through sensitivity and comparison analysis, and provide a valuable recommendation for enterprises to consider product service in forklift design.

Automated summary

This study introduces a comprehensive evaluation model for product-service system design by integrating rough sets and Shapley value decision methods to address the conflicting needs between customer value and economic objectives in PSS design. The reliability and effectiveness of the model are validated through a case study.