A rough-fuzzy DEMATEL-ANP method for evaluating sustainable value requirement of product service system

Abstract

Abstract Manufacturers are today striving to offer value-added Product Service System (PSS) with the purpose of achieving higher competiveness and more environmental benefits. Requirement elicitation and evaluation with sustainability concerns play a key role in a successful development of sustainable PSS. However, the previous literature rarely address the PSS requirement from the view of sustainability, while mainly focusing on the customer satisfaction. To accurately identify the requirement with respect to sustainable value from a long term perspective, it is necessary to develop effective methods for requirement elicitation for sustainable PSS. In addition, the prioritization of sustainable value requirement provides critical guidance for the later PSS design. The prioritization involves much judgement ambiguousness and diversity which may lead to inaccurate requirement analysis result. However, there are few researches on combinatory manipulation of the vagueness and diversity. Therefore, to solve these problems, an innovative methodology incorporating requirement elicitation and evaluation is developed for sustainable PSS. This study introduces the concept of value uncaptured into the identification of product value state, and offers the Product Value State Model (PVSM) method to elicit value requirements which help PSS deliver more sustainability. Moreover, a hybrid model for evaluating the sustainable value requirement is proposed by combining the fuzzy set, rough set, Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) methods. An application in an excavator PSS and the comparisons with some different methods demonstrate the feasibility and potential of the methodology. Theoretically, the proposed evaluation model provides more accurate and realistic analysis results of PSS requirements compared to traditional methods, since it supports to simultaneously manipulate judgement vagueness, group decision diversity, and complex interrelationship. In practical PSS design, the method helps PSS designers successfully recognize the most key value requirements with both respect of sustainability and customer satisfaction.