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Abstract. Product development of today is becoming increasingly knowledge intensive. 12Specifically, design teams face considerable challenges in making effective use of increasing 13 amounts of information. In order to support product information retrieval and reuse, one approach is 14 to use case-based reasoning (CBR) in which problems are solved "by using or adapting solutions to 15 old problems." In CBR, a case includes both a representation of the problem and a solution to that 16 problem. Case-based reasoning uses similarity measures to identify cases which are more relevant to 17 the problem to be solved. However, most non-numeric similarity measures are based on syntactic 18 grounds, which often fail to produce good matches when confronted with the meaning associated to 19 the words they compare. To overcome this limitation, ontologies can be used to produce similarity 20 measures that are based on semantics. This paper presents an ontology-based approach that can 21 determine the similarity between two classes using feature-based similarity measures that replace 22 features with attributes. The proposed approach is evaluated against other existing similarities. 23Finally, the effectiveness of the proposed approach is illustrated with a case study on 24 product-service-system design problems.

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Although solar power systems are considered as one of the most promising renewable energy sources, some uncertain factors as well as the high cost could be barriers which create customer resistance. Leasing instead of purchase, as one type of product service system, could be an option to reduce consumer concern on such issues. This study focuses on consumer concerns about uncertainty and willingness to pay for leasing solar power systems. Conjoint analysis method is used to find part worth utilities and estimate gaps of willingness to pay between attribute levels, including various leasing time lengths. The results show the part worth utilities and relative importance of four major attributes, including leasing time. Among concerns about uncertainties, government subsidy, electricity price, reliability, and rise of new generation solar power systems were found to be significantly related to the additional willingness-to-pay for a shorter leasing time. Cluster analysis is used to identify two groups standing for high and low concerns about uncertainty. People with more concerns tend to pay more for a shorter lease time.

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