Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91591
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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorSong, Wen_US
dc.creatorNiu, Zen_US
dc.creatorZheng, Pen_US
dc.date.accessioned2021-11-09T07:10:28Z-
dc.date.available2021-11-09T07:10:28Z-
dc.identifier.issn0360-8352en_US
dc.identifier.urihttp://hdl.handle.net/10397/91591-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2021 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Wenyan Song, Zixuan Niu, Pai Zheng, Design concept evaluation of smart product-service systems considering sustainability: An integrated method, Computers & Industrial Engineering, Volume 159, 2021, 107485 is available at https://doi.org/10.1016/j.cie.2021.107485.en_US
dc.subjectSmart product service systemen_US
dc.subjectSustainabilityen_US
dc.subjectRough set theoryen_US
dc.subjectBest worst methoden_US
dc.subjectCriteria importance though inter-criteriaen_US
dc.subjectCorrelationen_US
dc.titleDesign concept evaluation of smart product-service systems considering sustainability : an integrated methoden_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume159en_US
dc.identifier.doi10.1016/j.cie.2021.107485en_US
dcterms.abstractIntelligent products and services are integrated into Smart product-service systems (PSS) through information and communication technology (ICT). Various feasible Smart PSS designs are usually created in the design stage, and the design concept selection directly affects the delivery performance of the Smart PSS. However, existing methods often require more comparisons, omit criteria objective weights, and consider less about the impact of information subjectivity and impreciseness on the Smart PSS design concept selection. To solve the problems, a new integrated method is proposed, which integrates both subjective and objective weights to improve the accuracy of evaluation. Firstly, for criteria weighting, the proposed approach integrates the merits of the Best Worst Method (BWM) in reducing the burden of pair-wise comparisons when determining the subjective weights, and the strengths of the Criteria Importance Though Inter-criteria Correlation (CRITIC) method in considering the correlation and contrast between all criteria when determining the objective weights. Then, Rough Set Theory is used to flexibly deal with the decision-making vagueness without much prior information. Finally, a case study of a smart washing machine is adopted to validate the effectiveness of the proposed method.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationComputers and industrial engineering, Sep. 2021, v. 159, 107485en_US
dcterms.isPartOfComputers and industrial engineeringen_US
dcterms.issued2021-09-
dc.identifier.isiWOS:000679957900017-
dc.identifier.eissn1879-0550en_US
dc.identifier.artn107485en_US
dc.description.validate202111 bchyen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera1047-n06-
dc.identifier.SubFormID43847-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Key Research and Development Program of China (No. 2019YFB1405502), and the National Natural Science Foundation of China (Grant No. 71971012, 71501006). It is also supported in part by the National Science and Technology Major Project (2017-Ⅰ-0011-00120) and the Fundamental Research Funds for the Central Universities.en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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