{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T06:16:01Z","timestamp":1764569761146,"version":"3.41.2"},"reference-count":41,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2016,11,7]],"date-time":"2016-11-07T00:00:00Z","timestamp":1478476800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["GS"],"published-print":{"date-parts":[[2016,11,7]]},"abstract":"\nPurpose<\/jats:title>\nThe purpose of this paper is to identify most favorable (or quasi-preferred) industry characteristics of remanufacturing industry and most favorable (or quasi-preferred) industry factors which have an effect on these characteristics so as to improve these factors.<\/jats:p>\n<\/jats:sec>\n\nDesign\/methodology\/approach<\/jats:title>\nGrey system theory has prominent advantage of using few data and uncertainty information to analyze many factors. Therefore, it is more suited for system analysis than traditional statistical analysis methods like regression analysis, variance analysis and principal component analysis, which require massive data, certain probability distribution in the data and few variant factors. So in this paper, grey incidence analysis method, which is an important part of grey system theory, is used to identify industry characteristics and key industry factor of remanufacturing industry in China and then put forward appropriate industrial policies and countermeasures to improve these industry factors.<\/jats:p>\n<\/jats:sec>\n\nFindings<\/jats:title>\nAccording to the results of this study, it reveals that there are no most favorable industry characteristics and no most favorable industry factors in remanufacturing industry of China. \u201cAnnual sale of remanufacturing industry\u201d is identified as quasi-preferred industry characteristic, and \u201ctotal number of employees with master degree or above in remanufacturing enterprise\u201d is identified as the quasi-preferred industry factor. \u201cTotal building area of remanufacturing enterprise\u201d is referred as the most unfavorable industry factors.<\/jats:p>\n<\/jats:sec>\n\nPractical implications<\/jats:title>\nJudging from the findings of this study, four practical implications are summarized as follows: \u201cannual sale of remanufacturing industry\u201d should be given great importance because it is a quasi-preferred industry characteristic. \u201cTotal number of employees with master degree or above in remanufacturing enterprise\u201d and \u201ctotal number of research institution and university participated in remanufacturing\u201d should be further strengthened by establishing an industry-university-research institute collaboration network, due to the fact that they are the top two quasi-preferred industry factors. \u201cTotal investment of remanufacturing industry\u201d and \u201ctotal annual R&D expenditures\u201d have not played their due role in improving remanufacturing industry, so they should be moderately controlled so as to reduce waste of investment. \u201cTotal building area of remanufacturing enterprise\u201d must be strictly controlled because of its little impact on remanufacturing industry.<\/jats:p>\n<\/jats:sec>\n\nOriginality\/value<\/jats:title>\nIn this research, grey incidence analysis is applied to identify key industry factors of remanufacturing industry for the first time. It helps in finding industry factors which are in urgent need of improvement and assists in making appropriate industrial policies and countermeasures to improve them by studying relationships between industry characteristic and industry factors.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/gs-08-2016-0016","type":"journal-article","created":{"date-parts":[[2016,12,6]],"date-time":"2016-12-06T02:58:38Z","timestamp":1480993118000},"page":"398-414","source":"Crossref","is-referenced-by-count":9,"title":["Identifying key industry factors of remanufacturing industry using grey incidence analysis"],"prefix":"10.1108","volume":"6","author":[{"given":"Wenjie","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenfan","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangyun","family":"Chang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"issue":"5","key":"key2020121103370509200_ref001","doi-asserted-by":"crossref","first-page":"483","DOI":"10.3401\/poms.1080.0051","article-title":"Product reuse economics in closed-loop supply chain research","volume":"17","year":"2008","journal-title":"Production Operations Management"},{"issue":"1","key":"key2020121103370509200_ref002","first-page":"33","article-title":"Analysis of the development patterns of Chinese automobile remanufacturing industry","year":"2010","journal-title":"Forum on Science and Technology in China"},{"first-page":"32","article-title":"Grey incidence analysis based on coefficient of determination and its economic application with the data of Central Henan Urban Agglomeration","year":"2009","key":"key2020121103370509200_ref003"},{"key":"key2020121103370509200_ref004","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.jclepro.2014.10.048","article-title":"A combined input-output\/decision making trial and evaluation laboratory method for evaluating effect of the remanufacturing sector development","volume":"114","year":"2016","journal-title":"Journal of Cleaner Production"},{"key":"key2020121103370509200_ref005","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.jclepro.2014.11.040","article-title":"Grey decision making as a tool for the classification of the sustainability level of remanufacturing companies","volume":"105","year":"2015","journal-title":"Journal of Cleaner Production"},{"key":"key2020121103370509200_ref006","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.jclepro.2015.06.092","article-title":"Application of fuzzy analytic network process for barrier evaluation in automotive parts remanufacturing towards cleaner production e a study in an Indian scenario","volume":"114","year":"2016","journal-title":"Journal of Cleaner Production"},{"issue":"2","key":"key2020121103370509200_ref007","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1108\/20439371211260243","article-title":"Applying fuzzy grey relational analysis for ranking the advanced manufacturing systems","volume":"2","year":"2012","journal-title":"Grey Systems Theory & Application"},{"key":"key2020121103370509200_ref008","unstructured":"Gray, C. and Charter, M. 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