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Identifying key industry factors of remanufacturing industry using grey incidence analysis a case of Jiangsu province

机译:基于灰色关联分析的再制造关键产业要素识别-以江苏省为例

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Purpose - The 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. Design/methodology/approach - Grey 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. Findings - According 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. "Annual sale of remanufacturing industry" is identified as quasi-preferred industry characteristic, and "total number of employees with master degree or above in remanufacturing enterprise" is identified as the quasi-preferred industry factor. "Total building area of remanufacturing enterprise" is referred as the most unfavorable industry factors. Practical implications - Judging from the findings of this study, four practical implications are summarized as follows: "annual sale of remanufacturing industry" should be given great importance because it is a quasi-preferred industry characteristic. "Total number of employees with master degree or above in remanufacturing enterprise" and "total number of research institution and university participated in remanufacturing" 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. "Total investment of remanufacturing industry" and "total annual R&D expenditures" have not played their due role in improving remanufacturing industry, so they should be moderately controlled so as to reduce waste of investment. "Total building area of remanufacturing enterprise" must be strictly controlled because of its little impact on remanufacturing industry. Originality/value - In 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.
机译:目的-本文的目的是确定再制造行业的最有利(或半优选)行业特征以及对这些特征有影响的最有利(或半优选)行业因素,以改善这些因素。设计/方法/方法-灰色系统理论具有使用很少的数据和不确定性信息来分析许多因素的显着优势。因此,它比传统的统计分析方法(例如回归分析,方差分析和主成分分析)更适合系统分析,因为传统统计分析方法需要大量数据,数据中具有一定的概率分布且变异因子很少。因此,本文将灰色关联分析法作为灰色系统理论的重要组成部分,用于识别中国再制造行业的行业特征和关键行业因素,然后提出适当的行业政策和对策以改善这些行业因素。研究结果-根据这项研究的结果,我们发现中国再制造行业没有最有利的行业特征,也没有最有利的行业因素。将“再制造行业的年销售额”确定为准首选行业特征,将“再制造企业中具有硕士或以上学历的员工总数”确定为准首选行业因素。 “再制造企业总建筑面积”被称为最不利的行业因素。实际意义-从本研究的结果来看,有四个实际意义总结如下:“再制造行业的年度销售”应被高度重视,因为它是准首选行业特征。通过建立产学研合作网络,进一步加强“再制造企业中具有硕士以上学历的员工总数”和“参与再制造的研究机构和大学的总数”。准首选的两个行业因素。 “再制造行业总投资”和“年度研发总支出”在改善再制造行业中没有发挥应有的作用,因此应适当控制它们以减少投资浪费。必须严格控制“再制造企业总建筑面积”,因为这对再制造行业影响很小。原创性/价值-在本研究中,灰色关联分析首次用于识别再制造行业的关键行业因素。它通过研究行业特征和行业因素之间的关系,帮助找到迫切需要改进的行业因素,并帮助制定适当的行业政策和对策以改善它们。

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