Identifying key industry factors of remanufacturing industry using grey incidence analysis

Abstract

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.

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Recycling/Production and Incentive-Penalty Strategies in Closed-Loop Supply Chains under Remanufacturing Policies

“…Remanufacturing, which involves sorting, inspecting, disassembling, cleaning, reprocessing, and assembling products to restore them to a like-new condition for reuse, has been widely embraced by enterprises due to its environmental and cost benefits [1]. In 2015, the annual sales revenue of China's remanufacturing industry reached approximately 7.9 billion dollars, with Jiangsu Province, a hub for the remanufacturing industry, achieving a sales revenue of 285 million dollars due to the development of this industry [2]. As a leader in the automotive manufacturing industry, Volkswagen began engaging in remanufacturing as early as the 1940s and has since accumulated a total of 7.48 million remanufactured engines, reducing carbon emissions by nearly 570,000 tons [3,4].…”

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