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Assessing the sustainable performance of Chinese industrial sector

机译:评估中国工业部门的可持续表现

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Sustainability management is a subject of growing interest in economic development, business management, and environmental management. Data envelopment analysis (DEA) has been widely used to integrate this diverse nature of sustainable performance in economy. However, existing DEA frameworks suffer from two critical limitations: First, they follow traditional radial assumptions, which may lead to difficulties in characterizing the real production process. Second, they do not estimate the determinants of sustainable performance. In this regard, this paper presents a two-stage DEA model that can overcome these limitations. In the first stage, non-radial and non-oriented DEA frameworks with the slacks-based measure (SBM) are introduced. In the second stage, the truncated bootstrap regression identifies the determinants of sustainable performance with industries in 30 regions of China.? The eastern region showed the highest sustainable performance, whereas the western region showed the lowest performance. The level of industrialization had no effect on sustainability management. However, GDP per capita, the promotion of the service industry, energy efficiency, public investment in environmental pollution control, and the waste reuse technology level had positive effects on sustainable performance.
机译:可持续发展管理对经济发展,业务管理和环境管理越来越感兴趣。数据包络分析(DEA)已被广泛用于整合经济中可持续绩效的多样性。但是,现有的DEA框架有两个关键局限性:首先,它们遵循传统的径向假设,这可能会导致难以描述真实生产过程。其次,他们没有估计可持续绩效的决定因素。在这方面,本文提出了可以克服这些限制的两阶段DEA模型。在第一阶段,引入具有基于松弛的度量(SBM)的非径向和非定向DEA框架。在第二阶段,截短的Bootstrap回归确定了中国30个地区的行业可持续绩效的决定因素。东部地区的可持续绩效最高,而西部地区的可持续绩效最低。工业化水平对可持续性管理没有影响。但是,人均国内生产总值,服务业的发展,能源效率,环境污染控制方面的公共投资以及废物再利用技术水平对可持续绩效产生积极影响。

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