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Developing distinctive two-stage data envelopment analysis models: An application in evaluating the sustainability of supply chain management

机译:开发独特的两阶段数据包络分析模型:在评估供应链管理可持续性中的应用

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Sustainable supply chain management (SSCM) has received much attention from scholars and practitioners in the past years. It has become a method for simultaneous improvement of economic, social, and environmental performance. SSCM evaluation, therefore, is a significant duty for any types of organizations. Among evaluation methods, data envelopment analysis (DEA) seems to be an appropriate technique for assessment of the SSCM. One of the uses of DEA is to evaluate the efficiency of two-stage processes, where all the outputs from the first stage are intermediate measures that are considered as the inputs to the second stage. The resulting two-stage DEA models assess both the overall efficiency score of the whole process and each of the individual stages. Notwithstanding, there are major weaknesses in the previous extensions of two-stage DEA models. Firstly, a challenging issue is that suggestions for improvements are offered only for input and output measures, and intermediate measures are neglected. Although, some extensions for network structures take into account intermediate measures, they arbitrarily assign an input or output role for the measures, thus in optimal solution for inefficient DMUs, this measures are forced to respectively take a lower or upper amount. Secondly, the efficiency scores are calculated based on inputs and outputs. That is, while the models consider these measures by corresponding constraints, the intermediate measures are not included in the objective function, or incorrectly assign an input or output role. Thirdly, in some cases, the former developments specify points on the efficient frontier only for inefficient stages, while for a network which is entirely inefficient such points are also required. Moreover, the organization (which in DEA terminology is named decision making unit) is supposed to be divided into two autonomous departments. It means that the performance of one department is quite unrelated to another department, while from the organizational perspective this is called into the question. To overcome these shortcomings, in this paper, innovative models are proposed. The proposed ideas are used for evaluating the sustainability of supply chains in resin producing companies. (C) 2015 Elsevier Ltd. All rights reserved.
机译:过去几年中,可持续供应链管理(SSCM)受到了学者和实践者的广泛关注。它已成为一种同时改善经济,社会和环境绩效的方法。因此,SSCM评估对于任何类型的组织都是一项重要职责。在评估方法中,数据包络分析(DEA)似乎是评估SSCM的合适技术。 DEA的用途之一是评估两阶段流程的效率,其中第一阶段的所有输出都是中间措施,被视为第二阶段的输入。最终的两阶段DEA模型会评估整个过程的整体效率得分以及各个阶段的效率。尽管如此,以前的两阶段DEA模型扩展仍存在主要缺陷。首先,一个具有挑战性的问题是,仅针对投入和产出措施提出了改进建议,而忽略了中间措施。尽管网络结构的某些扩展考虑了中间措施,但它们为这些措施任意分配输入或输出角色,因此,对于效率低下的DMU的最佳解决方案,这些措施分别被迫降低或提高。其次,基于输入和输出来计算效率得分。也就是说,尽管模型通过相应的约束条件来考虑这些度量,但是中间度量未包含在目标函数中,或者错误地分配了输入或输出角色。第三,在某些情况下,以前的发展仅在效率低下的阶段指定了效率边界上的点,而对于完全效率低下的网络,也需要这些点。此外,应该将组织(在DEA术语中称为决策部门)划分为两个自治部门。这意味着一个部门的绩效与另一部门的绩效完全无关,而从组织的角度来看,这就是一个问题。为了克服这些缺点,本文提出了创新的模型。提议的想法用于评估树脂生产公司的供应链的可持续性。 (C)2015 Elsevier Ltd.保留所有权利。

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