Fuzzy clustering of homogeneous decision making units with common weights in data envelopment analysis

Data Envelopment Analysis (DEA) is the most popular mathematical approach to assess efficiency of decision-making units (DMUs). In complex organizations, DMUs face a heterogeneous condition regarding environmental factors which affect their efficiencies. When there are a large number of objects, non-homogeneity of DMUs significantly influences their efficiency scores that leads to unfair ranking of DMUs. The aim of this study is to deal with non-homogeneous DMUs by implementing a clustering technique for further efficiency analysis. This paper proposes a common set of weights (CSW) model with ideal point method to develop an identical weight vector for all DMUs. This study proposes a framework to measuring efficiency of complex organizations, such as banks, that have several operational styles or various objectives. The proposed framework helps managers and decision makers (1) to identify environmental components influencing the efficiency of DMUs, (2) to use a fuzzy equivalence relation approach proposed here to cluster the DMUs to homogenized groups, (3) to produce a common set of weights (CSWs) for all DMUs with the model developed here that considers fuzzy data within each cluster, and finally (4) to calculate the efficiency score and overall ranking of DMUs within each cluster

The Chinese position as a global player in international comparison with the WTO members: Efficiency analysis and 4IR

During the last quarter-century, globalisation processes affected changes in the world economy in the form of intensifying competition in the international and internal markets. The result is the creation of a global marketplace that is mostly indifferent to national borders and governmental influences. This development has generated widespread interest in competitiveness. Competitiveness affects international relations, especially nowadays, given the changing position of the global leaders and the growth of new economic powers such as China. China has come a long way and has the opportunity to be a global leader in several required fields that will be the cornerstones of global growth in the next decades. Led by China, emerging economies are increasing their share in the worldwide economy and intensifying competition in nearly all sectors. It creates new threats and challenges for players in the global economy, and growing competitiveness must be efficient. The article evaluates the Chinese competitiveness in comparison with the World Trade Organization members by the Data Envelopment Analysis in the pre-in-post crisis period and considering the Fourth Industrial Revolution shifting humanity into a new phase.Web of Science6148

Cross-Efficiency Evaluation Method with Compete-Cooperate Matrix

Cross-efficiency evaluation method is an effective and widespread adopted data envelopment analysis (DEA) method with self-assessment and peer-assessment to evaluate and rank decision making units (DMUs). Extant aggressive, benevolent, and neutral cross-efficiency methods are used to evaluate DMUs with competitive, cooperative, and nontendentious relationships, respectively. In this paper, a symmetric (nonsymmetric) compete-cooperate matrix is introduced into aggressive and benevolent cross-efficiency methods and compete-cooperate cross-efficiency method is proposed to evaluate DMUs with diverse (relative) relationships. Deviation maximization method is applied to determine the final weights of cross-evaluation to enhance the differentiation ability of cross-efficiency evaluation method. Numerical demonstration is provided to illustrate the reasonability and practicability of the proposed method