Optimal weights in DEA models with weight restrictions

According to a conventional interpretation of a multiplier DEA model, its optimal weights show the decision making unit under the assessment, denoted DMUo, in the best light in comparison to all observed DMUs. For multiplier models with additional weight restrictions such an interpretation is known to be generally incorrect (specifically, if weight restrictions are linked or nonhomogeneous), and the meaning of optimal weights in such models has remained unclear. In this paper we prove that, for any weight restrictions, the optimal weights of the multiplier model show DMUo in the best light in comparison to the entire technology expanded by the weight restrictions. This result is consistent with the fact that the dual envelopment DEA model benchmarks DMUo against all DMUs in the technology, and not only against the observed DMUs. Our development overcomes previous concerns about the use of weight restrictions of certain types in DEA models and provides their rigorous and meaningful interpretation

An efficiency evaluation problem including fuzzy weights

This paper presents a procedure to dissolve a fuzzy weights CCR model with numerical input and output data in the objective function. This technique is a combination of utilizing fuzzy operations arithmetic and traditional method in DEA in order to convert the model into two simple linear programming problems with the purpose of detecting the effect of uncertain factors on the efficiency scores of decision making units (DMUs). It is in accordance with our determination to provide a method based on data envelopment analysis (DEA), supporting efficiency evaluation problems in fold fuzziness in factor weights to assist decision making issues

Performance evaluation of nonhomogeneous hospitals : the case of Hong Kong hospitals

Throughout the world, hospitals are under increasing pressure to become more efficient. Efficiency analysis tools can play a role in giving policymakers insight into which units are less efficient and why. Many researchers have studied efficiencies of hospitals using data envelopment analysis (DEA) as an efficiency analysis tool. However, in the existing literature on DEA-based performance evaluation, a standard assumption of the constant returns to scale (CRS) or the variable returns to scale (VRS) DEA models is that decision-making units (DMUs) use a similar mix of inputs to produce a similar set of outputs. In fact, hospitals with different primary goals supply different services and provide different outputs. That is, hospitals are nonhomogeneous and the standard assumption of the DEA model is not applicable to the performance evaluation of nonhomogeneous hospitals. This paper considers the nonhomogeneity among hospitals in the performance evaluation and takes hospitals in Hong Kong as a case study. An extension of Cook et al. (2013) [1] based on the VRS assumption is developed to evaluated nonhomogeneous hospitals' efficiencies since inputs of hospitals vary greatly. Following the philosophy of Cook et al. (2013) [1], hospitals are divided into homogeneous groups and the product process of each hospital is divided into subunits. The performance of hospitals is measured on the basis of subunits. The proposed approach can be applied to measure the performance of other nonhomogeneous entities that exhibit variable return to scale

Developing a Bi-Level Structure for Evaluation of Regional Bank Branch Managers Focusing on their Consumption

Regional bank branch management is the most important elements of a bank’s structure. Each regional bank branch manager (RBBM) manages a large group of branches. In this paper, we develop a bi-level structure for the evaluation of RBBMs. In the developed bi-level structure, RBBMs are positioned at the upper level, and each RBBM has a group of branches located at the lower level. Generally, each RBBM, including their branches, tries to use inputs and produce outputs efficiently. However, each branch performs according to its goals and limited resources. The evaluation is a data envelopment analysis (DEA)-based model that focuses on the bank’s consumption perspective. We apply the suggested model to a real-world case study to evaluate five RBBMs, who altogether manage 110 branches in one of the expert banking systems

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

A DEA-Based Approach to Evaluate the Efficiency of Non-Homogeneous Service Locations

This study aims at evaluating the performance of a company, ‘XYZ Company’, that has 115 service locations. Because of its ability of handling large numbers of inputs and outputs, and removing the need of predefining the factors’ weights, Data Envelopment Analysis (DEA) is used. DEA is benchmark tool that measures the efficiency of entities with respect to each other by assessing their performance of utilizing inputs to produce outputs. Researchers have developed several DEA models, all of which have different characteristics.A main assumption of DEA is that the entities are homogeneous – i.e. operating under similar conditions, which is not applicable sometimes. Thus, various approaches have been introduced to relax the homogeneity assumption. In this study, we propose an approach that estimates the efficiency over some stages, obtains efficiency scores from each stage, and then calculates the final weighted score by assigning a higher weight to the stage that represents the actual conditions of the entity more clearly.We apply three DEA models, utilizing the proposed approach to overcome the entities’ heterogeneity, to the data set of XYZ Company. Then, we compare the results of the three models, analyze the efficiency scores of the 115 service locations, and provide some major findings

Operations capability, productivity and business performance: the moderating effect of environmental dynamism

Purpose – The purpose of this study is to investigate the relationships between operations capability, productivity and business performance in the context of environmental dynamism. Design/methodology/approach – A proposed conceptual framework grounded in the resourcebased view (RBV) and dynamic capability view (DCV) is analysed using archival data from 193 automakers in the UK. Findings – The results show that operations capability, as an important dynamic capability, has a significant positive effect on productivity, which in turn leads to improved business performance. The results also suggest that productivity fully mediates the relationship between operations capability and business performance, and that environmental dynamism significantly moderates the relationship between operations capability and productivity. Practical implications – The research findings provide practical insights that will help managers develop operations capability to gain greater productivity and business performance in a dynamic environment

Nonparametric production technologies with multiple component processes

We develop a nonparametric methodology for assessing the efficiency of decision making units operating in a production technology with several component processes. The latter is modeled by the new multiple hybrid returns-to-scale (MHRS) technology, formally derived from an explicitly stated set of production axioms. In contrast with the existing models of data envelopment analysis (DEA), the MHRS technology allows the incorporation of component-specific and shared inputs and outputs that represent several proportional (scalable) component production processes, as well as nonproportional inputs and outputs. Our approach does not require information about the allocation of shared inputs and outputs to component processes or any assumptions about this allocation. We demonstrate the usefulness of the suggested approach in an application in the context of secondary education, and also in a Monte Carlo study based on a simulated data generating process

Innovative value-based price assessment in data-rich environments: Leveraging online review analytics through Data Envelopment Analysis to empower managers and entrepreneurs

This work introduces, develops, and empirically applies an innovative approach aimed at assessing selling prices based on the value perceived by the customers, as measured by electronic word-of-mouth (eWOM) in the guise of online reviews. To achieve this aim, it applies a constant return to scale Data Envelopment Analysis (DEA) approach where the price is the input, and the value attributes are the outputs measured through eWOM in the form of online reviews. We empirically apply the model to the hotel sector by considering both the prices and the service attributes (i.e., staff, location, cleanliness, comfort, facilities and free wi-fi) of 364 hotels based in two leading Italian tourism destinations: Milan and Rome. Our findings suggest that online review analytics can be suitably embedded into analytical models to assess prices. The index developed innovatively supports value-based pricing by means of online review analytics and it is easy-to-perform, and parsimonious as it is based on widely available information on the Internet