Presence Of Dual-role Factors Research Articles

Weight restrictions for the DEA model in the presence of dual-role factors: An application to the Iranian banking sector

A production process transforming multiple inputs to different outputs is considered in conventional data envelopment analysis (DEA) models. In various settings, however, there are factors that simultaneously play the roles of both input and output called dual-role factors. In some situations, additional information is available to impose on a DEA model with dual-role factors, or the decision maker is forced to impose some restrictions regarding the importance of dual-role factors on the model. Toward this end, the current research employs two different weighting methods to introduce various weighted DEA models in the presence of dual-role factors. To strengthen the accuracy of the new models, their properties are discussed. Then, each new model is illustrated in details by a numerical example. Moreover, to show that the new models are applicable, they are applied to the Iranian banking sector. To do this, 20 bank branches which have dual-role factors are assessed. At last, to show the outcome of weight restrictions, the results obtained by each new model are compared with those from Cook and Zhu’s model [Eur. J. Oper. Res. 180 (2007) 692–699].

Efficiency measurement to identify the best efficient unit in the presence of dual-role factors

Efficiency measurement is crucial to management for performance evaluation of several decision-making units (DMUs) in order to find the most efficient unit. Data envelopment analysis (DEA) is a practical and popular method that has been used widely for efficiency measurement in many applications. Thus, in the literature of DEA, several mixed integer DEA models are developed to efficiency measure and find the best efficient unit. In some situations, some factors named dual-role factors may be simultaneously considered as both inputs and outputs. However, a little attention has been paid in the literature of DEA to these types of factors. The current paper develops a new mixed integer linear DEA model to identify the best efficient DMU in the presence of dual-role factors. The basic DEA models consider different roles for each dual-role factor, and also solve at least one model for each DMU to determine the best unit. However, the developed approach in this paper considers a unique role for each dual-role factor, and also determines the best unit through by solving just one mixed integer DEA model. Two numerical examples are used to illustrate the profits and applicability of the developed approach.

Efficiency measurement to identify the best efficient unit in the presence of dual-role factors

Efficiency measurement is crucial to management for performance evaluation of several decision-making units (DMUs) in order to find the most efficient unit. Data envelopment analysis (DEA) is a practical and popular method that has been used widely for efficiency measurement in many applications. Thus, in the literature of DEA, several mixed integer DEA models are developed to efficiency measure and find the best efficient unit. In some situations, some factors named dual-role factors may be simultaneously considered as both inputs and outputs. However, a little attention has been paid in the literature of DEA to these types of factors. The current paper develops a new mixed integer linear DEA model to identify the best efficient DMU in the presence of dual-role factors. The basic DEA models consider different roles for each dual-role factor, and also solve at least one model for each DMU to determine the best unit. However, the developed approach in this paper considers a unique role for each dual-role factor, and also determines the best unit through by solving just one mixed integer DEA model. Two numerical examples are used to illustrate the profits and applicability of the developed approach.

How to Assess Sustainability of Suppliers in the Presence of Dual-Role Factor and Volume Discounts? A Data Envelopment Analysis Approach

Sustainability factors play critical role for long-term achievement of a supply chain management and purchasing process becomes more complicated with social and environmental pressures. Managing supplier selection process is a necessary step for companies seeking to manage their corporate legitimacy and reputations. Data envelopment analysis (DEA) has been widely used for supplier selection problems. In this paper, we propose a new super-efficiency method for evaluating sustainability of suppliers in the presence of dual-role factors and volume discounts. We show that enhanced Russell model (ERM) fails to present a complete ranking of suppliers. Our new model presents a complete ranking and also preserves properties of the ERM. Capabilities of our proposed method are shown using a couple of examples. A case study is presented to illustrate our proposed approach. The proposed method is used to select the best sustainable suppliers.

A decision model for supplier selection in the presence of dual-role factors

Best suppliers help manufacturers to gain and sustain a competitive advantage by improving product quality, reducing cost, shortening lead-time and so on. The crucial role played by suppliers in a supply chain renders the selection of a supplier or suppliers a significant work that attracts the attention of both researchers and practitioners. In the literature, data envelopment analysis (DEA) as a nonparametric technique is often applied to conduct a performance analysis. Little attention, however, has been paid to dual-role factors in the supplier selection process. This paper proposes a novel two-step approach to select suppliers in the presence of dual-role factors. As a combination of DEA and two-person zero-sum game theory, our work considers the strategic behaviour of the external environment and is able to handle the supplier selection in a competitive environment. Moreover, the proposed model circumvents the requirement to specify the status of a dual-role factor ahead of an evaluation and is easy to solve. Finally, the applicability of the procedure is illustrated by an application to a data set of 18 suppliers.

A new super-efficiency dual-role FDH procedure: an application in dairy cold chain for vehicle selection

Cold chain management (CCM) is a system in which perishable products are managed. For the success of transportation system of CCM, optimal selection of vehicle is a significant subject. Data envelopment analysis (DEA) can be used for vehicle selection problems. However, in this particular area, conventional DEA models are faced with difficulties. The problem are: 1) dual-role factors which classical DEA models cannot deal with them; 2) comparing decision making units (DMUs) with virtual DMUs (not with actual DMUs); 3) tie between DMUs (i.e., many DMUs are recognised efficient; 4) infeasibility of DEA ranking model for certain data. In this paper, a new procedure is developed to rectify the mentioned shortcomings. The proposed procedure, which utilises free disposal hull (FDH) technology, is a super-efficiency approach to provide a full ranking of efficient DMUs in the presence of dual-role factors. A case study illustrates application of the proposed procedure.

A novel network data envelopment analysis model for evaluating green supply chain management

Green supply chain management (GSCM) has become a method to improve environmental performance. Under stakeholder pressures, forces and regulations, companies need to improve the GSCM practice, which are effected by practices such as green purchasing, green design, product recovery, and collaboration with patrons and suppliers. As companies promote the GSCM, their economic performance and environmental performance will be enhanced. Hence, GSCM evaluation is very important for any company. One of the techniques that can be used for evaluating GSCM is data envelopment analysis (DEA). Traditional models of data envelopment analysis (DEA) are based upon thinking about production as a “black box”. One of the drawbacks of these models is to omit linking activities. The objective of this paper is to propose a novel network DEA model for evaluating the GSCM in the presence of dual-role factors, undesirable outputs, and fuzzy data. A case study demonstrates the application of the proposed model. A case study demonstrates the applicability of the proposed model.

The use of data envelopment analysis for international market selection in the presence of multiple dual-role factors

Selection of international market IM is a critical decision and needs to be made with considerable attention and deliberation. In some situations however, some criteria have the nature of both cost and profit. Likewise, in data envelopment analysis DEA some criteria play both input cost and output profit roles, simultaneously. In the DEA literature such criteria are called dual-role factors. Hence, the objective of this paper is to develop a new model for international market selection IMS, using DEA based on ternary variable in the presence of dual-role factors. A case study illustrates the application of the proposed model.

Measuring corporate sustainability management: A data envelopment analysis approach

Despite the increased awareness of the conceptual and practical definition of corporate sustainability, questions remain on how to measure performance. The objective of this paper is to advance our understanding of the measurement of corporate sustainability management by introducing a data envelopment analysis (DEA) technique and an empirical case of a Korean electronics industry. In particular, we employ cross-efficiency in the presence of dual-role factors by reflecting some complexity of a real-world case, donations for tax benefits. By employing the combined approach of cross-efficiency and dual-role factors, we offer a new model to measure corporate sustainability management. The new model and study findings contribute to the body of knowledge in corporate sustainability management and its performance measurement.

Supplier selection in the presence of dual-role factors, non-discretionary inputs and weight restrictions

The decision of supplier selection is strategic and crucial to the success of corporations. For selecting suppliers, data envelopment analysis (DEA), as a multiple criteria decision-making tool, has been applied for several times. However, there may exist some particular situations in supplier selection problem; i.e. (1) the presence of dual-role factor which may be classified either an input or an output. The quantity of such a factor may influence the relative efficiency of the suppliers, (2) the presence of non-discretionary or exogenously fixed inputs; in any realistic situation, there may exist non-discretionary criteria that are beyond the control of a management and (3) the presence of weight restrictions; sometimes it is needed to incorporate the preferences of managers and decision-makers into DEA model which is used to select suppliers. The objective of this paper is to propose a DEA model for selecting suppliers in the presence of dual-role factors, non-discretionary inputs and weight restrictions. A numerical example demonstrates the application of the proposed model.

Technology selection in the presence of dual-role factors

Technologies have varied strengths and weaknesses which require careful assessment by the purchasers. One of the uses of data envelopment analysis (DEA) is technology selection. The traditional models of DEA do not consider dual-role factors. The objective of this paper is to use a model for selecting the best technologies in the presence of dual-role factors. The model determines whether in a technology the factors are behaving predominantly like inputs, hence the technology would benefit from having less of the factors, like outputs where more of the factors are desirable, or where they are in equilibrium. A numerical example demonstrates the application of the method.

Restricting weights in supplier selection decisions in the presence of dual-role factors

One of the uses of data envelopment analysis (DEA) is supplier selection. Weight restrictions allow for the integration of managerial preferences in terms of relative importance levels of various inputs and outputs. As well, in some situations there is a strong argument for permitting certain factors to simultaneously play the role of both inputs and outputs. The objective of this paper is to propose a method for selecting the best suppliers in the presence of weight restrictions and dual-role factors. This paper depicts the supplier selection process through a DEA model, while allowing for the incorporation of decision maker’s preferences and considers multiple factors which simultaneously play both input and output roles. The proposed model does not demand exact weights from the decision maker. This paper presents a robust model to solve the multiple-criteria problem. A numerical example demonstrates the application of the proposed method.