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DEA-based competition strategy in the presence of undesirable products : an application to paper mills

Amirteimoori Alireza, Masrouri Simin

Operations Research and Decisions

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2021

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Vol. 31, No. 2

5--21

EN

In real applications of data envelopment analysis (DEA), there are cases in which undesirable outputs are produced along with desirable outputs in such a way that the total sum of the produced undesirable outputs over the production units must be fixed and constant. In this case, a trade-off between the decision-making units (DMUs) is needed to balance the production of undesirable outputs. In a rational sight, this trade-off is done in such a way that all DMUs improve their relative performances. In this paper, a single DEA-based model is proposed to model fixed and variable-sum undesirable outputs in production processes. A common equilibrium efficient frontier is constructed and after reallocating the input/output factors, all decision-making units (DMUs) prevail as efficient. A real case of 32 paper mills in China is given. The results of the analysis demonstrated that some economically developed paper mills have better performance than less developed paper mills; in particular, all efficient paper mills are the developed ones.

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Assessment of mixed network processes with shared inputs and undesirable factors

Nematizadeh Maryam, Amirteimoori Alireza, Kordrostami Sohrab, Vaez-Ghasemi Mohsen

Operations Research and Decisions

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2020

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Vol. 30, No. 1

97--118

EN

In the real world, there are processes whose structures are like a parallel-series mixed network. Network data envelopment analysis (NDEA) is one of the appropriate methods for assessing the performance of processes with these structures. In the paper, mixed processes with two parallel and series components are considered, in which the first component or parallel section consists of the shared inputs, and the second component or series section consists of undesirable factors. By considering the weak disposability assumption for undesirable factors, a DEA approach as based on network slackbased measure (NSBM) is introduced to evaluate the performance of processes with mixed structures. The proposed model is illustrated with a real case study. Then, the model is developed to discriminate efficient units.

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Performance analysis of two-stage network processes with feedback flows and undesirable factors

Nematizadeh Maryam, Amirteimoori Alireza, Kordrostami Sohrab

Operations Research and Decisions

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2019

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Vol. 29, No. 3

51--66

EN

Network data envelopment analysis (NDEA) is a non-parametric technique to evaluate the relative efficiency of decision-making units (DMUs) with network structures. An interesting and important network structure is a two-stage feedback process in which the outputs of the second stage are used as the inputs for the first stage. The existing approach did not consider undesirable products and from experience though we know that in real applications, network structures may consist of desirable and undesirable products outputs in which undesirable products can be used in the systems. The present paper proposes a DEA-based method for evaluating the relative efficiency of such a two-stage-feedback network structure with undesirable factors. Directional distance function along with weak disposability assumption for undesirable outputs has been used to analyse the performance of the network. A real case on ecological system of 31 regions in China is used to illustrate the applicability of the proposed approach.