Dobos, Imre and Vörösmarty, Gyöngyi (2023) Green supplier selection problems with data scaling and production frontier estimations in a DEA model. Society and Economy, 45 (2). pp. 91-111. DOI https://doi.org/10.1556/204.2023.00001
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Official URL: https://doi.org/10.1556/204.2023.00001
Abstract
Considering ecological issues in supplier evaluation and management alongside business considerations is getting more recognition among firms. Data envelopment analysis (DEA) is one of those methods, which is frequently suggested by the literature to support management decisions. However, the data requirements of the method should be an important consideration. The literature often addresses the issue of desirable outputs and undesirable input as an important data related problem in case of the ecological use of DEA. This paper will present a new solution to manage these data problems along with connecting the evaluation of management criteria, environmental criteria and total cost aspects. The proposed environmental supplier selection problem is an extension of a former paper. The new model examines the effect of inventory related costs, such as EOQ costs of inventory holding or ordering costs on the selected supplier, extended with newly introduced scaled values of input and output indicators. The usage of scaled values is motivated by the problem of invariance to data alteration. In addition to the uncertainty of the data, the paper looks for a functional relationship between the input and output criterion values and the efficiency that can be assigned to them using DEA.
Item Type: | Article |
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Uncontrolled Keywords: | supplier selection; data envelopment analysis (DEA); data scaling; production frontiers |
JEL classification: | C13 - Estimation: General C60 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling: General M11 - Production Management |
Subjects: | Mathematics, Econometrics |
DOI: | https://doi.org/10.1556/204.2023.00001 |
ID Code: | 8279 |
Deposited By: | Alexa Horváth |
Deposited On: | 12 Jun 2023 12:52 |
Last Modified: | 12 Jun 2023 12:52 |
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