ǂa ǂcase of selection and evaluation of environmental efficiency of suppliers
Evelin Vatovec-Krmac (Author), Boban Đorđević (Author)

Abstract

Supply Chain Management (SCM) represents an example of a complex multi-stage system. The SCM involves and connects different activities, from customer’s orders to received services, all with the aim of satisfying customers. The evaluation of a particular SCM is a complex problem because of the internally linked hierarchical activities and multiple entities. In this paper, the introduction of a non-radial DEA (Data Envelopment Analysis) model for the evaluation of different components of SCM, primarily in terms of sustainability, is the main contribution. However, in order to confirm the novelty and benefits of this new model in the field of SCM, a literature review of past applications of DEA-based models and methods are also presented. The non-radial DEA model was applied for the selection and evaluation of the environmental efficiency of suppliers considering undesirable inputs and outputs resulting in a better ranking of suppliers. Via perturbation of the data used, behavior, as well as the benefits and weaknesses of the introduced model are presented through sensitivity analysis.

Keywords

upravljanje oskrbovalnih verig;podatkovne analize;dobavitelji;vrednotenje učinkovitosti;okolje;DEA modeli;supply chain management;data envelopment analysis;non-radial DEA model;suppliers;efficiency evaluation;environment;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL FPP - Faculty of Maritime Studies and Transport
UDC: 005:658.7
COBISS: 2909283 Link will open in a new window
ISSN: 2073-8994
Views: 182
Downloads: 59
Average score: 0 (0 votes)
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Other data

Secondary language: Slovenian
Secondary keywords: upravljanje oskrbovalnih verig;podatkovne analize;dobavitelji;vrednotenje učinkovitosti;okolje;DEA modeli;
Type (COBISS): Article
Pages: str. [1]-21
Volume: ǂVol. ǂ11
Issue: ǂiss. ǂ4
Chronology: 2019
DOI: 10.3390/sym11040565
ID: 13729680
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