Abstract
The efficiency analysis of retail stores is critical to identify possible areas of improvement. At this point, data envelopment analysis (DEA) is widely used for efficiency measurement of service and production units. On the other hand, the values of input and output variables must be deterministic and precise in the conventional DEA models such as CCR and BCR. However, the input and output values are usually imprecise for real world problems. In order to overcome this shortcoming, fuzzy data envelopment analysis models have been developed. This study aims to use the fuzzy data envelopment analysis for measuring and ranking the efficiency of stores in a grocery retailer in Turkey. In this study, total floor area, average inventory at cost, total number of customers that visited the store and average number of employees in the store are considered as the input variables while GMROI (gross margin return on investment), net sales, inventory turnover and stock-out rate are considered as output variables in the fuzzy DEA. The proposed model is solved by using LINGO 17.0 optimization software. According to the model results, the inefficient stores are ranked and compared using a minimax regret approach.
Original language | English |
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Title of host publication | Industrial Engineering in the Industry 4.0 Era - Selected Papers from ISPR2023 |
Editors | Numan M. Durakbasa, M. Güneş Gençyılmaz |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 85-94 |
Number of pages | 10 |
ISBN (Print) | 9783031539909 |
DOIs | |
Publication status | Published - 2024 |
Event | International Symposium for Production Research, ISPR 2023 - Antalya, Turkey Duration: 5 Oct 2023 → 7 Oct 2023 |
Publication series
Name | Lecture Notes in Mechanical Engineering |
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ISSN (Print) | 2195-4356 |
ISSN (Electronic) | 2195-4364 |
Conference
Conference | International Symposium for Production Research, ISPR 2023 |
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Country/Territory | Turkey |
City | Antalya |
Period | 5/10/23 → 7/10/23 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Keywords
- Data Envelopment Analysis
- Efficiency Measurement
- Fuzzy Sets
- Retailing