Abstract
Appraising sustainable supply chain performance is of great importance in today’s world. Businesses, for attaining competitive advantages, call for some methods to appraise their sustainable supply chains. Applying valid performance evaluation methods along with using accurate accounting data leads to valid and reliable results. A performance appraisal method using sustainability accounting information, which is provided based on environmental, social, and economic sides of sustainability, supports managers perfectly in achieving their long-lasting aims. On the other hand, data derived from accounting systems are both positive and non-positive. Therefore, a performance evaluation model should be able to work with negative and zero data. In this research, to present a powerful mathematical technique for appraising network structure of supply chains, a network data envelopment analysis (NDEA) model is developed. Since traditional NDEA models do not work with non-positive data and fail to rank DMUs with the same efficiency scores, the main purpose of this paper is to develop a new super-efficiency NDEA (SNDEA) model for evaluating sustainable supply chains in the presence of both positive and non-positive data. To get more reliable results, a new formula of "output surplus index” is introduced to calculate the super-efficiency scores when some data are non-positive. To show the presented model’s ability, a case study in the construction industry is given.
Original language | English |
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Pages (from-to) | 809-824 |
Number of pages | 16 |
Journal | Operations Management Research |
Volume | 15 |
Issue number | 3-4 |
DOIs | |
Publication status | Accepted/In press - 2022 |
Keywords
- Network data envelopment analysis (NDEA)
- Non-positive data
- Performance appraisal
- Super-efficiency
- Sustainability accounting
- Sustainable supply chain
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
- Management of Technology and Innovation