A hybrid model of network data envelopment analysis and data mining to predict efficiency in the green supply chain of the poultry industry

Analyzing and predicting efficiency in industries is very important in order to evaluate the performance of units and plan to improve their performance. Poultry industry, as one of the strategic and complex industries, has taken an important part of the food chain basket of the societies, and from this point of view, the analysis of its supply network is very important.In this research, using the network data coverage analysis model and data mining, research gaps in the field of measuring and predicting the efficiency of the green supply chain in the poultry industry have been covered. This research is descriptive and survey in terms of its practical purpose and in terms of the nature of implementation, which is done by developing mathematical models in the field of data coverage analysis.First, using the Delphi approach, the effective indicators were identified and screened based on the opinion of experts, and then a new mathematical model was presented based on the coverage analysis of network data. In the following, the efficiency of 9 chains was evaluated in five years using the alpha cut method based on the enveloping analysis method of fuzzy data. The results showed that the presented model is able to evaluate the efficiency of the green and multi-level supply chain of the poultry industry in consecutive years.