A Network Data Envelopment Analysis Approach for Efficiency Measurement of Poultry Industry Production Chains
Subject Areas : International Journal of Decision IntelligenceAli Taherinezhad 1 , Alireza Alinezhad 2 , Saber Gholami 3 , Mahsa Abdolvand 4
1 - PhD Candidate, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2 - Associate Professor, Department of Industrial Engineering, Faculty of Industrial and
Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
3 - Master Student of Industrial Engineering, Caspian Higher Education Institute, Qazvin, Iran.
4 - M.Sc., Department of Industrial Engineering, Faculty of Engineering, University of Qom, Qom, Iran.
Keywords: performance, Efficiency, Network DEA, Poultry Industry, Production chain, Traditional DEA,
Abstract :
In this paper, models of data envelopment analysis (DEA) were investigated with the aim of measuring the efficiency of production chains in Iran's poultry industry. DEA tool can determine the efficiency frontier and the reference production chain to improve the performance of the poultry industry. Statistical data were collected for 28 active production chains and 8 variables including: Material cost, human resource cost, equipment and facilities cost, transport cost, number of poultry, poultry price, profit, and cost of slaughter. Then, the relative efficiency of each chain was measured using traditional and network DEA. Finally, cross efficiency method was used to rank efficient chains. Traditional DEA results showed 25% of production chains to be efficient. Meanwhile, this percentage was equal to 10.7% in the proposed model of the paper (two-stage DEA). Therefore, the scientific accuracy of the reference production chain will be higher in the network model. The rest of the results and their details were presented and discussed. The results of this paper can be useful in the decision-making and policies of poultry industry managers and also improve the performance of production chains in this industry.