Performance Evaluation of Production Chain using Two-Stage DEA Method (Case Study: Iranian Poultry Industry)

Document Type : Research Paper

Authors

1 Associate Professor, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin branch, Islamic Azad University, Qazvin, Iran.

2 Master of Science Student, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Abstract

Abstract
Today, the poultry industry is one of the most important food industries in any country in providing food to the communities. Knowledge of how the production chain works in this industry is essential. The purpose of this paper is to evaluate the performance of 28 active production chains in the Iranian poultry industry and to calculate their relative efficiency and also determines the supply chain pattern for other chains. In order to achieve this goal, non-parametric data envelopment analysis (DEA) method has been used. The relative efficiency of each unit is first calculated with the network DEA approach and then the traditional DEA and the results of the two methods are compared. Finally, the cross-efficiency method is used to rank the efficient units. The results showed that in the network and traditional model, out of 28 production chains under study, 3 and 7 efficient chains, respectively. In models, the minimum efficiency is 63% and 67%, respectively. Given the number of efficient units in the traditional DEA model, it is obvious that the decision to determine the pattern production chain for other production chains is difficult. This study proposes a network DEA model to evaluate the performance of Iranian poultry industry production chains.

Keywords: Efficiency, Supply chain, Two-stage DEA, Poultry Industry.
JEL Classification: C67, H0, L80

Keywords


Alinezhad, A., and Khalili, J. (2018). Performance Evaluation in Green Supply Chain Using BSC, DEA and Data Mining. International Journal of Supply and Operations Management, 5(2): 182-191.
Alinezhad, A., Behrouzinezhad, A.S. (2011). Introduction to multi-criteria decision making of data envelopment analysis and their relationship. Jahad Daneshgahi AmirKabir, Tehran. (In Persian)
Alinezhad, A., Zohrehbandian, M., and Esfandiari N., (2011). Introduction to Performance Measurement Systems. Qazvin Azad University Press. (In Persian)
Amini, A., Alinezhad, A., and Salmanian, S. (2016). Development of data envelopment analysis for the performance evaluation of green supply chain with undesirable outputs. International journal of supply and operations management, 3(2): 1267-1283.
Banker, R.D., Charnes, A. and Cooper, W.W. (1984). Some models for estimating technical and scale inefficiencies in Data Envelopment Analysis. Management Science, 30: 1078-1092.
Charnes, A., Cooper, W. W., and Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2: 429–444.
Chen, C., and Yan, H.  (2011). Network DEA Model for Supply Chain Performance Evaluation. European Journal of Operational Research, 213(1): 147-155.
Del Angizan, S., and Provokani Jashni, K. (2017). A Study of the Supply Chain of Kermanshah Province Poultry Industry. Scientific-Extension Quarterly of Supply Chain, 58: 29-39. (In Persian)
Fao, (2020). Food and agriculture data. http://www.fao.org/faostat/en/#home
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3): 253-281.
Farsijani, H., Arman, M.H., Hossein Beigi, A., and Jalili, A. (2011). Presentation of Data Envelopment Analysis Model with Input-Output Axis Approach. Industrial Management Perspective, 1: 39-56. (In Persian)
Gilanpour, O., Kohansal, M., Perm, Z., and Ismailipour, E., (2012). Investigating the Impact of Government Interventions in the Chicken Meat Market. Business Research Journal, 63: 137-168. (In Persian)
Hosseini, S.A., Kouchakzade, M.M., and Sydabadi, H.R. (2015). Determination of the share of cost-effective price per kilogram of broilers by using a multi-criteria decision analysis in Tehran province. Journal of Animal Production, 17(1): 51-58. (In Persian)
Hosseini, S.M., and Sheikhi, N. (2012). Explaining the strategic role of supply chain management operations in improving company performance: Iran Food Industry Study. Strategic Management Studies, 10: 31-57. (In Persian)
Hosseinzadeh, F., and Rahimi, A. (2019). Evaluation of Efficiency and Returns to Scale of Resin Chemical Industry Supply Chain using Crisp and Fuzzy Data Envelopment. Production and Operations Management, 10: 47-63.
Jain, V., Tiwari, M., and Chan, F. (2004). Evaluation of the Supplier Performance using an Evolutionary Fuzzy-Based Approach. Journal of Manufacturing Technology Management, 15(8): 735-744.
Jezghani, F., Moghaddasi, R., Yazdani S., and Mohammadinejad A., (2015). Spatial price transfer model of Iranian chicken meat and the most important business partner. Journal of Agricultural Economics, 7 (28): 99-112. (In Persian)
Khodakarami, M., Shabani, A., Farzipoor Saen R., and Azadi, M. (2015). Developing Distinctive Two-Stage Data Envelopment Analysis Models: An Application in Evaluating Sustainability of Supply Chain Management. Measurement, 70: 62-74.
Mishra. (2012). Measuring Supply Chain Efficiency: a DEA Approach. Journal of Operations and Supply Chain Management. 5(1): 45-68.
Nozari, N., Ghaderzadeh, M., and Hamed Mirzaei, K. (2012). A Study of the Cost Structure of Broiler Breeding Units: A Case Study of Sanandaj and Kamyaran Countries. Journal of Animal Science and Research, 13: 83-98. (In Persian)
Pishbahar, A., Assadollahpour, F., and Ferdowsi R. (2015). Investigating the Effects of Input Price Shocks on Chicken Meat Prices: Markov-Switching Nonlinear Approach. Animal Science Research (Agricultural Science), 1: 79-94. (In Persian)
Rahmani, Z., and Ghaderzadeh, H. (2013). Estimation of the cost function of poultry farms in Sanandaj. Journal of Agricultural Economics Research, 6(1): 67-80. (In Persian)
Sexton, T.R., Silkman, R.H., and Hogan, A.J. (1986). Data Envelopment Analysis: Critique and Extension. Jossey-Bass. San Francisco. CA: 73-105.
Seyed Hosseini, M., and Yadranji Aghdam, B. (2009). A Model Based on Knowledge Management in the Supply Chain Distribution Ring, Transportation and Logistics. Journal of Civil Engineering, Islamic Azad University, 2(1): 84-96. (In Pesrsian)
Solgi, O., GHidar-Khanjani, J., Saeidi, M., and Dehghani, E. (2019). Implementing an efficient data envelopment analysis method for assessing suppliers of complex product systems. Journal of Industrial and Systems Engineering, 12(2): 113-137.
Tavana, M., Kaviani, MA., Di Caprio, D., and Rahpeyma, B. (2016). A two-stage data envelopment analysis model for measuring performance in three-level supply chains. Measurement, 78: 322-333.