Evaluation and Ranking of Citrus Gardens’ Risks Using TOPSIS Method (Case Study: East of Mazandaran Province)

Subject Areas : Decision-making

سیمین دخت  قاسمیان ¹ (دانشگاه پیام نور تهران)
غلامرضا  یاوری ² (دانشگاه پیام نور ماهدشت)
وحید  ماجد ³ (Associate Professor, Department of Economics, Faculty of Economics, University of Tehran. Iran.)
ابوالفضل  محمودی ⁴ (Associate Professor, Department of Agricultural Economics, Faculty of Agriculture, University of Payam- Noor East Tehran. Iran)
ابوالفضل  جوادیان ⁵ (Associate Professor and Member of Direction Board for Agricultural Insurance Fund in Iran.)

Received: 2016-09-28 Accepted : 2017-03-07 Published : 2018-03-01

Keywords: Risk, citrus, Mazandaran, TOPSIS technique, weighted Shannon Entropy,

Abstract :

Citrus production has a great importance and position in Iran. The growth and sustainability of the agriculture sector is impossible without appropriate and effective risk identification and management. In this study, the main risks of citrus gardens were identified based on the Delphi method through questionnaires completed by 16 experts. Then, using the TOPSIS technique, the risks involved in the horticultural industry of Mazandaran Province were prioritized during 2010-2016 and the most important risk of Mazandaran gardens was selected based on the Shannon unweighted entropy matrix. The results showed that the most important horticultural risks were related to the risks of pests and diseases, price, damage, and production, respectively. In addition, the lowest risks were related to technical, labor and credit risks, respectively. Therefore, the results indicated the significant influence of the risks of pests and diseases, price and loss in horticulture. Among the risks of pests and diseases, mealy bugs, red mites and aphids with 76, 73 and 70 percent, respectively, were of the highest risk and risks arising from financing, purchasing the product and the damage caused by drip irrigation and emitters were of the lowest risk. The risk exposure represented that risk management should be considered in these fields. In this regard, it is essential to make major reforms in risk management areas involved in orchards. Thus, the planners and policymakers must consider this issue.

References:

Alimi, T., & Wall, A. (2005). Risk and risk management strategies in onion production in Kebbi state of Nigeria. Journal of Social Science, 10(1), 1-8.

Asgharpour, M. J. (2006). Multi-criteria decision-making. Tehran: Tehran University Press,pp. 15-18.

Azar, A.S., & Rajabzadeh, A.S. (2008). The decision applied (approach M.A.D.M) (Third Edition). Tehran, knowledge, pp.120-132.

Chena, Y.W., & Larbanib, M. (2006). Two-person zero-sum game approach for fuzzy multiple attribute decision making problems. Fuzzy Sets and Systems, 157(1), 34-51.

Chu, T.C., &Lin,Y.C. (2003). Afuzzy TOPSIS method for robot selection. International Journal of Manufacturing Technology, 21, 284-290.

Ghatee, M., & Mohades, A. (2009). Motion planning in order to optimize the length and clearance applying a Hopfield neural network, 36, 4688-4695.

Higgs, G. (2006). Integrating multi-criteria techniques with geographical information systems in waste facility location to enhance public participation. Journal of Waste Management & Research, 24, 105-117.

Horticultural Crops Agricultural Statistics (2014). Department of statistics and information technology, Agriculture Organization of Mazandaran Province. (2), 38-50. 

Hsu-Shin, Shin, Huan-JyhShyur, E., &Stanley, Lee (2007). An extension of TOPSIS for group decision making. Mathematical and Computer Modeling, 45, 801-813.

Hwang, C.L., &Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer Verlag, New York, Pp. 95-101.

Khakpour, b., Tall, E., &Salehifard, M. (2010). Evaluation of urban management in the development of public green spaces (parks) using TOPSIS (Case Study: Mashhad, Iran). Journal of Geography and Regional Development, 14, 1-27.

Kiyani Rad, A., &Yazdani, S. (2003). Risk management and crop insurance: Experiences and the tested. Fourth Iranian conference of agricultural economics, College of Agriculture, Tehran University, Iran.

Mohammadi, A. (2011). Comparison of linear and taxonomy application Topsis allocation of financial evaluation. Journal of Economic Research, 11(1), 273-302.

Phuson, N., Yamada, R., & Doan Khoi, L.N. (2003). Some solutions for limiting risks and disadvantages in agricultural production of farm households in can the province .Japan International Resource Center. The International Bank for Reconstruction and Development. 75-78

Simonovic, S. P., &Verma, R. (2008). A new methodology for water resources multicriteria decision making under uncertainty. Physics and Chemistry of the Earth, Parts A/B/C, 33(5), 322-329.

Tsou, C.-S. (2008). Multi-objective inventory planning using MOPSO and TOPSIS. Expert Systems with Applications, 35(1), 136-142.

Wang, T.C., Lee, H. D., & Wu, C.C. (2007). A fuzzy TOPSIS approach with subjective weights and objective weights. Paper presented at the Proceedings of the 6 Conference on WSEAS International Conference on Applied Computer Science -Volume 6, Hangzhou, China.

Yalkin, N. & Bayrakdaroglu, A. (2009). Fuzzy performance evaluation in Turkish banking using AHP and TOPSIS. Expert Systems with Applications, 36, 699-709.

You, Q.H.,&Ding. R.H. (2005). Negative Problem of Topsis Technoology Groud, 2-27.

Zaheri, M., Aghayarihir, M., & Zakerimiyab, K. (2015). Prioritization of agricultural processing and complementary industries in Azarshahr County by Delphi and TOPSIS Combined Methods. Journal of Geography and Planning, 51,  221-246.

Zibaie, M., &Telkani, n. (2010). Ranking goals Ranchers and forest dwellers city Tonekabon using fuzzy logic and simple rankings. Journal of Agricultural Economics and Development, 18(69), 138-165.