Malek Hassanpour

DOI Number
First page
Last page


Data Envelopment Analysis (DEA) is a prominent procedure in the decision-making process with a pivotal role in the sustainable development assay. Project identification is the first step of sustainability assessment in the Environmental Impact Assessment (EIA) program for the industrial projects prior to complete establishment. The present review research comprised 405 Iranian industries assessment regarding both input and output criteria via DEA integrated with the ratio model of Additive Ratio ASsessment (ARAS) and weighing systems of Kendall and Friedman's tests supported by SPSS software. The findings deployed a classification for Iranian industries pertaining to industries' nominal capacity in certain clusters. Also, the current review paved the pathway towards executing both energy and materials streams in industries.


Iranian Industries, DEA, EIA, ARAS Model, Assessment

Full Text:



Mensah, E.K., 2019, Robust optimization in data envelopment analysis, PhD Thesis, University of Insubria Department of Economics, Varese - Milano.

Zurano-Cervello, P., Pozo, C., Mateo-Sanz, J.M., Jimenez, L., Guillen-Gosalbez, G., 2018, Eco-efficiency assessment of EU manufacturing sectors combining input-output tables and data envelopment analysis following production and consumption-based accounting approaches, Journal of Cleaner Production, 174, pp. 1161-1189.

Baker, M.J., 2003, The marketing book, Fifth Edition, Butterworth-Heinemann An imprint of Elsevier Science Linacre House, Jordan Hill, Oxford OX2 8DP, Chapter 9, pp. 1-875.

Kuçukonder, H., Demirarslan1, C.P, Burgut, A., Boga, M., 2019, A Hybrid Approach of Data Envelopment Analysis Based Grey Relational Analysis: A Study on Egg Yield, Pakistan J. Zool, 51(3), pp. 903-912.

Anouze, A.L., Osman, I.H., 2014, Mismanagement or mis-measurement: the application of DEA to generate performance values and insights from big data, methodologies, tools, and applications, chapter 6, pp. 276-322.

Pastor, J.T., Ruiz, J.L., Sirvent, I., 1999, A statistical test for detecting influential observations in DEA, European Journal of Operational Research, 115, pp. 542-554.

Cheraghali, Z., Papi, S., 2017, Investigating the performance of the healthcare sector in the provinces of Iran by using a window analysis in data, Int. J. Data Envelopment Analysis, 5(3), pp. 1353-1360.

Mardani, A., Zavadskas, E.K., Streimikiene, D., Jusoh, A., Khoshnoudi, M., 2017, A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency, Renewable and Sustainable Energy Reviews, 70, pp. 1298-1322.

Tabatabaei, M.H., M., Amiri., Ghahremanloo, M., Keshavarz-Ghorabaee, M., Zavadskas, E.K., Antucheviciene, J., 2019, Hierarchical decision-making using a new mathematical model based on the best-worst method, International journal of computers communications & control, 14(6), pp. 710-725.

Kaklauskas, A., Zavadskas, E.K., 2015, Multiple criteria analysis of the life cycle of the built environment, Monograph, Funded by European Social Fund, pp. 1-448

Hassanpour, M., 2020, Evaluation of Iranian small and medium-sized industries, A Ph. D thesis submitted to Osmania University, Telengana state, India.

Gerami, J., 2017, An extended of multiple criteria data envelopment analysis models for ratio data, Int. J. Data Envelopment Analysis, 5(4), pp. 1361-1386.

Vahidi, H., Hoveidi, H., Kazemzadeh, Khoie, J., 2016, Challenges and Opportunities of Industrial Ecology Development in Iran, Int. J. Environ. Res., 10(2), pp. 217-226.

Glasson, J., Therivel, R., Chadwick, A., 2005, Introduction to environmental impact assessment, 2nd edition, Taylor & Francis e-Library, USA.

Aravossis, K.G., Kapsalis, V.C., Kyriakopoulos, G.L, Xouleis, T.G., 2019, Development of a Holistic Assessment Framework for Industrial Organizations, Sustainability, 11, pp. 1-24.

Munn, R.E., 1979, Environmental Impact Assessment, Principles and Procedures, Scope 5, John Wiley and Sons, New York.

Zwikael, O., Chih, Y.Y., Meredith, J.K., 2018, Project benefit management: Setting effective target benefits, International Journal of Project Management, 36, pp. 650-658.

Amini, A., Alinezhad, A., 2016, A combined evaluation method to rank alternatives based on VIKOR and DEA with BELIEF Structure under Uncertainty, Iranian Journal of Optimization, 8(2), pp. 111-122.

Gupta, S., Bandyopadhyay, G., Bhattacharjee M, Biswas, S., 2019, Portfolio selection using DEA-COPRAS at risk – return interface based on NSE (India), International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(10), pp. 4078-4086.

Azadi, M., Mirhedayatian, S.M., Saen, R.F., Hatamzad, M., Momeni, E., 2017, Green supplier selection: a novel fuzzy double frontier data envelopment analysis model to deal with undesirable outputs and dual-role factors, Int. J. Industrial and Systems Engineering, 25(2), pp. 160-181.

An, Q., Wen, Y., Xiong, B., Yang, M., Chen, X., 2017, Allocation of carbon dioxide emission permits with the minimum cost for Chinese provinces in big data environment, Journal of Cleaner Production, 142, pp. 886-893.

Xiong, B., Li, Y., Song, M., 2017, Eco-efficiency measurement and improvement of Chinese industry using a new closest target method, International Journal of Climate Change Strategies and Management, 9(5), pp. 666-681.

Tabasi, M., Navabakhsh, M., Kotobashkan, H., Tavakkoli-Moghaddam, R., 2019, Performance evaluation using network data envelopment analysis approach with game theory under mixed grey-fuzzy uncertainty in Iran Khodro Company, International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 10 (13), pp. 1-19.

Lu, C.C, Lu, L.C., 2019, Evaluating the energy efficiency of European Union countries: The dynamic data envelopment analysis, Energy & Environment, 30(1), pp. 1-17.

Bulak, M.E., Turkyilmaz, A., 2014, Performance assessment of manufacturing SMEs: a frontier approach, Industrial Management & Data Systems, 114(5), pp. 797-816.

Duman, G.M, Tozanli, O., Kongar, E., Gupta, M.S., 2017, A holistic approach for performance evaluation using quantitative and qualitative data: A food industry case study, Expert Systems with Applications 81, pp. 410–422.

Azbari, M.E., Olfat, L., Amiri, M., Soofi, J.B., 2014, A network data envelopment analysis model for supply chain performance evaluation: real case of Iranian pharmaceutical industry, International Journal of Industrial Engineering & Production Research, 25(2), pp. 125-137.

Anthony, P., Behnoee, B., Hassanpour, M., Pamucar, D., 2019, Financial performance evaluation of seven Indian chemical companies, Decision Making: Applications in Management and Engineering, 2(1), pp. 19-37.

Shafiee, M., Amirzadeh, M., 2011, Evaluating Performance of the 37 areas of N.I.O.P.D.C using a mathematical model, 3rd International Conference on Information and Financial Engineering IPEDR vol.12, IACSIT Press, Singapore.

Azadi, M., Jafarian, M., Saen, R.F., Mirhedayatian, S.M., 2015, A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context, Computers & Operations Research, 54, pp. 274–285.

Toloo, M., Tavana, M., Santos-Arteaga, F.J., 2019, An integrated data envelopment analysis and mixed integer non-linear programming model for linearizing the common set of weights, CEJOR, 27, pp. 887–904.

Bansal, V.R., 2018, Efficiency evaluation of Indian oil and gas sector: data envelopment analysis, International Journal of Emerging Markets, 14(2), pp. 362-378.

Alidrisi, H., Aydin, M.E., Bafail, A.O., Abdulal, R., Karuvatt, S.A., 2019, Monitoring the Performance of Petrochemical Organizations in Saudi Arabia Using Data Envelopment Analysis, Mathematics, 7, pp. 1-16.

Kim, J.M., Sun, B., Jun, S., 2019, Sustainable technology analysis using data envelopment analysis and state space models, Sustainability, 11(3), pp. 2-19.

Tapia, J.F.D., Promentilla, M.A.B., Tseng, M.L., Tan, R.R., 2017, Screening of carbon dioxide utilization options using hybrid Analytic Hierarchy Process-Data Envelopment Analysis method, Journal of Cleaner Production, 165, pp. 1361-1370.

Tsai, C.H., Wu, H.Y, Chen, I.S., Chen, J.K., Ye, R.W., 2017, Exploring benchmark corporations in the semiconductor industry based on efficiency, Journal of High Technology Management Research, 28, pp. 188–207.

Li, X., Liu, Y., Wang, Y., Gao, Z,. 2016, Evaluating transit operator efficiency: An enhanced DEA model with constrained fuzzy-AHP cones, Journal of traffic and transportation engineering (English edition), 3(3), pp. 215-225.

Nemati, M., Matin, R.K., 2019, A data envelopment analysis approach for resource allocation with undesirable outputs: an application to home appliance production companies, Sadhana, 44, article no. 11.

Saravi, N.A., Yazdanparast, R., Momeni, O., Heydarian, D., Jolai, F., 2019, Location optimization of agricultural residues-based biomass plant using Z-number DEA, Journal of Industrial and Systems Engineering, 12(1), pp. 39-65.

Ülengin, F., Kabak, Ö., Önsel, S., Aktas, E., & Parker, B.R., 2011, The competitiveness of nations and implications for human development, Socio-Economic planning sciences, 45(1), pp. 16-27.

Sevinç, A., Eren, T., 2019, Determination of KOSGEB support models for small- and medium-scale enterprises by means of data envelopment analysis and multi-criteria decision making methods, Processes, 7(3), pp. 1-27.

Woo, S.H., Lai, P.L., Chen, Y.H., Yang, C.C., 2019, Meta-frontier function approach to operational efficiency for shipping companies, Maritime policy & management, 46(5), pp. 529–544.

Heldman, K., 2009, Project management professional exam study guide, Fifth Edition, Copyright by Wiley Publishing, Inc., Indianapolis, Indiana Published simultaneously in Canada, pp. 1-677.

Zavadskas, E.K., Sušinskas, S., Daniunas, A., Turskis, Z., Sivilevicius, H., 2012, Multiple criteria selection of pile-column construction technology, Journal of civil engineering and management, 18(6), pp. 834–842.

Hassanpour, M., 2019, Efficiency Score Assessment of Iranian Plastic Industries, Proceedings of Business and Economic Studies, 2(5), pp. 1-5.

Hassanpour, M., 2019, Efficiency score assessment of Iranian Mining, Wood and Textile Industries, Iranian Journal of Optimization, 11(3), pp. 1-15.

Hassanpour, M., 2019, Efficiency Score Assessment of Iranian Automotive and Food Industries, Int. J. Data Envelopment Analysis, 7(2), pp. 65-82.

Hassanpour, M., 2019, Evaluation of Iranian electronic products manufacturing industries using an unsupervised model, ARAS, SAW and DEA models, Journal of Industrial Engineering and Management Studies, 6(2), pp. 1-24.

Hassanpour, M., Pamucar, D., 2019, Evaluation of Iranian household appliance industries using MCDM models, Operational Research in Engineering Sciences: Theory and Applications, 2(3), pp. 1-25.

Rahmani, M., 2017, A productivity analysis of Iranian industries using an additive data envelopment analysis, Management Science Letters, 7, pp. 197–204.

Azar, A., Mahmoudabadi, Z.M, Emrouznejad, A., 2016, A new fuzzy additive model for determining the common set of weights in Data Envelopment Analysis, Journal of Intelligent & Fuzzy Systems, 30, pp. 61–69.

Amini, A., Alinezhad, A., 2016, A combined evaluation method to rank alternatives based on VIKOR and DEA with belief structure under uncertainty, Iranian Journal of Optimization, 8(2), pp. 111-122.

Lu, W.M., Wang, W.K., Kweh, Q.L., 2014, Intellectual capital and performance in the Chinese life insurance industry, Omega. 42, pp. 65–74.

Shermeh, H.E., Najafi, S.E., Alavidoost, M.H., 2016, A novel fuzzy network SBM model for data envelopment analysis: A case study in Iran regional power companies, Energy, 112, pp. 686-697.

Ahmadi, V., Ahmadi, A., 2012. Application of Data Envelopment Analysis in manufacturing industries of Iran, Interdisciplinary journal of contemporary research in business, 4(8), pp. 534-544.

Bayyurt, N., duzu, G., 2008, Performance Measurement of Turkish and Chinese Manufacturing Firms, A Comparative Analysis, Eurasian Journal of Business and Economics, 1(2), pp. 71-83.

Karamidou, J., Mimis, A., Pappa, E. 2011, Estimating technical and scale efficiency of meat products industry: the Greek Case, Journal of Applied Science, 11(6), pp. 971-979.

Rezaee, M.J., Ghanbarpour T., 2016, Energy resources consumption performance in Iranian manufacturing industries using cost/revenue efficiency model, IJE Transactions C: Aspects, 29(9), pp. 1282-1291.

Puska, A., Stojanovic, I., Maksimovic, A., 2019, Evaluation of sustainable rural tourism potential in BRCKO district of Bosnia and Herzegovina using multi-criteria analysis, Operational Research in Engineering Sciences: Theory and Applications, 2(2), pp. 40-54

Biswas, T.K., Chaki, S., Das, M.C., 2019, MCDM technique application to the selection of an Indian institute of technology, Operational Research in Engineering Sciences: Theory and Applications, 2(3), pp. 65-76.

Feroz, E.H., Kim S., Raab, RL, 2017, Financial statement analysis: a data envelopment analysis approach, Journal of the Operational Research Society, 54, pp. 48-58.

Sinha, R.P., 2015, A Dynamic DEA model for Indian Life insurance companies, Global Business Review, 16(2), pp. 1-12.

DOI: https://doi.org/10.22190/FUME200426030H


  • There are currently no refbacks.

ISSN: 0354-2025 (Print)

ISSN: 2335-0164 (Online)

COBISS.SR-ID 98732551

ZDB-ID: 2766459-4