Evaluation of Iranian household appliance industries using MCDM models
DOI:
https://doi.org/10.31181/oresta1903001hKeywords:
Evaluation, Household Appliance Industries, ARAS, CODAS, DEA ModelsAbstract
Technology development and maturation in the field of household appliance industries, approach to the initial media and aims of Industry 4.0 are promising scenarios for the future. However, the present cluster study of Iranian Household Appliance Industries (IHAI) empirically seeks the full details of IHAI based on the preliminary studies of both Iranian industries organization and Iranian environment protection agency once in the industry confirmation step and issue the authorities and licenses to stakeholders. Simple Additive Weighing (SAW), Additive Ratio ASsessment (ARAS) and COmbinative Distance-based ASsessment (CODAS) method and Data Envelopment Analysis (DEA) were employed to classify IHAI based on the main criteria via SPSS and Excel 2013 soft-wares. By the way, the Friedman test and Entropy Shannon weighing systems were also applied to distinguish the values of weights. The findings were revealed three prominent steps to achieve sustainable development purposes, economic estimation and efficiency appraise of industries in the easiest possible situation. Also, by current study IHAI were classified by a ranking system of DEA, in terms of efficiency score.
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References
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Rezaee, MJ, Ghanbarpour, T. (2016). Energy Resources Consumption Performance in Iranian Manufacturing Industries Using Cost/Revenue Efficiency Model. IJE TRANSACTIONS C: Aspects, 29(9), 1282-1291.
Rahmani, M. (2017). A productivity analysis of Iranian industries using an additive data envelopment analysis. Management Science Letters, 7, 197–204.
Sinha, RP. (2015). A Dynamic DEA Model for Indian Life Insurance Companies. Global Business Review, 16(2), 1-12.
Saranga, H., Nagpal, R. (2016). Drivers of operational efficiency and its impact on market performance in the Indian Airline industry. Journal of Air Transport Management, 53, 165-176.
Stanujkic, D., Jovanovic, R. (2012). Measuring a quality of faculty website using ARAS method. Contemporary issues in business, management and education, 5, 545-554.
Turskis, Z., Lazauskas, M., Zavadskas, EK. (2012). Fuzzy multiple criteria assessment of construction site alternatives for nonhazardous waste incineration plant in Vilnius city, applying ARAS-F and AHP methods. Journal of environmental engineering and landscape management, 20(2), 110–120.
Tupenaite L, Zavadskas, EK, Kaklauskas, A, Turskis, Z, Seniut, M. (2010). Multiple criteria assessment of alternatives for built and human environment renovation. Journal of civil engineering and management, 16(2), 257–266.
Xavier, JM., Moutinho, VF, Moreira, AC. (2015). An empirical examination of performance in the clothing retailing in-dustry: A case study. Journal of Retailing and Consumer Services, 25, 96–105.
Zavadskas, EK, Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multi-criteria decision-making Technological and Economic Development of Economy, 16(2): 159–172.
Ahmadi, V., Ahmadi, A. (2012). Application of Data Envelopment Analysis in manufacturing industries of Iran. Interdisciplinary journal of contemporary research in business, 4(8), 534-544.
Badi IA, Abdulshahed AM, Shetwan AG. (2018). A case study of supplier selection for a steel making company in Libya by using the combinative distance-based assessment (codas) model. Decision Making: Applications in Management and Engineering, 1(1), 1-12.
Bulak, ME., Turkyilmaz, A. (2014). Performance assessment of manufacturing SMEs: a frontier approach. Industrial Management & Data Systems, 114(5), 797-816.
Badi, I., Ballem, M., Shetwan, A. (2016). Site selection of desalination plant in LIBYA by using combinative distance-based assessment (CODAS) method. International Journal for Quality Research, 12(3), 609–624.
Balezentiene, L., Kusta, A. (2012). Reducing Greenhouse Gas Emissions in Grassland Ecosystems of the Central Lithuania: Multi-Criteria Evaluation on a Basis of the ARAS Method. The Scientific World Journal, ID 908384, 1-12.
Dahooei, JH, Zavadskas, EK, Vanaki, AS., Firoozfar, HR., Keshavarz-Ghorabae, M. (2018). An evaluation model of business intelligence for enterprise systems with new extension of codas (CODAS-IVIF). Information Management. 2018, XXI, 3. 171-187.
Eisinga, R., Heskes, T., Pelzer, B., Grotenhuis, MT. (2017). Exact p-values for pairwise comparison of Friedman rank sums, with application to comparing classifiers. BMC Bioinformatics, 18(68), 2-18.
Emrouznejad, A., Podinovski, V. (2004). Data Envelopment Analysis and Performance Management: Proceedings of the 4th International Conference on DEA, September 2004, Birmingham, UK, 417pp.
Ghorabaee, MK., Zavadskas, EK, Turskis, Z., Antucheviciene, J. (2016). A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Economic Computation and Economic Cybernetics Studies and Research, 50 (3), 25-44.
Hassanpour, M. (2019a). Evaluation of Iranian Textile and Leather Industries. J. Appl. Res. Ind. Eng, 6(1), 33–51.
Hassanpour, M. (2019b). Evaluation of Iranian Mining and Aggregate Industries. Industrial Engineering Journal, 12(3), 1-15.
Hassanpour, M. (2018). Hierarchical cluster classification of Iranian Food manufacturing and processing industries. J Food Safe & Hyg, 4 (1-2), 27-40.
Jandaghi, G., Safarzadeh, H., Amini, A., Bahiraei, S. (2011). Evaluating and comparing brand equity of Iranian and South Korean home appliance brands in the view of Tehran bazaar retailers. Am. J. Sci. Ind. Res, 2(5), 786-797.
Karabasevic, D., Paunkovic, J., Stanujkic, D. (2016). Ranking of companies according to the indicators of corporate social responsibility based on SWARA and ARAS methods. Serbian Journal of Management, 11 (1), 43 – 53.
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), 971-979.
Krmac, E., Djordjevic, B. (2019). A New DEA Model for Evaluation of Supply Chains: A Case of Selection and Evaluation of Environmental Efficiency of Suppliers. Symmetry, 11(4), 1-21.
Kersuliene, V., Turskis, Z. (2011). Integrated fuzzy multiple criteria decision making model for architect selection. Technological and economic development of economy, 17(4): 645–666.
Lu, W-M., Wang, W-K., Kweh, QL. (2014). Intellectual capital and performance in the Chinese life insurance industry. Omega, 42, 65–74.
Munn, RE. (1979). Environmental Impact Assessment, Principles and Procedures. Scope 5. John Wiley and Sons, New York.
Mukhametzyanov, I., Pamucar, D. (2018). A sensitivity analysis in MCDM problems; a statistical approach. Decision Making: Applications in Management and Engineering, 1(2), 51-80.
Mathew, M., Sahu, S. (2018). Comparison of new multi-criteria decision making methods for material handling equipment selection. Management Science Letters, 8, 139–150.
Panchal, D., Chatterjee, P., Shukla, RK, Choudhury, T., Tamosaitiene, J. (2017). Integrated fuzzy AHP-CODAS framework for maintenance decision in urea fertilizer industry. Economic Computation and Economic Cybernetics Studies and Research, 51(3), 179-196.
Pamucar, D., Badi, I., Sanja, K, Obradovic, R. (2018). A Novel Approach for the Selection of Power-Generation Technology Using a Linguistic Neutrosophic CODAS Method: A Case Study in Libya. Energies, 11, 1-25.
Roy J, Das S., Kar S., Pamucar D. (2019). An Extension of the CODAS Approach Using Interval-Valued Intuitionistic Fuzzy Set for Sustainable Material Selection in Construction Projects with Incomplete Weight Information. Symmetry, 11(3), 1-24.
Roy, A., Chatterjee, P., Chakraborty, S., Mondal, S. (2018). An Integrated Entropy-Combinative Distance-Based Assessment (CODAS) Method for Aerospace Material Selection. National Conference on Advanced Materials, Manufacturing and Metrology (NCAMMM - 2018) on 16-17 February, 2018 at CSIR-CMERI, Durgapur.
Rezaee, MJ, Ghanbarpour, T. (2016). Energy Resources Consumption Performance in Iranian Manufacturing Industries Using Cost/Revenue Efficiency Model. IJE TRANSACTIONS C: Aspects, 29(9), 1282-1291.
Rahmani, M. (2017). A productivity analysis of Iranian industries using an additive data envelopment analysis. Management Science Letters, 7, 197–204.
Sinha, RP. (2015). A Dynamic DEA Model for Indian Life Insurance Companies. Global Business Review, 16(2), 1-12.
Saranga, H., Nagpal, R. (2016). Drivers of operational efficiency and its impact on market performance in the Indian Airline industry. Journal of Air Transport Management, 53, 165-176.
Stanujkic, D., Jovanovic, R. (2012). Measuring a quality of faculty website using ARAS method. Contemporary issues in business, management and education, 5, 545-554.
Turskis, Z., Lazauskas, M., Zavadskas, EK. (2012). Fuzzy multiple criteria assessment of construction site alternatives for nonhazardous waste incineration plant in Vilnius city, applying ARAS-F and AHP methods. Journal of environmental engineering and landscape management, 20(2), 110–120.
Tupenaite L, Zavadskas, EK, Kaklauskas, A, Turskis, Z, Seniut, M. (2010). Multiple criteria assessment of alternatives for built and human environment renovation. Journal of civil engineering and management, 16(2), 257–266.
Xavier, JM., Moutinho, VF, Moreira, AC. (2015). An empirical examination of performance in the clothing retailing in-dustry: A case study. Journal of Retailing and Consumer Services, 25, 96–105.
Zavadskas, EK, Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multi-criteria decision-making Technological and Economic Development of Economy, 16(2): 159–172.
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Published
2019-11-12
How to Cite
Hassanpour, M., & Pamucar, D. (2019). Evaluation of Iranian household appliance industries using MCDM models. Operational Research in Engineering Sciences: Theory and Applications, 2(3), 1–25. https://doi.org/10.31181/oresta1903001h
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