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A grey combined compromise solution (CoCoSo-G) method for supplier selection in construction management

    Morteza Yazdani Affiliation
    ; Zhi Wen Affiliation
    ; Huchang Liao   Affiliation
    ; Audrius Banaitis Affiliation
    ; Zenonas Turskis Affiliation

Abstract

This study investigates an extended version of the combined compromise solution method with grey numbers, named CoCoSo-G for short, to measure the performance of suppliers in a construction company in Madrid. Seven criteria from a relevant previous study are the basis for assessing the performance of suppliers, while ten suppliers are composing our decision matrix. To initiate the decision-making process, we invite experts to aid us in the qualitative evaluation of the suppliers using grey interval values. Two weighting methods, including the DEMATEL (Decision Making Trial and Evaluation Laboratory) and BWM (best worst method) are used to achieve the importance of supplier criteria in a combined manner. The DEMATEL method is used to realise the best and worst criteria, and the BWM is used to sort the criteria according to a linear programming formulation.  The CoCoSo-G method used to release the score of each supplier and rank them. We compare the results obtained by the CoCoSo-G with those obtained by the Complex Proportional Assessment method. It is evident that offering grey values for supplier qualification, using the combined weighting tool and proposing the new CoCoSo-G approach facilitate the evaluation process while indicating trustable outcomes.

Keyword : multi-criteria decision-making, supplier selection, grey values, Combined Compromise Solution method, CoCoSo, CoCoSo-G, Best-Worst method

How to Cite
Yazdani, M., Wen, Z., Liao, H., Banaitis, A., & Turskis, Z. (2019). A grey combined compromise solution (CoCoSo-G) method for supplier selection in construction management. Journal of Civil Engineering and Management, 25(8), 858-874. https://doi.org/10.3846/jcem.2019.11309
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Nov 22, 2019
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Abdullah, L., Zulkifli, N., Liao, H. C., Herrera-Viedma, E., & AlBarakati, A. (2019). An interval-valued intuitionistic fuzzy DEMATEL method combined with Choquet integral for sustainable solid waste management. Engineering Applications of Artificial Intelligence, 82, 207-215. https://doi.org/10.1016/j.engappai.2019.04.005

Aboutorab, H., Saberi, M., Asadabadi, M. R., Hussain, O., & Chang, E. (2018). ZBWM: The Z-number extension of Best Worst method and its application for supplier development. Expert Systems with Applications, 107, 115-125. https://doi.org/10.1016/j.eswa.2018.04.015

Ahmadi, H. B., Kusi-Sarpong, S., & Rezaei, J. (2017). Assessing the social sustainability of supply chains using Best Worst Method. Resources, Conservation and Recycling, 126, 99-106. https://doi.org/10.1016/j.resconrec.2017.07.020

Akintoye, A., McIntosh, G., & Fitzgerald, E. (2000). A survey of supply chain collaboration and management in the UK construction industry. European Journal of Purchasing & Supply Management, 6(3-4), 159-168. https://doi.org/10.1016/S0969-7012(00)00012-5

Brunelli, M., & Rezaei, J. (2019). A multiplicative Best-Worst method for multi-criteria decision making. Operations Research Letters, 47, 12-15. https://doi.org/10.1016/j.orl.2018.11.008

Chalekaee, A., Turskis, Z., Khanzadi, M., Ghodrati Amiri, G., & Keršulienė, V. (2019). A new hybrid MCDM model with grey numbers for the construction delay change response problem. Sustainability, 11(3), 776. https://doi.org/10.3390/su11030776

Chang, B., Chang, C. W., & Wu, C. H. (2011). Fuzzy DEMATEL method for developing supplier selection criteria. Expert Systems with Applications, 38(3), 1850-1858. https://doi.org/10.1016/j.eswa.2010.07.114

Chatterjee, K., Zavadskas, E., Tamošaitienė, J., Adhikary, K., & Kar, S. (2018). A hybrid MCDM technique for risk management in construction projects. Symmetry, 10(2), 46. https://doi.org/10.3390/sym10020046

Chen, K., Chen, P., Yang, L., & Jin, L. (2019). Grey clustering evaluation based on AHP and interval grey number. International Journal of Intelligent Computing and Cybernetics, 12(1), 127-137. https://doi.org/10.1108/ijicc-04-2018-0045

Christopher, M. (2016). Logistics & supply chain management. London: Pearson.

Chitsaz, N., & Azarnivand, A. (2017). Water scarcity management in arid regions based on an extended multiple criteria technique. Water Resources Management, 31(1), 233-250. https://doi.org/10.1007/s11269-016-1521-5

Dadhich, P., Genovese, A., Kumar, N., & Acquaye, A. (2015). Developing sustainable supply chains in the UK construction industry: A case study. International Journal of Production Economics, 164, 271-284. https://doi.org/10.1016/j.ijpe.2014.12.012

Deng, J. (1982). Control problems and grey systems. Systems and Control Letters, 5(2), 288-294. https://doi.org/10.1016/S0167-6911(82)80025-X

Gabus, A., & Fontela, E. (1972). World problems, an invitation to further thought within the framework of DEMATEL. Geneva: Battelle Geneva Research Centre.

Govindan, K., Khodaverdi, R., & Vafadarnikjoo, A. (2015). Intuitionistic fuzzy based DEMATEL method for developing green practices and performances in a green supply chain. Expert Systems with Applications, 42(20), 7207-7220. https://doi.org/10.1016/j.eswa.2015.04.030

Guan, J., Zhang, Z. H., & Wu, Y. (2013). Using fuzzy matter-element model and triangular fuzzy AHP method to select the international construction project material suppliers. Applied Mechanics and Materials, 357-360, 2277-2281. https://doi.org/10.4028/www.scientific.net/AMM.357-360.2277

Guo, S., & Zhao, H. (2017). Fuzzy best-worst multi-criteria decision-making method and its applications. Knowledge-Based Systems, 121, 23-31. https://doi.org/10.1016/j.knosys.2017.01.010

Gupta, H. (2018). Assessing organizations performance on the basis of GHRM practices using BWM and Fuzzy TOPSIS. Journal of Environmental Management, 226, 201-216. https://doi.org/10.1016/j.jenvman.2018.08.005

Hafezalkotob, A., Hafezalkotob, A., Liao, H. C., & Herrera, F. (2019). Interval MULTIMOORA method: Integrating interval Borda rule and interval Best-Worst-Method-based weighting model. IEEE Transactions on Cybernetics, 99, 1-13. https://doi.org/10.1109/TCYB.2018.2889730

Hashemkhani Zolfani, S., Zavadskas, E. K., & Turskis, Z. (2013). Design of products with both International and Local perspectives based on Yin-Yang balance theory and SWARA method. Economic Research – Ekonomska Istraživanja, 26(2), 153-166. https://doi.org/10.1080/1331677X.2013.11517613

Hashemkhani Zolfani, S., Chatterjee, P., & Yazdani, M. (2019, May). A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model. In International Scientific Conference “Contemporary Issues in Business, Management and Economics Engneering’2019” (pp. 797-804). Vilnius, Lithuania. https://doi.org/10.3846/cibmee.2019.081

Hosseini, M. R., Martek, I., Chileshe, N., Zavadskas, E. K., & Arashpour, M. (2018). Assessing the influence of virtuality on the effectiveness of engineering project networks: “Big Five Theory” perspective. Journal of Construction Engineering and Management, 144(7), 04018059. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001494

Hsu, C. W., Kuo, T. C., Chen, S. H., & Hu, A. H. (2013). Using DEMATEL to develop a carbon management model of supplier selection in green supply chain management. Journal of Cleaner Production, 56, 164-172. https://doi.org/10.1016/j.jclepro.2011.09.012

Kalibatas, D., & Turskis, Z. (2008). Multicriteria evaluation of inner climate by using MOORA method. Information Technology and Control, 37(1), 79-83.

Kaur, J., Sidhu, R., Awasthi, A., Chauhan, S., & Goyal, S. (2018). A DEMATEL based approach for investigating barriers in green supply chain management in Canadian manufacturing firms. International Journal of Production Research, 56(1-2), 312-332. https://doi.org/10.1080/00207543.2017.1395522

Keršulienė, V., & Turskis, Z. (2011). Integrated fuzzy multiple criteria decision making model for architect selection. Technological and Economic Development of Economy, 17(4), 645666. https://doi.org/10.3846/20294913.2011.635718

Keshavarz Ghorabaee, M. K., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016). Extended EDAS method for fuzzy multi-criteria decision-making: an application to supplier selection. International Journal of Computers Communications & Control, 11(3), 358-371. https://doi.org/10.15837/ijccc.2016.3.2557

Kumar, V., Kumar, V., Rao, Y. V., & Veeramalla, S. (2019). Supply chain performance influencer in construction domain: a key factor analysis. International Journal of Supply Chain Management, 4(1), 1-7. https://doi.org/10.14419/ijet.v7i4.26.27938

Kumar, A., Kaviani, M., Hafezalkotob, A., & Zavadskas, E. K. (2017). Evaluating innovation capabilities of real estate firms: a combined fuzzy Delphi and DEMATEL approach. International Journal of Strategic Property Management, 21(4), 401416. https://doi.org/10.3846/1648715X.2017.1409291

Liang, R., Zhang, J., Wu, C., Sheng, Z. & Wang, X. (2018). Jointventure contractor selection using competitive and collaborative criteria with uncertainty. Journal of Construction Engineering and Management, 145(2), 04018123. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001588

Liao, H. C., Mi, X. M., Yu, Q., & Luo, L. (2019a). Hospital performance evaluation by a hesitant fuzzy linguistic best worst method with inconsistency repairing. Journal of Cleaner Production, 232, 657-671. https://doi.org/10.1016/j.jclepro.2019.05.308

Liao, H. C., Tang, M., Li, Z.M., Lev, B. (2019b). Bibliometric analysis for highly cited papers in operations research and management science based on Essential Science Indicators. Omega, 88, 223-236. https://doi.org/10.1016/j.omega.2018.11.005

Liu, S. F., Dang, Y. G., Fang, Z. G., & Xie, N. M. (2010). Grey systems theory and its applications. Beijing: Science Press.

Liu, W. S., & Liao, H. C. (2017). A bibliometric analysis of fuzzy decision research during 1970–2015. International Journal of Fuzzy Systems, 19(1), 1-14. https://doi.org/10.1007/s40815-016-0272-z

Liu, A. J., Ji, X. H., Lu, H., & Liu, H. Y. (2019). The selection of 3PRLs on self-service mobile recycling machine: Intervalvalued Pythagorean hesitant fuzzy Best-Worst multi-criteria group decision-making. Journal of Cleaner Production, 230, 734-750. https://doi.org/10.1016/j.jclepro.2019.04.257

Love, P., Irani, Z., & Edwards, D. (2004). A seamless supply chain management model for construction. Supply Chain Management: An International Journal, 9, 43-56. https://doi.org/10.1108/13598540410517575

Mi, X., & Liao, H. (2019). An integrated approach to multiple criteria decision making based on the average solution and normalized weights of criteria deduced by the hesitant fuzzy best worst method. Computers & Industrial Engineering, 133, 83-94. https://doi.org/10.1016/j.cie.2019.05.004

Mi, X. M., Tang, M., Liao, H. C., Shen, W. J., & Lev, B. (2019). The state-of-the-art survey on integrations and applications of the Best Worst Method in decision making: Why, what, what for and what’s next? Omega, 87, 205-225. https://doi.org/10.1016/j.omega.2019.01.009

Mou, Q., Xu, Z. S., & Liao, H. C. (2016). An intuitionistic fuzzy multiplicative Best-Worst method for multi-criteria group decision making. Information Sciences, 374, 224-239. https://doi.org/10.1016/j.ins.2016.08.074

Peldschus, F., Zavadskas, E. K., Turskis, Z., & Tamosaitiene, J. (2010). Sustainable assessment of construction site by applying game theory. Inzinerine Ekonomika – Engineering Economics, 21(3), 223-237.

Plebankiewicz, E., & Kubek, D. (2016). Multicriteria selection of the building material supplier using AHP and fuzzy AHP. Journal of Construction Engineering and Management, 142(1), 04015057. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001033

Polat, G., & Eray, E. (2015). An integrated approach using AHPER to supplier selection in railway projects. Procedia Engineering, 123, 415-422. https://doi.org/10.1016/j.proeng.2015.10.068

Polat, G., Eray, E., & Bingol, B. N. (2017). An integrated fuzzy MCGDM approach for supplier selection problem. Journal of Civil Engineering and Management, 23(7), 926-942. https://doi.org/10.3846/13923730.2017.1343201

Qian, L., Liu, S., & Fang, Z. (2018). Grey risky multi-attribute decision-making method based on regret theory and EDAS. Grey Systems: Theory and Application, 9(1), 101-113. https://doi.org/10.1108/GS-05-2018-0025

Ranjan, R., Chatterjee, P., & Chakraborty, S. (2016). Performance evaluation of Indian railway zones using DEMATEL and VIKOR methods. Benchmarking: An International Journal, 23(1), 78-95. https://doi.org/10.1108/BIJ-09-2014-0088

Raut, R. D., & Mahajan, V. C. (2015). A new strategic approach of fuzzy-quality function deployment and analytical hierarchy process in construction industry. International Journal of Logistics Systems and Management, 20(2), 260-290. https://doi.org/10.1504/IJLSM.2015.067296

Rezaei, J. (2015). Best-Worst multi-criteria decision-making method. Omega, 53, 49-57. https://doi.org/10.1016/j.omega.2014.11.009

Rezaei, J., Wang, J., & Tavasszy, L. (2015). Linking supplier development to supplier segmentation using Best Worst Method. Expert Systems with Applications, 42(23), 9152-9164. https://doi.org/10.1016/j.eswa.2015.07.073

Rezaei, J., Nispeling, T., Sarkis, J., & Tavasszy, L. (2016). A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method. Journal of Cleaner Production, 135, 577-588. https://doi.org/10.1016/j.jclepro.2016.06.125

Rezaei, J., Kothadiya, O., Tavasszy, L., & Kroesen, M. (2018). Quality assessment of airline baggage handling systems using SERVQUAL and BWM. Tourism Management, 66, 85-93. https://doi.org/10.1016/j.tourman.2017.11.009

Schramm, F., & Morais, D. C. (2012). Decision support model for selecting and evaluating suppliers in the construction industry. Pesquisa Operacional, 32(3), 643-662. https://doi.org/10.1590/S0101-74382012005000020

Seth, D., Nemani, V. K., Pokharel, S., & Al Sayed, A. Y. (2018). Impact of competitive conditions on supplier evaluation: a construction supply chain case study. Production Planning & Control, 29(3), 217-235. https://doi.org/10.1080/09537287.2017.1407971

Sivilevičius, H., Zavadskas, E. K., & Turskis, Z. (2008). Quality attributes and complex assessment methodology of the asphalt mixing plant. Baltic Journal of Road & Bridge Engineering, 3(3), 161-166. https://doi.org/10.3846/1822-427X.2008.3.161-166

Štreimikienė, D., Šliogerienė, J., & Turskis, Z. (2016). Multi-criteria analysis of electricity generation technologies in Lithuania. Renewable Energy, 85, 148-156. https://doi.org/10.1016/j.renene.2015.06.032

Tamošaitienė, J., Zavadskas, E. K., Šileikaitė, I., & Turskis, Z. (2017). A novel hybrid MCDM approach for complicated supply chain management problems in construction. Procedia Engineering, 172, 1137-1145. https://doi.org/10.1016/j.proeng.2017.02.168

Turskis, Z., & Zavadskas, E. K. (2010). A novel method for multiple criteria analysis: grey additive ratio assessment (ARAS-G) method. Informatica, 21, 597-610.

Tsai, W. H., Lin, S. J., Lee, Y. F., Chang, Y. C., & Hsu, J. L. (2013). Construction method selection for green building projects to improve environmental sustainability by using an MCDM approach. Journal of Environmental Planning and Management, 56(10), 1487-1510. https://doi.org/10.1080/09640568.2012.731385

Van de Kaa, G., Scholten, D., Rezaei, J., & Milchram, C. (2017). The battle between battery and fuel cell powered electric vehicles: a BWM approach. Energies, 10(11), 1707. https://doi.org/10.3390/en10111707

Vrijhoef, R., & Koskela, L. (2000). The four roles of supply chain management in construction. European Journal of Purchasing & Supply Management, 6(3-4), 169-178. https://doi.org/10.1016/S0969-7012(00)00013-7

Wang, T. K., Zhang, Q., Chong, H. Y., & Wang, X. (2017). Integrated supplier selection framework in a resilient construction supply chain: an approach via Analytic Hierarchy Process (AHP) and grey relational analysis (GRA). Sustainability, 9(2), 289. https://doi.org/10.3390/su9020289

Wen, Z., Liao, H. C., Zavadskas, E. K., & Al-BaIrakati, A. (2019). Selection third-party logistics service providers in supply chain finance by a hesitant fuzzy linguistic combined compromise solution method. Economic Research – Ekonomska Istrazivanja. https://doi.org/10.1080/1331677X.2019.1678502

Wu, C., & Barnes, D. (2016). An integrated model for green partner selection and supply chain construction. Journal of Cleaner Production, 112, 2114-2132. https://doi.org/10.1016/j.jclepro.2015.02.023

Yang, Y. J. (2007). Extended grey numbers and their operations. In Proceedings of 2007 IEEE International Conference on Fuzzy Systems and Intelligent Services, Man and Cybernetics (pp. 2181-2186). Montreal, Canada. https://doi.org/10.1109/ICSMC.2007.4413838

Yazdani, M., Chatterjee, P., Zavadskas, E. K., & Zolfani, S. H. (2017). Integrated QFD-MCDM framework for green supplier selection. Journal of Cleaner Production, 142, 3728-3740. https://doi.org/10.1016/j.jclepro.2016.10.095

Yazdani, M., Zarate, P., Zavadskas, E. K., & Turskis, Z. (2018). A Combined Compromise Solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision. https://doi.org/10.1108/MD-05-2017-0458

Yazdani, M., Chatterjee, P., Pamucar, D., & Abad, M. D. (2019). A risk-based integrated decision-making model for green supplier selection: A case study of a construction company in Spain. Kybernetes. https://doi.org/10.1108/K-09-2018-0509

Zavadskas, E. K., & Turskis, Z. (2011). Multiple criteria decision making (MCDM) methods in economics: an overview. Technological and Economic Development of Economy, 17(2), 397-427. https://doi.org/10.3846/20294913.2011.593291

Zavadskas, E. K., Kaklauskas, A., Turskis, Z., & Tamošaitiene, J. (2008). Selection of the effective dwelling house walls by applying attributes values determined at intervals. Journal of Civil Engineering and Management, 14(2), 85-93. https://doi.org/10.3846/1392-3730.2008.14.3

Zavadskas, E. K., Turskis, Z., Volvačiovas, R., & Kildiene, S. (2013). Multi-criteria assessment model of technologies. Studies in Informatics and Control, 22(4), 249-258. https://doi.org/10.24846/v22i4y201301

Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), 165179. https://doi.org/10.3846/20294913.2014.892037

Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2015). Selecting a contractor by using a novel method for multiple attribute analysis: Weighted Aggregated Sum Product Assessment with grey values (WASPAS-G). Studies in Informatics and Control, 24(2), 141-150. https://doi.org/10.24846/v24i2y201502

Zavadskas, E. K., & Podvezko, V. (2016). Integrated determination of objective criteria weights in MCDM. International Journal of Information Technology & Decision Making, 15(2), 267-283. https://doi.org/10.1142/S0219622016500036

Zhou, H., Wang, J. Q., & Zhang, H. Y. (2019). Stochastic multicriteria decision‐making approach based on SMAA‐ELECTRE with extended gray numbers. International Transactions in Operational Research, 26, 2032-2052. https://doi.org/10.1111/itor.12380

Zionts, S. (1979). MCDM – If not a Roman numeral, then what? Interfaces, 9(4), 94-101. https://doi.org/10.1287/inte.9.4.94