Measuring Sustainability Performance Indicators Using FUCOM-MARCOS Methods

  • Ibrahim Badi Libyan Academy, Department of Mechanical Engineering, Misurata - Libya
  • L. J. Muhammad Mathematics and Computer Science Department, Federal University of Kashere, Gombe- Nigeria
  • Mansir Abubakar Department of Mathematical Sciences, Al-Qalam University, Katsina State – Nigeria
  • Mahmut Bakır Department of Aviation Management, Samsun University, Samsun - Turkey
Keywords: MCDM, MARCOS, FUCOM, Green innovation, performance indicators

Abstract

Due to rising environmental concerns, green innovation has become a familiar and appealing topic worldwide in recent years. In addition, population growth, globalization, urbanization, and industrialization have given rise to many problems, such as damage to the environment, the economy, and the living conditions of society. This paper aims to evaluate and prioritize aspects of green innovation, taking into account sustainability performance indicators. FUCOM-MARCOS hybrid methods were used. The experimental results of the proposed method showed that management technological innovation (C1) is the most influential part for adopting green practices in the textile industry in Nigeria. The study also showed that greening the supplier (C6) and product technology innovation (C5) are the second and third most important aspects of green innovation. Furthermore, it analyzed the sustainability performance indicators using the MARCOS method. The findings reveal that social performance (SPI-3) was the most sustainable and vital indicator in terms of green innovation practices in the textile sector in Nigeria. Sensitivity analysis was also conducted using five other methods, and the results obtained showed stability in the order of the indicators. 

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References

Acar, E., Kiliç, M., & Güner, M. (2015). Measurement of sustainability performance in textile industry by using a multi-criteria decision making method. Textile and apparel, 25(1), 3–9.

Alosta, A., Elmansuri, O., & Badi, I. (2021). Resolving a location selection problem by means of an integrated AHP-RAFSI approach. Reports in Mechanical Engineering, 2(1), 135–142. https://doi.org/10.31181/rme200102135a DOI: https://doi.org/10.31181/rme200102135a

Aly, A. H., & Mansour, M. E. (2017). Evaluating the sustainable performance of corporate boards: the balanced scorecard approach. Managerial Auditing Journal, 32(2), 167–195. https://doi.org/10.1108/MAJ-04-2016-1358 DOI: https://doi.org/10.1108/MAJ-04-2016-1358

Asadi, S., OmSalameh Pourhashemi, S., Nilashi, M., Abdullah, R., Samad, S., Yadegaridehkordi, E., Aljojo, N., & Razali, N. S. (2020). Investigating influence of green innovation on sustainability performance: A case on Malaysian hotel industry. Journal of Cleaner Production, 258, 120860. https://doi.org/10.1016/j.jclepro.2020.120860

Badi, I., & Ballem, M. (2018). Supplier selection using the rough BWM-MAIRCA model: A case study in pharmaceutical supplying in Libya. Decision Making: Applications in Management and Engineering, 1(2), 16–33. https://doi.org/10.31181/dmame1802016b DOI: https://doi.org/10.31181/dmame1802016b

Badi, I., & Kridish, M. (2020). Landfill site selection using a novel FUCOM-CODAS model: A case study in Libya. Scientific African, 9, e00537. https://doi.org/10.1016/j.sciaf.2020.e00537

Badi, I., & Pamucar, D. (2020). Supplier selection for steelmaking company by using combined Grey-MARCOS methods. Decision Making: Applications in Management and Engineering, 3(2), 37–48. https://doi.org/10.31181/dmame2003037b DOI: https://doi.org/10.31181/dmame2003037b

Božanic, D., Tešic, D., & Kocic, J. (2019). Multi-criteria fucom -fuzzy mabac model for the selection of location for construction of single-span bailey bridge. Decision Making: Applications in Management and Engineering, 2(1), 132–146. https://doi.org/10.31181/dmame1901132b DOI: https://doi.org/10.31181/dmame1901132b

Cainelli, G., Mazzanti, M., & Montresor, S. (2012). Environmental Innovations, Local Networks and Internationalization. Industry and Innovation, 19(8), 697–734. https://doi.org/10.1080/13662716.2012.739782 DOI: https://doi.org/10.1080/13662716.2012.739782

Chen, H., & Wang, L. (2017). Coproducts Generated from Biomass Conversion Processes. In H. Chen & L. Wang (Eds.), Technologies for Biochemical Conversion of Biomass (pp. 219–264). Elsevier Inc. https://doi.org/10.1016/b978-0-12-802417-1.00009-0 DOI: https://doi.org/10.1016/B978-0-12-802417-1.00009-0

del Río, P., Peñasco, C., & Romero-Jordán, D. (2016). What drives eco-innovators? A critical review of the empirical literature based on econometric methods. Journal of Cleaner Production, 112, 2158–2170. https://doi.org/10.1016/j.jclepro.2015.09.009 DOI: https://doi.org/10.1016/j.jclepro.2015.09.009

Durotoye, T. O., Adeyemi, A. A., Omole, D. O., & Onakunle, O. (2018). Impact assessment of wastewater discharge from a textile industry in Lagos, Nigeria. Cogent Engineering, 5(1), 1–11. https://doi.org/10.1080/23311916.2018.1531687

Ecer, F., & Pamucar, D. (2022). A novel LOPCOW-DOBI multi-criteria sustainability performance assessment methodology: An application in developing country banking sector. Omega, 102690. https://doi.org/10.1016/j.omega.2022.102690

Elkington, J. (1998). Accounting for the Triple Bottom Line. Measuring Business Excellence, 2(3), 18–22. https://doi.org/10.1108/eb025539 DOI: https://doi.org/10.1108/eb025539

Fazlollahtabar, H., Smailbašic, A., & Stevic, Ž. (2019). Fucom method in group decision-making: Selection of forklift in a warehouse. Decision Making: Applications in Management and Engineering, 2(1), 49–65. https://doi.org/10.31181/dmame1901065f DOI: https://doi.org/10.31181/dmame1901065f

Gbolarumi, F. T., Wong, K. Y., & Olohunde, S. T. (2021). Sustainability Assessment in The Textile and Apparel Industry: A Review of Recent Studies. IOP Conference Series: Materials Science and Engineering, 1051(1), 1–16. https://doi.org/10.1088/1757-899x/1051/1/012099

Ghorabaee, M. K., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS). Informatica, 26(3), 435–451. https://doi.org/10.15388/Informatica.2015.57 DOI: https://doi.org/10.15388/Informatica.2015.57

Glavič, P., Pintarič, Z. N., & Bogataj, M. (2021). Process design and sustainable development—a european perspective. Processes, 9(1), 1–21. https://doi.org/10.3390/pr9010148

Goodridge, W. S. (2016). Sensitivity analysis using simple additive weighting method. International Journal of Intelligent Systems and Applications, 8(5), 27–33. https://doi.org/10.5815/ijisa.2016.05.04 DOI: https://doi.org/10.5815/ijisa.2016.05.04

Gupta, S., & Dhingra, S. (2021). Modeling the key factors influencing the adoption of mobile financial services: an interpretive structural modeling approach. Journal of Financial Services Marketing. https://doi.org/10.1057/s41264-021-00101-4

Houck, M., Speaker, P. J., Fleming, A. S., & Riley, R. A. (2012). The balanced scorecard: Sustainable performance assessment for forensic laboratories. Science and Justice, 52(4), 209–216. https://doi.org/10.1016/j.scijus.2012.05.006 DOI: https://doi.org/10.1016/j.scijus.2012.05.006

Jakovljevic, V., Zizovic, M., Pamucar, D., Stević, Ž., & Albijanic, M. (2021). Evaluation of human resources in transportation companies using multi-criteria model for ranking alternatives by defining relations between ideal and anti-ideal alternative (Raderia). Mathematics, 9(9), 1–25. https://doi.org/10.3390/math9090976

Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard: measures that drive performance. Harvard Business Review, 70(1), 71–79.

Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Symmetry, 13(4). https://doi.org/10.3390/sym13040525

Keshavarz Ghorabaee, M., Zavadskas, E. K., 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.

Lin, H., Zeng, S. X., Ma, H. Y., & Chen, H. Q. (2015). How Political Connections Affect Corporate Environmental Performance: The Mediating Role of Green Subsidies. Human and Ecological Risk Assessment, 21(8), 2192–2212. https://doi.org/10.1080/10807039.2015.1044937 DOI: https://doi.org/10.1080/10807039.2015.1044937

Lu, M. T., Hsu, C. C., Liou, J. J. H., & Lo, H. W. (2018). A hybrid MCDM and sustainability-balanced scorecard model to establish sustainable performance evaluation for international airports. Journal of Air Transport Management, 71, 9–19. https://doi.org/10.1016/j.jairtraman.2018.05.008 DOI: https://doi.org/10.1016/j.jairtraman.2018.05.008

Mardani, A., Nilashi, M., Zakuan, N., Loganathan, N., Soheilirad, S., Saman, M. Z. M., & Ibrahim, O. (2017). A systematic review and meta-Analysis of SWARA and WASPAS methods: Theory and applications with recent fuzzy developments. Applied Soft Computing, 57, 265–292. https://doi.org/10.1016/j.asoc.2017.03.045 DOI: https://doi.org/10.1016/j.asoc.2017.03.045

Muhammad, L. J., Badi, I., Haruna, A. A., & Mohammed, I. A. (2021). Selecting the Best Municipal Solid Waste Management Techniques in Nigeria Using Multi Criteria Decision Making Techniques. Reports in Mechanical Engineering, 2(1), 180–189. https://doi.org/10.31181/rme2001021801b DOI: https://doi.org/10.31181/rme2001021801b

Owen, R., Brennan, G., & Lyon, F. (2018). Enabling investment for the transition to a low carbon economy: government policy to finance early stage green innovation. Current Opinion in Environmental Sustainability, 31, 137–145. https://doi.org/10.1016/j.cosust.2018.03.004 DOI: https://doi.org/10.1016/j.cosust.2018.03.004

Özdağoğlu, A., Keleş, M. K., Altınata, A., & Ulutaş, A. (2021). Combining Different McDm Methods With the Copeland Method: An Investigation on Motorcycle Selection. Journal of Process Management and New Technologies, 9(3–4), 13–27. https://doi.org/10.5937/jpmnt9-34120

Pamucar, D., Badi, I., & Stevic, Z. (2022). An Integrated FUCOM-RAFSI Model for Assessing the Potential of a New Gateway Port in Libya for Some African Landlocked Countries. International Journal for Quality Research, 16(2), 613–624. https://doi.org/10.24874/IJQR16.02-17

Pamučar, D., & Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications, 42(6), 3016–3028. https://doi.org/10.1016/j.eswa.2014.11.057 DOI: https://doi.org/10.1016/j.eswa.2014.11.057

Pamučar, D., Stević, Ž., & Sremac, S. (2018). A New Model for Determining Weight Coefficients of Criteria in MCDM Models: Full Consistency Method (FUCOM). Symmetry, 10(9), 1–22. https://doi.org/10.3390/sym10090393

Pamučar, D., Žižović, M., Biswas, S., & Božanić, D. (2021). A New Logarithm Methodology of Additive Weights (LMAW) For Multi-Criteria Decision-Making: Application in Logistics. Facta Universitatis, Series: Mechanical Engineering, 19(3), 361–380. https://doi.org/10.22190/FUME210214031P

Peng, W., Yin, Y., Kuang, C., Wen, Z., & Kuang, J. (2021). Spatial spillover effect of green innovation on economic development quality in China: Evidence from a panel data of 270 prefecture-level and above cities. Sustainable Cities and Society, 69, 102863. https://doi.org/10.1016/j.scs.2021.102863

Popović, M. (2021). An MCDM Approach for Personnel Selection Using the CoCoSo Method. Journal of Process Management and New Technologies, 9(3–4), 78–88. https://doi.org/10.5937/jpmnt9-34876

Popović, M., Popović, G., & Karabašević, D. (2021). Determination of the importance of evaluation criteria during the process of recruitment and selection of personnel based on the application of the SWARA method. Ekonomika, 67(4), 1–9. https://doi.org/10.5937/ekonomika2104001P

Shujah-ur-Rahman, Chen, S., Saud, S., Bano, S., & Haseeb, A. (2019). The nexus between financial development, globalization, and environmental degradation: Fresh evidence from Central and Eastern European Countries. Environmental Science and Pollution Research, 26(24), 24733–24747. https://doi.org/10.1007/s11356-019-05714-w

Simić, J. M., Stević, Ž., Zavadskas, E. K., Bogdanović, V., Subotić, M., & Mardani, A. (2020). A novel critic‐fuzzy fucom‐dea‐fuzzy marcos model for safety evaluation of road sections based on geometric parameters of road. Symmetry, 12(12), 1–27. https://doi.org/10.3390/sym12122006

Singh, S. K., Giudice, M. Del, Chierici, R., & Graziano, D. (2020). Green innovation and environmental performance: The role of green transformational leadership and green human resource management. Technological Forecasting and Social Change, 150, 119762. https://doi.org/10.1016/j.techfore.2019.119762

Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers and Industrial Engineering, 140, 106231. https://doi.org/10.1016/j.cie.2019.106231

Torkayesh, A. E., & Deveci, M. (2021). A mulTi-noRmalization mUlti-distance aSsessmenT (TRUST) approach for locating a battery swapping station for electric scooters. Sustainable Cities and Society, 74, 103243. https://doi.org/10.1016/j.scs.2021.103243

Torkayesh, A. E., Hashemkhani Zolfani, S., Kahvand, M., & Khazaelpour, P. (2021). Landfill location selection for healthcare waste of urban areas using hybrid BWM-grey MARCOS model based on GIS. Sustainable Cities and Society, 67. https://doi.org/10.1016/j.scs.2021.102712

Ullah, S., Khan, F. U., & Ahmad, N. (2022). Promoting sustainability through green innovation adoption: a case of manufacturing industry. Environmental Science and Pollution Research, 29(14), 21119–21139. https://doi.org/10.1007/s11356-021-17322-8

United Nations. (2020). Goal 13: Take urgent action to combat climate change and its impacts. https://www.un.org/sustainabledevelopment/climate-change/

Wang, Y., & Yang, Y. (2021). Analyzing the green innovation practices based on sustainability performance indicators: a Chinese manufacturing industry case. Environmental Science and Pollution Research, 28(1), 1181–1203. https://doi.org/10.1007/s11356-020-10531-7

Wong, C. Y., Wong, C. W. Y., & Boon-itt, S. (2020). Effects of green supply chain integration and green innovation on environmental and cost performance. International Journal of Production Research, 58(15), 4589–4609. https://doi.org/10.1080/00207543.2020.1756510

World Trade Organization. (2021). World Trade Statistical Review 2021. https://www.wto.org/english/res_e/statis_e/wts2021_e/wts2021_e.pdf

Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., & Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(9), 2501–2519. https://doi.org/10.1108/MD-05-2017-0458

Zakeri, S., Ecer, F., Konstantas, D., & Cheikhrouhou, N. (2021). The vital-immaterial-mediocre multi-criteria decision-making method. Kybernetes. https://doi.org/10.1108/K-05-2021-0403 DOI: https://doi.org/10.1108/K-05-2021-0403

Zhang, F., & Zhu, L. (2019). Enhancing corporate sustainable development: Stakeholder pressures, organizational learning, and green innovation. Business Strategy and the Environment, 28(6), 1012–1026. https://doi.org/10.1002/bse.2298

Žižović, M., & Pamučar, D. (2019). New model for determining criteria weights: Level Based Weight Assessment (LBWA) model. Decision Making: Applications in Management and Engineering, 2(2). https://doi.org/10.31181/dmame1902102z DOI: https://doi.org/10.31181/dmame1902102z

Žižović, M., Pamućar, D., Albijanić, M., Chatterjee, P., & Pribićević, I. (2020). Eliminating rank reversal problem using a new multi-attribute model - The RAFSI method. Mathematics, 8(6), 1–16. https://doi.org/10.3390/math8061015

Published
2022-07-04
How to Cite
Badi, I., L. J. Muhammad, Mansir Abubakar, & Mahmut Bakır. (2022). Measuring Sustainability Performance Indicators Using FUCOM-MARCOS Methods. Operational Research in Engineering Sciences: Theory and Applications. https://doi.org/10.31181/040722060b
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Articles