Vol. 9 No. 4 (2021): Business & Management Studies: An International Journal

A Fuzzy Best Worst approach to the determination of the importance level of digital supply chain on sustainability

Kevser Arman
Research Assistant, Pamukkale University, Denizli, Turkey
Arzu Organ
Prof. Dr., Pamukkale University, Denizli, Turkey

Published 2021-12-25

How to Cite

Arman, K., & Organ, A. (2021). A Fuzzy Best Worst approach to the determination of the importance level of digital supply chain on sustainability. Business & Management Studies: An International Journal, 9(4), 1366–1379. https://doi.org/10.15295/bmij.v9i4.1901


In today's world where the importance of digitalization is increasing day by day, companies to increase their competitiveness have focused on digital supply chain instead of traditional supply chain. In a world where resources are constantly decreasing, the concept of sustainability has become very crucial in every part of life. Digital technologies, on the other hand, have a direct relationship with sustainability. Sustainability has three main dimensions: economic, environmental, and social. Therefore, the aim of this study is to evaluate digital supply chain on 3 basic dimensions of sustainability. For this purpose, Fuzzy Best Worst Method (F-BWM) was used to define the importance level of criteria. Findings reveal that the concept of sustainability in textile firms in Turkey is generally perceived within an economic and environmental area, rather than within a social dimension. This study is very important in putting forward digital technologies which utilizing in supply chain and the impact of the digital supply chain on sustainability.


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  1. “Türkiye Tekstil Sektörü”, https://uib.org.tr/tr/kbfile/turkiye_tekstil_sektoru_ve_bursa_ocak_2020, (22.02.2021).
  2. Abdel-Basset, M., Manogaran, G., & Mohamed, M. (2018). Internet of Things (IoT) And Its Impact On Supply Chain: A Framework For Building Smart, Secure And Efficient Systems. Future Generation Computer Systems, 86, 614-628.
  3. Ajayi, A., Oyedele, L., Delgado, J. M. D., Akanbi, L., Bilal, M., Akinade, O., & Olawale, O. (2019). Big Data Platform For Health And Safety Accident Prediction. World Journal Of Science, Technology And Sustainable Development.
  4. Akandere, G., & Paksoy, T. (2020). Smart And Sustainable/Green SCM. Logistics 4.0: Digital Transformation of Supply Chain Management, 284.
  5. Amiri, M., Hashemi-Tabatabaei, M., Ghahremanloo, M., Keshavarz-Ghorabaee, M., Zavadskas, E. K., & Banaitis, A. (2020). A New Fuzzy BWM Approach For Evaluating And Selecting A Sustainable Supplier in Supply Chain Management. International Journal Of Sustainable Development & World Ecology, 28(2), 125-142.
  6. Anitha, P., & Patil, M. M. (2018). A Review On Data Analytics For Supply Chain Management: A Case Study. International Journal of Information Engineering And Electronic Business, 11(5), 30.
  7. Arslan, M. (2020). Corporate Social Sustainability in Supply Chain Management: A Literature Review. Journal of Global Responsibility.
  8. Attaran, M. (2020). Digital Technology Enablers And Their Implications For Supply Chain Management. In Supply Chain Forum: An International Journal (Vol. 21, No. 3, pp. 158-172). Taylor & Francis.
  9. Awasthi, A., Govindan, K. & Gold, S. (2018). Multi-Tier Sustainable Global Supplier Selection Using A Fuzzy AHP-VIKOR Based Approach ,International Journal Of Production Economics, 195, 106-117.
  10. Bag, S., Telukdarie, A., Pretorius, J. H. C., & Gupta, S. (2018). Industry 4.0 And Supply Chain Sustainability: Framework And Future Research Directions. Benchmarking: An International Journal.
  11. Bellman, R. E., & Zadeh, L. A. (1970). Decision-Making in A Fuzzy Environment. Management Science, 17(4), B-141.
  12. Brandon-Jones, E., Squire, B., Autry, C.W., & Petersen, K.J. (2014). A Contingent Resource-Based Perspective Of Supply Chain Resilience And Robustness. J. Suppl. Chain Manag. 50 (3), 55–73.
  13. Büyüközkan, G., & Göçer, F. (2018). Digital Supply Chain: Literature Review And A Proposed Framework For Future Research. Computers in Industry, 97, 157-177.
  14. Carter, C. R., & Rogers, D. S. (2008). A Framework of Sustainable Supply Chain Management: Moving Toward New Theory. International Journal of Physical Distribution & Logistics Management.
  15. Chen, Z., Ming, X., Zhou, T., & Chang, Y. (2020). Sustainable Supplier Selection For Smart Supply Chain Considering Internal And External Uncertainty: An Integrated Rough-Fuzzy Approach. Applied Soft Computing, 87, 106004.
  16. Cole, R., Stevenson, M., & Aitken, J. (2019). Blockchain Technology: Implications For Operations And Supply Chain Management. Supply Chain Management: An International Journal, 24/4, 469–483.
  17. Cooper, M. C., Lambert, D. M., & Pagh, J. D. (1997). Supply Chain Management: More Than A New Name For Logistics. The International Journal of Logistics Management, 8(1), 1-14.
  18. Çakır, E., & Can, M. (2019). Best-Worst Yöntemine Dayalı ARAS Yöntemi ile Dış Kaynak Kullanım Tercihinin Belirlenmesi: Turizm Sektöründe Bir Uygulama. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 23(3), 1273-1300.
  19. Çifçi, G., & Büyüközkan, G. (2011). A Fuzzy MCDM Approach To Evaluate Green Suppliers. International Journal Of Computational Intelligence Systems, 4(5), 894-909.
  20. De Vass, T., Shee, H., & Miah, S. J. (2020). IoT in Supply Chain Management: A Narrative On Retail Sector Sustainability. International Journal of Logistics Research And Applications, 1-20.
  21. Diabat, A., Kannan, D., & Mathiyazhagan, K. (2014). Analysis of Enablers For Implementation of Sustainable Supply Chain Management–A Textile Case. Journal of Cleaner Production, 83, 391-403.
  22. Dubey, R., Gunasekaran, A., Childe, S.J., Wamba, S.F., Papadopoulos, T. (2016). The Impact Of Big Data On World-Class Sustainable Manufacturing. Int. J. Adv. Manuf. Technol. 84, 631–645.
  23. Ecemiş, O., & Yaykaşlı, M., (2018), Çok Kriterli Karar Verme Yöntemleriyle Sürdürülebilir Tedarikçi Seçimi Ve Bir Uygulama, Akademik Sosyal Araştırmalar Dergisi, Yıl: 6, Sayı: 83,Ss:382-399.
  24. Ecer, F. (2015). Performance Evaluation of Internet Banking Branches Via A Hybrid MCDM Model Under Fuzzy Environment. Econ. Comput. Econ. Cybern. Stud. Res. 49 (2), 211e230.
  25. Ecer, F., & Pamucar, D. (2020). Sustainable Supplier Selection: A Novel Integrated Fuzzy Best Worst Method (F-BWM) And Fuzzy Cocoso With Bonferroni (Cocoso’b) Multi-Criteria Model. Journal Of Cleaner Production, 266, 121981.
  26. Ecer, F. (2021). Sürdürülebilir Tedarikçi Seçimi: FUCOM Sübjektif Ağırlıklandırma Yöntemi Temelli MAIRCA Yaklaşımı. Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi , 8 (1) , 26-48.
  27. Elkington, J. (1998), “Partnerships From Cannibals With Forks: The Triple Bottom Line Of 21st-Century Business”, Environmental Quality Management, Vol. 8 No. 1, Pp. 37-51.
  28. Ertuğrul, İ., & Karakaşoğlu, N. (2009). Performance Evaluation Of Turkish Cement Firms With Fuzzy Analytic Hierarchy Process And TOPSIS Methods. Expert Systems With Applications, 36(1), 702-715.
  29. Frank, A. G., Dalenogare, L. S., & Ayala, N. F. (2019). Industry 4.0 Technologies: Implementation Patterns in Manufacturing Companies. International Journal of Production Economics, 210, 15-26.
  30. Giannakis, M., Spanaki, K., & Dubey, R. (2019). A Cloud-Based Supply Chain Management System: Effects On Supply Chain Responsiveness. Journal of Enterprise Information Management.
  31. Govindan, K., Cheng, T.C.E., Mishra, N., & Shukla, N. (2018). Big Data Analytics And Application For Logistics And Supply Chain Management. Transp. Res. Pt. e-Logist. Transp. Rev. 114, 343–349.
  32. Griffin, A., & Hauser, J. R. (1993). The Voice of The Customer. Marketing Science, 12(1), 1-27.
  33. Gunasekaran, A., Papadopoulos, T., Dubey, R., Wamba, S.F., Childe, S.J., Hazen, B., & Akter, S. (2017). Big Data and Predictive Analytics For Supply Chain And Organizational Performance. J. Bus. Res. 70, 308–317.
  34. Guo, S., & Zhao, H. (2017). Fuzzy Best-Worst Multi-Criteria Decision-Making Method And Its Applications. Knowledge-Based Systems, 121, 23-31.
  35. Hoseini, S. A., Fallahpour, A., Wong, K. Y., Mahdiyar, A., Saberi, M., & Durdyev, S. (2021). Sustainable Supplier Selection in Construction Industry through Hybrid Fuzzy-Based Approaches. Sustainability, 13(3), 1413.
  36. Huq, F. A., Stevenson, M., & Zorzini, M. (2014). Social Sustainability in Developing Country Suppliers: An Exploratory Study in The Ready Made Garments Industry of Bangladesh. International Journal of Operations & Production Management.
  37. Jaiswal, D., & Kant, R. (2018). Green Purchasing Behaviour: A Conceptual Framework And Empirical İnvestigation of Indian Consumers. Journal of Retailing And Consumer Services, 41, 60-69.
  38. Karmaker, C. L., Ahmed, T., Ahmed, S., Ali, S. M., Moktadir, M. A., & Kabir, G. (2021). Improving Supply Chain Sustainability in The Context of COVID-19 Pandemic in An Emerging Economy: Exploring Drivers Using An Integrated Model. Sustainable Production and Consumption, 26, 411-427.
  39. Khan, S., Haleem, A., & Khan, M. I. (2021, January). Assessment of Risk in the Management of Halal Supply Chain Using Fuzzy BWM Method. In Supply Chain Forum: An International Journal (Vol. 22, No. 1, Pp. 57-73). Taylor & Francis.
  40. Kocak, H., Caglar, A., & Oztas, G. Z. (2018). Euclidean Best–Worst Method And Its Application. International Journal Of Information Technology & Decision Making, 17(05), 1587-1605.
  41. Kuo, R. J., Wang, Y. C., & Tien, F. C. (2010). Integration of Artificial Neural Network And MADA Methods For Green Supplier Selection. Journal of Cleaner Production, 18(12), 1161-1170.
  42. Kusi-Sarpong, S., Gupta, H., & Sarkis, J. (2019). A Supply Chain Sustainability Innovation Framework and Evaluation Methodology. International Journal of Production Research, 57(7), 1990-2008.
  43. Luthra, S., Govindan, K., Kannan, D., Mangla, S. K., & Garg, C. P. (2017). An Integrated Framework For Sustainable Supplier Selection And Evaluation in Supply Chains. Journal of Cleaner Production, 140, 1686-1698.
  44. Mahdiraji, H. A., Hafeez, K., Kord, H., & Kamardi, A. A. (2020). Analysing The Voice Of Customers By A Hybrid Fuzzy Decision-Making Approach in A Developing Country's Automotive Market. Management Decision.
  45. Melo, S., Macedo, J., Baptista, P. (2019). Capacity-sharing in Logistics Solutions: A New Pathway Towards Sustainability. Transp. Policy (Oxf), 73, 143–151.
  46. Moslem, S., Gul, M., Farooq, D., Celik, E., Ghorbanzadeh, O., & Blaschke, T. (2020). An Integrated Approach Of Best-Worst Method (BWM) And Triangular Fuzzy Sets For Evaluating Driver Behavior Factors Related To Road Safety. Mathematics, 8(3), 414.
  47. Nasiri, M., Ukko, J., Saunila, M., & Rantala, T. (2020). Managing The Digital Supply Chain: The Role Of Smart Technologies. Technovation, 96, 102121.
  48. Organ, A., & Kenger, M. D. (2012). Bulanık Analitik Hiyerarşi Süreci ve Mortgage Banka Kredisi Seçim Problemine Uygulanması. Niğde Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 5(2), 119-135.
  49. Özek, A., & Yıldız, A. (2020). Digital Supplier Selection for a Garment Business Using Interval Type-2 Fuzzy TOPSIS. Journal of Textile & Apparel/Tekstilve Konfeksiyon, 30(1).
  50. Raman, S., Patwa, N., Niranjan, I., Ranjan, U., Moorthy, K., & Mehta, A. (2018). Impact of Big Data On Supply Chain Management. International Journal of Logistics Research And Applications, 21(6), 579-596.
  51. Rezaei, J. (2015). Best-Worst Multi-Criteria Decision-Making Method. Omega, 53, 49-57.
  52. Rezaei, J. (2016). Best-Worst Multi-Criteria Decision-Making Method: Some Properties and A Linear Model, Omega, Vol. 64, Pp. 126-130.
  53. Saryatmo, M. A., & Sukhotu, V. (2021). The Influence of the Digital Supply Chain on Operational Performance: A Study of the Food and Beverage Industry in Indonesia. Sustainability, 13(9), 5109.
  54. Seuring, S., Sarkis, J., Müller, M., & Rao, P. (2008). Sustainability And Supply Chain Management–An Introduction to The Special Issue.
  55. Shin, D. (2018). Empathy And Embodied Experience in Virtual Environment: To What Extent Can Virtual Reality Stimulate Empathy And Embodied Experience?. Computers in Human Behavior, 78, 64-73.
  56. 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 & Industrial Engineering, 140, 106231.
  57. Sudusinghe, J. I., & Seuring, S. (2020). Social Sustainability Empowering The Economic Sustainability in The Global Apparel Supply Chain. Sustainability, 12(7), 2595.
  58. Torkayesh, S. E., Iranizad, A., Torkayesh, A. E., & Basit, M. N. (2020). Application of BWM-WASPAS Model for Digital Supplier Selection Problem: A Case Study in Online Retail Shopping. Journal of Industrial Engineering And Decision Making, 1(1), 12-23.
  59. Triantaphyllou, E. (2000). Multi-Criteria Decision Making Methods. In Multi-Criteria Decision Making Methods: A Comparative Study (Pp. 5-21). Springer, Boston, MA.
  60. Uçal Sarı, İ., Çayır Ervural, B., & Bozat, S. (2017). Sürdürülebilir Tedarik Zinciri Yönetiminde DEMATEL Yöntemiyle Tedarikçi Değerlendirme Kriterlerinin İncelenmesi ve Sağlık Sektöründe Bir Uygulama. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 23(4), 477-485.
  61. Wang Chen, H. M., Chou, S. Y., Luu, Q. D., & Yu, T. H. K. (2016). A Fuzzy MCDM Approach For Green Supplier Selection From The Economic and Environmental Aspects. Mathematical Problems in Engineering, 2016.
  62. WCED (World Commission On Environment And Development) (1987). Our Common Future. Oxford University Press, Oxford.
  63. Wilding, R., Wagner, B., Gimenez, C., & Tachizawa, E. M. (2012). Extending Sustainability to Suppliers: A Systematic Literature Review. Supply Chain Management: An International Journal With Applications, Vol. 107, Pp. 115-125.
  64. Wu, H. K., Lee, S. W. Y., Chang, H. Y., & Liang, J. C. (2013). Current Status, Opportunities And Challenges Of Augmented Reality in Education. Computers & education, 62, 41-49.
  65. Wu, L., Yue, X., Jin, A., & Yen, D. C. (2016). Smart Supply Chain Management: A Review And Implications For Future Research. The International Journal of Logistics Management.
  66. Xu, L., & Yang, J. B. (2001). Introduction to Multi-Criteria Decision Making and the Evidential Reasoning Approach (Vol. 106). Manchester: Manchester School Of Management.
  67. Yang, M., Fu, M., & Zhang, Z. (2021). The Adoption of Digital Technologies in Supply Chains: Drivers, Process And Impact. Technological Forecasting and Social Change, 169, 120795.
  68. Yawar, S. A., & Seuring, S. (2017). Management of Social Issues in Supply Chains: A Literature Review Exploring Social Issues, Actions And Performance Outcomes. Journal of Business Ethics, 141(3), 621-643.
  69. Yıldız, A. (2018a). Endüstri 4.0 ve Akıllı Fabrikalar. Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 22(2), 546-556.
  70. Yıldız, A. (2018b). Endüstri 4.0 ile Bütünleştirilmiş Dijital Tedarik Zinciri. BMIJ, 6(4), 1215-1230.
  71. Zadeh, L. A. (1965). Fuzzy Sets, Information and Control, 8, 338-353.