Skip to main content
SpringerLink
Log in

Evaluating the Impact of Risk Component in Supply Chain Management Using Intuitionistic Fuzzy Cognitive Map

  • Conference paper
  • First Online:
Intelligent and Fuzzy Systems (INFUS 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 759))

Included in the following conference series:

  • 379 Accesses

Abstract

The growing complexity of supply chains is attributed to a range of factors, including globalization, competitive conditions, growing relationships among supply chain partners, and evolving technology. This phenomenon is associated with increased uncertainties and new risks that adversely affect many firms. Therefore, identifying, assessing, and managing these risks is essential for establishing a profitable, competitive, and sustainable supply chain over the long term. Supply chain risk management (SCRM) has emerged as a critical area of inquiry and practice for managing these risks. The primary objective of this study is to develop a model that predicts supply chain risks. To achieve this objective, the study commences with a comprehensive literature review to identify relevant articles related to the topic of interest. Based on the document coding rules using the identified articles, variables were determined. The identified variables were subsequently transformed into linguistic variables and triangular membership functions using a fuzzy set approach. An intuitionistic fuzzy cognitive map was created using the adjacency matrix obtained from the normalization process. Furthermore, scenario analyses were conducted to identify measures. The resulting model provides a comprehensive framework for predicting supply chain risks and identifying measures to mitigate them. This study advances the state of the art in SCRM research and practice.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bakhtavar, E., Valipour, M., Yousefi, S., Sadiq, R., Hewage, K.: Fuzzy cognitive maps in systems risk analysis: a comprehensive review. Complex Intell. Syst. 7(2), 621–637 (2020). https://doi.org/10.1007/s40747-020-00228-2

    Article  Google Scholar 

  2. Kosko, B.: Fuzzy cognitive maps. Int. J. Man. Mach. Stud. 24(1), 65–75 (1986)

    Article  MATH  Google Scholar 

  3. Zadeh, L.A.: Fuzzy sets. Inform. Control 8(3), 338–353 (1965)

    Article  MATH  Google Scholar 

  4. Rahmen, M.: The impact of social customer relationship management on operational per- formance in the service sector. J. Serv. Manage. Res. 6(1), 23–36 (2022). https://doi.org/10.1016/jsmr.2022.01.004

  5. Gurtu, A., Johny, J.: Supply chain risk management: literature review. Risks 9(1), 16 (2021)

    Article  Google Scholar 

  6. Karaali, F. Ç., & Ülengin, F.: Yapay Sinir Ağları ve bilişsel haritalar kullanılarak işsizlik oranı öngörü çalışması. İTÜ DERGİSİ/d, 7(3) (2008)

    Google Scholar 

  7. Axelrod, R. (ed.): Structure of Decision: The Cognitive Maps of Political Elites. Princeton University Press (2015)

    Google Scholar 

  8. Hugos, M.H.: Essentials of Supply Chain Management. Wiley (2018)

    Google Scholar 

  9. Dursun, M., Gumus, G.: Intuitionistic fuzzy cognitive map approach for the evaluation of supply chain configuration criteria. Math. Meth. Appl. Sci. 43(13), 7788–7801 (2020)

    Article  MathSciNet  Google Scholar 

  10. Singh A.R., Jain R., Mishra P.K.: Risk in Supply Chain Management, National Conference on Advances in Mechanical Engineering (2009)

    Google Scholar 

  11. Purnomo, M.R.A., Anugerah, A.R., Dewipramesti, B.T.: Sustainable supply chain management framework in a higher education laboratory using intuitionistic fuzzy cognitive map. J. Indust. Eng. Manage. 13(2), 417–429 (2020)

    Google Scholar 

  12. Rezaee, M.J., Yousefi, S., Valipour, M., Dehdar, M.M.: Risk analysis of sequential processes in food industry integrating multi-stage fuzzy cognitive map and process failure model and effects analysis. Comput. Ind. Eng. 123, 325–337 (2018)

    Article  Google Scholar 

  13. Rezaei Pandari, A., Azar, A.: A fuzzy cognitive mapping model for service supply chains performance. Meas. Bus. Excell. 21(4), 388–404 (2017)

    Article  Google Scholar 

  14. Xu, Z.: Intuitionistic fuzzy set theory: a survey and recent applications. Comput. Intell. Neurosci. 2017, 1–21 (2017)

    Google Scholar 

  15. Atanassov, K.: Intuitionistic fuzzy implications and Modus Ponens, Notes on Intuitionistic Fuzzy Sets, vol. 11, 2005, no. 1, 1–5. R. Feys, Modal logics. Gauthier-Villars, Paris (1965)

    Google Scholar 

  16. Torra, V.: Hesitant fuzzy sets. Int. J. Intell. Syst. 25(6), 529–539 (2010)

    MATH  Google Scholar 

  17. Nieto-Morote, A., Ruz-Vila, F.: A fuzzy approach to construction project risk assessment. Int. J. Project Manage. 29(2), 220–231 (2011)

    Article  MATH  Google Scholar 

  18. Užga-Rebrovs, O., Kuļešova, G.: Comparative analysis of fuzzy set defuzzification methods in the context of ecological risk assessment. Inform. Technol. Manage. Sci. 20(1), 25–29 (2017)

    Google Scholar 

  19. Mogharreban, N., Dilalla, L.F.: Comparison of defuzzification techniques for analysis of non-interval data. In: NAFIPS 2006–2006 Annual Meeting of the North American Fuzzy Information Processing Society, pp. 257–260 (2006)

    Google Scholar 

  20. Özesmi, U., Özesmi, S.L.: Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach. Ecol. Model. 176, 43–64 (2004)

    Article  Google Scholar 

  21. Ülengin, F., Işık, M., Ekici, ŞÖ., Özaydın, Ö., Kabak, Ö., Topçu, Y.İ: Policy developments for the reduction of climate change impacts by the transportation sector. Transp. Policy 61, 36–50 (2018)

    Article  Google Scholar 

  22. Li, J., Zhou, Y., Zhu, Q., Huang, W.: The impact of risk information sharing on supply chain financial performance: evidence from China. Sustainability 11(17), 4672 (2019)

    Google Scholar 

  23. Shokouhyar, S., Pahlevani, N., Mir Mohammad Sadeghi, F.: Scenario analysis of smart, sustainable supply chain on the basis of a fuzzy cognitive map. Manage. Res. Rev. 43(4), 463–496 (2019)

    Google Scholar 

  24. Wan, C., Yan, X., Zhang, D., Qu, Z., Yang, Z.: An advanced fuzzy Bayesian-based FMEA approach for assessing maritime supply chain risks. Transport. Res. Part E: Logist. Transport. Rev. 125, 222–240 (2019)

    Google Scholar 

  25. Korucuk, A., Memiş, S.: Investigating the effects of financial risk on supply chain risk. J. Account. Finan. Audit. Stud. 4(1), 55–68 (2018)

    Google Scholar 

  26. Abdel-Basset, M., Mohamed, R.: A novel plithogenic TOPSIS-CRITIC model for sustainable supply chain risk management. J. Clean. Prod. 247, 119586 (2020)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Istanbul-Cerrahpasa University, Istanbul, Turkey

    Hasibe Berfu Öztürk & Şule Önsel Ekici

Authors
  1. Hasibe Berfu Öztürk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Şule Önsel Ekici
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hasibe Berfu Öztürk .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Türkiye

    Cengiz Kahraman

  2. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Türkiye

    Irem Ucal Sari

  3. Department of Industrial Engineering, Istanbul Technical University, İstanbul, Türkiye

    Basar Oztaysi

  4. Department of Industrial Engineering, Yildiz Technical University, Istanbul, Türkiye

    Selcuk Cebi

  5. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Türkiye

    Sezi Cevik Onar

  6. Department of Industrial Engineering, Galatasaray University, Istanbul, Türkiye

    A. Çağrı Tolga

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Öztürk, H.B., Ekici, Ş.Ö. (2023). Evaluating the Impact of Risk Component in Supply Chain Management Using Intuitionistic Fuzzy Cognitive Map. In: Kahraman, C., Sari, I.U., Oztaysi, B., Cebi, S., Cevik Onar, S., Tolga, A.Ç. (eds) Intelligent and Fuzzy Systems. INFUS 2023. Lecture Notes in Networks and Systems, vol 759. Springer, Cham. https://doi.org/10.1007/978-3-031-39777-6_57

Download citation

Publish with us

Policies and ethics

Search

Navigation