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Evaluating the Vulnerability of Forestry Supply Chains Through Fuzzy Cognitive Map

Yıl 2025, Cilt: 11 Sayı: 1, 30 - 41, 17.06.2025

Mirac Murat , Ertuğrul Ayyıldız , Umut Asan

https://doi.org/10.33904/ejfe.1517968

Öz

It is crucial to address the significant role of the supply chain in economic activity and its vulnerable areas. This research focuses on the forestry industry, where obtaining and maintaining the primary raw material source is notably more challenging than other supply chains. The primary objective of this study is to analyze vulnerability factors specific to the forestry supply chain (FSC) by modeling their interactions and potential influences on each other. Initially, relevant factors were defined through a comprehensive literature review, encompassing vulnerabilities both in the general supply chain and pertinent to the forestry industry, such as natural disruptions. Then, the relationships between these factors were modeled and simulated using an input-sensitive fuzzy cognitive map (FCM). A cognitive map was constructed based on expert opinions, facilitated by triangular fuzzy numbers to express expert judgments accurately. FCM simulations using a new reasoning mechanism were conducted to analyze the effects of FSC vulnerability factors on one another across three sustainability-themed scenarios: economically related vulnerabilities, socially related vulnerabilities, and environmentally related vulnerabilities. Supply chain structure, government support, and source availability were the main vulnerability factors influencing the overall resilience of the FSC. Environmental stressors such as natural disturbances and climate change, and economic shocks, were found to significantly impact FSC dynamics, highlighting the need for adaptive strategies and robust contingency planning. This research is significant for stakeholders in the forestry industry as it elucidates the vulnerability factors within the FSC and demonstrates how different vulnerabilities can influence one another.

Anahtar Kelimeler

Forestry supply chain sustainable forestry supply chain vulnerability scenario analysis triangular fuzzy numbers fuzzy cognitive mapping

Kaynakça

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  • Dashtpeyma, M., Ghodsi, R. 2021. Forest Biomass and Bioenergy Supply Chain Resilience: A Systematic Literature Review on the Barriers and Enablers. Sustainability, 3(12):6964. https://doi.org/10.3390/ SU13126964.
  • Dechprom, S., Jermsittiparsert, K. 2019. Sustainability Related Supply Chain Risks: A Case of Multiple Organizational Strategic Networks. International Journal of Innovation, Creativity and Change, 5(2):769–785.
  • Deshpande, S., Hudnurkar, M., Rathod, U. 2023. An exploratory study into manufacturing supply chain vulnerability and its drivers. Benchmarking, 30(1):23–49. https://doi.org/10.1108/BIJ-04-2021-0233/FULL/PDF.
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  • Elias, A.A., Donadelli, F., Paiva, E.L., Bacic Araujo, P.P. 2021. Analysing the complexities of sustainable wood supply chain in the Amazon: a systems thinking approach. International Journal of Logistics Management, 32(4):1481–1505. https://doi.org/10. 1108/IJLM-07-20200276/FULL/PDF.
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Yıl 2025, Cilt: 11 Sayı: 1, 30 - 41, 17.06.2025

Mirac Murat , Ertuğrul Ayyıldız , Umut Asan

https://doi.org/10.33904/ejfe.1517968

Öz

Kaynakça

  • Acuna, M., Sessions, J., Zamora, R., Boston, K., Brown, M., Ghaffariyan, M.R. 2019. Methods to Manage and Optimize Forest Biomass Supply Chains: a Review. Current Forestry Reports, 5(3):124–141. https:// doi.org/10.1007/s40725-019-00093-4.
  • Asan, U., Kadaifçi, Ç. 2020. A new product positioning approach based on fuzzy cognitive mapping. Journal of the Faculty of Engineering and Architecture of Gazi University, 35(2):1047–1061.
  • Barnett, J. 2018. Addressing policy challenges to woody biopower production: Social acceptance, biomass certification and limited policy support. Open Access Dissertation, Michigan Technological University, Department of Social Sciences, Michigan.
  • Bueno, S., Salmeron, J.L. 2009. Benchmarking main activation functions in fuzzy cognitive maps. Expert Systems with Applications, 36(3):5221–5229. https://doi.org/10.1016/j.eswa.2008.06.072.
  • Cambero, C., Sowlati, T. 2016. Incorporating social benefits in multi-objective optimization of forest-based bioenergy and biofuel supply chains. Applied Energy, 178:721–735. https://doi.org/10.1016/j.apen ergy. 2016.06.079.
  • Chen, J., Wang, L., Li, L., Magalhães, J., Song, W., Lu, W., Xiong, L., Chang, W.Y., Sun, Y. 2020. Effect of forest certification on international trade in forest products. Forests, 11(12):1270. https://doi.org/10. 3390/ f11121270.
  • Curtis, P.G., Slay, C.M., Harris, N.L., Tyukavina, A., Hansen, M.C. 2018. Classifying drivers of global forest loss. Science, 361(6407). https://doi.org/ 10.1126/science.aau3445.
  • Dashtpeyma, M., Ghodsi, R. 2021. Forest Biomass and Bioenergy Supply Chain Resilience: A Systematic Literature Review on the Barriers and Enablers. Sustainability, 3(12):6964. https://doi.org/10.3390/ SU13126964.
  • Dechprom, S., Jermsittiparsert, K. 2019. Sustainability Related Supply Chain Risks: A Case of Multiple Organizational Strategic Networks. International Journal of Innovation, Creativity and Change, 5(2):769–785.
  • Deshpande, S., Hudnurkar, M., Rathod, U. 2023. An exploratory study into manufacturing supply chain vulnerability and its drivers. Benchmarking, 30(1):23–49. https://doi.org/10.1108/BIJ-04-2021-0233/FULL/PDF.
  • Dubey, R., Bryde, D.J., Dwivedi, Y.K., Graham, G., Foropon, C., Papadopoulos, T. 2023. Dynamic digital capabilities and supply chain resilience: The role of government effectiveness. International Journal of Production Economics, 258:108790. https://doi.org/10.1016/J.IJPE.2023.108790.
  • Dursun, M., Goker, N., Gumus, G. 2019. Evaluation of supply chain configuration criteria using fuzzy cognitive map, in: AIP Conference Proceedings. American Institute of Physics Inc., Rhodes, p. 2116. https://doi.org/10.1063/1.5114530/754221.
  • Elias, A.A., Donadelli, F., Paiva, E.L., Bacic Araujo, P.P. 2021. Analysing the complexities of sustainable wood supply chain in the Amazon: a systems thinking approach. International Journal of Logistics Management, 32(4):1481–1505. https://doi.org/10. 1108/IJLM-07-20200276/FULL/PDF.
  • Elleuch, H., Dafaoui, E., Elmhamedi, A., Chabchoub, H. 2016. Resilience and Vulnerability in Supply Chain: Literature review. IFAC-PapersOnLine, 49(12):1448–1453. https://doi.org/10.1016/J.IFACOL .2016.07. 775.
  • Feng, Y., Audy, J.F.,2021. Forestry 4.0: A framework for the forest supply chain toward industry 4.0. Gestao e Producao, 27(4). https://doi.org/10.1590/0104-530X5677-20.
  • Frias, M., Filiberto, Y., Nápoles, G., García-Socarrás, Y., Vanhoof, K., Bello, R. 2018. Fuzzy cognitive maps reasoning with words based on triangular fuzzy numbers, in: Castro, F., Miranda-Jiménez, S., González-Mendoza, M. (Eds.), Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, pp. 197–207. https://doi.org/10.1007/978-3-030-02837-4_16/FIG URES/5.
  • Garrett, R.D., Levy, S.A., Gollnow, F., Hodel, L., Rueda, X. 2021. Have food supply chain policies improved forest conservation and rural livelihoods? A systematic review. Environmental Research Letters, 16(3):033002. https://doi.org/10.1088/1748-9326/abe0ed.
  • Gavrilut, I., Halalisan, A.F., Giurca, A., Sotirov, M. 2016. The interaction between FSC certification and the implementation of the EU timber regulation in Romania. Forests, 7(1):3. https://doi.org/10.3390/ f7010003.
  • Gomes, L. de C. 2022. Mitigation of Supply Chain Vulnerability Through Collaborative Planning, Forecasting, and Replenishment (CPFR), in: Khojasteh, Y., Xu, H.,, Zolfaghari, S. (Eds.), International Series in Operations Research and Management Science. Springer, Cham. https:// doi.org/10.1007/978-3-031-09183-4_5.
  • Greenslade, C., Murphy, R.J., Morse, S., Griffiths, G.H. 2021. Breaking Down the Barriers: Exploring the Role of Collaboration in the Forestry Sector of South East England. Sustainability, 13(18):10258. https://doi.org/10.3390/SU131810258.
  • He, Z., Turner, P. 2021. A Systematic Review on Technologies and Industry 4.0 in the Forest Supply Chain: A Framework Identifying Challenges and Opportunities. Logistics, 5(4):88. https://doi.org/ 10.3390/logistics5040088.
  • Hoffmann, S., Jaeger, D., Shuirong, W. 2018. Adapting chinese forest operations to socio-economic developments: What is the potential of plantations for strengthening domestic wood supply? Sustainability, 10(4):1042. https://doi.org/10.3390/su10041042.
  • Irvanizam, I., Rusdiana, S., Amrusi, A., Arifah, P., Usman, T. 2018. An application of fuzzy multiple-attribute decision making model based onsimple additive weighting with triangular fuzzy numbers to distribute the decenthomes for impoverished families. Journal of Physics: Conference Series, 1116(2): 022016. https://doi.org/10.1088/1742-6596/1116/2/ 022016.
  • Ivanov, D. 2017. Simulation-based single vs. dual sourcing analysis in the supply chain with consideration of capacity disruptions, big data and demand patterns. International Journal of Integrated Supply Management, 11(1):24–43. https://doi.org/ 10.1504/IJISM.2017.083005.
  • Ivanov, D., Sokolov, B. 2019. Simultaneous structural–operational control of supply chain dynamics and resilience. Annals of Operations Research, 283(1–2). https://doi.org/10.1007/s10479-019-03231-0.
  • Jüttner, U., Peck, H., Christopher, M. 2003. Supply chain risk management: outlining an agenda for future research. International Journal of Logistics: Research and Applications, 6(4):197–210. https:// doi.org/ 10.1080/13675560310001627016.
  • Korhonen, J., Honkasalo, A., Seppälä, J. 2018. Circular Economy: The Concept and its Limitations. Ecological Economics, 143. https://doi.org/10.1016/ j.ecolecon.2017.06.041.
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  • Ramage, M.H., Burridge, H., Busse-Wicher, M., Fereday, G., Reynolds, T., Shah, D.U., Wu, G., Yu, L., Fleming, P., Densley-Tingley, D., Allwood, J., Dupree, P., Linden, P.F., Scherman, O. 2017. The wood from the trees: The use of timber in construction. Renewable and Sustainable Energy Reviews, 68:333–359. https://doi.org/10.1016/ j.rser.2016.09.107.
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  • riangular fuzzy number representation of relations in Fuzzy Cognitive Maps, in: IEEE International Conference on Fuzzy Systems. Beijing, pp. 1021–1028. https://doi.org/10.1109/FUZZ-IEEE.2014.6891653.
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Toplam 66 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Bilgi Sistemleri (Diğer)
Bölüm Research Articles
Yazarlar

Mirac Murat 0000-0001-9980-9608

Ertuğrul Ayyıldız 0000-0002-6358-7860

Umut Asan 0000-0002-0838-1421

Erken Görünüm Tarihi 21 Mart 2025
Yayımlanma Tarihi 17 Haziran 2025
Gönderilme Tarihi 18 Temmuz 2024
Kabul Tarihi 24 Eylül 2024
Yayımlandığı Sayı Yıl 2025 Cilt: 11 Sayı: 1

Kaynak Göster

APA Murat, M., Ayyıldız, E., & Asan, U. (2025). Evaluating the Vulnerability of Forestry Supply Chains Through Fuzzy Cognitive Map. European Journal of Forest Engineering, 11(1), 30-41. https://doi.org/10.33904/ejfe.1517968
 Kapak Resmi İndir

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