Document Type : Research Paper

Authors

1 Master Graduate, department of business administration, faculty of financial science, management and entrepreneurship, university of Kashan, Kashan, Iran

2 Esmaeil Mazroui Nasrabadi assistant professor, department of business administration, faculty of financial science, management and entrepreneurship, university of Kashan, Kashan, Iran

Abstract

The supply chain of the food industry is crucial for countries, yet it is vulnerable to disruptions caused by natural disasters like floods, frost, and heatwaves, as well as operational shutdowns. These disruptions can trigger a ripple effect throughout the food supply chain, posing significant challenges for the country. Therefore, it is imperative to identify and analyze strategies to mitigate the ripple effect. This research has been conducted in two stages: qualitative and quantitative. The qualitative stage aimed to identify coping strategies, employing thematic analysis. The quantitative stage involved scenario modeling and analysis using fuzzy cognitive maps. The findings revealed 84 primary codes grouped into 21 sub-categories and 4 main categories: "Strategic Management," "Operations Management," "Compilation and Correct Implementation of Laws," and "Supply Chain Management." Analysis of backward scenarios underscored the importance of "supplier relationship management," "cooperation and coordination in the supply chain," and "contingency plans." Conversely, analysis of forward scenarios highlighted the significance of "monitoring environmental changes" and "strategic planning." Focusing on short-term plans, enhancing managers' decision-making and problem-solving skills, refining supplier selection criteria, optimizing supply network design with backup locations, and maintaining safety stock for critical goods are recommended actions for industry stakeholders.
Introduction
The growth of supply chains and their increasing interdependence raise concerns about vulnerability and the likelihood of supply chain failure (Kek et al., 2022). One significant contributor to supply chain failure is the propagation of disruption, commonly known as the ripple effect (Ghadge et al., 2022). The ripple effect exerts various negative impacts on the agricultural supply chain (Wei & Chen, 2010), with factors such as climate change exacerbating these effects on the agricultural sector and food supply chain (Galli et al., 2023). A prominent example of the ripple effect is the COVID-19 pandemic, which led to crises in the food supply chain, including human resource shortages, transportation disruptions, and input cost escalations (Waris et al., 2022). In Iran, the pandemic significantly disrupted the food supply chain, resulting in decreased profitability, sales rates, flexibility, and investment returns (Afzali and Zare Mehrjardi, 2020). Thus, investigating this issue in Iran's food supply is imperative. The objectives of the research are:

Identifying strategies to cope with the ripple effect in Iran's food product supply chain.
Presenting a fuzzy cognitive map of strategies to cope with the ripple effect in Iran's food product supply chain.
Conducting scenario analysis of strategies to cope with the ripple effect in Iran's food product supply chain.

Materials and Methods
This research adopts a mixed-method approach, comprising qualitative and quantitative stages. In the qualitative stage, participants include experts and managers with a minimum of 10 years of experience in the food processing supply chain, possessing academic qualifications, and experience with supply chain disruptions. The statistical population for the quantitative stage encompasses the participants from the qualitative stage, supplemented by university professors with publications in the field of supply chain ripple effects. Thematic analysis is employed in the qualitative part to analyze the data. Subsequently, based on the qualitative findings, a researcher-designed questionnaire is developed for the quantitative phase. The fuzzy cognitive map method is then utilized to analyze the quantitative data gathered.
Results
Semi-structured interviews were conducted with experts to identify strategies for coping with the ripple effect in Iran's food supply chain. From these interviews, 84 primary codes were identified, which were then organized into 21 sub-categories and 4 main categories: "strategic management," "operations management," "drafting and correct implementation of laws," and "supply chain management." Notably, nearly half of the obtained codes were attributed to the "supply chain management" category, indicating its significant importance in addressing the ripple effect. In the second stage of the research, a questionnaire was designed based on the findings of the previous stage and administered to 10 experts for completion. In this questionnaire, experts were asked to assess the importance of each of the 21 sub-categories. Subsequently, FCMapper software was employed to construct a fuzzy cognitive map depicting coping strategies.
Table 1: Analysis of strategies to cope with the ripple effect




Type


Centrality


Outdegree


Indegree


Strategy


Total Components






ordinary


17٫29


5٫73


11٫56


1


21




ordinary


12٫3


2٫45


9٫85


2


Total Connections




driver


10٫11


10٫11


0


3


191




ordinary


11٫12


8٫97


2٫15


4


Density




receiver


9٫64


0


9٫64


5


0.45




ordinary


8٫28


2٫98


5٫3


6


Connections per Component




ordinary


16٫91


4٫87


12٫04


7


9.09




ordinary


10٫27


8٫91


1٫36


8


Number of Driver Components




ordinary


17٫64


6٫91


10٫73


9


3




ordinary


10٫58


6٫43


4٫15


10


Number of Receiver Components




ordinary


5٫19


2٫55


2٫64


11


1




driver


5٫81


5٫81


0


12


Number of Ordinary Components




driver


8٫9


8٫9


0


13


17




ordinary


16٫33


6٫33


10


14


Complexity Score




ordinary


16٫39


7٫37


9٫02


15


0.33




ordinary


8٫89


7٫64


1٫25


16




ordinary


15٫81


6٫36


9٫45


17




ordinary


14٫18


4٫84


9٫34


18




ordinary


11٫64


4٫19


7٫45


19




ordinary


4٫72


3٫26


1٫46


20




ordinary


11٫48


7٫13


4٫35


21




As shown in Table 1, 'Environmental change monitoring,' 'Strategic planning,' and 'Technology upgrade' strategies have the highest degree of effectiveness, while 'Inventory management,' 'Contingency programs,' and 'Production flexibility' strategies also exhibit high effectiveness. Furthermore, 'Production flexibility,' 'Contingency plans,' and 'Inventory management' demonstrate the highest degree of centrality. Figure 1 depicts the fuzzy cognitive mapping of strategies to cope with the ripple effect in the supply chain of Iran's food products.
Figure 1: Fuzzy cognitive mapping of strategies to cope with the ripple effect
 
To examine the scenarios, three backward and three forward scenarios were designed. In the backward scenario, the most effective variables were selected.
 
 
Figure 2: The first backward scenario of coping strategies




Cooperation and Coordination








Supplier Relationship Management








Contingency Planning








Inventory Management




Figure 3: Second backward scenario of coping strategies




Supplier Relationship Management








Cooperation and Coordination








Contingency Planning




Figure 4: The third scenario backward coping strategies




Cooperation and Coordination








Supplier Relationship Management








Contingency Planning








Production Flexibility




Figure 5: Overlap of the backward scenarios of coping strategies




Cooperation and Coordination
 








Supplier Relationship Management
 








Production Flexibility
 








Contingency Planning
 








Inventory Management
 




To draw forward scenarios, strategies No. 3, 4, and 8, which represent 'monitoring environmental changes,' 'strategic program,' and 'technology improvement,' respectively, were selected.
Figure 6: First forward scenario of coping strategies




Multi-Skilled Workforce








Short Term Planning








HRM








Technology Upgrade








Monitoring Environmental Changes




 Figure 7: Second forward scenario of coping strategies




HRM








Multi-skilled Workforce








Short Term Planning
 








Horizontal Integration








Strategic Planning




 
 
Figure 8: The third forward scenario of coping strategies




Multi-Skilled Workforce
 








Short Term Planning








HRM








Technology Upgrade




 
 
Figure 9: Overlap of the forward scenario of coping strategies




Multi-skilled Workforce
 








Short Term Planning
 








HRM








Technology Upgrade
 








Monitoring Environmental changes
 








Horizontal Integration








Strategic Planning




Conclusions
Food product supply chain managers should consider long-term factors, price flexibility, and contract support clauses in contracts with suppliers. For foreign products, it is recommended to contract with companies that have active agencies in the country, as other companies may quickly cease their services due to new sanctions. The purchase of critical parts of the supply chain, known as vertical integration, is recommended to reduce risk. Contingency plans are necessary to cope with the ripple effect, but to develop suitable contingency plans, environmental and political issues must be carefully monitored. As a result, it is necessary to create management teams in food products to investigate environmental issues.

Keywords

Main Subjects

  1. Angkiriwang, R., Pujawan, I. N., & Santosa, B (2014). Managing uncertainty through supply chain flexibility: reactive vs. proactive approaches. Production & Manufacturing Research2(1), 50-70.‏ https://doi.org/10.1080/21693277.2014.882804
  2. Bamakan, S. M. H., Malekinejad, P., Ziaeian, M., & Motavali, A. (2021). Bullwhip effect reduction map for COVID-19 vaccine supply chain. Sustainable Operations and Computers, 2, 139-148.‏ https://doi.org/10.1016/j.susoc.2021.07.001
  3. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative research in psychology, 3(2), 77-101.‏ http://dx.doi.org/10.1191/1478088706qp063oa
  4. Chopra, Sunil; & Meindl, Peter. (2017). Supply Chain Management: Strategy, Planning, and Operation. Boston, Mass., Pearson. https://www.pearson.com
  5. Dolgui, A., Ivanov, D., & Sokolov, B (2018). Ripple effect in the supply chain: an analysis and recent literature. International Journal of Production Research56(1-2), 414-430. https://doi.org/10.1080/00207543.2017.1387680
  6. Durach, C. F., Wieland, A., & Machuca, J. A. (2015). Antecedents and dimensions of supply chain robustness: a systematic literature review. International Journal of Physical Distribution & Logistics Management, 45(1/2), 118-137.‏ https://doi.org/10.1108/IJPDLM-05-2013-0133
  7. Ebbrecht, G., & Chen, J (2023). Enhancing equitable resilience of urban energy systems via strategic planning of EV charging infrastructure. The Electricity Journal36(5), 107275.‏ https://doi.org/10.1016/j.tej.2023.107275
  8. Galli, N., Govoni, C., & Rulli, M. C. (2023). Assessing food security disruptions in the aftermath of extreme events. Authorea. https://doi.org/10.22541/essoar.167751603.31304821/v1
  9. Ghadge, A., Er, M., Ivanov, D., & Chaudhuri, A. (2022). Visualisation of ripple effect in supply chains under long-term, simultaneous disruptions: a system dynamics approach. International Journal of Production Research60(20), 6173-6186.‏ https://doi.org/10.1080/00207543.2021.1987547
  10. Giannoccaro, I., & Iftikhar, A. (2022). Mitigating ripple effect in supply networks: the effect of trust and topology on resilience. International Journal of Production Research60(4), 1178-1195.‏ https://doi.org/10.1080/00207543.2020.1853844
  11. Hassanzadeh Rad, M (2008). Lead Time Reduction Case study: BEAB etikett & system AB.‏ University of Borås, School of Engineering (master thesis). http://hb.diva-portal.org/smash/record.jsf?pid=diva2:1310771
  12. Ivanov, D (2017). Simulation-based ripple effect modelling in the supply chain. International Journal of Production Research, 55(7), 2083-2101.‏ https://doi.org/10.1080/00207543.2016.1275873
  13. Ivanov, D. Dolgui, A. Sokolov, B. & Ivanova, M. (2017). Literature review on disruption recovery in the supply chain. International Journal of Production Research55(20), 6158-6174.‏ http://dx.doi.org/10.1080/00207543.2017.1330572
  14. Ivanov, D., & Dolgui, A. (2019). New disruption risk management perspectives in supply chains: Digital twins, the ripple effect, and resileanness. IFAC-PapersOnLine52(13), 337-342.‏ https://doi.org/10.1016/j.ifacol.2019.11.138
  15. Ivanov, D., Sokolov, B., Solovyeva, I., Dolgui, A., & Jie, F. (2015a). Ripple effect in the time-critical food supply chains and recovery policies. IFAC-PapersOnLine48(3), 1682-1687.‏ https://doi.org/10.1016/j.ifacol.2015.06.328
  16. Ivanov, D., Dolgui, A., & Sokolov, B (2015b). Supply chain design with disruption considerations: Review of research streams on the ripple effect in the supply chain. IFAC-PapersOnLine48(3), 1700-1707.‏ https://doi.org/10.1016/j.ifacol.2015.06.331
  17. Ivanov, D., Dolgui, A., & Sokolov, B. (2019). Ripple effect in the supply chain: Definitions, frameworks and future research perspectives. Handbook of ripple effects in the supply chain, 1-33.‏ http://dx.doi.org/10.1007/978-3-030-14302-2_1
  18. Ivanov, D., Sokolov, B., & Dolgui, A (2014). The Ripple effect in supply chains: trade-off ‘efficiency-flexibility-resilience’in disruption management. International Journal of Production Research, 52(7), 2154-2172.‏ https://doi.org/10.1080/00207543.2013.858836
  19. Ivanov, D., Sokolov, B., Solovyeva, I., Dolgui, A., & Jie, F. (2015 b). Ripple effect in the time-critical food supply chains and recovery policies. IFAC-PapersOnLine, 48(3), 1682-1687.‏‏ https://doi.org/10.1016/j.ifacol.2015.06.328
  20. KEk, V., Nadeem, S. P., Ravichandran, M., Ethirajan, M., & Kandasamy, J. (2022). Resilience strategies to recover from the cascading ripple effect in a copper supply chain through project management. Operations Management Research15(1-2), 440-460.‏ https://doi.org/10.1007/s12063-021-00231-x
  21. Li, Y., Chen, K., Collignon, S., & Ivanov, D. (2021). Ripple effect in the supply chain network: Forward and backward disruption propagation, network health and firm vulnerability. European Journal of Operational Research291(3), 1117-1131.‏ https://doi.org/10.1016%2Fj.ejor.2020.09.053
  22. Monostori, J. (2021). Mitigation of the ripple effect in supply chains: Balancing the aspects of robustness, complexity and efficiency. CIRP Journal of Manufacturing Science and Technology32, 370-381.‏ https://doi.org/10.1016/j.cirpj.2021.01.013
  23. Özçelik, G., Faruk Yılmaz, Ö., & Betül Yeni, F. (2021). Robust optimisation for ripple effect on reverse supply chain: an industrial case study. International Journal of Production Research59(1), 245-264.‏ https://doi.org/10.1080/00207543.2020.1740348
  24. Özçelik, G., Yeni, F. B., Gürsoy Yılmaz, B., & YILMAZ, Ö. F. (2022). Achieving Medical Supply Chain Resiliency in Case of the Ripple Effect: A Bi-Objective Robust Optimization Model and an Exact Solution Method. Available at SSRN 4129641.‏ https://doi.org/10.2139/ssrn.4129641
  25. Palma, F., Saucedo, J. A., & Marmolejo, J. A. (2018, October). Recovery Method of Supply Chain Under Ripple Effect: Supply Chain Event Management (SCEM) Application. In International Conference on Intelligent Computing & Optimization (pp. 455-465). Springer, Cham.‏ http://dx.doi.org/10.1007/978-3-030-00979-3_48
  26. Radulović, D., & Radulović, S (2022). Teleworking and International Legal and Economic Framework for Building Resilience. Journal of Entrepreneurship and Business Resilience5(1), 49-63.‏ https://jebr.fimek.edu.rs/index.php/jebr/article/view/10/6
  27. Rodriguez-Repiso, L., Setchi, R., & Salmeron, J. L. (2007). Modelling IT projects success with fuzzy cognitive maps. Expert systems with applications, 32(2), 543-559. http://dx.doi.org/10.1016/j.eswa.2006.01.032
  28. Scarpin, M. R. S., Scarpin, J. E., Musial, N. T. K., & Nakamura, W. T. (2022). The implications of COVID-19: Bullwhip and ripple effects in global supply chains. International Journal of Production Economics251, 108523.‏ http://dx.doi.org/10.1016/j.ijpe.2022.108523
  29. Simangunsong, E., Hendry, L. C., & Stevenson, M (2012). Supply-chain uncertainty: a review and theoretical foundation for future research. International Journal of Production Research, 50(16), 4493-4523.‏ https://doi.org/10.1080/00207543.2011.613864
  30. Waris, A., Jangaiah, B., & Harish, J. (2022). Constraints Faced by Farmers due to COVID-19 Disruptions on Agricultural Activities in Nalgonda District of Telangana, India. International Journal of Environment and Climate Change12(10), 688-695.‏ https://doi.org/10.9734/ijecc/2022/v12i1030851
  31. Wei, L., & Chen, H. (2010, October). The ripple effect of natural disaster on the agricultural industry chain. In 2010 International Conference on Management of e-Commerce and e-Government(pp. 85-89). IEEE.‏ https://doi.org/10.1109/ICMeCG.2010.25
  32. Afzali, Z., & zare Nehrjerdi, M. (2021). Investigating the Impact of Corona on the Decline of Agricultural Cooperatives Business. Journal of International Business Administration4(3), 91-103. doi: 10.22034/jiba.2021.45467.1681.. doi: 10.22034/jiba.2021.45467.1681(In Persian)
  33. Mazroui Nasrabadi, E., Habibirad, A., & Shoul, A. (2023). Presenting a Model of Critical Success Factors to Cope with the Ripple Effect in Iran's Machine-Made Carpet Supply Chain: Corona Pandemic Effects. Journal of Industrial Management Perspective13(Issue 1, Spring 2023), 199-217. doi: 10.48308/jimp.13.1.199 . doi: 10.52547/jimp.13.1.199(In Persian)