Agro-Food Supply Chain Risk Assessment: A Review Based on Technique and Approach
DOI:
https://doi.org/10.37385/jaets.v5i2.3688Keywords:
Supply Chain Risk, Risk Assessment, Agro-Food, Technique and Approaches, Literature ReviewAbstract
Risk assessment in agro-food supply chains is crucial in managing the complexity and uncertainty associated with food product production, distribution, and consumption. This study aims to classify risks and mapping techniques or approaches used in risk assessment of agro-food product supply chains. Mapping technique or approaches to risk assessment of agro-food supply chains was carried out based on the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) framework, which consists of several stages of identification, screening eligibility, and inclusion, resulting in a total of 72 relevant journal articles. They were selected from 58 different journals with high-impact factors and rankings. The literature review results show that agro-food's supply chain risk classification has much to do with risk assessment: macro-level risk, operational risk outside the company, and internal risk. Furthermore, the most studied agro-food products are general food (44%), horticultural products (28%), meat products (11%), dairy products (10%), fishery products (6%) and bread products (1%). The techniques and approaches most widely used in assessing the risk of the agro-food supply chain are semi-quantitative (49.3%), quantitative (31.5%), mixed (12.3%), and qualitative (6.9%). A better knowledge of the topic being addressed in the research community is sped up by identifying these techniques and approaches since the literature on supply chain risk management for agro-food is voluminous, complicated, and challenging to grasp.
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Abdel-Basset, M., Gunasekaran, M., Mohamed, M., & Chilamkurti, N. (2019). A framework for risk assessment, management and evaluation: Economic tool for quantifying risks in supply chain. Future Generation Computer Systems, 90(1), 489–502. https://doi.org/10.1016/j.future.2018.08.035
Alabi, M. O., & Ngwenyama, O. (2023). Food security and disruptions of the global food supply chains during COVID-19: building smarter food supply chains for post COVID-19 era. British Food Journal, 125(1), 167–185. https://doi.org/10.1108/BFJ-03-2021-0333
Anugerah, A. R., Ahmad, S. A., Samin, R., Samdin, Z., & Kamaruddin, N. (2022). Modified failure mode and effect analysis to mitigate sustainable related risk in the palm oil supply chain. Advances in Materials and Processing Technologies, 8(2), 2229–2243. https://doi.org/10.1080/2374068X.2021.1898180
Asfaw, D., Black, E., Brown, M., Jane Nicklin, K., Otu-Larbi, F., Pinnington, E., Challinor, A., Maidment, R., & Quaife, T. (2018). TAMSAT-ALERT v1: A new framework for agricultural decision support. Geoscientific Model Development, 11(6), 2353–2371. https://doi.org/10.5194/gmd-11-2353-2018
Asrol, M., Marimin, Machfud, Yani, M., & Taira, E. (2021). Risk management for improving supply chain performance of sugarcane agroindustry. Industrial Engineering and Management Systems, 20(1), 9–26. https://doi.org/10.7232/iems.2021.20.1.9
Assefa, T. T., Meuwissen, M. P. M., & Oude Lansink, A. G. J. M. (2017). Price risk perceptions and management strategies in selected European food supply chains: An exploratory approach. NJAS - Wageningen Journal of Life Sciences, 80, 15–26. https://doi.org/10.1016/j.njas.2016.11.002
Azizsafaei, M., Hosseinian-Far, A., Khandan, R., Sarwar, D., & Daneshkhah, A. (2022). Assessing Risks in Dairy Supply Chain Systems: A System Dynamics Approach. Systems, 10(4). https://doi.org/10.3390/systems10040114
Azmi, F. R., Musa, H., Chew, B. C., & Jagiripu, I. P. (2021). Supply risk management: A case study of halal food industry in Malaysia. Uncertain Supply Chain Management, 9(2), 501–512. https://doi.org/10.5267/j.uscm.2021.1.001
Bai, L., Shi, C., Guo, Y., Du, Q., & Huang, Y. (2018). Quality Risk Evaluation of the Food Supply Chain Using a Fuzzy Comprehensive Evaluation Model and Failure Mode, Effects, and Criticality Analysis. Journal of Food Quality, 2018. https://doi.org/10.1155/2018/2637075
Baihaqi, A., Sofiana, U., Usman, M., & Bagio, B. (2021). Risk analysis of arabica coffee supply chain in Aceh Tengah regency, Aceh Province, Indonesia. Coffee Science, 16. https://doi.org/10.25186/.v16i.1984
Barbosa, M. W. (2021). Uncovering research streams on agri-food supply chain management: A bibliometric study. Global Food Security, 28. https://doi.org/10.1016/j.gfs.2021.100517
Baron, P., & Frattaroli, S. (2016). Awareness and perceptions of food safety risks and risk management in poultry production and slaughter: A qualitative study of direct-market poultry producers in Maryland. PLoS ONE, 11(6). https://doi.org/10.1371/journal.pone.0158412
Behzadi, G., O’Sullivan, M. J., Olsen, T. L., & Zhang, A. (2018a). Agribusiness supply chain risk management: A review of quantitative decision models. Omega (United Kingdom), 79, 21–42. https://doi.org/10.1016/j.omega.2017.07.005
Behzadi, G., O’Sullivan, M. J., Olsen, T. L., & Zhang, A. (2018b). Allocation flexibility for agribusiness supply chains under market demand disruption. International Journal of Production Research, 56(10), 3524–3546. https://doi.org/10.1080/00207543.2017.1349955
Benabdallah, C., El-Amraoui, A., Delmotte, F., & Frikha, A. (2022). Evaluation on Risks of Sustainable Supply Chain Based on Integrated Rough DEMATEL in Tunisian Dairy Industry. International Journal of Supply and Operations Management, 9(3), 338–359. https://doi.org/10.22034/ijsom.2021.109143.2205
Bhagat, D., & Dhar, U. R. (2011). Agriculture Supply Chain Management: A Review. IUP Journal of Supply Chain Management, 8(3), 7–25.
Bintara, R., Yadiati, W., Zarkasyi, M. W., & Tanzil, N. D. (2023). Management of Green Competitive Advantage: A Systematic Literature Review and Research Agenda. Economies, 11(2). https://doi.org/10.3390/economies11020066
Brosas, M. E., Kilantang, M. A., Li, N. B., Ocampo, L., Promentilla, M. A., & Yu, K. D. (2017). Novel approach for manufacturing supply chain risk analysis using fuzzy supply inoperability input-output model. Manufacturing Letters, 12, 1–5. https://doi.org/10.1016/j.mfglet.2017.03.001
Brusa, V., Costa, M., Padola, N. L., Etcheverría, A., Sampedro, F., Fernandez, P. S., Leotta, G. A., & Signorini, M. L. (2020). Quantitative risk assessment of haemolytic uremic syndrome associated with beef consumption in Argentina. PLoS ONE, 15(11 November). https://doi.org/10.1371/journal.pone.0242317
Cao, S., Bryceson, K., & Hine, D. (2019). An Ontology-based Bayesian network modelling for supply chain risk propagation. Industrial Management and Data Systems, 119(8), 1691–1711. https://doi.org/10.1108/IMDS-01-2019-0032
Chaudhuri, A., Srivastava, S. K., Srivastava, R. K., & Parveen, Z. (2016). Risk propagation and its impact on performance in food processing supply chain: A fuzzy interpretive structural modeling based approach. Journal of Modelling in Management, 11(2), 660–693. https://doi.org/10.1108/JM2-08-2014-0065
Chen, S., Brahma, S., Mackay, J., Cao, C., & Aliakbarian, B. (2020). The role of smart packaging system in food supply chain. Journal of Food Science, 85(3), 517–525. https://doi.org/10.1111/1750-3841.15046
Christopher, M., & Peck, H. (2004). Building The Resilient Supply Chain. International Journal OfLogistics Management, 15(2), 1–13.
Costa, C., Antonucci, F., Pallottino, F., Aguzzi, J., Sarriá, D., & Menesatti, P. (2013). A Review on Agri-food Supply Chain Traceability by Means of RFID Technology. Food and Bioprocess Technology, 6(2), 353–366. https://doi.org/10.1007/s11947-012-0958-7
Cui, Y., & Basnet, C. (2015). An exploratory study of supply chain risk management in the New Zealand fast food industry. Int. J. Logistics Systems and Management, 20(2), 199–215. https://doi.org/https://doi.org/10.1504/IJLSM.2015.067256
Diabat, A., Govindan, K., & Panicker, V. V. (2012). Supply chain risk management and its mitigation in a food industry. International Journal of Production Research, 50(11), 3039–3050. https://doi.org/10.1080/00207543.2011.588619
Duret, S., Hoang, H. M., Derens-Bertheau, E., Delahaye, A., Laguerre, O., & Guillier, L. (2019). Combining Quantitative Risk Assessment of Human Health, Food Waste, and Energy Consumption: The Next Step in the Development of the Food Cold Chain? Risk Analysis, 39(4), 906–925. https://doi.org/10.1111/risa.13199
Ennouri, W. (2013). Risks Management: New-Literature Review. Polish Journal of Management Studies, 8(1), 288–297.
Enyinda, C. I., & Mbah, C. H. (2017). Quantifying Sources of Risk in Global Food Operations and Supply Chain. Thunderbird International Business Review, 59(6), 653–661. https://doi.org/10.1002/tie.21842
Fingerman, S. (2006). Web of Science and Scopus: Current features and Capabilities. Issues in Science and Technology Librarianship, 48. https://doi.org/https://doi.org/10.29173/istl2081
Garvey, M. D., Carnovale, S., & Yeniyurt, S. (2015). An analytical framework for supply network risk propagation: A Bayesian network approach. European Journal of Operational Research, 243(2), 618–627. https://doi.org/10.1016/j.ejor.2014.10.034
Ge, H., Nolan, J., & Gray, R. (2015). Identifying strategies to mitigate handling risks in the canadian grain supply chain. Canadian Journal of Agricultural Economics, 63(1), 101–128. https://doi.org/10.1111/cjag.12039
Ghadge, A., Dani, S., & Kalawksy, R. (2012). Supply Chain Risk Management: Present and Future Scope Purpose. International Journal of Logistics Management, 23(3), 313–339.
Giannakis, M., & Louis, M. (2011). A multi-agent based framework for supply chain risk management. Journal of Purchasing and Supply Management, 17(1), 23–31. https://doi.org/10.1016/j.pursup.2010.05.001
Guan, G. F., Dong, Q. L., & Li, C. H. (2011). Risk identification and evaluation research on F-AHP evaluation based supply chain. 2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management, IE and EM 2011, PART 3, 1513–1517. https://doi.org/10.1109/ICIEEM.2011.6035447
Halim, Z. (2010, January 9). Literature Review and Future Directions in SCM Research. Proceedings of the 2010 International Conference on Industrial Engineering and Operations Management.
Han, Y., Cui, S., Geng, Z., Chu, C., Chen, K., & Wang, Y. (2019). Food quality and safety risk assessment using a novel HMM method based on GRA. Food Control, 105, 180–189. https://doi.org/10.1016/j.foodcont.2019.05.039
Heinzova, R., Vichova, K., Peterek, K., & Strohmandl, J. (2022). Supply Chain Risk Management In Dairy Industry Of The Czech Republic. Acta Logistica, 9(4), 441–448. https://doi.org/10.22306/al.v9i4.343
Hidayat, S., & Marimin, M. (2014). Agent Based Modeling for Investment and Operational Risk Considerations in Palm Oil Supply Chain. International Journal of Supply Chain Management, 20(10), 1–7. https://doi.org/10.1109/ICACSIS.2014.7065841
Horr, T., & Pradhan, A. K. (2020). Evaluation of public health risk for Escherichia coli O157:H7 in cilantro. Food Research International, 136. https://doi.org/10.1016/j.foodres.2020.109545
Imbiri, S., Rameezdeen, R., Chileshe, N., & Statsenko, L. (2021). A novel taxonomy for risks in agribusiness supply chains: A systematic literature review. Sustainability (Switzerland), 13(16). https://doi.org/10.3390/su13169217
Jianying, F., Bianyu, Y., Xin, L., Dong, T., & Weisong, M. (2021). Evaluation on risks of sustainable supply chain based on optimized BP neural networks in fresh grape industry. Computers and Electronics in Agriculture, 183. https://doi.org/10.1016/j.compag.2021.105988
Jonkman, J., Barbosa-Póvoa, A. P., & Bloemhof, J. M. (2019). Integrating harvesting decisions in the design of agro-food supply chains. European Journal of Operational Research, 276(1), 247–258. https://doi.org/10.1016/j.ejor.2018.12.024
Kasemset, C., Wannagoat, J., Wattanutchariya, W., & Tippayawong, K. Y. (2014). A risk management framework for new product development: A case study. Industrial Engineering and Management Systems, 13(2), 203–209. https://doi.org/10.7232/iems.2014.13.2.203
Khan, S., Khan, M. I., Haleem, A., & Jami, A. R. (2022). Prioritising the risks in Halal food supply chain: an MCDM approach. Journal of Islamic Marketing, 13(1), 45–65. https://doi.org/10.1108/JIMA-10-2018-0206
Khan, W., Khan, S., Dhamija, A., Haseeb, M., & Ansari, S. A. (2022). Risk assessment in livestock supply chain using the MCDM method: a case of emerging economy. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-022-23640-2
Kim, R. B. (2013). Food risk management quality (FRMQ) of government and the private firms: Consumers’ perspectives in China and Korea. International Food Research Journal, 20(3), 133–791.
Leat, P., & Revoredo-Giha, C. (2013). Risk and resilience in agri-food supply chains: The case of the ASDA PorkLink supply chain in Scotland. Supply Chain Management, 18(2), 219–231. https://doi.org/10.1108/13598541311318845
Leblanc, D. I., Villeneuve, S., Beni, L. H., Otten, A., Fazil, A., McKellar, R., & Delaquis, P. (2015). A national produce supply chain database for food safety risk analysis. Journal of Food Engineering, 147(C), 24–38. https://doi.org/10.1016/j.jfoodeng.2014.09.026
Li, F., Guo, K., & Liao, X. (2023). Risk Assessment of China Rapeseed Supply Chain and Policy Suggestions. International Journal of Environmental Research and Public Health, 20(1). https://doi.org/10.3390/ijerph20010465
Liu, L., Liu, X., & Liu, G. (2018). The risk management of perishable supply chain based on coloured Petri Net modeling. Information Processing in Agriculture, 5(1), 47–59. https://doi.org/10.1016/j.inpa.2017.12.001
Liu, Z., Qu, S., Raza, H., Wu, Z., Qu, D., & Du, J. (2021). Two-Stage Mean-Risk Stochastic Mixed Integer Optimization Model for Location-Allocation Problems under Uncertain Environment. Journal of Industrial and Management Optimization, 17(5), 2783–2804. https://doi.org/10.3934/jimo.2020094
Luo, J., Ji, C., Qiu, C., & Jia, F. (2018). Agri-food supply chain management: Bibliometric and content analyses. In Sustainability (Switzerland) (Vol. 10, Issue 5). MDPI. https://doi.org/10.3390/su10051573
Maman, U., Mahbubi, A., & Jie, F. (2018). Halal risk mitigation in the Australian–Indonesian red meat supply chain. Journal of Islamic Marketing, 9(1), 60–79. https://doi.org/10.1108/JIMA-12-2015-0095
Manuj, I., & Mentzer, J. T. (2008). Global Supply Chain Risk Management. Journal of Business Logistics, 29(1), 133–155. https://doi.org/10.1002/j.2158-1592.2008.tb00072.x
Mithun Ali, S., Moktadir, M. A., Kabir, G., Chakma, J., Rumi, M. J. U., & Islam, M. T. (2019). Framework for evaluating risks in food supply chain: Implications in food wastage reduction. Journal of Cleaner Production, 228, 786–800. https://doi.org/10.1016/j.jclepro.2019.04.322
Mulyati, H., & Geldermann, J. (2017). Managing risks in the Indonesian seaweed supply chain. Clean Technologies and Environmental Policy, 19(1), 175–189. https://doi.org/10.1007/s10098-016-1219-7
Nakandala, D., Lau, H., & Zhao, L. (2017). Development of a hybrid fresh food supply chain risk assessment model. International Journal of Production Research, 55(14), 4180–4195. https://doi.org/10.1080/00207543.2016.1267413
Nguyen, P. H. (2022). Agricultural Supply Chain Risks Evaluation with Spherical Fuzzy Analytic Hierarchy Process. Computers, Materials and Continua, 73(2), 4211–4229. https://doi.org/10.32604/cmc.2022.030115
Niknejad, A., & Petrovic, D. (2016). A fuzzy dynamic Inoperability Input-output Model for strategic risk management in Global Production Networks. International Journal of Production Economics, 179, 44–58. https://doi.org/10.1016/j.ijpe.2016.05.017
Nyamah, E. Y., Jiang, Y., Feng, Y., & Enchill, E. (2017). Agri-food supply chain performance: an empirical impact of risk. Management Decision, 55(5), 872–891. https://doi.org/10.1108/MD-01-2016-0049
OECD-FAO. (2016). OECD-FAO Guidance for Responsible Agricultural Supply Chains. OECD. https://doi.org/10.1787/1286bb3f-id
Onggo, B. S., Panadero, J., Corlu, C. G., & Juan, A. A. (2019). Agri-food supply chains with stochastic demands: A multi-period inventory routing problem with perishable products. Simulation Modelling Practice and Theory, 97. https://doi.org/10.1016/j.simpat.2019.101970
Paillin, D. B., & Tupan, J. M. (2021). The supply chain risk assessment for tuna during the Covid-19 pandemic in Ambon by using the House of Risk Method. IOP Conference Series: Earth and Environmental Science, 1–11. https://doi.org/10.1088/1755-1315/797/1/012024
Paillin, D., Tupan, J., Paillin, J., Latuny, W., & Lawalata, V. (2022). Risk Assessment And Risk Mitigation In A Sustainable Tuna Supply Chain. Acta Logistica, 9(1), 51–61. https://doi.org/10.22306/al.v9i1.270
Pang, H., Lambertini, E., Buchanan, R. L., Schaffner, D. W., & Pradhan, A. K. (2017). Quantitative microbial risk assessment for Escherichia coli O157:H7 in fresh-cut lettuce. Journal of Food Protection, 80(2), 302–311. https://doi.org/10.4315/0362-028X.JFP-16-246
Pereira, S. C. F., Scarpin, M. R. S., & Neto, J. F. (2020). Agri-food risks and mitigations: a case study of the Brazilian mango. Production Planning and Control, 1–11. https://doi.org/10.1080/09537287.2020.1796134
Prakash, S., Soni, G., Rathore, A. P. S., & Singh, S. (2017). Risk analysis and mitigation for perishable food supply chain: a case of dairy industry. Benchmarking, 24(1), 2–23. https://doi.org/10.1108/BIJ-07-2015-0070
Qazi, A., Dickson, A., Quigley, J., & Gaudenzi, B. (2018). Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks. International Journal of Production Economics, 196, 24–42. https://doi.org/10.1016/j.ijpe.2017.11.008
Raihan, A. S., Ali, S. M., Roy, S., Das, M., Kabir, G., & Paul, S. K. (2022). Integrated Model for Soft Drink Industry Supply Chain Risk Assessment: Implications for Sustainability in Emerging Economies. International Journal of Fuzzy Systems, 24(2), 1148–1169. https://doi.org/10.1007/s40815-020-01039-w
Ramos, E., Pettit, T. J., Habib, M., & Chavez, M. (2021). A model ISM-MICMAC for managing risk in agri-food supply chain: An investigation from the Andean region of Peru. International Journal of Value Chain Management, 12(1), 62–85. https://doi.org/10.1504/IJVCM.2021.112845
Rao, M., Bast, A., & de Boerd, A. (2021). European private food safety standards in global agri-food supply chains: a systematic review. International Food and Agribusiness Management Review, 24(5), 739–754. https://doi.org/10.22434/IFAMR2020.0146
Rath, B., Wonginta, T., & Amchang, C. (2022). Risk analysis of the rice supply chain in Cambodia. Journal of International Logistics and Trade, 20(2), 58–77. https://doi.org/10.1108/JILT-05-2022-0007
Rathore, R., Thakkar, J. J., & Kumar Jha, J. (2017). A quantitative risk assessment methodology and evaluation of food supply chain. The International Journal of Logistics Management, 28(4), 1387. https://doi.org/10.13140/RG.2.2.15023.84643
Robson, K., Dean, M., Haughey, S. A., & Elliott, C. T. (2021). The identification of beef crimes and the creation of a bespoke beef crimes risk assessment tool. Food Control, 126. https://doi.org/10.1016/j.foodcont.2021.107980
Rosales, F. P., Oprime, P. C., Royer, A., & Batalha, M. O. (2020). Supply chain risks: findings from Brazilian slaughterhouses. Supply Chain Management, 25(3), 343–357. https://doi.org/10.1108/SCM-03-2019-0130
Santeramo, F. G., Bevilacqua, A., Caroprese, M., Speranza, B., Ciliberti, M. G., Tappi, M., & Lamonaca, E. (2021). Assessed versus perceived risks: Innovative communications in agri-food supply chains. Foods, 10(5). https://doi.org/10.3390/foods10051001
Sari, E. Y., Djoko Guritno, A., & Sukartiko, A. C. (2021). Risk Assessment on Supply Chain of the Geographical Indication Granulated Coconut Sugar in Kulon Progo Regency, Special Region of Yogyakarta, Indonesia. International Journal on Advanced Science, Engineering and Information Technology , 11(1), 236–243.
Shen, Y., & Liao, K. (2022). An Application of Analytic Hierarchy Process and Entropy Weight Method in Food Cold Chain Risk Evaluation Model. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.825696
Singh, A., Shukla, N., & Mishra, N. (2018). Social media data analytics to improve supply chain management in food industries. Transportation Research Part E: Logistics and Transportation Review, 114, 398–415. https://doi.org/10.1016/j.tre.2017.05.008
Srivastava, S. K., Chaudhuri, A., & Srivastava, R. K. (2015). Propagation of risks and their impact on performance in fresh food retail. International Journal of Logistics Management, 26(3), 568–602. https://doi.org/10.1108/IJLM-02-2014-0032
Stefanou, C. R., Bartodziejska, B., & Szosland-Fa?tyn, A. (2022). Quantitative microbiological risk assessment of traditional food of animal origin produced in short supply chains in Poland. EFSA Journal, 20(S2). https://doi.org/10.2903/j.efsa.2022.e200921
Sufiyan, M., Haleem, A., Khan, S., & Khan, M. I. (2019). Evaluating food supply chain performance using hybrid fuzzy MCDM technique. Sustainable Production and Consumption, 20, 40–57. https://doi.org/10.1016/j.spc.2019.03.004
Sumrit, D., & Srisawad, S. (2022). Fuzzy Failure Mode And Effect Analysis Model For Operational Supply Chain Risks Assessment: An Application In Canned Tuna Manufacturer In Thailand. Logforum, 18(1), 77–96. https://doi.org/10.17270/J.LOG.2022.645
Sun, C., Zhu, S., Zhao, B., Li, W., Gao, X., & Wang, X. (2020). Effect of land use conversion on surface soil heavy metal contamination in a typical karst plateau lakeshore wetland of southwest China. International Journal of Environmental Research and Public Health, 17(1). https://doi.org/10.3390/ijerph17010084
Suryaningrat, I. B., Amilia, W., Wibowo, Y., Rusdianto, A. S., & Karismasari, D. R. (2021). Risk identification of post-harvest losses at farm level: A case study of edamame in Indonesia. Agriculture and Natural Resources, 55(2), 292–300. https://doi.org/10.34044/j.anres.2021.55.2.18
Ta?k?ner, T., & Bilgen, B. (2021). Optimization Models for Harvest and Production Planning in Agri-Food Supply Chain: A Systematic Review. Logistics, 5(3), 1–27. https://doi.org/10.3390/logistics5030052
Tavakoli, H. A. Y., & Darestan, S. A. (2023). Evaluation of Sustainable Supply Chain Risk: evidence from the Iranian food industry. Journal of Science and Technology Policy Management , 14(1), 127–156.
Tian, D., & Li, C. (2019). Risk assessment of raw milk quality and safety index system based on primary component analysis. Sustainable Computing: Informatics and Systems, 21, 47–55. https://doi.org/10.1016/j.suscom.2018.11.006
Tran, T. H., Dobrovnik, M., & Kummer, S. (2018). Supply chain risk assessment: A content analysis-based literature review. International Journal of Logistics Systems and Management, 31(4), 562–591. https://doi.org/10.1504/IJLSM.2018.096088
Tsolakis, N. K., Keramydas, C. A., Toka, A. K., Aidonis, D. A., & Iakovou, E. T. (2014). Agrifood supply chain management: A comprehensive hierarchical decision-making framework and a critical taxonomy. Biosystems Engineering, 120, 47–64. https://doi.org/10.1016/j.biosystemseng.2013.10.014
Wang, X., Li, D., & Shi, X. (2012). A fuzzy model for aggregative food safety risk assessment in food supply chains. Production Planning and Control, 23(5), 377–395. https://doi.org/10.1080/09537287.2011.561812
Wang, Y., & Hao, H. (2016). Research on the supply chain risk assessment of the fresh agricultural products based on the improved TOPTSIS Algorithm. Chemical Engineering Transactions, 51, 445–450. https://doi.org/10.3303/CET1651075
Welburn, J., Bier, V., & Hoerning, S. (2016). Import Security: Assessing the Risks of Imported Food. Risk Analysis, 36(11), 2047–2064. https://doi.org/10.1111/risa.12560
Yadav, V. S., Singh, A. R., Gunasekaran, A., Raut, R. D., & Narkhede, B. E. (2022). A systematic literature review of the agro-food supply chain: Challenges, network design, and performance measurement perspectives. Sustainable Production and Consumption, 29, 685–704.
Yan, B., Wang, X., & Shi, P. (2017). Risk assessment and control of agricultural supply chains under Internet of Things. Agrekon, 56(1), 1–12. https://doi.org/10.1080/03031853.2017.1284680
Yan, B., Wu, J., & Wang, F. (2019). CVaR-based risk assessment and control of the agricultural supply chain. Management Decision, 57(7), 1496–1510. https://doi.org/10.1108/MD-11-2016-0808
Yang, J., & Liu, H. (2018). Research of Vulnerability for Fresh Agricultural-Food Supply Chain Based on Bayesian Network. Mathematical Problems in Engineering, 2018. https://doi.org/10.1155/2018/6874013
Yin, R. K., Calvin, Y., & Mali, G. (2018). Case study research and applications (6th ed.). Sage Publication, Inc . https://doi.org/http://dx.doi.org/10.1563
Yu, C., & Huatuco, L. H. (2016). Supply chain risk management identification and mitigation: A case study in a Chinese dairy company. Smart Innovation, Systems and Technologies, 52, 475–486. https://doi.org/10.1007/978-3-319-32098-4_41
Zhai, T., Wang, D., Zhang, Q., Saeidi, P., & Raj Mishra, A. (2022). Assessment of the agriculture supply chain risks for investments of agricultural small and medium-sized enterprises (SMEs) using the decision support model. Economic Research-Ekonomska Istrazivanja . https://doi.org/10.1080/1331677X.2022.2126991
Zhang, G., Li, G., & Peng, J. (2020). Risk assessment and monitoring of green logistics for fresh produce based on a support vector machine. Sustainability (Switzerland), 12(18). https://doi.org/10.3390/su12187569
Zhao, G., Liu, S., Lopez, C., Chen, H., Lu, H., Mangla, S. K., & Elgueta, S. (2020). Risk analysis of the agri-food supply chain: A multi-method approach. International Journal of Production Research, 58(16), 4851–4876. https://doi.org/10.1080/00207543.2020.1725684
Zhao, G., Liu, S., Lopez, C., Lu, H., Elgueta, S., Chen, H., & Boshkoska, B. M. (2019). Blockchain technology in agri-food value chain management: A synthesis of applications, challenges and future research directions. Computers in Industry, 109, 83–99. https://doi.org/10.1016/j.compind.2019.04.002
Zsidisin, G. A. (2003). A grounded definition of supply risk. Journal of Purchasing and Supply Management, 9(5–6), 217–224. https://doi.org/10.1016/j.pursup.2003.07.002