Recovery strategies for government-led food supply chain in COVID-19 pandemic: A simulation study
Qingqi LONG, Xiaobo WU, Juanjuan PENG
Recovery strategies for government-led food supply chain in COVID-19 pandemic: A simulation study
The COVID-19 pandemic caused severe and enduring effects globally, impacting public health, normalcy, and productivity significantly. In response, government-led food supplies became crucial in many countries to counter the adverse effects of pandemic control measures on daily activities. Focusing on government-led food supply chain during the COVID-19 pandemic, this study employed simulations across different pandemic phases to identify and confirm effective recovery strategies. Our analysis pinpointed insufficient transportation capacity, uneven distribution of district warehouses, and production-demand mismatches as the main factors contributing to food shortages. Strategies such as enhancing transportation capacity, establishing new district warehouses, and increasing production capacity proved to significantly bolster supply chain resilience, stabilize supplies, and meet escalating demands. Opening municipal emergency warehouses ahead of potential disruptions also showed a positive recovery effect. However, while food aid from other provinces and more frequent inventory checks generally enhanced resilience, they occasionally led to unintended negative consequences. Surprisingly, reallocating food between district warehouses negatively impacted the supply chain. This research advances the understanding of government-led food supply chain vulnerabilities during significant public health crises and proposes targeted recovery strategies for different pandemic phases, aiding policymakers in better managing future emergencies.
government-led food supply chain / food shortages / recovery strategy / simulation analysis / COVID-19 pandemic
[1] |
Achmad A L H, Chaerani D, Perdana T, (2021). Designing a food supply chain strategy during COVID-19 pandemic using an integrated agent-based modelling and robust optimization. Heliyon, 7( 11): e08448
CrossRef
Google scholar
|
[2] |
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
CrossRef
Google scholar
|
[3] |
Ali I, Arslan A, Khan Z, Tarba S Y, (2021a). The role of industry 4.0 technologies in mitigating supply chain disruption: Empirical evidence from the Australian food processing industry. IEEE Transactions on Engineering Management, 71: 10600–10610
CrossRef
Google scholar
|
[4] |
Ali M H, Suleiman N, Khalid N, Tan K H, Tseng M L, Kumar M, (2021b). Supply chain resilience reactive strategies for food SMEs in coping to COVID-19 crisis. Trends in Food Science & Technology, 109: 94–102
CrossRef
Google scholar
|
[5] |
Bag S, Dhamija P, Luthra S, Huisingh D, (2023). How big data analytics can help manufacturing companies strengthen supply chain resilience in the context of the COVID-19 pandemic. International Journal of Logistics Management, 34( 4): 1141–1164
CrossRef
Google scholar
|
[6] |
Baležentis T, Morkunas M, Zickiene A, Volkov A, Ribasauskiene E, Streimikiene D, (2021). Policies for rapid mitigation of the crisis’ effects on agricultural supply chains: A multi-criteria decision support system with Monte Carlo simulation. Sustainability, 13( 21): 11899
CrossRef
Google scholar
|
[7] |
Ben Hassen T, El Bilali H, Allahyari M S, Berjan S, Karabasevic D, Radosavac A, Dasic G, Dervida R, (2021). Preparing for the worst? Household food stockpiling during the second wave of COVID-19 in Serbia. Sustainability, 13( 20): 11380
CrossRef
Google scholar
|
[8] |
Bender K E, Badiger A, Roe B E, Shu Y H, Qi D Y, (2022). Consumer behavior during the COVID-19 pandemic: An analysis of food purchasing and management behaviors in US households through the lens of food system resilience. Socio-Economic Planning Sciences, 82: 101107
CrossRef
Google scholar
|
[9] |
Benker B, (2021). Stockpiling as resilience: Defending and contextualising extra food procurement during lockdown. Appetite, 156: 104981
CrossRef
Google scholar
|
[10] |
Bidisha S H, Mahmood T, Hossain M, (2021). Assessing food poverty, vulnerability and food consumption inequality in the context of COVID-19: A case of Bangladesh. Social Indicators Research, 155( 1): 187–210
CrossRef
Google scholar
|
[11] |
Bukari C, Aning-Agyei M A, Kyeremeh C, Essilfie G, Amuquandoh K F, Owusu A A, Otoo I C, Bukari K I, (2022). Effect of COVID-19 on household food insecurity and poverty: Evidence from Ghana. Social Indicators Research, 159( 3): 991–1015
CrossRef
Google scholar
|
[12] |
Burgos D, Ivanov D, (2021). Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions. Transportation Research Part E, Logistics and Transportation Review, 152: 102412
CrossRef
Google scholar
|
[13] |
Chin C F, (2020). The impact of food supply chain disruptions amidst COVID-19 in Malaysia. Journal of Agriculture, Food Systems, and Community Development, 9( 4): 161–163
CrossRef
Google scholar
|
[14] |
Chitrakar B, Zhang M, Bhandari B, (2021). Improvement strategies of food supply chain through novel food processing technologies during COVID-19 pandemic. Food Control, 125: 108010
CrossRef
Google scholar
|
[15] |
Chowdhury M T, Sarkar A, Paul S K, Moktadir M A, (2022). A case study on strategies to deal with the impacts of COVID-19 pandemic in the food and beverage industry. Operations Management Research: Advancing Practice Through Research, 15( 1–2): 166–178
CrossRef
Google scholar
|
[16] |
Coleman P C, Dhaif F, Oyebode O, (2022). Food shortage, stockpiling and panic buying ahead of Brexit as reported by the British media: A mixed methods content analysis. BMC Public Health, 22( 1): 206
CrossRef
Google scholar
|
[17] |
Coluccia B, Agnusdei G P, Miglietta P P, De Leo F, (2021). Effects of COVID-19 on the Italian agri-food supply and value chains. Food Control, 123: 107839
CrossRef
Google scholar
|
[18] |
Cui M J, Zhang X H, Zhang Y F, Yang D G, Huo J W, Xia F Q, (2023). Effects of policy intervention on food system resilience to emergency risk shock: Experience from China during COVID-19 pandemic. Foods, 12( 12): 2345
CrossRef
Google scholar
|
[19] |
Ding C, Liu L, Zheng Y, Liao J X, Huang W X, (2022). Role of distribution centers disruptions in new retail supply chain: An analysis experiment. Sustainability, 14( 11): 6529
CrossRef
Google scholar
|
[20] |
Ekren B Y, Stylos N, Zwiegelaar J, Turhanlar E E, Kumar V, (2023). Additive manufacturing integration in E-commerce supply chain network to improve resilience and competitiveness. Simulation Modelling Practice and Theory, 122: 102676
CrossRef
Google scholar
|
[21] |
Falkendal T, Otto C, Schewe J, Jagermeyr J, Konar M, Kummu M, Watkins B, Puma M J, (2021). Grain export restrictions during COVID-19 risk food insecurity in many low- and middle-income countries. Nature Food, 2( 1): 11–14
CrossRef
Google scholar
|
[22] |
Farcas A C, Galanakis C M, Socaciu C, Pop O L, Tibulca D, Paucean A, Jimborean M A, Fogarasi M, Salanta L C, Tofana M, Socaci S A, (2020). Food security during the pandemic and the importance of the bioeconomy in the new era. Sustainability, 13( 1): 150
CrossRef
Google scholar
|
[23] |
Galal N M, El-Kilany K S, (2016). Sustainable agri-food supply chain with uncertain demand and lead time. International Journal of Simulation Modelling, 15( 3): 485–496
CrossRef
Google scholar
|
[24] |
Ge H, Goetz S J, Cleary R, Yi J, Gómez M I, (2022). Facility locations in the fresh produce supply chain: An integration of optimization and empirical methods. International Journal of Production Economics, 249: 108534
CrossRef
Google scholar
|
[25] |
Gholami-Zanjani S M, Klibi W, Jabalameli M S, Pishvaee M S, (2021). The design of resilient food supply chain networks prone to epidemic disruptions. International Journal of Production Economics, 233: 108001
CrossRef
Google scholar
|
[26] |
Hobbs J E, (2020). Food supply chains during the COVID-19 pandemic. Canadian Journal of Agricultural Economics, 68( 2): 171–176
CrossRef
Google scholar
|
[27] |
Huang Y K, Li J, Qi Y, Shi V, (2021). Predicting the impacts of the COVID-19 pandemic on food supply chains and their sustainability: A simulation study. Discrete Dynamics in Nature and Society, 2021: 7109432
CrossRef
Google scholar
|
[28] |
Ivanov D, (2019). Disruption tails and revival policies: A simulation analysis of supply chain design and production-ordering systems in the recovery and post-disruption periods. Computers & Industrial Engineering, 127: 558–570
CrossRef
Google scholar
|
[29] |
Ivanov D, (2020). Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case. Transportation Research Part E, Logistics and Transportation Review, 136: 101922
CrossRef
Google scholar
|
[30] |
Katsoras E, Georgiadis P, (2022). An integrated system dynamics model for closed loop supply chains under disaster effects: The case of COVID-19. International Journal of Production Economics, 253: 108593
CrossRef
Google scholar
|
[31] |
Kent K, Gale F, Penrose B, Auckland S, Lester E, Murray S, (2022). Consumer-driven strategies towards a resilient and sustainable food system following the COVID-19 pandemic in Australia. BMC Public Health, 22( 1): 1539
CrossRef
Google scholar
|
[32] |
Liang L, Qin K Y, Jiang S J, Wang X Y, Shi Y T, (2021). Impact of epidemic-affected labor shortage on food safety: A Chinese scenario analysis using the CGE model. Foods, 10( 11): 2679
CrossRef
Google scholar
|
[33] |
Liao C H, Lu Q H, Shui Y, (2022). Governmental anti-pandemic and subsidy strategies for blockchain-enabled food supply chains in the post-pandemic era. Sustainability, 14( 15): 9497
CrossRef
Google scholar
|
[34] |
Lohmer J, Bugert N, Lasch R, (2020). Analysis of resilience strategies and ripple effect in blockchain-coordinated supply chains: An agent-based simulation study. International Journal of Production Economics, 228: 107882
CrossRef
Google scholar
|
[35] |
Mahajan K, Tomar S, (2021). COVID‐19 and supply chain disruption: Evidence from food markets in India. American Journal of Agricultural Economics, 103( 1): 35–52
CrossRef
Google scholar
|
[36] |
McKay F H, Bastian A, Lindberg R, (2021). Exploring the response of the Victorian emergency and community food sector to the COVID-19 pandemic. Journal of Hunger & Environmental Nutrition, 16( 4): 447–461
CrossRef
Google scholar
|
[37] |
Min S, Zhang X H, Li G C, (2020). A snapshot of food supply chain in Wuhan under the COVID-19 pandemic. China Agricultural Economic Review, 12( 4): 689–704
CrossRef
Google scholar
|
[38] |
Moosavi J, Hosseini S, (2021). Simulation-based assessment of supply chain resilience with consideration of recovery strategies in the COVID-19 pandemic context. Computers & Industrial Engineering, 160: 107593
CrossRef
Google scholar
|
[39] |
Mustafee N, Katsaliaki K, Taylor S J, (2021). Distributed approaches to supply chain simulation: A review. ACM Transactions on Modeling and Computer Simulation, 31( 4): 1–31
CrossRef
Google scholar
|
[40] |
Nadig A P R, Krishna K L, (2020). Impact of lockdown during COVID-19 pandemic and its advantages. International Journal of Health & Allied Sciences, 9( 4): 316–321
CrossRef
Google scholar
|
[41] |
Narayanan S, Saha S, (2021). Urban food markets and the COVID-19 lockdown in India. Global Food Security, 29: 100515
CrossRef
Google scholar
|
[42] |
Ning Y, Li X Y, Xu S X, Yang S L, (2023). How do digital technologies improve supply chain resilience in the COVID-19 pandemic? Evidence from Chinese manufacturing firms. Frontiers of Engineering Management, 10( 1): 39–50
CrossRef
Google scholar
|
[43] |
Rahman T, Paul S K, Agarwal R, Shukla N, Taghikhah F, (2024). A viable supply chain model for managing panic-buying related challenges: lessons learned from the COVID-19 pandemic. International Journal of Production Research, 62( 10): 3415–3434
CrossRef
Google scholar
|
[44] |
Rahman T, Taghikhah F, Paul S K, Shukla N, Agarwal R, (2021). An agent-based model for supply chain recovery in the wake of the COVID-19 pandemic. Computers & Industrial Engineering, 158: 107401
CrossRef
Google scholar
|
[45] |
Ritzel C, Ammann J, Mack G, El Benni N, (2022). Determinants of the decision to build up excessive food stocks in the COVID-19 crisis. Appetite, 176: 106089
CrossRef
Google scholar
|
[46] |
Shen Z M, Sun Y Q, (2023). Strengthening supply chain resilience during COVID-19: A case study of JD.com. Journal of Operations Management, 69( 3): 359–383
CrossRef
Google scholar
|
[47] |
Sid S, Mor R S, Panghal A, Kumar D, Gahlawat V K, (2021). Agri-food supply chain and disruptions due to COVID-19: Effects and strategies. Brazilian Journal of Operations & Production Management, 18( 2): 1–14
CrossRef
Google scholar
|
[48] |
Singh S, Kumar R, Panchal R, Tiwari M K, (2021). Impact of COVID-19 on logistics systems and disruptions in food supply chain. International Journal of Production Research, 59( 7): 1993–2008
CrossRef
Google scholar
|
[49] |
Tsao Y C, (2016). Joint location, inventory, and preservation decisions for non-instantaneous deterioration items under delay in payments. International Journal of Systems Science, 47( 3): 572–585
CrossRef
Google scholar
|
[50] |
Tundys B, Wisniewski T, (2020). Benefit optimization of short food supply chains for organic products: A simulation-based approach. Applied Sciences, 10( 8): 2783
CrossRef
Google scholar
|
[51] |
Utomo D S, Onggo B S, Eldridge S, (2018). Applications of agent-based modelling and simulation in the agri-food supply chains. European Journal of Operational Research, 269( 3): 794–805
CrossRef
Google scholar
|
[52] |
Wang E R, Gao Z F, (2021). The Impact of COVID-19 on food stockpiling behavior over time in China. Foods, 10( 12): 3076
CrossRef
Google scholar
|
[53] |
Wang L K, Qi C J, Jiang P, Xiang S, (2022). The impact of blockchain application on the qualification rate and circulation efficiency of agricultural products: A simulation analysis with agent-based modelling. International Journal of Environmental Research and Public Health, 19( 13): 7686
CrossRef
Google scholar
|
[54] |
Yao C, Fan B, Zhao Y, Cheng X, (2023). Evolutionary dynamics of supervision-compliance game on optimal pre-positioning strategies in relief supply chain management. Socio-Economic Planning Sciences, 87: 101598
CrossRef
Google scholar
|
[55] |
Zheng Y, Liu L, Shi V, Huang W X, Liao J X, (2022). A resilience analysis of a medical mask supply chain during the COVID-19 pandemic: A simulation modeling approach. International Journal of Environmental Research and Public Health, 19( 13): 8045
CrossRef
Google scholar
|
[56] |
Zhu Q, Krikke H, (2020). Managing a sustainable and resilient perishable food supply chain (PFSC) after an outbreak. Sustainability, 12( 12): 5004
CrossRef
Google scholar
|
/
〈 | 〉 |