The Impact of Climate Change on Supply Chain Management
DOI:
https://doi.org/10.47941/ijscl.2733Keywords:
Climate Change Impact, Supply Chain Resilience, CO₂ Emissions and Logistics, Climate Risk Management, Sustainable Supply ChainAbstract
Purpose: This study examines the impact of climate change on global supply chain management by analyzing the influence of climate-related variables, specifically CO₂ emissions, temperature fluctuations, and flood-related economic damages, on key logistics performance indicators. These indicators include the customs score, infrastructure score, logistics performance index, and logistics competence and quality score.
Methodology: A mixed-methods analytical approach was employed, incorporating regression analysis, correlation matrix evaluation, and principal components analysis (PCA), supplemented by visual analytics. This methodology enabled the identification of relationships between selected climate variables and supply chain performance metrics across various countries.
Findings: The study reveals a statistically significant positive association between CO₂ emissions and improved logistics performance indicators. This suggests that regions with higher industrial output and consequently higher emissions often have more advanced logistics infrastructure and trade efficiency. Conversely, while flood-related economic damages exhibited a negative correlation with logistics performance, the relationship lacked statistical significance. The findings underscore the complex dynamic between industrial growth, environmental impact, and logistics efficiency.
Unique Contribution to Theory, Practice, and Policy (Recommendations): This research contributes to the theoretical discourse by highlighting the dual role of industrial activity in enhancing logistics performance while exacerbating environmental degradation. Practically, it calls for urgent investment in climate-resilient infrastructure and adaptive logistics strategies. From a policy perspective, the study advocates for integrated climate and trade policies that align economic development with environmental sustainability. Future research should explore indirect and long-term effects of climate change on supply chains to inform more robust mitigation strategies.
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Abhijeet Ghadge, H. W. (2019). Managing climate change risks in global supply chains: a review and research agenda. International Journal of Production Research, 44-64. doi:https://doi.org/10.1080/00207543.2019.1629670
Appfluence. (2024, January 1). Supply chain risk-value matrix. https://sync.appfluence.com/templates/supply-chain-risk-value-matrix/
Asariotis, R. (2021). Climate change impacts seaports: A growing threat to sustainable trade and development. UNCTAD Transport and Trade Facilitation Newsletter, Article 75. https://unctad.org/es/isar/news/climate-change-impacts-seaports-growing-threat-sustainable-trade-and-development
Azadegan, A., Mellat Parast, M., Lucianetti, L., Nishant, R., & Blackhurst, J. (2020). Supply chain disruptions and business continuity: An empirical assessment. Decision Sciences, 51(1), 38–73. https://doi.org/10.1111/deci.12395
Bag, S., Dhamija, P., & Pretorius, J.-H. C. (2021). Sustainable supply chain transformation: Alignment of digital technology with circular economy and net-zero objectives. Journal of Cleaner Production, 320, 128618.
Baruti, R. (2023). Analysis and implementation of a business intelligence QlikView application for logistic and procurement management: Sews Cabind case for the shortage problem [Doctoral dissertation, Politecnico di Torino].
Becker, A., Ng, A. K., McEvoy, D., & Mullett, J. (2018). Implications of climate change for shipping and ports in Australia. Climate Risk Management, 20, 11–27.
Bellini, P., Bilotta, S., Collini, E., Fanfani, M., & Nesi, P. (2024). Data sources and models for integrated mobility and transport solutions. Sensors, 24(2), Article 441. https://doi.org/10.3390/s24020441
Bi, S., Li, Z., Brown, M., Wang, L., & Xu, Y. (2022). Dynamic weighted and heat-map integrated scalable information path-planning algorithm. EAI Endorsed Transactions on Scalable Information Systems, 10(2), Article 1567. https://doi.org/10.4108/eetsis.v9i5.1567
Bin Wan, W. W. (2022). Logistics performance and environmental sustainability: Do green innovation, renewable energy, and economic globalization matter? Frontiers in Environmental Science, 10. doi:https://doi.org/10.3389/fenvs.2022.996341
Bui, T. D., Tsai, F. M., Tseng, M. L., Tan, R. R., Yu, K. D. S., & Lim, M. K. (2021). Sustainable supply chain management towards disruption and organizational ambidexterity: A data-driven analysis. Sustainable Production and Consumption, 26, 373–410. https://doi.org/10.1016/j.spc.2020.09.017
Chartis. (2023). Climate Risk Modeling Solutions 2023: Market and Vendor Landscape.
Choi, T. M., Wallace, S. W., & Wang, Y. (2023). Big Data Analytics in Operations and Supply Chain Management: Theory and Applications. Annals of Operations Research, 316(2), 407–429.
Copernicus Climate Change Service. (2024, January 1). Climate datasets. https://climate.copernicus.eu/climate-datasets
Cruz, A. M., & Krausmann, E. (2013). Vulnerability of the oil and gas sector to climate change and extreme weather events. Climatic Change, 121(1), 41–53. https://doi.org/10.1007/s10584-013-0891-4
Dask. (n.d.). GridSearchCV. https://ml.dask.org/modules/generated/dask_ml.model_selection.GridSearchCV.html
Data.gov. (2024). Climate change datasets. https://catalog.data.gov/dataset/?tags=climate-change&res_format=CSV
Datahub.io. (2024). Climate change data collections. https://datahub.io/collections/climate-change
Datrics. (2024). Demand forecasting and planning in retail: Datrics use cases. https://www.datrics.ai/articles/demand-forecasting-and-planning-in-retail-datrics-use-cases
Doll, C. N. H., & Klug, S. (2021). Climate Resilience in Transport Infrastructure: The Need for a Sectoral and Regional Perspective. Transport Reviews, 41(3), 365–386
Emmanuel, T., Maupong, T., Mpoeleng, D., Semong, T., Mphago, B., & Tabona, O. (2021). A survey on missing data in machine learning. Journal of Big Data, 8, Article 16. https://doi.org/10.1186/s40537-021-00516-9
Er Kara, M., Ghadge, A., & Bititci, U. S. (2021). Modelling the impact of climate change risk on supply chain performance. International Journal of Production Research, 59(24), 7317–7335. https://doi.org/10.1080/00207543.2020.1849844
Everstream AI. (2022, June 22). Everstream now available on Oracle Cloud marketplace - Everstream Analytics. Everstream Analytics. https://www.everstream.ai/media/everstream-available-oracle-cloud-marketplace/
George, G., Merrill, R. K., & Schillebeeckx, S. J. D. (2021). Digital sustainability and entrepreneurship: How digital innovations are helping tackle climate change and sustainable development. Entrepreneurship Theory and Practice, 45(5), 999–1027.
Ghadge, A., Wurtmann, H., & Seuring, S. (2020). Managing climate change risks in global supply chains: A review and research agenda. International Journal of Production Research, 58(1), 44–64. https://doi.org/10.1080/00207543.2019.1629670
Godde, C. M., Mason-D'Croz, D., Mayberry, D. E., Thornton, P. K., & Herrero, M. (2021). Impacts of climate change on the livestock food supply chain: A review of the evidence. Global Food Security, 28, Article 100488. https://doi.org/10.1016/j.gfs.2020.100488
Hugos, M. H. (2024). Essentials of supply chain management (5th ed.). John Wiley & Sons.
Icograms. (2024). Supply chain diagram: Simplify supply chain visualization with Icograms Designer: Empower your business efficiency. https://icograms.com/usage-supply-chain-diagram
Intergovernmental Panel on Climate Change. (2021). Climate change 2021: The physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. https://www.ipcc.ch/report/ar6/wg1/
Ivanov, D., & Dolgui, A. (2021). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control, 32(9), 775–788. https://doi.org/10.1080/09537287.2020.1768450
James, G. (2013). An introduction to statistical learning. Springer. https://doi.org/10.1007/978-1-4614-7138-7
Kanike, U. K. (2023). Factors disrupting supply chain management in manufacturing industries. Journal of Supply Chain Management Science, 4(1–2), 1–24. https://doi.org/10.18757/jscms.2023.6986
Katsaliaki, K., Galetsi, P., & Kumar, S. (2022). Supply chain disruptions and resilience: A major review and future research agenda. Annals of Operations Research, 1–38. https://doi.org/10.1007/s10479-020-03912-1
Khakpour, A., Colomo-Palacios, R., & Martini, A. (2021). Visual analytics for decision support: A supply chain perspective. IEEE Access, 9, 81326–81344. https://doi.org/10.1109/ACCESS.2021.3085496
KPMG. (2019). The road to everywhere: The future of supply chain. KPMG Global. https://assets.kpmg.com/content/dam/kpmg/uk/pdf/2021/06/kpmg-future-of-supply-chain-report.pdf
Leal, L. J. M. (2019). A business intelligence approach for operational performance monitoring and improvement in a logistics operator [Master’s thesis, University of Porto].
Leung, T. C. H., Guan, J., & Lau, Y. Y. (2023). Exploring environmental sustainability and green management practices: Evidence from logistics service providers. Sustainability Accounting, Management and Policy Journal, 14(3), 461–489. https://doi.org/10.1108/SAMPJ-03-2022-0133
MacCarthy, B. L., Ahmed, W. A., & Demirel, G. (2022). Mapping the supply chain: Why, what, and how? International Journal of Production Economics, 250, Article 108688. https://doi.org/10.1016/j.ijpe.2022.108688
Maheshwari, S., Gautam, P., & Jaggi, C. K. (2021). Role of big data analytics in supply chain management: Current trends and future perspectives. International Journal of Production Research, 59(6), 1875–1900. https://doi.org/10.1080/00207543.2020.1793011
McDonnell, T. (2013, August 18). MAP: Global flood damage could exceed $1 trillion annually by 2050. Mother Jones. Retrieved from https://www.motherjones.com/environment/2013/08/map-top-cities-billion-dollar-floods/
McSweeney, R. (2022, April 11). Explainer: What the new IPCC report says about extreme weather and climate change. Carbon Brief. https://www.carbonbrief.org/explainer-what-the-new-ipcc-report-says-about-extreme-weather-and-climate-change/
Mehdizadeh, A. (2021). Data analytics methods for supply chain risk management with applications in transportation and manufacturing safety (Doctoral dissertation, Auburn University).
Mukwarami, S., Nkwaira, C., & van der Poll, H. M. (2023). Environmental management accounting implementation challenges and supply chain management in emerging economies' manufacturing sector. Sustainability, 15(2), Article 1061. https://doi.org/10.3390/su15021061
Nabil, D. H., Rahman, M. H., Chowdhury, A. H., & Menezes, B. C. (2023). Managing supply chain performance using a real-time Microsoft Power BI dashboard by action design research (ADR) method. Cogent Engineering, 10(2), Article 2257924. https://doi.org/10.1080/23311916.2023.2257924
National Centers for Environmental Information. (2024). Climate data online (CDO). https://www.ncdc.noaa.gov/cdo-web/datasets
National Oceanic and Atmospheric Administration. (2023). A collage of typical climate and weather-related events: Floods, heatwaves, drought, hurricanes, wildfires, and loss of glacial ice. https://www.commerce.gov/images/collage-typical-climate-and-weather-related-events-floods-heatwaves-drought-hurricanes
OECD. (2023). Harnessing trade and environmental policies to accelerate the green transition.
Ojo, B. (2024). Resilience and sustainability of supply chains in the face of natural disasters and climate change. International Journal of Science and Research Archive, 12(1), 2996–3007. https://doi.org/10.30574/ijsra.2024.12.1.1184
Pankratz, N. M., & Schiller, C. M. (2024). Climate change and adaptation in global supply-chain networks. The Review of Financial Studies, 37(6), 1729–1777. https://doi.org/10.1093/rfs/hhad093
Pawar, P. V., & Paluri, R. A. (2022). Big data analytics in logistics and supply chain management: A review of literature. Vision. Advance online publication. https://doi.org/10.1177/09722629221091655
Provost, F. (2013). Data science for business: What you need to know about data mining and data-analytic thinking (Vol. 355). O'Reilly Media, Inc.
Ravindran, A. R., Warsing Jr., D. P., & Griffin, P. M. (2023). Supply chain engineering: Models and applications. CRC Press. https://doi.org/10.1201/9781003283393
Rawat, A., Kumar, D., & Khati, B. S. (2024). A review on climate change impacts, models, and its consequences on different sectors: A systematic approach. Journal of Water and Climate Change, 15(1), 104–126. https://doi.org/10.2166/wcc.2023.536
Razack, Z. A. (2020). Effect of climate change on stability of multinational supply chains [Doctoral dissertation, Northcentral University].
Rüttinger, L., Ackern, P. V., Lepold, T., Vogt, R., & Auberger, A. (2020). Impacts of climate change on mining, related environmental risks, and raw material supply (Final report No. UBA-FB-000279/ENG). Umweltbundesamt.
Saadi, S. U. R. (2022). Climate change impact on Pakistan's agriculture and livestock. AgriHunt. https://agrihunt.com/articles/climate-changes-impact-on-pakistans-agriculture-and-livestock/
Samera Nazir, L. Z. (2024). Impact of Green Supply Chain Management Practices on the Environmental Performance of Manufacturing Firms Considering Institutional Pressure as a Moderator. Sustainability, 16(6). doi:https://doi.org/10.3390/su16062278
Sarkis, J., Cohen, M. J., Dewick, P., & Schröder, P. (2020). A brave new world: Lessons from the COVID-19 pandemic for transitioning to sustainable supply and production. Resources Conservation and Recycling, 159, Article 104894. https://doi.org/10.1016/j.resconrec.2020.104894
Scott, M. (2023). Supply chain mapping for emergency management decision-making (Report No. IHS/CR-2023-1027). The Sam Houston State University Institute for Homeland Security.
Sharma, N. (2024). Redefine your inventory management with Power BI Inventory Dashboard. The Sunflower Lab. https://www.thesunflowerlab.com/power-bi-inventory-dashboard/
Shokouhyar, S., Pahlevani, N., & Mir Mohammad Sadeghi, F. (2019). Scenario analysis of smart, sustainable supply chain on the basis of a fuzzy cognitive map. Management Research Review, 43(4), 463–496. https://doi.org/10.1108/MRR-01-2019-0002
Song, M.J., Seo, Y.J., & Lee, H.Y. (2023). The dynamic relationship between industrialization, urbanization, CO₂ emissions, and transportation modes in Korea: empirical evidence from maritime and air transport. Transportation, 50, 2111–2137. https://doi.org/10.1007/s11116-022-10303-x
Sousa, R., Miranda, R., Moreira, A., Alves, C., Lori, N., & Machado, J. (2021). Software tools for conducting real-time information processing and visualization in industry: An up-to-date review. Applied Sciences, 11(11), Article 4800. https://doi.org/10.3390/app11114800
UNCTAD. (2022). Making Trade Work Better for the Planet. United Nations Conference on Trade and Development.
Worden, K., Staszewski, W. J., & Hensman, J. J. (2010). Natural computing for mechanical systems research: A tutorial overview. Mechanical Systems and Signal Processing, 25(1), 4–111. https://doi.org/10.1016/j.ymssp.2010.07.013
World Bank. (2024). Climate change data. https://data.worldbank.org/topic/climate-change
Zhang, Z., & Baranzini, A. (2004). What do we know about carbon taxes? An inquiry into their impacts on competitiveness and distribution of income. Energy Policy, 32(4), 507–518. https://doi.org/10.1016/S0301-4215(03)00152-6
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