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A decision support model to manage demand disruptions of fast-moving consumer goods during a pandemic in Sri Lanka

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dc.contributor.author Pathirawasam, D
dc.contributor.author Hewage, U
dc.contributor.editor Abeysooriya, R
dc.contributor.editor Adikariwattage, V
dc.contributor.editor Hemachandra, K
dc.date.accessioned 2024-03-22T05:43:55Z
dc.date.available 2024-03-22T05:43:55Z
dc.date.issued 2023-12-09
dc.identifier.citation D. Pathirawasam and U. Hewage, "A Decision Support Model to Manage Demand Disruptions of Fast-Moving Consumer Goods During a Pandemic in Sri Lanka," 2023 Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka, 2023, pp. 60-65, doi: 10.1109/MERCon60487.2023.10355466. en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/22376
dc.description.abstract Decision support models play a crucial role within an organization’s demand planning process when emerging pandemics cause disturbances in demand. The increasing trend of pandemics and the long-lasting struggle it create with unpredicted consumer demand and behaviors necessitate the identification of solutions for sudden demand fluctuations during a disruption. The study addresses the absence of quantitative models in the Sri Lankan context to mitigate disruptions in the demand for fast-moving consumer goods caused by pandemics. The results highlight a substantial difference between the aggregate consumption of "Personal Care" and "Home Care" commodities before and after the pandemic. A literature review identified 23 factors that influence demand disruption during a pandemic globally. Then, validated factors for the Sri Lankan context and assessed using Grey relational analysis. The results highlight inflation, consumer wages, prices, and government regulations have a significant impact on disrupting demand during a pandemic in Sri Lanka. The Grey model with 2-AGO is the most suitable model to manage demand disruptions of ‘Personal Care’ and ‘Home Care’ commodities during a pandemic when compared to traditional time series models. The results will assist companies in managing demand disruptions with rapid demand forecasts and taking precautionary actions against fluctuating influencing factors. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.uri https://ieeexplore.ieee.org/document/10355466 en_US
dc.subject Time Series en_US
dc.subject COVID-19 en_US
dc.subject Personal and home care en_US
dc.subject Grey prediction model en_US
dc.subject Grey relational analysis en_US
dc.title A decision support model to manage demand disruptions of fast-moving consumer goods during a pandemic in Sri Lanka en_US
dc.type Conference-Full-text en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Engineering Research Unit, University of Moratuwa en_US
dc.identifier.year 2023 en_US
dc.identifier.conference Moratuwa Engineering Research Conference 2023 en_US
dc.identifier.place Katubedda en_US
dc.identifier.pgnos pp. 60-65 en_US
dc.identifier.proceeding Proceedings of Moratuwa Engineering Research Conference 2023 en_US
dc.identifier.email dinithipathirawasam@gmail.com en_US
dc.identifier.email uthpaleesh@uom.lk en_US


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