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.
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.