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 |