dc.contributor.advisor |
Mathugama SC |
|
dc.contributor.author |
Wijesiri MSI |
|
dc.date.accessioned |
2022 |
|
dc.date.available |
2022 |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Wijesiri, M.S.I. (2022). Improving transparency in supply chain for better brand performance :a statistical approach [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/21217 |
|
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/21217 |
|
dc.description.abstract |
The competition of the economic environment is increasing rapidly and it has been a
prevailing issue in many businesses to achieve the balance between the supply and
demand. This issue is further increased when there is a lack of transparency in the
supply chain both internally and externally. Proper analysis on how to mitigate the gap
of lack of transparency would lead to better performance of the business. Various time
series forecasting analyses with the soft computing of neural networks can be utilized
to hinder the gap of supply chain transparency. Further, application of queuing theory
for the complete process enables to mitigate the issues created due to lack of
transparency in the supply chain process.
In this study, the focus was to improve the transparency by in depth study of produced
and sold garments of a particular style in a global brand. The quantities of produced
and sold were taken from a leading manufacturing company in Sri Lanka. The study
was carried out with both time series analysis and queuing theory. For time series
analysis, decomposition method, ARIMA method, VAR method have been applied.
The VAR model was statistically adequate where models were derived for
manufactured and sold quantities. Application of queuing theory has been carried out
to understand the finished good quantity that would be stored in the warehouse before
selling it to the consumer. Apart from that, a mathematical model has been carried out
to identify the extensive stocks that were stored in the warehouse with a percentage
reduction. This mathematical model could reduce further stock amount and thereby
lead to better financial performance as well. The final short-term solution of stock
reduction model is helpful to reduce the stock that will be stored in the warehouses
and also opens for more holistic queueing modelling in future. |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
FORECASTING |
en_US |
dc.subject |
QUEUING |
en_US |
dc.subject |
SUPPLY CHAIN |
en_US |
dc.subject |
BUSINESS STATISTICS -Dissertation |
en_US |
dc.subject |
MATHEMATICS -Dissertation |
en_US |
dc.title |
Improving transparency in supply chain for better brand performance :a statistical approach |
en_US |
dc.type |
Thesis-Abstract |
en_US |
dc.identifier.faculty |
Engineering |
en_US |
dc.identifier.degree |
MSc in Business Statistics |
en_US |
dc.identifier.department |
Department of Mathematics |
en_US |
dc.date.accept |
2022 |
|
dc.identifier.accno |
TH4844 |
en_US |