Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
5-2013
Abstract
In this paper, we look at demand forecasting by using a growth model and negative binomial regression framework. Using cumulative sales, we model the sales data for different wristwatch brands and relate it to their sales and growth characteristics. We apply clustering to determine the distinctive characteristics of each individual cluster. Four different growth models are applied to the clusters to find the most suitable growth model to be used. After determining the appropriate growth model to be applied, we then forecast the sales by applying the model to new products being launched in the market and continue to monitor the model further.
Keywords
Growth models, watch industry, sales forecasting, MITB student
Discipline
Computer Sciences | Operations Research, Systems Engineering and Industrial Engineering | Sales and Merchandising
Research Areas
Intelligent Systems and Optimization
Publication
SAS Global Forum 2013: Proceedings: Data Mining (SUGI 31)
First Page
1
Last Page
17
Publisher
SAS
City or Country
San Francisco
Citation
ONG, Cally Yeru; CHOY, Murphy; and CHEONG, Michelle L. F..
Demand Forecasting Using a Growth Model and Negative Binomial Regression Framework. (2013). SAS Global Forum 2013: Proceedings: Data Mining (SUGI 31). 1-17.
Available at: https://ink.library.smu.edu.sg/sis_research/1675
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://support.sas.com/resources/papers/proceedings13/088-2013.pdf
Included in
Computer Sciences Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Sales and Merchandising Commons