An optimization method to estimate models with store-level data: A case study
The quality of the estimation of a latent segment model when only store-level aggregate data is available seems to be dependent on the computational methods selected and in particular on the optimization methodology used to obtain it. Following the stream of work that emphasizes the estimation of a segmentation structure with aggregate data, this work proposes an optimization method, among the deterministic optimization methods, that can provide estimates for segment characteristics as well as size, brand/product preferences and sensitivity to price and price promotion variation estimates that can be accommodated in dynamic models. It is shown that, among the gradient based optimization methods that were tested, the Sequential Quadratic Programming method (SQP) is the only that, for all scenarios tested for this type of problem, guarantees of reliability, precision and efficiency being robust, i.e., always able to deliver a solution. Therefore, the latent segment models can be estimated using the SQP method when only aggregate market data is available.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Sivakumar, K., 2004. "Manifestations and measurement of asymmetric brand competition," Journal of Business Research, Elsevier, vol. 57(8), pages 813-820, August.
- Ostermark, Ralf, 1999. "Solving Irregular Econometric and Mathematical Optimization Problems with a Genetic Hybrid Algorithm," Computational Economics, Society for Computational Economics, vol. 13(2), pages 103-15, April.
- Still, Claus & Westerlund, Tapio, 2010. "A linear programming-based optimization algorithm for solving nonlinear programming problems," European Journal of Operational Research, Elsevier, vol. 200(3), pages 658-670, February.
- Shen, Chungen & Xue, Wenjuan & Chen, Xiongda, 2010. "Global convergence of a robust filter SQP algorithm," European Journal of Operational Research, Elsevier, vol. 206(1), pages 34-45, October.
- González-Benito, Óscar & Martínez-Ruiz, María Pilar & Mollá-Descals, Alejandro, 2009. "Using store level scanner data to improve category management decisions: Developing positioning maps," European Journal of Operational Research, Elsevier, vol. 198(2), pages 666-674, October.
- Randolph E. Bucklin & Sunil Gupta, 1999. "Commercial Use of UPC Scanner Data: Industry and Academic Perspectives," Marketing Science, INFORMS, vol. 18(3), pages 247-273.
When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:217:y:2012:i:3:p:664-672. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Shamier, Wendy)
If references are entirely missing, you can add them using this form.