Forecasting model with asymmetric market response and its application to pricing of consumer package goods

Nobuhiko Terui, Yuuki Imano

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This paper presents a dynamic forecasting model that accommodates asymmetric market responses to marketing mix variable-price promotion-by threshold models. As a threshold variable to generate a mechanism for different market responses, we use the counterpart to the concept of a price threshold applied to a representative consumer in a store. A Bayesian approach is taken for statistical modelling because of advantages that it offers over estimation and forecasting. The proposed model incorporates the lagged effects of a price variable. Thereby, myriad pricing strategies can be implemented in the time horizon. Their effectiveness can be evaluated using the predictive density. We intend to improve the forecasting performance over conventional linear time series models. Furthermore, we discuss efficient dynamic pricing in a store using strategic simulations under some scenarios suggested by an estimated structure of the models. Empirical studies illustrate the superior forecasting performance of our model against conventional linear models in terms of the root mean square error of the forecasts. Useful information for dynamic pricing is derived from its structural parameter estimates. This paper develops a dynamic forecasting model that accommodates asymmetric market responses to marketing mix variable-price promotion-by the threshold models.

Original languageEnglish
Pages (from-to)541-560
Number of pages20
JournalApplied Stochastic Models in Business and Industry
Volume21
Issue number6
DOIs
Publication statusPublished - 2005 Nov 1

Keywords

  • Asymmetric market response
  • Markov chain Monte Carlo
  • Sales forecasting
  • Store data
  • Threshold models

ASJC Scopus subject areas

  • Modelling and Simulation
  • Business, Management and Accounting(all)
  • Management Science and Operations Research

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