Forecast information and traditional retailer performance in a dual-channel competitive market

• Published in: Journal of business research Vol. 63; no. 1; pp. 77 - 83
• Main Authors: Yan, Ruiliang, Ghose, Sanjoy
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 2010; Elsevier; Elsevier Sequoia S.A
• Series: Journal of Business Research
• Subjects: Accuracy; Bertrand competition game; Channel competition; Competition; Competitiveness; Economic performance; Forecast information; Forecast information Channel competition Uncertainty modeling Bertrand competition game Marketing research; Forecasts; Game theory; Information economics; Market strategy; Marketing research; Retail trade; Retailing; Studies; Uncertainty modeling; Willingness to pay; Bertrand competition game; Forecast information; Marketing research; Channel competition; Uncertainty modeling
• ISSN: 0148-2963; 1873-7978
• DOI: 10.1016/j.jbusres.2009.02.017

Independent firms in a dual-channel competitive market are expected to have their own information about the nature of the market. In this research, we develop a game-theoretic model to examine the value of forecast information about consumers' willingness to pay. The model is based on a simultaneously played Bertrand game. Our results indicate that the profits of online as well as traditional retailers always increase with forecast accuracy, and that forecast accuracy has a greater effect on the performance of the traditional retailer than on that of the online retailer. Our results also show that the difference in profit between that of the traditional retailer and the online retailer increases with forecast accuracy. In addition we find that forecast accuracy is much more valuable to the traditional retailer when there is an increasing volatility in the market, an increasing level of consumer valuation of the product, and an increasing intensity in market competition. Based on our results, we derive optimal market strategies and identify directions of future research.