Information acquisition in new product introduction Li, Yongquan; Zhu, Kaijie

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Li, Yongquan ; Zhu, Kaijie
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European Journal of Operational Research
Business, general; Business, international; Business
Academic; Trade
To link to full-text access for this article, visit this link: Byline: Yongquan Li, Kaijie Zhu Keywords: Decision analysis; Dynamic programming; Forecasting; Marketing; Production Abstract: In the presence of huge losses from unsuccessful new product introductions, companies often seek forecast information from various sources. As the information can be costly, companies need to determine how much effort to put into acquiring the information. Such a decision is strategically important because an insufficient investment may cause lack of knowledge of product profitability, which in turn may lead to introducing a loss-making product or scrapping a potentially profitable one. In this paper, we use decision analytical models to study information acquisition for new product introduction. Specifically, we consider a decision maker (DM) who, prior to introducing a new product, can purchase forecasts and use the information to update his knowledge of the market demand. We analyze and compare two approaches: The first approach is to determine the total amount of forecasts to purchase all at once. The second one is to purchase forecasts sequentially and, based on the purchased forecasts, determine whether those forecasts are informative enough for making an introduction decision or an additional forecast is needed. We present dynamic programming formulations for both approaches and derive the optimal policies. Via a numerical study, we find the second approach, i.e., purchasing forecasts sequentially, can generate a significant profit advantage over the first one when (1) the cost of acquiring forecasts is neither too high nor too low, (2) the precision of the forecasts is of a moderate level, and (3) the profit margin of the new product is small. Author Affiliation: Department of Industrial Engineering and Logistics Management, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong Article History: Received 15 December 2006; Accepted 26 September 2008
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