An exploratory study on the new product demand curve estimation using online auction data

As the importance of time-based competition is increasing, information systems for supporting the immediate decision making is strongly required. Especially high-tech product firms are under extreme pressure of rapid response to the demand side due to relatively short life cycle of the product. Therefore, the objective of our research is proposing a framework of estimating demand curve based on e-auction data, which are extremely easy to access and well reflect the limited demand curve in that channel. Firstly, we identify the advantages of using e-auction data for full demand curve estimation and then verify it using Agent-Based-Modeling and Tobin's censored regression model.