Willingness-to-pay estimation using generalized maximum-entropy: A case study

© 2015 Elsevier Inc. All rights reserved. Abstract Estimation of potential customers' willingness-to-pay provides essential information for setting the price of new products. When no market data are available, one usually has to resort to customer surveys. To avoid biases encountered when direc...

全面介紹

Saved in:
書目詳細資料
Main Authors: Sriboonchitta,S., Liu,J., Sirisrisakulchai,J.
格式: Article
出版: Elsevier Inc. 2015
主題:
在線閱讀:http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84926375527&origin=inward
http://cmuir.cmu.ac.th/handle/6653943832/39151
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Chiang Mai University
實物特徵
總結:© 2015 Elsevier Inc. All rights reserved. Abstract Estimation of potential customers' willingness-to-pay provides essential information for setting the price of new products. When no market data are available, one usually has to resort to customer surveys. To avoid biases encountered when directly asking respondent how much they would be willing to pay for some products, a useful strategy is to propose some tentative prices and ask the customers whether they would agree to buy the product at those prices. The resulting data can then be analyzed using latent variable models. However, it is often very difficult to specify the error distribution for such models. In this paper, we investigate the use of generalized maximum-entropy (GME) approach as a solution to this problem. Using simulations, this method is shown to be robust to misspecification of the error distribution. As an illustration, the approach is then applied to the determination of the entrance fee to the Royal Park Rajapruek in Chiang Mai, Thailand.