We propose a Bayesian framework to model bid placement time in retail secondary market online business‐to‐business auctions. In doing so, we propose a Bayesian beta regression model to predict the first bidder and time to first bid, and a dynamic probit model to analyze participation. In our development, we consider both auction‐specific and bidder‐specific explanatory variables. While we primarily focus on the predictive performance of the models, we also discuss how auction features and bidders' heterogeneity could affect the bid timings, as well as auction participation. We illustrate the implementation of our models by applying to actual auction data and discuss additional insights provided by the Bayesian approach, which can benefit auctioneers.

中文翻译：

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零售二级市场在线拍卖中的首次出价建模：贝叶斯方法

我们提出了一个贝叶斯框架来模拟零售二级市场在线 B2B 拍卖中的投标放置时间。为此，我们提出了一个贝叶斯 beta 回归模型来预测第一个投标者和首次投标的时间，并提出一个动态概率模型来分析参与度。在我们的开发中，我们同时考虑了拍卖特定和投标人特定的解释变量。虽然我们主要关注模型的预测性能，但我们也讨论了拍卖特征和投标人的异质性如何影响投标时间以及拍卖参与。我们通过应用于实际拍卖数据来说明我们模型的实施，并讨论贝叶斯方法提供的其他见解，这可以使拍卖师受益。