”Too hurry to decide” : A “ Big Data” Investigation of Antecedents and Consequences of Bidder Decision Quality in Fast Live Auctions
- Wenyu DOU (Principal Investigator / Project Coordinator)Department of Marketing
- Hairong LI (Co-Investigator)
- Liye MA (Co-Investigator)
- Kaida QIN (Co-Investigator)
DescriptionFast decision-making is a subset of decision making research and typical in flora auctions, where bidding time windows are usually a few seconds, bidders make hundreds of decisions continuously for several hours, and the processes repeat on a daily basis. Such auctions provide an ideal environment to explore several under-studied issues on bidders in fast decision-making contexts, such as decision quality, levels of performance, learning styles, and job satisfaction, as well as mediating variables such as competitive arousal, number of rivalries, and demand urgency. Based on a pilot study of one of the largest flora auctions in Asia, we propose a hierarchical Bayesian model of the antecedents and consequences of fast decision-makings and plan to test it with a set of rich, big data. The data we plan to collect will consist of real-time tracking data of million bids over six months, daily in-depth interviews of a panel of bidders for one month, and observational data of these bidders’ facial and emotional responses in the bidding processes. These structured and unstructured data will be integrated and subject to a series of Markov-Chain Monte Carlo analyses to test the validity and reliability of our theoretical model. The findings should be able to contribute to the literature of fast decision-makings and offer implications for auction operators and participants.
|Effective start/end date||1/08/14 → 14/02/18|
- Auction,decision making,competition,learning,