We study multi-unit sequential Dutch auctions in a complex B2B context. Using a large real-world dataset, we apply structural econometric analysis to recover the parameters governing the distribution of bidders' valuations. The identification of these parameters allows us to simulate auction results under different designs and perform policy counterfactuals. We also develop a dynamic optimization approach to guide the setting of key auction parameters. Given the bounded rationality of human decision makers, we propose to augment auctioneers' capabilities with high performance decision support tools in the form of software agents. Our paper contributes to both theory and practice of auction design. From the theoretical perspective, this is the first study that explicitly models the sequential aspects of Dutch auctions using structural econometric analysis. From the managerial perspective, this paper offers useful implications to business practitioners for complex decision making in B2B auctions.

Auction design, B2B market, Decision support systems, Dynamic programming, Multi-unit sequential auctions, Software agents, Structural modeling
hdl.handle.net/1765/85602
International Conference on Information Systems, ICIS 2013
Rotterdam School of Management (RSM), Erasmus University

Lu, Y, Gupta, A, Ketter, W, & van Heck, H.W.G.M. (2013). Designing intelligent software agents for B2B sequential dutch auctions: A structural econometric approach. Presented at the International Conference on Information Systems, ICIS 2013. Retrieved from http://hdl.handle.net/1765/85602