Essays on channel management in electronic markets

The general theme of my dissertation research is channel management and the related pricing issues. My research aims to contribute to the extant marketing literature by providing both theories and empirical analyses regarding the emerging channels of distribution, namely, the various electronic exchange platforms. This dissertation consists of two essays. The first essay develops an analytical model to study the practice of a dual-channel distribution system which is comprised of a traditional posted-price channel as well as an auction mechanism. We develop a model of channel configurations that incorporates consumer perceptions of price unfairness and consumer heterogeneity in channel preferences. Both factors play important roles in the firm\u27s channel configuration decisions. By jointly managing posted-price and auction channels on the same platform, firms achieve efficiency in terms of extracting consumer surplus, which can compensate for the loss of profits due to consumer perceptions of price unfairness in the posted-price channel. However, consumer loyalty to the posted-price channel limits the firm\u27s ability to leverage the auction channel. Therefore, simultaneous use of posted-price and auction channels can help a firm achieve higher expected profits but only in some cases. If it adopts auctions, the firm should adjust the posted price in a dual channel case to make it higher than the optimal price in a single retail channel. The second essay is an empirical study based on a proprietary data set of electronic reverse auctions (eRA\u27s) that contains rich information of firm behavior and market conditions. We study one of the most prominent yet understudied issues in electronic reverse auctions (eRA), also known as procurement auctions, is understanding the participation behavior of suppliers. There is general agreement among business buyers (and third-party auctioneers) that active supplier participation is crucial to the success of online auctions as it encourages competition among suppliers. Based on actual data on business-to-business (B2B) auctions in various automobile parts markets, we study the suppliers\u27 participation behavior over time and identify the factors that influence such behavior. We adopt a count data survival framework and model repeated auction participation as recurrent events. Inferences are made using Bayesian MCMC techniques which allow us to impute the missing values for the non-participating eligible suppliers. Our results indicate that past attendance behavior, suppliers\u27 competitiveness in terms of providing low prices and complete quotes all significantly influence suppliers\u27 participation decisions. Though completeness of a quote is required to win an auction, the role it plays in influencing supplier\u27s participation is not as important as that of price. The findings of the paper stress the importance of managing supplier\u27s perceived competitiveness of eRAs. Last but not least we find substantial unobserved heterogeneity among suppliers and across markets, which provides additional information to the auctioneer as to how to target and incentivize suppliers firms