Fairs for e-commerce: the benefits of aggregating buyers and sellers

In recent years, many new and interesting models of successful online business have been developed. Many of these are based on the competition between users, such as online auctions, where the product price is not fixed and tends to rise. Other models, including group-buying, are based on cooperation between users, characterized by a dynamic price of the product that tends to go down. There is not yet a business model in which both sellers and buyers are grouped in order to negotiate on a specific product or service. The present study investigates a new extension of the group-buying model, called fair, which allows aggregation of demand and supply for price optimization, in a cooperative manner. Additionally, our system also aggregates products and destinations for shipping optimization. We introduced the following new relevant input parameters in order to implement a double-side aggregation: (a) price-quantity curves provided by the seller; (b) waiting time, that is, the longer buyers wait, the greater discount they get; (c) payment time, which determines if the buyer pays before, during or after receiving the product; (d) the distance between the place where products are available and the place of shipment, provided in advance by the buyer or dynamically suggested by the system. To analyze the proposed model we implemented a system prototype and a simulator that allow to study effects of changing some input parameters. We analyzed the dynamic price model in fairs having one single seller and a combination of selected sellers. The results are very encouraging and motivate further investigation on this topic

Bundling Customers: How to Exploit Trust Among Customers to Maximize Seller Profit

We consider an auction of identical digital goods to customers whose valuations are drawn independently from known distributions. Myerson's classic result identifies the truthful mechanism that maximizes the seller's expected profit. Under the assumption that in small groups customers can learn each others' valuations, we show how Myerson's result can be improved to yield a higher payoff to the seller using a mechanism that offers groups of customers to buy bundles of items.Comment: 11 pages, 1 figure. After posting the first version of this paper we learned that much of its mathematical content already appears in the literature, for example in "Multiproduct nonlinear pricing" by Armstrong (1996), although in a slightly different context of bundling products, rather than customer

eBay users form stable groups of common interest

Market segmentation of an online auction site is studied by analyzing the users' bidding behavior. The distribution of user activity is investigated and a network of bidders connected by common interest in individual articles is constructed. The network's cluster structure corresponds to the main user groups according to common interest, exhibiting hierarchy and overlap. Key feature of the analysis is its independence of any similarity measure between the articles offered on eBay, as such a measure would only introduce bias in the analysis. Results are compared to null models based on random networks and clusters are validated and interpreted using the taxonomic classifications of eBay categories. We find clear-cut and coherent interest profiles for the bidders in each cluster. The interest profiles of bidder groups are compared to the classification of articles actually bought by these users during the time span 6-9 months after the initial grouping. The interest profiles discovered remain stable, indicating typical interest profiles in society. Our results show how network theory can be applied successfully to problems of market segmentation and sociological milieu studies with sparse, high dimensional data.Comment: Major revision of the manuscript. Methodological improvements and inclusion of analysis of temporal development of user interests. 19 pages, 12 figures, 5 table

Market Experience and willingness to trade: evidence from repeated markets with symmetric and asymmetric information

Many studies have found a gap between willingness-to-pay and willingness-to-accept that is inconsistent with standard theory. There is also evidence that the gap is eroded by experience gained in the laboratory and naturally occurring markets. This paper argues that the gap and the effects of experience are explained by a caution heuristic. This conjecture is tested in a repeated market experiment with symmetric and asymmetric information. The results support the conjecture: people do seem to use heuristics rather than reacting optimally and their behavior adjusts slowly when the environment changes.WTA/WTP disparity, endowment effect, market experience, bounded rationality, asymmetric information

Market Structure and Conduct of the North Dakota Livestock Marketing Industry

Industrial Organization, Marketing,

Analysing B2B electronic procurement benefits – Information systems perspective

This paper presents electronic procurement benefits identified in four case companies. The benefits achieved in the case companies were classified according to taxonomies from the Information Systems discipline. Existing taxonomies were combined into a new taxonomy which allows evaluation of the complex e-procurement impact. Traditional financial-based methods failed to capture the nature of e-procurement benefits. In the new taxonomy, eprocurement benefits are classified using scorecard dimensions (strategic, tactical and operational), which allows the identification of areas of e-procurement impact, in addition the benefits characteristic is captured (tangible, intangible, financial and non-financial)