Joni L. Jones

Buyer intention to use internet-enabled reverse auctions: the role of asset specificity, product specialization, and non-contractibility

Information technology enabled exchanges in electronic markets have significant implications for buyer-supplier relationships. Building on studies that emphasize the role of intangible assets in interorganizational relationships, this study argues that buyers are less likely to use reverse auctions for supplier relationships involving a high degree of non-contractibility. The argument complements traditional transaction cost economics arguments that focus on the impact of asset specificity and product specialization. We identify six dimensions of non-contractibility-quality, supplier technological investments, information exchange, responsiveness, trust, and flexibility-which encompass task-based and interaction-based non-contractibility. The study finds that, together with product specialization, these non-contractible elements of interorganizational relationships have greater explanatory power for reverse auction use than asset specificity. This result highlights the importance of supplier investments in non-contractible elements of exchange relationships in an increasingly dynamic service- and knowledge-based economy.

Combinatorial auctions using rule-based bids

The migration of auctions to the Internet provides a unique opportunity to harness the power of computing to create new auction forms that were previously impossible. We describe a new type of combinatorial auction that accepts rule-based bids. Allowing bids in the form of high-level rules relieves the buyer from the burden of enumerating all possible acceptable bundles. The allocation of goods requires solving a complex combinatorial problem, a task that is completely impractical in a conventional auction setting. We describe simplifying winner determination heuristics developed in this study to make large problems of this nature manageable.

Market Segmentation Within Consolidated E-Markets: A Generalized Combinatorial Auction Approach

We analyze an e-market design that allows multiple market segments to be served simultaneously with a single generalized combinatorial auction. The mechanism uses rule-based bids designed to accommodate various kinds of bidders, such as those more sensitive to price or those more restricted in their requirements. We demonstrate experimentally—using agent-based simulation of the actual market for television advertising slots—that the rule-based approach effectively handles the wide range of market segments, while maintaining buyer and seller surplus and efficiently allocating goods.

A Heuristic for Winner Determination in Rule-Based Combinatorial Auctions

Combinatorial auctions address the sale of materials where there exist complementarities between items. A major stumbling block to the widespread use of combinatorial auctions is the complexity of the winner-determination problem, which is known to be NP-complete. We consider a rich version of combinatorial auctions, rule-based combinatorial auctions, where bids consist of rules that describe acceptable bundles rather than provide complete enumerations of acceptable bundles. This makes the winner-determination problem potentially harder because the problem must find bundles meeting bid criterion as well as finding an optimal selection of winning bids. This paper describes in detail a heuristic that achieves a satisfying solution to the winner-determination problem for large problems where exact solutions may not be attainable. Our contribution is threefold. First, we give a general approach to providing good approximations to the winner-determination problem for rule-based auctions. Although the approach requires adaptation for specific instances, it is conceptually tractable and implementable. Second, the approach is illustrated and tested on an auction format for selling prime-time television advertising time formed from data and interviews with industry sources. Third, while some researchers have used commercial solvers that appeared to obviate the need for specialized solution approaches to the winner-determination problem, we give evidence that, at least for the problem studied here, specialized approaches are necessary.

A Tale of Three Classes: Case Studies in Course Complexity

Introduction Pedagogical research is unusual within academic research in that nearly all the researchers in the area are also practitioners, which is to say they teach as well as research teaching. For this reason, interest in the answers to the research questions is personal as well as professional. Will distance learning teaching be as effective as face-to-face techniques? Is the case method really more effective than lecture? Should laptops be allowed in the classroom? The number of questions that might be posed is essentially unbounded. No one would dispute that research on teaching and learning can be challenging. After all, there are many variables that must be considered. Who could plausibly argue, for example, that factors such as the experience of the instructor, the characteristics of the students, the form of content being presented, the method of delivery, and the setting of the class are irrelevant to learning? Nonetheless, often for causal relationships that involve many variables, the individual effects of specific factors can be teased out using techniques such as regression or structural equation modeling (SEM). In such cases, the underlying process can be described as nearly decomposable (Simon, 1981). Additionally, sometimes the interrelationship between variables is so great that such decomposition is impossible. In such cases, the relationship is complex. Where such complexity exists, the research strategy needs to be reevaluated, since an individual variables impact on overall effectiveness can be highly dependent upon the values of other variables. A particularly significant implication of complexity relates to the value of quantitative analytical techniques, such as those just mentioned. Recent research has demonstrated that, under the reasonable assumption that individuals continuously attempt to improve fitness, complex underlying relationships can produce statistically significant yet entirely misleading results (Gill & Sincich, 2008). Thus, the assumption of decomposability needs to be carefully tested prior to applying these techniques. At the present time, such tests require qualitative analysis of the process; quantitative tests for this form of complexity have yet to be devised (Gill, 2008). The present paper considers the question of the decomposability of teaching situations by presenting a qualitative analysis of three case studies of MIS courses. The cases themselves are intrinsically interesting--all three illustrate innovative teaching techniques, 2 of the 3 were winners of the Decision Science Institutes (DSI) Innovative Curriculum Competition, and all demonstrated substantial evidence of learning and student satisfaction. The research also finds that by comparing the three cases side-by-side considerable insight is gained into the complexity of the relationship between teaching approach, course setting, and outcome. The paper begins by introducing the concept of a rugged fitness landscape, taken directly from a model proposed in evolutionary biology (Kauffman, 1993). Then the research design is presented, which involves a qualitative search for interactions across four key areas of the course context: instructor characteristics, content characteristics, design/delivery characteristics, and student characteristics. Each class is presented, with details provided in two appendices, and the key interactions that were observed are identified. Because the first of these courses--referred to as Ism3232.A--evolved dramatically over time, it is presented in both longitudinal and cross sectional terms. The remaining two courses--Ism3232.B and Ism6155.A--experienced relatively few design changes from the time they were first offered. Both are therefore presented only in cross sectional terms. By comparing time slices and cross sectional observations, observational evidence of high levels of interaction between areas is acquired. The paper concludes by considering how this evidence might change the conduct of future research into IT education. …

Price discovery in combinatorial auctions using Gibbs sampling

Considerable research discusses the advantages and disadvantages of combinatorial auctions. This study addresses a disadvantage, the loss of price discovery for the individual items sold as bundles. Prior studies confirm that there may not be a unique unit-level equilibrium price. We claim a distribution of prices satisfy a given allocation and describe a technique to determine these distributions. Gibbs Sampling allows us to discover characteristics of combinatorial auctions based on the allocated bids. We extract the market-influenced unit-level price, bidder profit, reservation discount distributions and are able to find patterns that depict synergies between products. The posterior distribution provides insights useful to managerial decision making.