5555268
User Heterogeneity and its Impact on Electronic Auction Market Design: An Empirical Exploration1Research Essays
While traditional information systems research emphasizes understanding of end users from perspectives such as cognitive fit and technology acceptance, it fails to consider the economic dimensions of their interactions with a system. When viewed as economic agents who participate in electronic markets, it is easy to see that users' preferences, behaviors, personalities, and ultimately their economic welfare are intricately linked to the design of information systems. We use a data-driven, inductive approach to develop a taxonomy of bidding behavior in online auctions. Our analysis indicates significant heterogeneity exists in the user base of these representative electronic markets. Using online auction data from 1999 and 2000, we find a stable taxonomy of bidder behavior containing five types of bidding strategies. Bidders pursue different bidding strategies that, in aggregate, realize different winning likelihoods and consumer surplus. We find that technological evolution has an impact on bidders' strategies. We demonstrate how the taxonomy of bidder behavior can be used to enhance the design of some types of information systems. These enhancements include developing user-centric bidding agents, inferring bidders' underlying valuations to facilitate real-time auction calibration, and creating low-risk computational platforms for decision making.
62621279
Estimating Internet Users' Demand Characteristics
We investigate two parametric approaches and one non-parametric approach toestimating Internet users' value-of-time, an important characteristic ofdemand for Internet services. The advantages of these approaches are madeclear and their limitations discussed. The models are tested with datagenerated from our similation model of the Internet economy. Given thecharacteristics of the data, we investigate parametric count-data modelsfirst. While reasonably good results are obtained on all medium- andlarge-sized jobs, the method fails on small-sized ones. Second, we develop anonparametric quasi-Bayesian update algorithm for retrieving the underlyingdistribution function of Internet users' value-of-time purely fromobservations on their choices. Compared with the parametric count-data models,good results are obtained in every case.
166893960
Priority pricing of integrated services networks
11409534
Risk profile and consumer shopping behavior in electronic and traditional channels
This paper develops an economic model that captures consumer shopping channel choices based on shopping channel characteristics and consumer risk profiles--risk-neutral or risk-averse. Analyses of results show that after making purchases through one channel, electronic or traditional, risk-averse consumers tend to be more loyal customers than risk-neutral consumers. Further, the two types of consumers may exhibit split channel behavior--risk-neutral consumers prefer one channel and risk-averse consumers prefer the other. However, risk-neutral consumers are not always more likely to prefer electronic channel than risk-averse consumers. Implications for retailer pricing strategies are discussed.
57631
Insights and analyses of online auctions
15718873
A predictive empirical model for pricing and resource allocation decisions
We present a semi-parametric model that describes pricing behaviors in a market environment, and we show how that model can be used to guide resource allocation and pricing decisions in an autonomous trading agent. We validate our model by presenting experimental results obtained in the Trading Agent Competition for Supply Chain Management.
7664269
Management of Conflicting Obligations in Self-Protecting Policy-Based Systems
Policy-based management of business systems is increasingly becoming the norm for autonomic computing since these systems can adapt to the changing needs and increasing complexity of the underlying organizations or enterprises. One of the vital characteristics of these systems is self-protection, ie., the ability to secure information and resources, by anticipating, detecting, identifying and protecting against any form of unauthorised access and permitting all authorised accesses based on the users' roles and pre-established policies. In this paper, we focus on one aspect of self-protecting autonomous systems, which is, how to automatically enforce privacy policies related to data handling, for compliance and auditing purposes. The automatic management of privacy sensitive information based on enterprise policies that are driven by a combination of user preferences, internal objectives and external regulations is a key aspect to any enterprise to prevent misuse of this information. These policies extend beyond simple authorization rules, and also mandate obligations to be enforced under certain conditions. One issue in the automatic enforcement of obligations is the presence of conflicts among different obligations which mandate different actions on the same resource, based on different conditions in which the resource is accessed. In this paper we propose algorithms for detecting and resolving conflicts among obligations in both static and runtime environments. We then briefly describe our prototype obligation management system with the conflict resolution module that achieves the automated enforcement of obligations for data-handling based on privacy policies
5590959
CAD for polyp detection: an invaluable tool to meet the increasing need for colon-cancer screening
Abstract Colorectal cancer is the third most common cancer in both men and women and it was estimated that in 2003 nearly 150,000 cases would be diagnosed and 57,000 people would die. Screening has been accepted as a means for early detection of the disease, yet only a portion of the eligible population undergoes colorectal cancer screening, partially due to comfort issues of undergoing a full colonoscopic examination. Virtual colonoscopy (VC) has been demonstrated to be an effective means of performing screening and given the number of people who are candidate for screening better tools, such as Computer Aided Detection (CAD), are required to fulfill this increasing need. The developed CAD system, presented in this paper, has focused on the detection of polyps of sizes up to and including 20 mm. The results have demonstrated that: the developed algorithm generalizes, the sensitivity and specificity for middle- to large-sized polyps is on the average 95% while the overall sensitivity is roughly 88% and the false positive has remained at a manageable 4 per volume.
2504115
Database-guided segmentation of anatomical structures with complex appearance
The segmentation of anatomical structures has been traditionally formulated as a perceptual grouping task, and solved through clustering and variational approaches. However, such strategies require the a priori knowledge to be explicitly defined in the optimization criterion, e.g., "high-gradient border", "smoothness"', or "similar intensity or texture". This approach is limited by the validity of underlying assumptions and cannot capture complex structure appearance. This paper introduces database-guided segmentation as a new data-driven paradigm that directly exploits expert annotation of interest structures in large medical databases. Segmentation is formulated as a two-step learning problem. The first step is structure detection where we learn how to discriminate between the object of interest and background. The resulting classifier based on a boosted cascade of simple features also provides a global rigid transformation of the structure. The second step is shape inference where we use a sample-based representation of the joint distribution of appearance and shape annotations. To learn the association between the complex appearance and shape we propose a feature selection mechanism and the corresponding metric. We show that the selected features are better than using directly the appearance and illustrate the performance of the proposed method on a large set of ultrasound heart images.
30968721
Tracking Deformable Templates Using a Shortest Path Algorithm
This paper proposes a new technique to track deformable templates. We extend the typical graph algorithms that have been used for active contour recovery to incorporate shape information. The advantage of graph algorithms is that they are guaranteed to find the global minimum of the energy function. The difficulty with their traditional use for active contours is that they consider only two pixels at a time when recovering the contour, making it impossible to enforce shape constraints. We define the deformable template as a polygonal contour, demonstrate the proper mapping between the image, the contour, and a graph, and show how to apply Dijkstra's algorithm to track contours in image sequences. Examples are shown for deforming contours, articulated objects, and smooth contours being tracked in simple and complicated backgrounds. We also provide an analysis of the computational requirements.
887786
Efficient Design of Boltzmann Machines