166893960
Priority pricing of integrated services networks
57631
Insights and analyses of online auctions
7914809
Predicting Bidders' Willingness to Pay in Online Multiunit Ascending Auctions: Analytical and Empirical Insights
We develop a real-time estimation approach to predict bidders' maximum willingness to pay in a multiunit ascending uniform-price and discriminatory-price (Yankee) online auction. Our two-stage approach begins with a bidder classification step, which is followed by an analytical prediction model. The classification model identifies bidders as either adopting a myopic best-response (MBR) bidding strategy or a non-MBR strategy. We then use a generalized bid-inversion function to estimate the willingness to pay for MBR bidders. We empirically validate our two-stage approach using data from two popular online auction sites. Our joint classification-and-prediction approach outperforms two other naive prediction strategies that draw random valuations between a bidder's current bid and the known market upper bound. Our prediction results indicate that, on average, our estimates are within 2% of bidders' revealed willingness to pay for Yankee and uniform-price multiunit auctions. We discuss how our results can facilitate mechanism-design changes such as dynamic-bid increments and dynamic buy-it-now prices.
17233820
IT-enabled transparent electronic markets: the case of the air travel industry
The electronic market hypothesis predicts that by reducing coordination costs, information technology (IT) will shift industrial organization from hierarchical to market-based forms of economic activity. While academic researchers and practitioners have witnessed these shifts with the advent of the Internet, there is little understanding about the process and the underlying forces that drive them. In this paper, we provide an in-depth analysis of the air travel industry, which has recently experienced significant IT-driven transformations. We conclude that, together with IT, pro-competitive laws and the information-intensive nature of air travel products have triggered competition for consumers with transparent market mechanisms, which is leading to the emergence of more transparent electronic markets in the air travel industry.
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.
30721210
Economic analysis of consumer purchase intentions in electronic and traditional retail channels: competitive and strategic implications
We develop a multiattribute economic model to analyze consumer behavior for traditional and electronic channels based on consumers' risk profiles and risk-neutral or risk-averse. We then conduct comparative analyses of consumer purchase decisions to derive strategies for different channels. We study the attitudinal and economic factors that lead to specific purchase decisions under different combinations of price, delivery time, and product customization. We develop theoretical propositions concerning consumer channel switching behavior, incentives to consumers, and pricing strategies for different channels. We also use simulations to gain insights for cases where analytical model becomes intractable.
14869645
Multi-modality model-based registration in the cardiac domain
Recent advances in CT technology have made possible the acquisition of high resolution images of the heart in which important anatomical features such as the coronary vessels are visible. The state of the art in MR Imaging techniques, on the other hand, typically provides lower resolution but can facilitate the differentiation of viable (healthy) cardiac tissue from infarcted (injured) tissue. The registration of CT and MR images of the same heart permit the association of anatomy with function. As an example, given an infarcted region, the coronary vessels responsible for irrigating that region may be isolated and targeted for treatment (e.g., coronary bypass). We demonstrate a software package, PROTEUS, which is capable of registering CT and MR images. Since the manifestation of cardiac tissue in the two modalities differs so greatly we rely on features to perform the matching. Specifically, we employ a model-based approach that relies on segmented contours delineating the inner and outer borders of the left ventricle (LV). Given these contours, our technique is completely automatic.
155165
Multivariate Integration on Hypercubic and Mesh Networks
Abstract We analyze a class of adaptive algorithms for integration over N-dimensional hyper-rectangular or simplical regions, on distributed systems. An adaptive algorithm attempts to achieve the requested accuracy by refining the subdivision of the integration region, thus allowing for a concentration of subdivisions near singularities. At the subdivision of a region, the error behaves according to a prescribed model, relating the error of the parent region to that of its children. The analysis can also be applied to problems in other areas, as long as the task selection is based on a priority function which behaves according to a suitable model. Using an efficient management of the subregions, we show that an O (p/ log p) speedup can be achieved on a p-processor hypercubic network, such as shuffle exchange, butterfly and hypercube. Furthermore, a speedup of O ( p ) can be achieved on a p × p mesh network. We also show that our algorithms compare favorably with well-known dynamic load balancing strategies.
46325618
Policy Framework for Autonomic Data Managemen
41429895
Explanation-based Failure Recovery
Interactions are inherent in design-type problem-solving tasks where only partially compiled operators are available. Failures arising from such interactions can best be recovered by explaining them in the underlying domain models. In this paper we explain how Explanation-Based Learning provides a framework for recovering in this manner. This approach also alleviates some of the problems associated with the least-commitment approach to design-type problem-solving.
1276171
Using Lagrangean Relaxation for Service Location Planning with QoS Constraints in Large-Scale Networks
Current trends in computing indicate that there is a great potential for service oriented computing and similar technologies, such as Cisco's Application Oriented Networks, where services provide a higher-level of abstraction to traditional applications. In such cases, providing and consuming services and establishing a relationship between consumers (users of services) and producers (providers of services) are still challenging and vastly researched aspects. We define a service location planning problem (SLP) that is novel in the approach it takes to match consumers to producers, such that the cost of providing services is minimized while taking into account quality of service constraints of throughput and delay. In previous work, we presented an integer linear programming (ILP) model to formulate the service location planning problem. In this paper, we present Lagrangean Relaxation of the model for large-scale networks. We use the approach of Trick [3] to decrease computational overheads.