57631
Insights and analyses of online auctions
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.
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.
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.
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.
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.
5989555
Enhanced Business Intelligence using EROCS
The EROCS technology automatically links unstructured data with relevant structured data from an external relational database. We demonstrate how EROCS can be used for enhancing business intelligence by allowing OLAP tools to analyze structured and unstructured data in a consolidated manner. Our demonstration showcases the use of EROCS in exploiting latent information in customer emails, which helps in building a complete view of the customer. This results in new insights about the business which are not possible with the existing state of the art.
22600988
Towards Automated Privacy Compliance in the Information Life Cycle
Management of data is an increasingly challenging task for enterprises because of the increasingly diverse and complex requirements that come to bear from various fronts. One issue is the protection of the privacy of the information held, while ensuring compliance with various rules and regulations relating to data management.One issue is the protection of the privacy of the information held, while ensuring compliance with various rules and regulations relating to data management. Privacy may be defined as the claim of individuals, groups and institutions to determine for themselves when, how and to what extent information about them is communicated to others. In its broadest scope this is a problem that has challenged civil rights advocates the world over, at different times.
195894838
Dynamic Access Control Framework Based On Events.
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.
62972305
On the complexity of computation and learning in neural networks
This dissertation is on the complexity of computation and learning in Neural Networks. One of the reasons for studying neural networks is that they provide a computational model which seems closer to the computational framework employed by the human brain for information processing than the conventional computers. Neural networks are highly simplified model of the human brain and one hopes that by attaining a proper understanding of the computational aspects in neural networks, one can gain significant insights into the computational characteristics of the human brain. 
In this dissertation, we have considered three different kinds of neural networks, namely, the Boltzmann Machines, the Hopfield Nets and the Feedforward Neural Nets. We studied the computational and learning abilities of these networks from a complexity theory point of view. We also related the computational power of various neural nets, in particular, the Boltzmann Machines and the Feedforward Neural Nets which are also known as Threshold circuits in the complexity theory literature.