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.
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.
57631
Insights and analyses of online auctions
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.
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.
166893960
Priority pricing of integrated services networks
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.
17746198
Large—scale parallel numerical integration
We present and analyze strategies which can be used for the parallel computation of large numbers of integrals which may be of different levels of difficulty. Parallelization on the integral level, which is generally used for large numbers of integrals, is combined with parallelization on the subregion level, which enables handling local integration difficulties within individual problems. This results in a new, hierarchical algorithm which incorporates load balancing on the integral level and on the subregion level. We report test results of the software and show that the hierarchical approach leads to a scalable integration algorithm.
2044368
AGATHA: An Integrated Expert System to Test and Diagnose Complex Personal Computer Boards
PA-RISC is Hewlett-Packard's (HP) reduced instruction set computer (RISC) architecture that is used in its high-performance computer systems (Mahon et al. 1986). Implementations of this architecture have produced some of the most complex processor boards that HP makes (Robinson et al. 1987; Gassman et al. 1987): They can contain as many as 8 very large scale integrated (VLSI) chips—most of them custom, from central processing units to bus controllers to floating-point pro-cessors—several high-speed random-access memory arrays, one or more high-speed buses with over 100 lines, and many other components. In large part because of this complexity, the testing of PA-RISC processor boards became a bottleneck, resulting in an undesirable backlog of undiagnosed boards, growing at a rate of 10 percent each month.
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.
37839097
Retaining personal expression for social search
Web is being extensively used for personal expression, which includes ratings, reviews, recommendations, blogs. This user created content, e.g. book review on Amazon.com, becomes the property of the website, and the user often does not have easy access to it. In some cases, user's feedback may get averaged with feedback from other users e.g. ratings of a video. We argue that the creator of such content needs to be able to retain (a link to) her created content. We introduce the concept of MEB which is a user controlled store of such retained links. A MEB allows a user to access/share all the reviews she has given on different websites. With this capability users can allow their friends to search through their feedback. Searching through one's social network allows harnessing the power of social networks where known relationships provide the context & trust necessary to interpret feedback.