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.
166893960
Priority pricing of integrated services networks
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.
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.
3094106
LIPTUS: associating structured and unstructured information in a banking environment
Growing competition has made today's banks understand the value of knowing their customers better. In this paper, we describe a tool, LIPTUS, that associates the customer interactions (emails and transcribed phone calls) with customer and account profiles stored in an existing data warehouse. The associations discovered by LIPTUS enable analytics spanning the customer and account profiles on one hand and the meta-data associated or derived from the interaction (using text mining techniques) on the other. We illustrate the value derived from this consolidated analysis through specific customer intelligence applications. LIPTUS is today being extensively used in a large bank in India. A highlight of this paper is a discussion of the technical challenges encountered while building LIPTUS and deploying it on real-life customer data.
46325618
Policy Framework for Autonomic Data Managemen
107769190
Hack I.T. - Security Through Penetration Testing
Hack I.T. introduces penetration testing and its vital role in an overall network security plan. You will learn about the roles and responsibilities of a penetration testing professional, the motivation and strategies of the underground hack community, and potential system vulnerabilities, along with corresponding avenues of attack. Most importantly, the book provides a framework for performing penetration testing and offers step-by-step descriptions of each stage in the process. The latest information on the necessary hardware for performing penetrating testing, as well as an extensive reference on the available security tools, is included.
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.
11252982
Segmentation of range images as the search for geometric parametric models
Segmentation of range images has long been considered in computer vision as an important but extremely difficult problem. In this paper we present a new paradigm for the segmentation of range images into piecewise continuous surfaces. Data aggregation is performed via model recovery in terms of variable-order bi-variate polynomials using iterative regression. Model recovery is initiated independently in regularly placed seed regions in the image. All the recovered models are potential candidates for the final description of the data. Selection of the models is defined as a quadratic Boolean problem, and the solution is sought by the WTA (winner-takes-all) technique, which turns out to be a good compromise between the speed of computation and the accuracy of the solution. The overall efficiency of the method is achieved by combining model recovery and model selection in an iterative way. Partial recovery of the models is followed by the selection (optimization) procedure and only the “best” models are allowed to develop further.The major novelty of the approach lies in an effective combination of simple component algorithms, which stands in contrast to methods which attempt to solve the problem in a single processing step using sophisticated means. We present the results on several real range images.