86498042
Business Computing
This book is broadly organized in three parts. The first section ('Enhancing and Managing Customer Value') focuses on presenting the state-of-knowledge in managing and enhancing customer value through extraction of consumer-centric knowledge from mountains of data that modern interactive applications generate. The extracted information can then be used to provide more personalized information to customers, provide more relevant information or products, and even to create innovative business processes to enhance overall value to customers. The second section in the book ('Computational Approaches for Business Processes') focuses on presenting several specific innovative computing artifacts and tools developed by researchers that are not yet commercially used. These represent cutting-edge thought and advances in business computing research that should soon find utility in real-world applications or as a tool to analyze real-world scenarios.The final section in the book ('Supporting Knowledge Enterprise') presents approaches and frameworks that focus on ability of an enterprise to analyze, build, and protect computing infrastructure that supports value-added dimensions to the enterprise's existing business processes.
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.
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.
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.
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.
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.
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.
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.
62172477
A unified framework for uncertainty propagation in automatic shape tracking
Uncertainty handling plays an important role during shape tracking. We have recently shown that the fusion of measurement information with system dynamics and shape priors greatly improves the tracking performance for very noisy images such as ultrasound sequences [22]. Nevertheless, this approach required user initialization of the tracking process. This paper solves the automatic initialization problem by performing boosted shape detection as a generic measurement process and integrating it in our tracking framework. We show how to propagate the local detection uncertainties of multiple shape candidates during shape alignment, fusion with the predicted shape prior, and fusion with subspace constraints. As a result, we treat all sources of information in a unified way and derive the posterior shape model as the shape with the maximum likelihood. Our framework is applied for the automatic tracking of endocardium in ultrasound sequences of the human heart. Reliable detection and robust tracking results are achieved when compared to existing approaches and inter-expert variations.