Price Formation And Its Dynamics In Online Auctions

This research uses functional data modelling to study the price formation process of online auctions. It conceptualizes the price curve and its first and second derivatives(velocity and acceleration respectively) as the primary objects of interest. Together these three functional objects permit us to talk about the energy of an auction, and how the influence of its determinants vary as a function of auction time. For instance, we find that the incremental impact of an additional bidder's arrival on the rate of price increase is smaller towards the end of the auction. Our analysis suggests that "stakes" do matter and that the rate of price increase is faster for more expensive items, especially at the start and the end of an auction. It is observed that higher seller ratings (which correlate with experience) positively influence the price dynamics, but the effect is weaker in auctions with longer durations. Interestingly, we find that the price level is negatively related to auction duration when the seller has low rating whereas in auctions with high-rated sellers longer auctions achieve higher price levels throughout the auction, and especially at the start and end. Our methodological contributions include the introduction of functional data analysis as a viable toolkit for exploring the structural characteristics of electronic markets.

Explore cutting-edge statistical methodologies for collecting, analyzing, and modeling online auction data Online auctions are an increasingly important marketplace, as the new mechanisms and formats underlying these auctions have enabled the capturing and recording of large amounts of bidding data that are used to make important business decisions. As a result, new statistical ideas and innovation are needed to understand bidders, sellers, and prices. Combining methodologies from the fields of statistics, data mining, information systems, and economics, Modeling Online Auctions introduces a new approach to identifying obstacles and asking new questions using online auction data. The authors draw upon their extensive experience to introduce the latest methods for extracting new knowledge from online auction data. Rather than approach the topic from the traditional game-theoretic perspective, the book treats the online auction mechanism as a data generator, outlining methods to collect, explore, model, and forecast data. Topics covered include: Data collection methods for online auctions and related issues that arise in drawing data samples from a Web site Models for bidder and bid arrivals, treating the different approaches for exploring bidder-seller networks Data exploration, such as integration of time series and cross-sectional information; curve clustering; semi-continuous data structures; and data hierarchies The use of functional regression as well as functional differential equation models, spatial models, and stochastic models for capturing relationships in auction data Specialized methods and models for forecasting auction prices and their applications in automated bidding decision rule systems Throughout the book, R and MATLAB software are used for illustrating the discussed techniques. In addition, a related Web site features many of the book's datasets and R and MATLAB code that allow readers to replicate the analyses and learn new methods to apply to their own research. Modeling Online Auctions is a valuable book for graduate-level courses on data mining and applied regression analysis. It is also a one-of-a-kind reference for researchers in the fields of statistics, information systems, business, and marketing who work with electronic data and are looking for new approaches for understanding online auctions and processes. Visit this book's companion website by clicking here

Electronic commerce, and in particular online auctions, have received an extreme surge of popularity in recent years. While auction theory has been studied for a long time from a game-theory perspective, the electronic implementation of the auction mechanism poses new and challenging research questions. In this work, we focus on the price formation process and its dynamics. We present a new source of rich auction data and introduce an innovative way of modelling and analyzing price dynamics. We represent auctions as functional objects by accommodating the special structure of bidding data. We then use functional data analysis to characterize different types of auctions. Our findings suggest that there are several types of dynamics even for auctions of comparable items. By profiling these differences with respect to features associated with the auction format, the seller and the winner we find new relationships between dynamics and auction settings, and we tie these findings to the existing literature on online auctions.

This groundbreaking volume introduces new methodological approaches to data analysis as well as new techniques for collecting and cataloging transactional data to assist IS researchers in dealing with new and radical forms of IT innovation that continue to energize electronic commerce.

The methods and thinking of economics permeate a large part of the IS discipline. Reciprocally, newly emerging research methods relying on the IT-enabled treatment of massive data aggregates feed economic research. As new and radical forms of IT innovation continue to energize electronic commerce, IS researchers face a daunting task in using existing empirical methods and tools to understand the threats, opportunities, risks, and rewards of these new techniques. This groundbreaking volume leads the way. It introduces new methodological approaches to data analysis as well as new techniques for collecting and cataloging transactional data. The ideas it presents have broad appeal and demonstrate what is possible when new techniques and new ways of thinking are brought to bear on complex research problems.

Internet Auctions reviews recent empirical and theoretical works on internet auctions with a focus on internet auction design, formats, and features that are currently debated in the marketing literature.

Focuses on presenting specific innovative computing artifacts and tools developed by researchers that are not commercially used. This work 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 business processes.

Dr. Jay Liebowitz Orkand Endowed Chair in Management and Technology University of Maryland University College Graduate School of Management & Technology 3501 University Boulevard East Adelphi, Maryland 20783-8030 USA jliebowitz@umuc. edu When I first heard the general topic of this book, Marketing Intelligent Systems or what I’ll refer to as Marketing Intelligence, it sounded quite intriguing. Certainly, the marketing field is laden with numeric and symbolic data, ripe for various types of mining—data, text, multimedia, and web mining. It’s an open laboratory for applying numerous forms of intelligentsia—neural networks, data mining, expert systems, intelligent agents, genetic algorithms, support vector machines, hidden Markov models, fuzzy logic, hybrid intelligent systems, and other techniques. I always felt that the marketing and finance domains are wonderful application areas for intelligent systems, and this book demonstrates the synergy between marketing and intelligent systems, especially soft computing. Interactive advertising is a complementary field to marketing where intelligent systems can play a role. I had the pleasure of working on a summer faculty f- lowship with R/GA in New York City—they have been ranked as the top inter- tive advertising agency worldwide. I quickly learned that interactive advertising also takes advantage of data visualization and intelligent systems technologies to help inform the Chief Marketing Officer of various companies. Having improved ways to present information for strategic decision making through use of these technologies is a great benefit.

Agents are software processes that perceive and act in an environment, processing their perceptions to make intelligent decisions about actions to achieve their goals. Multi-agent systems have multiple agents that work in the same environment to achieve either joint or conflicting goals. Agent computing and technology is an exciting, emerging paradigm expected to play a key role in many society-changing practices from disaster response to manufacturing to agriculture. Agent and mul- agent researchers are focused on building working systems that bring together a broad range of technical areas from market theory to software engineering to user interfaces. Agent systems are expected to operate in real-world environments, with all the challenges complex environments present. After 11 successful PRIMA workshops/conferences (Pacific-Rim International Conference/Workshop on Multi-Agents), PRIMA became a new conference titled “International Conference on Principles of Practice in Multi-Agent Systems” in 2009. With over 100 submissions, an acceptance rate for full papers of 25% and 50% for posters, a demonstration session, an industry track, a RoboCup competition and workshops and tutorials, PRIMA has become an important venue for multi-agent research. Papers submitted are from all parts of the world, though with a higher representation of Pacific Rim countries than other major multi-agent research forums. This volume presents 34 high-quality and exciting technical papers on multimedia research and an additional 18 poster papers that give brief views on exciting research.