Moving from Data-Constrained to Data-Enabled Research: Experiences and Challenges in Collecting, Validating and Analyzing Large-Scale e-Commerce Data

Widespread e-commerce activity on the Internet has led to new opportunities to collect vast amounts of micro-level market and nonmarket data. In this paper we share our experiences in collecting, validating, storing and analyzing large Internet-based data sets in the area of online auctions, music file sharing and online retailer pricing. We demonstrate how such data can advance knowledge by facilitating sharper and more extensive tests of existing theories and by offering observational underpinnings for the development of new theories. Just as experimental economics pushed the frontiers of economic thought by enabling the testing of numerous theories of economic behavior in the environment of a controlled laboratory, we believe that observing, often over extended periods of time, real-world agents participating in market and nonmarket activity on the Internet can lead us to develop and test a variety of new theories. Internet data gathering is not controlled experimentation. We cannot randomly assign participants to treatments or determine event orderings. Internet data gathering does offer potentially large data sets with repeated observation of individual choices and action. In addition, the automated data collection holds promise for greatly reduced cost per observation. Our methods rely on technological advances in automated data collection agents. Significant challenges remain in developing appropriate sampling techniques integrating data from heterogeneous sources in a variety of formats, constructing generalizable processes and understanding legal constraints. Despite these challenges, the early evidence from those who have harvested and analyzed large amounts of e-commerce data points toward a significant leap in our ability to understand the functioning of electronic commerce.Comment: Published at http://dx.doi.org/10.1214/088342306000000231 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

An Empirical Investigation of Bidding Strategies and Their Effects on Online Single-Unit Auctions

Online bidding strategy is one of the most discussed topics in online auction research. This research aims to empirically confirm online bidding strategies in single-unit auctions and evaluate these strategies in the context of auction winning outcome, final price evaluation, and perceived enjoyment. Both objective and subjective data of online single-unit auctions were collected to validate our postulated hypotheses. Our findings suggest that there are three basic bidding strategies in single-unit auctions and they indeed have different impacts on auction biddings

Designing Intelligent Software Agents for B2B Sequential Dutch Auctions: A Structural Econometric Approach

We study multi-unit sequential Dutch auctions in a complex B2B context. Using a large real-world dataset, we apply structural econometric analysis to recover the parameters governing the distribution of bidders’ valuations. The identification of these parameters allows us to simulate auction results under different designs and perform policy counterfactuals. We also develop a dynamic optimization approach to guide the setting of key auction parameters. Given the bounded rationality of human decision makers, we propose to augment auctioneers’ capabilities with high performance decision support tools in the form of software agents. Our paper contributes to both theory and practice of auction design. From the theoretical perspective, this is the first study that explicitly models the sequential aspects of Dutch auctions using structural econometric analysis. From the managerial perspective, this paper offers useful implications to business practitioners for complex decision making in B2B auctions

Designing smart markets

Electronic markets have been a core topic of information systems (IS) research for last three decades. We focus on a more recent phenomenon: smart markets. This phenomenon is starting to draw considerable interdisciplinary attention from the researchers in computer science, operations research, and economics communities. The objective of this commentary is to identify and outline fruitful research areas where IS researchers can provide valuable contributions. The idea of smart markets revolves around using theoretically supported computational tools to both understand the characteristics of complex trading environments and multiechelon markets and help human decision makers make real-time decisions in these complex environments. We outline the research opportunities for complex trading environments primarily from the perspective o

Does it Pay Off to Bid Aggressively? An Empirical Study

In this research, we empirically investigate the payoff of aggressive bidding in an online auction. To address our research question, we use a unique and very rich dataset containing actual market transaction data for approximately 7,000 pay-per-bid auctions. Our research design allows us to isolate the impact of bidding aggressively in an attempt to signal a high valuation on the probability to win an auction. In particular, we analyze more than 600,000 bids placed manually by approximately 2,600 distinct auction participants. The strong and significantly negative effect of aggressive bidding on the likelihood of winning an auction revealed by our analysis suggests that an aggressive bidding strategy is not beneficial in increasing the chances of winning an online auction

Commitment Cost and Product Valuation in Online Auctions: An Experimental Research

This research aims to explore bidder behavioral conditionings and value creation when bidding in online auctions. The cost of commitment imposed by an auction mechanism is hypothesized to impact one’s willingness to pay, level of satisfaction with the transaction, and intention of using the auction mechanism in future online transactions. After reviewing auction mechanisms and behavioral economics, an experiment is proposed as the naturalistic setting of preference to study behavior in online auctions

A Principal-Agent Model of Bidding Firms in Multi-Unit Auctions

Principal-agent relationships in bidding firms are widespread in high-stakes auctions. Often only the agent has information about the value of the objects being sold. The board wants to maximize the profit, but the management wants to win the package with the highest value. In environments in which it is efficient for firms to coordinate on jointly winning packages, we show that the principals would coordinate, while the agents would not. We analyze environments with decreasing levels of information that the principal has about the valuations. Depending on the auction format it can be impossible to set budget constraints that align the agents’ strategies in equilibrium. The analysis helps explain price wars in high-stakes auctions

Assessing online e-marketing and disposal in Neyveli Lignite Corporation Limited (India)

Marketing function per se is undergoing a shift in managing transaction in a transparent emarketing way (Kauffman et al, 2004) especially in Indian Public Sector Undertakings (PSU) – see Reynolds et al (2007). The effectiveness of e-marketing and disposal system of scrap and purchases in PSUs, namely NLC Ltd and ICF, have been studied. Factors such as e-auction offers, time of auction, experience, security deposit (EMD), basic rate per unit, allotment of bid, acceptance of bid; payment and delivery of successful bids on select items in two PSUs over a period of three to five years have been dealt with. The study adds strength to the concept of e-marketing as well as to the theory of marketing