Results

Found 3 articles

Clear filters

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

2013 | International Conference on Information Systems | Citations: 0
Authors: Lu, Yixin; Gupta, Alok; Ketter, Wolfgang; Heck, Eric Van

Abstract: We study multi-unit sequential Dutch auctions in a complex B2B context. Using a ... Expand

Abstract: 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. Collapse

Semantic filters: software agent theory of bounded rationality

Topics: decision making business-to-business software agent decision support decision support system

Methods: optimization model econometric modeling simulation Kolmogorov-Smirnov test dynamic programming

Theories: theory of bounded rationality
Self-Selection and Information Role of Online Product Reviews
PDF
2008 | Information Systems Research | Citations: 14
Authors: Li, Xinxin; Hitt, Lorin M.

Abstract: Online product reviews may be subject to self-selection biases that impact consu ... Expand

Abstract: Online product reviews may be subject to self-selection biases that impact consumer purchase behavior, online ratings' time series, and consumer surplus. This occurs if early buyers hold different preferences than do later consumers about the quality of a given product. Readers of early product reviews may not successfully correct for these preference differences when interpreting ratings and making purchases. In this study, we develop a model that examines how idiosyncratic preferences of early buyers can affect long-term consumer purchase behavior as well as the social welfare created by review systems. Our model provides an explanation for the structure of product ratings over time, which we empirically test using online book reviews posted on Amazon.com. Our analysis suggests that firms could benefit from altering their marketing strategies such as pricing, advertising, or product design to encourage consumers likely to yield positive reports to self-select into the market early and generate positive word-of-mouth for new products. On the other hand, self-selection bias, if not corrected, decreases consumer surplus. Collapse

Semantic filters: software agent theory of bounded rationality

Topics: IS economics consumer surplus marketing management price management word of mouth

Methods: descriptive statistic time series analysis longitudinal research logistic regression statistical power analysis

Theories: theory of bounded rationality
Mechanism design for software agents with complete information
PDF
2005 | Decision Support Systems | Citations: 1
Authors: O'Connell, Thomas C.; Stearns, Richard E.

Abstract: We investigate the mechanism design problem when the agents and the mechanism ha ... Expand

Abstract: We investigate the mechanism design problem when the agents and the mechanism have computational restrictions. In particular, we examine how results in the mechanism design literature are affected when the social choice rule requires the mechanism to solve a computationally difficult optimization problem. Both dominant strategy and Nash implementation are considered for a multiagent version of the maximum satisfiability problem. We show that the best a mechanism can guarantee is that at least half of the maximum number of simultaneously satisfiable agents will be satisfied by the outcome. Our analysis highlights some of the difficulties that arise in applying results from mechanism design to computational problems. In particular, our results show that using approximation in multiagent settings can be much less successful than in traditional computational settings because of the game theoretic guarantees required of the outcomes. Collapse

Semantic filters: software agent theory of bounded rationality

Topics: software agent

Methods: computational algorithm optimization model

Theories: theory of bounded rationality game theory

Page 1 of 1

AIS11

Journals

Conferences

Semantic Filter

Found 3 articles

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

Self-Selection and Information Role of Online Product Reviews

Mechanism design for software agents with complete information