Design and Evaluation of Feedback Schemes for Multiattribute Procurement Auctions

Multiattribute auctions, which allow bids on multiple dimensions of the product, are IT-enabled sourcing mechanisms that increase the efficiency of procurement for configurable goods and services compared to price-only auctions. Given the strategic nature of procurement auctions, the amount of information concerning the buyer’s preferences that is disclosed to the suppliers has implications on the profits of the buyer and suppliers and, consequently, on the long-term relationship between them. This study develops novel feedback schemes for multiattribute auctions that protect buyer’s preference information from the supplier and suppliers’ cost schedule from the buyer. We conduct a laboratory experiment to study bidder behavior and profit implications under three different feedback regimes. Our results indicate that bidders are able to extract more profit with more information regarding the state of the auction in terms of provisional allocation and prices. Furthermore, bidding behavior is substantially influenced by the nature and type of feedback

Design and Effects of Information Feedback in Continuous Combinatorial Auctions

Advancements in information technologies offer opportunities for designing and deploying innovative market mechanisms. For example, combinatorial auctions, in which bidders can bid on combinations of goods, can increase the economic efficiency of a trade when goods have complementarities. However, lack of real-time bidder support tools has been a major obstacle preventing this mechanism from reaching its full potential. This study uses novel feedback mechanisms to aid bidders in formulating bids in real-time to facilitate participation in continuous combinatorial auctions. Laboratory experiments examine the effectiveness of our feedback mechanisms; the study is the first to examine how bidders behave in such information-rich environments. Our results indicate that feedback results in higher efficiency and higher seller’s revenue compared to the baseline case where bidders are not provided feedback. Furthermore, contrary to conventional wisdom, even in complex economic environments, individuals effectively integrate rich information in their decision making

Design implications of real-time feedback in continuous combinatorial auctions: an experimental investigation.

University of Minnesota Ph.D. dissertation. June 2009. Major: Business Administration. Advisors: Alok Gupta, Gediminas Adomavicius. 1 computer fie (PDF); ix, 134 pages, appendices 1-4. Ill. (some col.)Information Technology (IT) has spawned the growth of novel and innovative market mechanisms (such as online auctions) and associated businesses (such as eBay and Priceline) that were not feasible without the capabilities and reach of these modern information technologies. Previous studies on designing trading mechanisms for online markets primarily viewed them from an economic perspective. There has been virtually no study on how making changes to a mechanism alters its desirability as a mechanism or endogenously affects the behavior of its users. This dissertation takes a holistic look at the issue of designing mechanisms: exploring not only the economic properties of a mechanism but also the dimensions of user acceptance and of user behavior and its impact on the mechanism's performance. We take a multidisciplinary approach, using theories from economics, decision psychology and computer science. We employ laboratory experiments to collect primary data and use well-established methodologies in experimental economics to analyze the data; in addition, we use perceptual methodologies (such as the Technology Acceptance Model) to study the issues related to user acceptance and exploratory data analysis techniques to discover and explore emerging behaviors as features of the mechanism are changed. The combinatorial auction is the context for this study. It is a complex mechanism, where the role of IT in facilitating a user's interaction with the mechanism is abundantly clear. Furthermore, while the mechanism has been used for important resource allocation decisions in industry, its use in the online marketplace is limited, if not non existent. Therefore, the issues of the mechanism's economic adequacy and user acceptance are both of relevance. We find that the design of the mechanism significantly influences not only the economic properties of the mechanism but also its user perceptions. Furthermore, unlike in single-item auctions, in combinatorial auctions bidders are able to generate greater surplus with more transparency of the mechanism. Based on our results, we develop several insights on designing sustainable economic mechanisms

An Empirical Examination of the Economics of Mobile Application Security

The growth of mobile devices coupled with the advances in mobile technologies has resulted in the development and widespread use of a variety of mobile applications (apps). Mobile apps have been developed for social networking, banking, receiving daily news, maintaining fitness, and for job-related tasks. The security of the apps is an important concern. However, in some cases, the app developers may be less interested to invest in the security of the apps, if users are unwilling to pay for the added security. In this paper, we empirically examine whether consumers are less willing to pay for security features than for usability features. In addition, we examine whether a third-party certification of the security features makes customers more willing to pay for security. Furthermore, we investigate the impact of risk perceptions on the willingness of paying for security. To explore these issues, we conduct a scenario-based experiment of mobile app users. Results from our analyses show that, consumers are indeed less likely to pay for security features than usability features. However, the likelihood of paying for security can be significantly increased by third-party certification of the features. Based on our analysis, we offer insights to producers of mobile apps to monetize the enhanced security features of their apps.peerReviewe

Economic Experiments in Information Systems

It has been often suggested that much of the widespread use of economic experiments has been possible only because of the developments in information technology. Yet, the information systems (IS) domain has been largely lagging in its use of the methodology. This commentary is aimed at spurring the use of economic experiments in the IS domain by explaining the advantages of the methodology, and by defining its norms for the benefit of both the authors as well as the reviewers

An Empirical Examination of the Economics of Mobile Application Security

The growth of mobile devices coupled with advances in mobile technologies has resulted in the development and widespread use of a variety of mobile applications (apps). Mobile apps have been developed for social networking, banking, receiving daily news, maintaining fitness, and job-related tasks. The security of apps is an important concern. However, in some cases, app developers may be less interested in investing in the security of apps, if users are unwilling to pay for the added security. In this paper, we empirically examine whether consumers are less willing to pay for security features than for usability features. In addition, we examine whether a third-party certification of security features makes customers more willing to pay for security. Furthermore, we investigate the impact of risk perceptions on the willingness to pay for security. To explore these issues, we conducted a scenario-based experiment on mobile app users. Results from our analyses show that consumers are indeed less likely to pay for security features than usability features. However, the likelihood of paying for security features can be significantly increased by third-party certification of the features. Based on our analysis, we offer insights to producers of mobile apps to monetize the enhanced security features of their apps

Impact of Information Feedback in Continuous Combinatorial Auctions: An Experimental Study of Economic Performance

Advancements in information technology offer opportunities for designing and deploying innovative market mechanisms that can improve the allocation and procurement processes of businesses. For example, combinatorial auctions—in which bidders can bid on combinations of goods—have been shown to increase the economic efficiency of a trade when goods have complementarities. However, the lack of real-time decision support tools for bidders has prevented this mechanism from reaching its full potential. With the objective of facilitating bidder participation in combinatorial auctions, this study, using recent research in real-time bidder support metrics, discusses several novel feedback schemes that can aid bidders in formulating combinatorial bids in real-time. The feedback schemes allow us to conduct continuous combinatorial auctions, where bidders can submit bids at any time. Using laboratory experiments with two different setups, we compare the economic performance of the continuous mechanism under three progressively advanced levels of feedback. Our findings indicate that information feedback plays a major role in influencing the economic outcomes of combinatorial auctions. We compare several important bid characteristics to explain the observed differences in aggregate measures. This study advances the ongoing research on combinatorial auctions by developing continuous auctions that differentiate themselves from earlier combinatorial auction mechanisms by facilitating free-flowing participation of bidders and providing exact prices of bundles on demand in real time. For practitioners, the study provides insights on how the nature of feedback can influence the economic outcomes of a complex trading mechanism