Knowledge that Transforms

Digital business strategies (DBS) offer significant opportunities for firms to enhance competitiveness. Unlike the large proprietary systems of the 1980s, today's micro-applications allow firms t...

With an abundance of products available online, many online retailers provide sales rankings to make it easier for consumers to find the best-selling products. Successfully implementing product rankings online was done a decade ago by Amazon, and more recently by Apple’s App Store. However, neither market provides actual download data, a very useful statistic for both practitioners and researchers. In the past, researchers developed various strategies that allowed them to infer demand from rank data. Almost all of that work is based on an experiment that shifts sales or collaboration with a vendor to get actual sales data. In this research, we present an innovative method to use public data to infer the rank–demand relationship for the paid apps on Apple’s iTunes App Store. We find that the top-ranked paid app for iPhone generates 150 times more downloads compared to the paid app ranked at 200. Similarly, the top paid app on iPad generates 120 times more downloads compared to the paid app ranked at 200. We conclude with a discussion on an extension of this framework to the Android platform, in-app purchases, and free apps.

The production of performance data in organizations is often described as a functional process that managers enforce on their employees to provide leaders with accurate information about employees’ work and their achievements. This study draws on a 15-month ethnography of a desk sales unit to build a dramaturgical model that explains how managers participate in the production of performance data to impress rather than inform leaders. Research on management information systems is reviewed to outline a protective specification of this model where managers participate in the production of performance data to suppress information that threatens the image they present to leaders. Ethnographic data about the production and use of performance records and performance reports in a desk sales unit is examined to induce an exploitive specification of this dramaturgical model. This specification explains how people can take advantage of the opportunities, rather than just avoid the threats that performance data presents for impression management. It also demonstrates how managers can participate in the production of performance data to create an idealized version of their accomplishments and that leaders reify these data by using them in their own attempts at impressing others. By doing so, leaders and managers turn information systems into store windows to show achievement upward instead of transparent windows to monitor compliance downward.

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.