Knowledge that Transforms

Wicked problems like sustainable energy and financial market stability are societal challenges that arise from complex sociotechnical systems in which numerous social, economic, political, and technical factors interact. Understanding and mitigating these problems requires research methods that scale beyond the traditional areas of inquiry of information systems (IS) individuals, organizations, and markets and that deliver solutions in addition to insights. We describe an approach to address these challenges through competitive benchmarking (CB), a novel research method that helps interdisciplinary research communities tackle complex challenges of societal scale by using different types of data from a variety of sources such as usage data from customers, production patterns from producers, public policy and regulatory constraints, etc. for a given instantiation. Further, the CB platform generates data that can be used to improve operational strategies and judge the effectiveness of regulatory regimes and policies. We describe our experience applying CB to the sustainable energy challenge in the Power Trading Agent Competition (Power TAC) in which more than a dozen research groups from around the world jointly devise, benchmark, and improve IS-based solutions.

Timing online auctions to attract a large number of prospective buyers is important for sellers. This study examines whether online auction sellers need to account for exogenous effects like TV viewing when timing and predicting their auction results. An ongoing debate questions whether TV viewers can spread their attention across multiple devices while watching TV, for example, by concurrently shopping online or posting on social media. Recent research has focused on understanding cross-media effects; however, little attention has been given to TV viewership’s relationship with a very important economic activity, namely participation in online auctions. We examine this potential cross-media effect by analyzing the four-year sales history of a German online auction platform and addressing potential endogeneity problems with an instrumental variable approach. We use three different instrumental variables that have different advantages and disadvantages but can, in sum, be used for triangulation as they lead to the same result. The analyses reveal a significant negative cross media effect between TV consumption and online auction sales, indicating that TV consumption and online auction sales might compete for the scarce attention of consumers and are thus substitutes for each other rather than complements.

The number of mobile apps launched in the market has exponentially grown to more than 2 million, but little is known about how users choose and consume apps of numerous categories. This study devel...

The emerging field of data analytics and the increasing importance of data and information in decision making has created a large market for buying and selling information and information-related s...

The two leading online consumer-to-consumer platforms use very different revenue models: eBay.com in the United States uses a brokerage model in which sellers pay eBay on a transaction basis, whereas Taobao.com in China uses an advertising model in which sellers can use the basic platform service for free and pay Taobao for advertising services to increase their exposure. This paper studies how the chosen revenue model affects the revenue of a platform, buyers’ payoffs, sellers’ payoffs, and social welfare. We find that when little space can be dedicated to advertising under the advertising model, the brokerage model generates more revenue for the platform than the advertising model. When a significant proportion of space is dedicated to advertising under the advertising model, matching probability on a platform plays a critical role in determining which revenue model can generate more revenue: If the matching probability is high, the brokerage model generates more revenue; otherwise, the advertising model generates more revenue. Buyers are always better off under the advertising model because of larger participation by the sellers in the platform’s free service. Sellers are better off under the advertising model in most scenarios. The only exception is when the matching probability is low and the platform dedicates considerable space to advertising. Under these conditions, the sellers with payoffs similar to the marginal advertiser who is indifferent about advertising can be worse off under the advertising model. Finally, the advertising model generates more social welfare than the brokerage model.

In this article, we assess the value of information technology related intangible assets and then use data on business practices and management capabilities to understand how this value is distribu...