P rior research has generated considerable knowledge on information systems design from software engineering and user-acceptance perspectives. As organizational processes are increasingly embedded within information systems, one of the key considerations of many business processes-organizational incentives-should become an important dimension of any information systems design and evaluation, which we categorize as the third dimension: incentive alignment. Incentive issues have become important in many IS areas, including distributed decision support systems (DSS), knowledge management, and e-business supply chain coordination. In this paper we outline why incentives are important in each of these areas and specify requirements for designing incentive-aligned information systems. We identify and define important unresolved problems along the incentive-alignment dimension of information systems and present a research agenda to address them.

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W e study the stock market reaction to announcements of global green vehicle innovation over a 14-year time span (1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009) using the event study methodology. We document that the stock market generally reacts positively to automakers' announcements of environmental innovations, consistent with prior research on the wealth effects of innovation announcements. Our results indicate that crucial green product development decisions such as innovation type and market segment choices exert direct influence on a firm's market value. These results hold after controlling for firm size, leverage, profitability, R&D intensity, and oil price changes.

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There has been an extensive research literature on auctions, but recent developments in technology have resulted in new interest in auction mechanisms as a practical way of allocating resources. This paper presents a new double-auction mechanism to handle resource allocation for public goods when complementarity exists. The mechanism is placed in the context of an organization's internal knowledge investment. Knowledge goods have two distinct characteristics. First, knowledge within an organization can be considered a public good, so it is subject to the free-rider problem. Second, knowledge is interrelated and interdependent; that is, there is complementarity among knowledge components. The value of knowledge often derives from a bundle of knowledge components, rather than from its individual pieces. These two characteristics present a serious challenge to allocating organizational resources for knowledge goods. We introduce an internal market in which knowledge providers offer knowledge projects and knowledge consumers place bids to acquire them. The mechanism is a Groves-Clarke-type double auction that allows bundled knowledge goods to be traded so as to recognize complementarities between knowledge projects. The market mechanism we propose is incentive compatible; i.e., it induces people to reveal their true valuation. In addition, it allows trades of knowledge bundles to determine which knowledge components are most valuable from the organization's viewpoint. Under mild assumptions, the mechanism is a computationally tractable solution to operating a market of bundled public goods. We further show how "imputed prices" can be calculated for subsets of knowledge components and prove that a market mechanism that does not allow bundle orders or does not address the free-rider problem yields a systematic underinvestment in knowledge.Mechanism Design, Knowledge Sharing, Incentive Compatibility, Public Goods, Bundle Auction, Knowledge Investment

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Traditional development of large-scale information systems is based on centralized information processing and decision making. With increasing competition, shorter product life-cycle, and growing uncertainties in the marketplace, centralized systems are inadequate in processing information that grows at an explosive rate and are unable to make quick responses to real-world situations. Introducing a decentralized information system in an organization is a challenging task. It is often intertwined with other organizational processes. The goal of this research is to outline a new approach in developing a supply chain information system with a decentralized decision making process. Particularly, we study the incentive structure in the decentralized organization and design a market-based coordination system that is incentive aligned, i.e., it gives the participants the incentives to act in a manner that is beneficial to the overall system. We also prove that the system monotonically improves the overall organizational performance and is goal congruent.

Crowdsourcing relies on online platforms to connect a community of users to perform specific tasks. However, without appropriate control, the behavior of the online community might not align with the platform's designed objective, which can lead to an inferior platform performance. This paper investigates how the feedback information on a crowdsourcing platform and systematic bias of crowdsourcing workers can affect crowdsourcing outcomes. Specifically, using archival data from the online crowdsourcing platform Kaggle, combined with survey data from actual Kaggle contest participants, we examine the role of a systematic bias, namely the salience bias, in influencing the performance of the crowdsourcing workers and how the number of crowdsourcing workers moderates the impact of the salience bias as a result of the parallel path effect and competition effect. Our results suggest that the salience bias influences the performance of contestants, including the winners of the contests. Furthermore, the parallel path effect cannot completely eliminate the impact of the salience bias, but it can attenuate it to a certain extent. By contrast, the competition effect is likely to amplify the impact of the salience bias. Our results have critical implications for crowdsourcing firms and platform designers.