Information Systems Research current issue

Editorial Notes

Sambamurthy, V. — Mon, 28 Dec 2009 10:01:22 PST

The performance of the journal is reviewed and metrics for 2009 are presented. In addition, key editorial transitions are highlighted.

An Empirical Analysis of Contract Structures in IT Outsourcing

Chen, Y., Bharadwaj, A. — Mon, 28 Dec 2009 10:01:22 PST

Outsourcing of information technology (IT) services has received much attention in the information systems (IS) literature. However, considerably less attention has been paid to actual contract structures used in IT outsourcing (ITO). Examining contract structures yields important insights into how the contracting parties structure the governance provisions and the factors or transaction risks that influence them. Based on insights from prior literature, from practicing legal experts, and through in-depth content analysis of actual contracts, we develop a comprehensive coding scheme to capture contract provisions across four major dimensions: monitoring, dispute resolution, property rights protection, and contingency provisions. We then develop an empirical data set describing the contract structures across these distinct dimensions, using a sample of 112 ITO contracts from the Securities and Exchange Commission (SEC) database from 1993 to 2003.

Drawing on transaction cost, agency, and relational exchange theories, we hypothesize the effects of transaction and relational characteristics on the specific contractual provisions, as well as on overall contract extensiveness. Furthermore, we examine how these associations vary under conditions of fixed price and time and materials pricing structures. The results provide good support for the main hypotheses of the study and yield interesting insights about contractual governance of ITO arrangements.

Designing Intelligent Software Agents for Auctions with Limited Information Feedback

Adomavicius, G., Gupta, A., Zhdanov, D. — Mon, 28 Dec 2009 10:01:22 PST

This paper presents analytical, computational, and empirical analyses of strategies for intelligent bid formulations in online auctions. We present results related to a weighted-average ascending price auction mechanism that is designed to provide opaque feedback information to bidders and presents a challenge in formulating appropriate bids. Using limited information provided by the mechanism, we design strategies for software agents to make bids intelligently. In particular, we derive analytical results for the important characteristics of the auction, which allow estimation of the key parameters; we then use these theoretical results to design several bidding strategies. We demonstrate the validity of designed strategies using a discrete event simulation model that resembles the mechanisms used in treasury bills auctions, business-to-consumer (B2C) auctions, and auctions for environmental emission allowances. In addition, using the data generated by the simulation model, we show that intelligent strategies can provide a high probability of winning an auction without significant loss in surplus.

How Incorporating Feedback Mechanisms in a DSS Affects DSS Evaluations

Kayande, U., De Bruyn, A., Lilien, G. L., Rangaswamy, A., van Bruggen, G. H. — Mon, 28 Dec 2009 10:01:22 PST

Model-based decision support systems (DSS) improve performance in many contexts that are data-rich, uncertain, and require repetitive decisions. But such DSS are often not designed to help users understand and internalize the underlying factors driving DSS recommendations. Users then feel uncertain about DSS recommendations, leading them to possibly avoid using the system. We argue that a DSS must be designed to induce an alignment of a decision maker's mental model with the decision model embedded in the DSS. Such an alignment requires effort from the decision maker and guidance from the DSS. We experimentally evaluate two DSS design characteristics that facilitate such alignment: (i) feedback on the upside potential for performance improvement and (ii) feedback on corrective actions to improve decisions. We show that, in tandem, these two types of DSS feedback induce decision makers to align their mental models with the decision model, a process we call deep learning, whereas individually these two types of feedback have little effect on deep learning. We also show that deep learning, in turn, improves user evaluations of the DSS. We discuss how our findings could lead to DSS design improvements and better returns on DSS investments.

Trans-Situated Learning: Supporting a Network of Practice with an Information Infrastructure

Vaast, E., Walsham, G. — Mon, 28 Dec 2009 10:01:23 PST

This paper investigates the practice-based learning dynamics that emerge among peers who share occupational practices but do not necessarily work with each other or even know each other because of geographical or organizational distance. To do so, it draws on the literatures on situated learning, networks of practice, and information infrastructures, and on insights from a longitudinal case study of the implementation of a Web-based information system used by people working in the field of environmental health. The system was deeply involved in the transformations of local practices as well as relationships between peers. Based on a dialogue between existing literatures and observations from the case study, this research extends the practice-based perspective on learning to the computer-mediated context of a network of practice. To that effect, it proposes a model of what we call trans-situated learning that is supported by the local universality of an information infrastructure whose use becomes embedded with other infrastructures.

An Empirical Investigation of End-User Query Development: The Effects of Improved Model Expressiveness vs. Complexity

Bowen, P. L., O'Farrell, R. A., Rohde, F. H. — Mon, 28 Dec 2009 10:01:23 PST

Data models provide a map of the components of an information system. Prior research has indicated that more expressive conceptual data models (despite their increased size) result in better performance for problem solving tasks. An initial experiment using logical data models indicated that more expressive logical data models also enhanced end-user performance for information retrieval tasks. However, the principles of parsimony and bounded rationality imply that, past some point, increases in size lead to a level of complexity that results in impaired performance. The results of this study support these principles. For a logical data model of increased but still modest size, users composing queries for the more expressive logical data model did not perform as well as users composing queries for the corresponding less expressive but more parsimonious logical data model. These results indicate that, when constructing logical data models, data modelers should consider tradeoffs between parsimony and expressiveness.

Competitive Environment and the Relationship Between IT and Vertical Integration

Ray, G., Wu, D., Konana, P. — Mon, 28 Dec 2009 10:01:23 PST

The information systems (IS) literature suggests that by lowering coordination costs, information technology (IT) will lead to an overall shift towards more use of markets. Empirical work in this area provides evidence that IT is associated with a decrease in vertical integration (VI). Economy-wide data, however, suggests that over the last 25 years the average level of VI has, in fact, increased. This paper studies this empirical anomaly by explicating the moderating impact of two measures of competitive environment, demand uncertainty, and industry concentration, on the relationship between IT and VI. We examine firms included in 1995 to 1997 InformationWeek 500 and the COMPUSTAT database. Consistent with the IS literature, the analysis suggests that IT is associated with a decrease in VI when demand uncertainty is high or industry concentration is low. However, contrary to the IS literature, IT is found to be associated with an increase in VI when industry concentration is high or demand uncertainty is low. Furthermore, as demand uncertainty increases, less vertically integrated firms invest more in IT, while as industry concentration increases, more vertically integrated firms invest more in IT. The analysis also suggests that firms' choice of the level of VI and IT investment, under different levels of demand uncertainty and industry concentration, are rational. When demand uncertainty is high or industry concentration is low, increase in VI may increase coordination and production costs. Thus, less VI is rational. However, when industry concentration is high or demand uncertainty is low, increase in VI may decrease coordination and production costs. Thus, firms choose more VI in such industries. The implications for research and practice are discussed.

About Our Authors

Mon, 28 Dec 2009 10:01:23 PST

No abstract available.

Acknowledgment of Reviewers

Sambamurthy, V. — Mon, 28 Dec 2009 10:01:23 PST

We would like to thank the many reviewers who devoted their time, energy, and expertise to Information Systems Research, and whose dedicated efforts play a key role in ensuring the quality of the journal. The following individuals served as reviewers of manuscripts reviewed in 2009.