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Title:
Organizational information markets : conceptual foundation and an approach for software project risk management
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Language:
English
Creator:
Yassin, Areej
Publisher:
University of South Florida
Place of Publication:
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Subjects

Subjects / Keywords:
Prediction markets
Systems thinking
Structuration theory
Status reporting
Project management
Risk assessment
Whistle-blowing
Agency theory
Design science
Dissertations, Academic -- Information Sys and Decision Sci -- Doctoral -- USF   ( lcsh )
Genre:
non-fiction   ( marcgt )

Notes

Abstract:
ABSTRACT: This dissertation employs both design science and behavioral science research paradigms to investigate an emerging form of technology-enabled human collective intelligence known as information markets. This work establishes a conceptual foundation for the study of organizational information markets and the design and use processes of information markets inside organizations. This research conceptualizes markets from an information systems perspective and presents an information systems research framework for organizational information markets. This work develops a systems theory of information markets to facilitate investigation of the relationships and interactions between markets as systems and their context of use. It proposes a structuration model for design and use of IT artifacts in organizations and applies it to the study of information markets. A framework of market users is developed to guide market design to satisfy the different motivational and informational needs of market users. A design based solution is proposed to an important open question in the information markets literature; how to generate sufficient uninformed trades. This research extends structuration theory by developing the structuration model of technology-induced organization development. A well-designed information market can generate several benefits to organizations that contribute to their growth and development. Due to the importance of software in everyday life, and the high costs and percentages of failure in software projects, this dissertation proposes an information market solution to help organizations better manage the risks facing software projects. It also develops a theoretical framework for the determinants of software project risk assessment accuracy and evaluates the market's efficacy in improving assessment accuracy via the use of controlled laboratory experiments. The results of the experiments demonstrate the market's efficacy in improving assessment accuracy by increasing the currency, accuracy and completeness of reported status information about project main objectives such as cost, schedule, performance and functionality. The results also demonstrate the market's efficacy in increasing individual willingness to report negative status information by decreasing their perception of information asymmetry between them and management/clients, and by increasing their perception of both the anonymity of the reporting mechanism and their perceived self-interest in reporting negative status information.
Thesis:
Dissertation (Ph.D.)--University of South Florida, 2010.
Bibliography:
Includes bibliographical references.
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Mode of access: World Wide Web.
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Statement of Responsibility:
by Areej Yassin.
General Note:
Title from PDF of title page.
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Document formatted into pages; contains X pages.
General Note:
Includes vita.

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ABSTRACT: This dissertation employs both design science and behavioral science research paradigms to investigate an emerging form of technology-enabled human collective intelligence known as information markets. This work establishes a conceptual foundation for the study of organizational information markets and the design and use processes of information markets inside organizations. This research conceptualizes markets from an information systems perspective and presents an information systems research framework for organizational information markets. This work develops a systems theory of information markets to facilitate investigation of the relationships and interactions between markets as systems and their context of use. It proposes a structuration model for design and use of IT artifacts in organizations and applies it to the study of information markets. A framework of market users is developed to guide market design to satisfy the different motivational and informational needs of market users. A design based solution is proposed to an important open question in the information markets literature; how to generate sufficient uninformed trades. This research extends structuration theory by developing the structuration model of technology-induced organization development. A well-designed information market can generate several benefits to organizations that contribute to their growth and development. Due to the importance of software in everyday life, and the high costs and percentages of failure in software projects, this dissertation proposes an information market solution to help organizations better manage the risks facing software projects. It also develops a theoretical framework for the determinants of software project risk assessment accuracy and evaluates the market's efficacy in improving assessment accuracy via the use of controlled laboratory experiments. The results of the experiments demonstrate the market's efficacy in improving assessment accuracy by increasing the currency, accuracy and completeness of reported status information about project main objectives such as cost, schedule, performance and functionality. The results also demonstrate the market's efficacy in increasing individual willingness to report negative status information by decreasing their perception of information asymmetry between them and management/clients, and by increasing their perception of both the anonymity of the reporting mechanism and their perceived self-interest in reporting negative status information.
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Organizational Informati on Markets : Conceptual Foundation and an Approach for Software Project Risk Management B y Areej M. Yassin A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Information Systems and Decision Sciences College of Business University of South Florida Major Professor: Alan R. Hevner, Ph.D. J. Ellis Blanton, Ph.D. Terry L. Sincich, Ph.D. Richard P. Will, Ph.D. Date of Approval: April 15 2010 Keywords: p rediction markets, systems thinking, structuration theory, status reporting, project management risk assessment, whistle blowing agency theory, design science Copyright 20 10 Areej M. Yassin

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Dedication To Mom and Dad

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Acknowledgments First and foremost, I thank God for giving me the strength and courage to succeed and achieve my goals. I also thank my family for their love and support throughout my graduate studies and the writing of my dissertation. I owe my gratitude to my dissertation committee, whom without their help, this dissertation would have not been possible. I am particul arly grateful to my advisor Dr. Alan R. Hevner who through his respect instilled confidence in me, and by trusting me taught me to trust myself, a nd through his guidance, keen insight and encouraging remarks at the end of each stage in the process motivated me to go forward and to keep going. Dr. Hevner will always be a source of inspiration in my work and a role model to follow. It was an honor to have him as my mentor and dissertation chair. I am very thankful to Dr. Blanton for hi s help with the data collection and for carefully reading and commenting on my surveys. His comments were very helpful in clarifying my ideas. I am als o very thankful to Dr. Sincich who kept me thinking two steps ahead for long discussions that helped me sort out the details of my experiments. I am also very grateful to Dr. Will for giving me access to his classes which has been a trem endous help with my experiments and for his constant encouragement and support. I also wish to extend my appreciation to the faculty, staff and doctoral students of the Information Systems Department who supported me throughout the Ph.D. program. To them and to all who have, in one way or another, contributed to a worthwhile experience a heartfelt thank you.

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Note to Reader The original of this document contains color that is necess ary for understanding the data. The original dissertation is on file with the University of South Florida library in Tampa, Florida.

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i Table of Content List of Tables ................................ ................................ ................................ ..................... iv List of Figures ................................ ................................ ................................ .................... vi Abstract ................................ ................................ ................................ ............................ viii Chapter One : Motivatio n and Dissertation Objectives ................................ ....................... 1 Motivation ................................ ................................ ................................ ............... 1 Problem Statement ................................ ................................ ................................ .. 4 Dissertation Obj ectives ................................ ................................ ........................... 7 Research Approach ................................ ................................ ................................ 8 Research Questions ................................ ................................ ............................... 12 Research Description and Contributions ................................ .............................. 13 Dissertation Organization ................................ ................................ ..................... 17 Chapte r Two : Information Markets: Theory and Literature Review ................................ 18 Introduction ................................ ................................ ................................ ........... 18 Information Markets Theoretical Base ................................ ................................ 18 Hayek Hypothesis ................................ ................................ ..................... 18 Rational Expectations Theory ................................ ................................ ... 19 Random Walk Theory ................................ ................................ ............... 20 Efficient Market Hypothesis ................................ ................................ ..... 21 Marginal Trader Hypothesis ................................ ................................ ..... 22 A Closer Look at Information Markets ................................ ................................ 24 Market Design ................................ ................................ ........................... 25 Forecasting Goal ................................ ................................ ........... 26

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ii Portfolio Composition ................................ ................................ ... 26 Incentive Structure ................................ ................................ ........ 27 Trading Mechanism ................................ ................................ ...... 31 Information Markets Applications ................................ ................................ ........ 32 Information Aggregation Methods ................................ ................................ ....... 36 Information Markets Advantages ................................ ................................ ......... 39 Future Research Directions ................................ ................................ ................... 41 Chapter Three : A Foundation for the Study of Organizational Information Markets ...... 44 Introduction ................................ ................................ ................................ ........... 44 Markets as IT Artifa cts ................................ ................................ ......................... 48 A Systems Theory of Information Markets ................................ .......................... 52 Structuration Theory in Information Systems ................................ ....................... 56 Markets as IT Artifacts: A Structuration Perspective ................................ ........... 60 Information Markets Design ................................ ................................ ..... 62 Market Users ................................ ................................ ................. 65 Use Motivation ................................ ................................ .............. 66 Market Information ................................ ................................ ....... 70 Information Market Use ................................ ................................ ............ 72 Structuration Model of Technology Induced Organization Development 73 Design as a Group of Decisions ................................ ................................ 76 Conclusions and Future Directions ................................ ................................ ....... 78 Chapter Four : Information Markets for Software Projects Risk Management ................. 81 Introduction ................................ ................................ ................................ ........... 81 Challenges to Software Projects Risk Assessment ................................ ............... 85 Research Framework and Research Questions ................................ ..................... 88 Information Markets Design ................................ ................................ ................. 92 Information Markets Expected Utility ................................ ...................... 99 Information Markets Design Evaluation ................................ ............................. 108 Information Market Experiment ................................ ............................. 110

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iii Data Analysis and Results ................................ ................................ .................. 118 Scale Validation ................................ ................................ ...................... 118 Hypotheses Testing ................................ ................................ ................. 121 Discussion a nd Implications ................................ ................................ ............... 128 Limitations ................................ ................................ ................................ .......... 132 Contributions and Fu ture Directions ................................ ................................ ... 134 Chapter Five : Summary and Future Directions ................................ .............................. 137 List of References ................................ ................................ ................................ ........... 144 Bibliography ................................ ................................ ................................ ................... 156 Appendices ................................ ................................ ................................ ...................... 159 Appendix A: Information Markets Experimental Scenario ................................ 160 Appendix B: Information Structures ................................ ................................ ... 163 Appendix C: Risk Assessment Survey ................................ ............................... 168 Appendix D: Survey Experimental Scenario ................................ ...................... 171 Appendix E: Constructs and Measures ................................ ............................... 174 About the Author ................................ ................................ ................................ ... End Page

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iv List of Tables Table 1: Software Hall of Shame (From Charette, 2005) ................................ ................... 6 Table 2: IEM 2008 US Presidential Election Winner Takes All Contracts ...................... 28 Table 3: IEM 2008 US Presidential Election Vote Share Contracts ................................ 29 Table 4: Information Markets Contract Types ................................ ................................ .. 30 Table 5: Market Mechanisms Pros and Cons ................................ ................................ ... 32 ................................ ................................ ...... 40 Table 7: Guiding Aspects for Design of Information Markets ................................ ......... 65 Table 8: Theoretical Framework Propositions ................................ ................................ .. 89 Table 9: Information Markets Major Design Aspects ................................ ...................... 94 Table 10: Experimental Information Market Design for Software Proj ect Risk Assessment ................................ ................................ ................................ ............ 99 Table 11: Conceptual Model Propositions ................................ ................................ ...... 103 Table 12: Experimental Information Structures ................................ ............................. 111 Table 13: Risk Assessment Question ................................ ................................ .............. 112 Table 14: Market Participants Demographics ................................ ................................ 113 Table 15: Subjects Demographics ................................ ................................ .................. 115 Table 16: Item to Construct Standardized Loadings ................................ ...................... 119 Table 17: Constructs Reliability ................................ ................................ ..................... 120 Table 18: Discriminant Validity ................................ ................................ ..................... 121

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v Table 19: Groups Assessment of High Risk Probability ................................ ................ 123 Table 20: Market vs. Groups Risk Assessment Accuracy ................................ .............. 125 Table 21: Groups Risk Assessment Accuracy T Tests ................................ ................... 125 Table 22: Groups Risk Assessment Accuracy Wilcoxon tests ................................ ....... 126 Table 23: Scale Properties ................................ ................................ .............................. 126 Tabl e 24: Paired Samples Test ................................ ................................ ........................ 128 Table 25: Summary of Results ................................ ................................ ........................ 130

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vi List of Figures Figure 1: Information Systems Research Framework (From Hevner et al., 2004) ............. 9 Figure 2: Design Science Approach for Designing and Evaluating an IT Solution for an Identified Business Problem ................................ ................................ ....... 11 Figure 3: Information Markets Typology (From Jones at al., 2009) ................................ 24 Figure 4: Steps for Designing a Virtual Stock Market (from Spann and Skiera, 2003) ... 26 Figure 5: IEM 2008 US Presidential Election Winner Takes All Market ........................ 28 Figure 6 : IEM 2008 US Presidential Election Vote Share Market ................................ ... 30 Figure 7: Information Systems Research Framework for Information Markets (Adapted from Hevner et al., 2004) ................................ ................................ ...... 49 Figure 8: A Systems Theory of Organizational Information Markets .............................. 53 Figure 9: Infographic for Information Mar kets Consensus Making Mechanism on Design and Use of IT Artifacts ................................ ................................ ............. 61 Figure 10: A Structuration Model for Design and Use of Information ............................ 63 Figure 11: A Framework for Information Market Users ................................ .................. 66 Figure 12: Structuration Model of Technology Induced Organization Development ...... 74 Figure 13: Theoretical Framework for the Determinants of Software Projects Risk Assessment Accuracy ................................ ................................ ........................... 89 Figure 14: Design Science Approach for Designing and Evaluating an Information Market Solution for Softw are Project Risk Assessment ................................ ....... 91

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vii Figure 15: Definition of Impact Scales for Four Project Objectives ................................ 96 Figure 16: Risk Matrix ................................ ................................ ................................ ...... 97 Figure 17: Conceptual Model: Willingness to Report Bad News ................................ ... 103 Figure 18: Research Model: Information Market Impact on ................................ .......... 105 Figure 19: Price Curves of the Project Riski ness States ................................ ................. 121 Figure 20: Summary of Theoretical Framework Propositions ................................ ....... 129

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viii Organizational Information Markets: Conceptual Foundation and an Approach for Software Project Risk Management Areej M. Yassin ABSTRACT This dissertation employs both design science and behavioral science research paradigms to investigate an emerging form of technology enabled human collective intelligence known as information markets. This work establishes a concep tual foundation for the study of organizational information markets and the design and use processes of information markets inside organizations. This research conceptualize s markets from an information systems perspective and present s an information systems research framework for organizational information markets. This work develops a systems theory of information markets to facilitate investigation of the relationships and interactions between markets as systems and their context of use. It proposes a structuration model for design and use o f IT artifacts in organizations and applies it to the study of information markets. A framework of market users is developed to guide market design to satisfy the different motivational and informational needs of market users A design base d solution is proposed to an important open question in the information markets literature; how to generate sufficient

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ix uninformed trades. This research extends structuration theory by developing the structuration model of technology induced organization de velopment. A well designed information market can generate several benefits to organizations that contribute to their growth and development. Due to the importance of software in everyday life, and the high costs and percentages of failure in software proj ects, this dissertation proposes an information market solution to help organizations better manage the risks facing software projects It also develops a theoretical framework for the determinants of software project risk assessment accuracy and evaluates the via the use of controlled laboratory experiments. T he results of the experiments demonstrate the marke t efficacy in improving assessment accuracy by increasing the currency, accuracy and completeness of reported status information about project main objectives such as cost, schedule, performance and functionality. The results also demonstrate the market s efficacy in increasing individual willingness to report negative status information by decreasing their perception of information asymmetry between them and management/clients, and by increasing their perception of both the anonymity of the reporting mec hanism and their perceived self interest in reporting negative status information.

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1 Chapter One Motivation and Dissertation Objectives Motivation (Henri Fayol, 1916) Foresight is the oldest term used to describe an interdisciplinary field known today as Futurology; or the study of the future. H.G. Wells envisioned the establishment br th century, Futurology emerged as an academic imagi ned. But who could have imagined, few decades ago, that the most respected futurists of the 21 st century will not be professors, but rather markets? The Economist describing prediction m where the informed guesswork of many is consolidated into hard probability ( The Economist 2007 p.1 ) The article cited several markets forecasts of political outcomes, such as those of NewsFutures, Inkling Markets and InTrade. Other well known applications of prediction

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2 markets, such as the Iowa Electronic Market, has proven to outperform polls and experts forecasts in predicting the outcomes of the presidential elections more than 75 percent of the time over the last ten years. In 2009, Hollywood Stock Exchange announced a 78.4% success rate in predicting the 81st Ann ual Academy Awards nominations, bringing its 11 years average to an impressive 82.1%. The MIT center for collective intelligence calls for creating new forms of collective intelligence that take advantage of the opportunities created by the Internet and o ther new communication technologies, where human and machines can collectively act more in telligently than any individual, group, or collection of computers have ever done before. The center advocates prediction markets as a perspective on collective intel ligence in its own right. Undoubtedly prediction markets are at the frontier of predictive futures and collective intelligence research. Their impressive performance holds great potentials for the business world in areas such as forecasting, decision making and importantly risk management. The value of risk management, in any project, can be assessed based on three measures: the importance of the project itself or its outcomes, the likelihood of occurrence of the risks facing the project, and their expected impacts on the project objectives. Software development projects score very high on all of the scales. In the current era of ubiquitous computing, software is becoming an indispensable part of our daily lives, an absolute necessity for organizati ons to survive fierce competition with rivals, and even a matter of national security for governments.

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3 Organizations and governments spend billions of dollars each year in new software initiatives and projects, and yet by rough estimate, only about 35% su cceed (Rubinstein, 2007). Software failure can lead to tragic societal and economic consequences that go well beyond inconvenience. But the biggest tragedy of all, according to risk management expert Robert N. Charette, is that software failure is predicta ble and for the most part avoidable (Charette, 2005). The software development domain is in desperate need of better risk management tools and practices. Markets may prove to be invaluable in minimizing software projects chances of failure. By aggregatin g status information from all levels of the organization and providing early warning signals about risks, markets can assume the difficult task of s to become main stream risk management tools that inform strategic decisions, policy making and help in long term planning, organizations must first buy into them, understand how they work, know how to use them, and value the information they provide to inform their decisions. Research on predictio n markets used inside organizations is still in its infancy. Little is known about the impact of organizational environment s on market design, incentive structure s and types of questions asked in the market, or more simply put, what works and what does no t. Little is also known about the impact of the market on work processes, corporate culture, and formal and informal reporting mechanisms in the organization.

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4 Markets are, in essence, IT artifacts. To make the best out of this innovative technology, we mu st first theorize about it, and about the reciprocal relationship between it and its environment. We must understand how market s impact organizations, how the business setting impacts market desig n, and how design impacts use and consequently the market objectives. Also, studies are needed that empirically test the usefulness of prediction markets in managing risks facing organizations in general and software projects in particular. This dissertation is the first step in a long term research effort to acc omplish these goals. Problem Statement A list of failed s oftware projects s t ates the problem loud and clear ( Table 1 ). Software projects have a long history of failure that keeps repeating itself. Twenty years ago, the odds of a large software project finishing on time were close to zero (McConnell, 1996 ). Today the odds are not much better, but at l east we know they cannot get much worse. In 2006, 19 percent of initiated software projects in the US were outright failure s ; cancele d before completion or not deployed. 46 percent of projects failed to meet user requirements, had cost overrun s or were not delivered according to schedule (Rubinstein, 2007). In 2007, Dynamic Markets Limited surveyed 800 IT managers across eight countrie s. The results showed that failure rates are universal; 62 percent of IT projects failed to meet their schedules, 49 percent exceeded their budget, and 41 percent failed to deliver the expected business value and ROI.

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5 Identifying the risks facing software projects and reasons behind their failure s has occupied project managers, software industry consultants and ac ademics for a long time. The most cited reasons are also universal. The literature is full of case studies, postmortem analyses, lessons learned and recommended practices to improve the processes and outcomes of software projects. However, management is still unable to effectively manage the risks involved in these projects. Although current risk management approaches can be useful in identifying and prioritizing risks, as well as in suggesting mitigation strategies, none of them addresses the fundamental problem behind software project failure; communication. Many large scale software disasters have been attributed to communication problems and inaccurate status reporting, such as the case of the CONFIRM project (Oz, 1994). Reluctance to transmit bad news (Kiel, Smith, Pawlowski and Jin, 2004), and both status misperception, and deliberate misrepresentation by software developers and project mana gers (Snow and Keil, 2002) are some of the reasons that lead to inaccurate assessments of risks and, eventually, project failure. Existing risk management tools and initial risk assessments are ineffective in reducing a software project chances of failure unless there are methods that continuously provide complete, current, and accurate information about the status of project objectives as events unfold. Otherwise managers are left with unrealistic, dated assessments of project risks, an d as a result fail to take appropriate actions to mitigate them.

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6 Table 1 : Software Hall of Shame (From Charette, 2005) Year Outcome Costs in US $ 2005 Hudson Bay Co. (Canada) Problems with Inventory system contribute to $33.3 million loss. 2004 05 UK Inland Revenue Software errors contribute to $3.45 billion tax credit overpayment. 2004 Avis Europe PLC (UK) Enterprise resource planning (ERP) system canceled after $54.5 million Is spent. 2004 Ford Motor Co. Purchasing system abandoned steer deployment costing approximately $400 million. 2004 J Sainsbury PLC (UK) Supply chain management system abandoned after deployment costing $527 2004 Hewlett Packard Co. Problems with ERP system contribute to $160 million loss 2003 04 AT&T Wireless Customer relations management (CRM) upgrade problems lead to revenue loss of $100 million. 2002 McDonalds Corp. The Innovate information purchasing system canceled after $170 million Is spent. 2002 Sydney Water Corp. (Australia) Billing System canceled after $33.2 million is spent. 2002 CIGNA Corp. Problems with CRM system contribute to $445 million loss 2001 Nike Inc. Problems with supply chain management system contribute to $100 million loss 2001 Kmart Corp. Supply chain management system canceled after $130 million Is spent 2000 Washington D.C. City payroll system abandoned after deployment costing $25 million. 1999 United Way Administrative processing system canceled after $12 million is spent 1999 State of Mississippi Tax system canceled after $11.2 million is spent; state receives $185 million damages. 1999 Hershey Foods Corp. Problems with ERP system contribute to $151 million loss. 1998 Snap on Inc. Problems with order entry system contribute to revenue loss of $50 million 1997 U.S. Internal Revenue Service Tax modernization effort canceled after $4 billion is spent. 1997 State of Washington Department of Motor Vehicle (DMV) system canceled after $40 million is spent. 1997 Oxford Health Plane Inc. Billing and claim system problems contribute to quarterly loss; stock plummets, leading to $3.4 billion loss in corporate value. 1996 Arianespace (France) Software specification and design errors cause $350 million Ariane 5 rocket to explode 1996 FoxMeyer Drug Co. $40 million ERP system abandoned after deployment forcing company into bankruptcy. 1995 Toronto Stock Exchange (Canada) Electronic trading system canceled after $25.5 million is spent. 1994 U.S. Federal Aviation Administration Advanced Automation System canceled after $2.6 billion is spent. 1994 State of California DMV system canceled after $44 million is spent 1994 Chemical Bank Software error causes a total of $15 million to be deducted from 100 000 customer accounts. 1993 London Stock Exchange (UK] Taurus stock settlement system canceled after $600 million is spent. 1993 Allstate Insurance Co. Office automation system abandoned after deployment costing $130 million. 1993 London Ambulance Service [UK] Dispatch system canceled In 1990 at $1125 million; second attempt abandoned after deployment, costing $15 million. 1993 Greyhound Lines Inc. Bus reservation system crashes repeatedly upon introduction, contributing to revenue loss of $61 million. 1992 Budget Rent A Car, Hilton Hotels, Marriott International and AMA (American Airlines) Travel reservation system canceled after $165 million Is spent.

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7 Dissertation Objectives This dissertation seeks to accomplish the following objectives: First, establish a theoretical foundation for the study of organizational information markets and the design and use processes of markets inside organizations Second define the relationships and interactions between information markets and their environment Third d esign an information market solution to help organizations overcome an important business problem ; s oftware project r isk assessment. Fourth, evaluate the proposed information market s efficacy in increas ing assessment accuracy by empirically test ing the ma rket ability to: 1. Efficiently collect and combine information from the organization to provide an assessment based on information about the status of different project objectives, such as scope, quality, cost and schedule, 2. Respond to unfolding e vents by rapidly incorporating new information into the assessment to provide current an d up to date assessment of risk 3. Adjust for individual errors in perception of project status and risk assessment and thus, provide more accurate assessment of risk. 4. Motivate those who are involved in the project or have access to information about its progress to faith fully report status information

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8 Research Approach Technology and behavior are inseparable in an information system and thus ought to be inseparable in IS research ( Hevner, March, Park and Ram, 2004 ). The IS field needs an interdisciplinary conceptualizations of the IT artifact that articulate what the technology is, how it interacts with the social context artifacts are broadly defined as constructs (vocabulary and symbols), models (abstractions and representations), methods (algorithms and practices), and instantiations 2004, p. 77). Hevner et al. (2004) argue that IS research is conducted in alternating cycles between design science (technology) and behavioral science (behavior). The design science paradigm in essence is a problem solving paradigm rooted in engineering and the sciences of the artificial (Simon, 1996). It is concerned with building innovative IT perceptions, roles and capabilities within the organization, as well strategies, structures and cultures, and their existing and planned technologies form the problem space of business needs which warrants the relevance of design science research. Design science is also concerned with evaluating the I T artifact based on the utility provided in solving those problems. Evaluation can be carried out via case or field studies, lab experiments or simulation. Evaluation then feeds back into the design process to improve current understanding of the problem, the designed artifact, and the design process itself (Hevner et al., 2004).

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9 On the other hand, the behavioral science paradigm studies the IT artifact by developing and justifying theories to explain and predict its use and impact on individuals and o rganizations. The goal of behavioral science is truth that informs design, and the goal of design science is utility that informs theory (Hevner et al., 2004). Theories as well as designed artifacts are assessed for weaknesses, refined, and reassessed mult iple times until they accomplish their intended goals ( Figure 1 ) Figure 1 : Information Systems Research Framework ( From Hevner et al., 2004) Rigor is guaranteed by the application of existing knowledge such as foundational theories, frameworks, instruments, constructs, models, methods and instantiations in developing theories and building the artifact, and by the application of existing methodo logies such as data collection and analysis techniques, measures and validation criteria in justifying theories and evaluating artifacts. The contributions of IS research are Application in the Appropriate Environment Additions to the Knowledge Base People Organization Technology Foundations Methodologies Environment IS Research Knowledge Base Relevance Develop/Build Justify/Evaluate Business Needs Applicable Knowledge Assess Refine Rigor

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10 assessed based on the applicability of the artifact in the problem space, its abi lity to meet 2004). Thus, we are utilizing both the design science and behavioral science research paradigms to accomplish our research objectives. To establish a theoretical foundation for the study of information markets inside organizations, t his research starts by re conceptualizing markets as IT artifacts and presents an information systems research framework for information markets It employs and extends seve ral theoretical perspectives such as systems thinking concepts (Checkland, 1981) and structuration theory (Giddens, 1979) to facilitate investigation of the relationships and interactions between markets and their context of use, and the design and use pro cess es of markets inside organizations. The design science research paradigm is employed to design an experimental Web based information market solution to aid organizations and project managers in assessing software project risks ( Figure 2 ). Market design is informed by existing theories, methodologies, and empirical evidence in the information markets and software project managem ent literatures. The proposed market design and its expected utility in the area of software project risk assessment are evaluated using controlled experiments. Experimental studies on the use of information markets for business problems that use business related tasks and scenarios are needed to advance the theory of organizational information markets to explain and predict information markets

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11 performance in specific business settings. They provide sufficient degree s of control that allow us to draw concl usions about manipulation effects and causality, which in turn will allow us to build theoretical models to explain and predict the impact of various information markets designs on key business related dependent variables. Experimental results can also be used to refine market design and will contribute back to our knowledge base. Figure 2 : Design Science Approach for Designing and Evaluating an IT Solution for an Identified Business Problem Following the design science research guidelines proposed by Hevner et al. (2004), we advance a research approach for designing and evaluating IT artifacts developed to fulfill an identified business need ( Figure 2 ). The proposed approach for conducting design science research starts by organizing research questions into two sets: IT artifact design and IT artifact design evaluation. IT artifact design research questions IT Artifact Design RQ1: What is the design of the artifact? State artifact nature and specific design Form hypotheses IT Artifact Evaluation providing hypothesized utility? Decide on evaluation method Test hypotheses Business Need Knowledge Base Justify Inform Apply Add Evaluate Refine

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12 ask about (1) the n ature and the specific design of the proposed IT solution, and (2) its expected utility for the identified business need. After the nature and the proposed artifact design are articulated along with the theories and literature that inform the design, the I T artifact expected utility is stated in form of testable hypotheses. IT artifact design evaluation research questions ask about the efficacy of the designed artifact in providing its hypothesized utility in a particular business domain. To test the hyp otheses and answer design evaluation research questions, an appropriate evaluation method should be selected such as laboratory experiment or field studies supported with appropriate literature, and then the hypotheses can be tested by collecting the requi red data and analyzing i t using appropriate data analysi s techniques. Evaluation results can then be used to modify the artifact design and/or selected evaluation method, and will enhance our understanding of the problem either by developing or extending e xisting theories, or by adding empirical evidence to our knowledge base. The evaluated IT solution is then applied in a particular domain to help solve an identified business problem. Research Questions The IT artifact design research questions are : RQ1 What is the design of an information market for software projects risk assessment?

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13 RQ2 What is the e xpected utility of the designed information market for software projects risk assessment? Information markets are expected to improve the accuracy of s oftware projects risk assessment by improving the currency, accuracy and completeness of reported status information about projects var ious objectives such as scope, cost, quality and schedule. IT artifact evaluation research questions: RQ3 What is the ef fic acy of an information market providing complete, current, and accurate information about software project risks? Research Description and Contribution s This dissertation contributes to the theory and practice in the information systems literature, software project management literature, and the information markets literature. Research on information markets has increased significantly in the last 5 years and yet there have been few review s that cover the theoretical underpinnings of inf ormation markets and synthesize existing studies to make this knowledge accessible to information systems researchers. The information markets literature review presented in this dissertation is considered a contribution because it seeks to stimulate more general i nterest in information markets and suggests fruitful area s for future research.

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14 This dissertation establishes a theoretical foundation for organizational information markets by conceptualizing markets from an information systems perspective in four differe nt ways; as IT artifacts, systems within bigger systems, business intelligent tools, and consensus making systems and by developing a systems theory of information markets. These conceptualizations along with the developed theory fac ilitate investigation of the relationships and interactions between markets and their context of use, and are an important first step towards building new information systems theories about organizational information markets to describe, exp lain and predict their behavior and impacts on organizations. Attaining a better understanding of the design, implementation and use processes of IT artifacts in organizations is vital to devise design, implementation and use guidelines and procedures that promote effective structurati on process that leads to organization development. This dissertation proposes a structuration model for design and use of IT artifacts in organizations, and applies it to the study of information markets. It also provides guidance on the design of informat ion market s, their interfaces and information visualization used by developing a framework of market users to guide (Giddens, 1979) b y developing the structuration model of technology induced organization development that defines a goal and an ultimate outcome for the structuration process of IT artifacts. This model conceptualizes design as a group of decisions, envisions the design pr ocess as a

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15 decision making process, considers technology as a catalyst for organization change and development, and views the structuration process as a continuous change process that objectifies changeability as an organizational permanent structure that leads to organization development. A well designed information market provides utility to organizations that over the long run might lead to their growth and development. This dissertation proposes various ways by which organizations can utilize information markets to improve their assessment of software project risks. For example, a n information market can be designed to monitor the s tatus of each project objective in addition to the project overall riskiness level. It can also be used to predict the impact of a range of risk factors or the likelihood of various impact levels of a particular risk factor. To answer our research quest ions, this dissertation proposes an experimental information market design solution for software project risk assessment. The forecasting unmet objectives. Project main objectives are cost, schedule, functionality and performance. Objectives are considered unmet when they exceed a certain threshold over their planned limit. For example, cost exceeds budget by more than 15%. The higher the number of unmet objectives, the higher the overall riskiness level of the project. To test the designed information market efficacy in providing complete, current, and accurate information abou t software project risks, two controlled laboratory

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16 experiment s are conducted The results of the experiments provide evidence to information market efficacy in improving risk assessment accuracy by aggregating information from all participants in the mark et to provide more complete, current and accurate assessment of risks than any individual group of participants The results also prove information of information asymmetry, providing incentives for truthful revelation of status information identities from being exposed. This research contributes to the software project risk management literature by proposing an innovative technology based solution to risk assessment problems, along with a theoretical framework for the determinants of risk assessment accuracy. The results of the experiments improve our understanding of the fac tors that increase the accuracy of software projects status reports and consequently software project risk assessment and provide evidence to the market effectiveness in improving software risk assessment accuracy, which will consequently reduce software p rojects chances of failure and save organizations billions of dollars. This research highlights an additional benefit for information markets besides their anonymity and incentives offered for truthful tions of information asymmetry which can be very useful to organizations if utilized properly. This dissertation contribute s to the information markets li terature by first proposing a design based solution to an important open question in the information

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17 markets literature; how to generate sufficient uninformed trades required for information markets to function properly Second, it provides aggregation an d dissemination process es by conducting laboratory experiments using realistic information structure, business related tasks and scenarios Third, it evaluates an innovative application of information markets in business This in turn will allow us to build theoretical models to explain and predict the impact of various information markets designs on key business related dependent variables. Dissertation Organization The reminder of this dissertation is organized in three maj or chapters. Chapter Two review s the literature and the theoretical underpinnings of information markets. Chapter Three establishes a conceptual foundation for the study of organizationa l information markets and employs several theoretical perspectives to define the relationship between markets and organizations. Chapter Four utilizes a design science approach to design a technology enabled information market solution to aid organizations in managing risks facing software development projects and evaluates efficacy in solving the identified problems using two controlled experiment s Chapter 5 completes the dissertation with a summary of the research contributions and observations on future research directions.

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18 Chapter Two Information Markets: Theory and Literature Review Introduction This chapter begins by reviewing the theoretical underpinnings for information markets. It then provides a closer look at information markets structure and design. Successful applications of markets in g eneral areas such as politics, entertainment and sports are reviewed next. We also review the few studi es that empirically investigate the use of information markets in a business setting, to forecast sales and project delivery dates. The following sectio n discusses the market advantages compared to other information aggregation and forecasting methods used in organizations today. This chapter concludes by identifying areas for future research. Information Markets Theoretical Base Hayek Hypothesis Informat ion markets are a distinct form of futures markets whose main purpose is to aggregate information about uncertain future events. The ability of markets to aggregate information dispersed among individuals can be traced back to Adam Smith (1776) and his inv isible hand theory. The invisible hand process works via free markets and division of labor where outcomes are produced in a decentralized way with no

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19 explicit agreement between thousands of indepen dent, utility maximizing agents whose aims are neither coo rdinated nor identical with the actual outcome, yet bringing wealth to their nations. This vision of dece ntralized planning of economies that secures the b est use of knowledge in society is what Hayek (1945) believed can only be maintained through the free markets price system. Thus, according to the Hayek hypothesis, a s ociety is composed of i ndividual s each spatially separated from others or decentralized, who have only partial local knowledge of a phenomenon s are diverse and independent I t does not matter if only few kno w about a certain circumstance, as long as they all act and think independen tly seeking their self interest. Under these conditions, free markets can collect, coordinate and ensure cooperation wh ere the whole act as one bringing about, in form of prices, a collective wisdom purified from cognitive problems of those few (Surowiecki, 2004). Rational Expectations Theory The information aggregation property of prices is what gave rise to information m arkets. This property was formalized by Muth (1961) in the theory of rational expectations and price movement. According to rational expectations theory, individuals take all available information into account in forming expectations about future events. In a perfectly competitive market, the rational expectation equilibrium is the intersection point of supply and demand curves. Buyers and sellers make sequential trades at discrete points in time with imperfect information bringing about the price

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20 observed in the market. The p rocess of acquiring information in the market advances traders through different states ranging from no information to perfect information. As traders discover and learn, they adjust their expectations, and the observed price consequen tly evolves in a series of disequilibrium price adjustment s to an expected price which theoretically should soon become the equilibrium (Hess, 1972). Random Walk Theory s and their formation process in order to predict futu years. It is a fascinating area of study and a great way of making money. There are three major schools of thought with regard to how prices form; technical, fundamental value, and random walk. While all agree that market prices form through series of successive price adjustments, it is w hy these adjustments take place and how independent they are, t hat make them disagree. Technical analysts, also known as chartists, assume that the series of past price changes has memory and the past tends to repeat itself. They carefully analyze historical price changes to identify patterns to help them predict future prices and eventually increase their chances of making profit. On contrary to this implied dependency assumption, random walk theorists assume independence. In other words, patterns identified cannot be used to predict future changes and any profit made using technical analys is cannot exceed those made by chance, or by using a buy and hold trading strategy (Fama, 1965 b ). A Random Walk Down Wall Street (Malkiel, 1973) can even convince

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21 investors that buy and hold strategy is best since attempts to outperform the market based on technical, fundamental or any other forms of analysis are vain. Fundamental value analysis is consistent with the random walk independence assumption. Fundamental value analysts believe that each security has an intrinsic value. They evaluate the company investments, and the political and economic factors affecting them to estimate securities value and expected return. Changes in market prices can be caused by disagreement between traders on how valuable securities are, new information arriving at different impulsive betting behavior (Fama, 1965 a ). The arrival of new information or the noise created by irrational behavior can cause prices to change in a dependent way to levels above or below their intrinsic values. However, experienced intrinsic value analysts will sh ortly notice that activity and act quickly by selling or buying thus, driving price levels back towards their i ntrinsic values and eliminating any dependence in successive price changes (Fama 1965 a ). Efficient Market Hypothesis The Efficient Market Hypothesis (EMH) (Fama, 1970), which requires traders to have rational expectations, is connected to random walk theory. The EMH asserts that markets are informationally efficient, and thus are impossible to beat. In other words, price s of traded assets reflect all available information about future prospects of the asset. Since prospects are analogous to events. Prices in efficient information markets reflect all

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22 available information about the likelihood of the events. Thus, i nformati on markets utilize market efficiency to harness the collective knowledge of participants to predict the likelihood of future events. Modern behavioral finance has shown that people make systematic er rors when predicting the future. This irrational behavio r could also arise due to emotional errors (Clark, 2007), wishful thinking or making mistakes, biased or not ( Forsythe, Rietz, and Ross, 1999) These behaviors creat e market ineffici encies and anomalies in prices that may be inexplicable via any available hypothesis (Fox, 2002; Rosenberg, Reid and Lanstein, 1985). However, information markets effectiveness seems to be immune to irrationality. Forsythe, Nelson, Neumann, and Wright, (1992) a nalyzed Iowa political stock market data to test the market ability to aggregate information about political events. Trader level analysis showed that some traders appeared rational while others exhibited substantial cognitive and judgmental biases, such a s assimilation contrast and false consensus effects. In spite of that, the market forecasts were notably accurate. Marginal Trader Hypothesis In efficient information markets, it does not really matter if all traders are rational or not, as long as the mar ginal trader is r ational and motivated by profit; the market generated forecast will be fairly accurate ( Forsythe, Nelson, Neumann, and Wright, 1992; traders who are influen tial in setting market prices are all that is needed for the Hayek

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23 p 84 ). The marginal traders are those who submit limit orders close to the market price. While those who are inactive, make only market orders or make limit orders at prices far away from market prices are not considered marginal (Forsythe et al., 1999). Each market trade is determined by two separate acts, or two trader roles: a market maker submitting a limit order and a price taker accepting it (submitting a market order). Traders self select into these two roles. Violations of the law of one price, the no arbitrage assumption and those of individual rationality, can be classified into price taking and market making violations (Oliven and Ri etz, 2004). Even though average traders might exhibit judgment biases, marginal traders, or market makers, are who determine whether markets are efficient or not (Oliven and Rietz, 2004). Studies have foun d that marginal traders appear to b ehave more rati onally, exhibit less biased trades, and are more experienced and knowledgeable (Forsythe et al., 1992; Forsythe et al., 1999; Oliven and Rietz, 2004). It is worth noting though, that a market maker cannot exist without a price taker, otherwise the no trade theorem will bind and traders will not agree to disagree (Aumann 1976; Milgrom and Stocky 1982). It is still an important open question in the information markets literature on how to attract those price takers, despite their possible irrational behavio r, to participate in trading due to their critical role in executing trades (Wolfers and Zitzewitz, 2006)

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24 A Closer Look at Information Markets Information markets, often known as prediction markets, but also referred to as decision markets, event marke ts and idea futures, are an emerging form of futures markets created to aggregate information, rather than to hedge risks. Information markets can be organized into two main categories as shown in Figure 3 based on the market objective for which the information is aggregated (Jones, Collins and Berndt, 2009). Verifiable outcomes information markets seek to predict the likelihood of future states of either a discrete or a continuous variable Unverifiable outcomes information markets allow participants to either create or choose among a lterna tive or courses of action. Figure 3 : Information Markets Typology (From Jones at al., 2009) Thus, i nformation markets can be used to aggregate information about a wide range of events, such as sports outcomes interest rates, marketing campaigns, and Information Markets Idea Futures (Discovery of new Alternatives) Decision Markets (Choice between alternatives that create the future) Prediction Markets (Predict future events) Estimation Markets (Choice between continuous alternatives) Event Markets (Choice between discrete alternatives) Unverifiable Verifiable

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25 research ideas Although markets differ in many respects, such as market design and incentive structure, they gener ally consist of one or more events for which you would like a reliable forecast. The standard contract in the market is the binary contract, aka winner take all. It costs a certain amount and pays off, for instance, $1 if and only if the event occurs, and nothing otherwise. Traders buy and sell contracts of future events based on their beliefs in the events likelihood of occurrence. For example, if a trader believes the event is going to happen, s/he will buy contracts in the event. But if a trader has inf ormation to the contrary, s/he will sell contracts in the event. Contract prices and events probabilities are positively correlated. The higher the likelihood of the event the higher its contract price and vice versa. The result is a trading price that tra cks the consensus opinion (Hanson, 1992), and can be interpreted as market aggregated forecast of the event probability (Wolfers and Zitzewitz, 2004). For example, if a contract price is selling for $70, that means there is a 70% chance of the event happen ing. Market Design Based on research results in the fields of experimental economics, financial markets and political stock markets, Spann and Skiera (2003) grouped main aspects of information markets design into three categories, outlined in Figure 4

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26 Forecasting Goal The choice of forecasting goal is concerned with the types of questions asked about future events. In other words, what is specifically being predicted. Predicte d events must be easy to verify and future outcomes must be easy to measure. Questions can be formulated to predict the occurrence/ nonoccurrence of an event, such as whether a project will be delivered on a specific date or not. Other questions can predict numbers such as units sold, or sales in dollars or percentages such as market share, or election vote s hare. Questions must be clear, and ea sy to understand. They must be i nteresting enough to attract traders, and controversial enough to sustain trading. Portfolio Composition The designer of the market must decide on the composition portfolios and on whether traders will use their own money to buy shares, or will be given an initial endowment of shares. Another related design issue is the use of real or play money. Real money might motivate traders to collect mor e information about the events. On the other hand, it might deter informed, but risk adverse traders from Choice of forecasting goal Selection and description of prediction issue Incentives for participation and information revelation Composition of initial portfolios Choice of incentive mechanism Financial market design Choice of trading mechanism and market rules Figure 4 : Steps for Designing a Virtual Stock Market (from Spann and Skiera, 2003)

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27 participating. Additionally gambling laws might restrict the use of real money markets, making the play money alternative plausible. In terms of pred ictive accuracy, studies have shown that real and play money markets result in equally accurate predictions (Servan Schreiber, Wolfers, Pennock and Galebach, 2004). Incentive Structure Designers must also decide on an incentive structure to motivate trade rs to participate, and to truthfully reveal what they know about an event. After all, a trade requires a trader to put her money where her mouth is. The incentive structure, and the type of contracts used, can elicit the collective expectations of a range of different parameter, such as the probability, mean or median value of an outcome (Wolfers and Zitzewitz, 2004). For example, when the outcomes of an event are mutually exclusive, such as (yes/no), or (occur/not occur), the binary contract, described in the previous The s ame applies to events with more than two mutually exclusive outcomes. State contingent or winner take all contracts can be used, and their prices can be interpreted as the collective or the market forecast of the event probability. As long as the no arbitrage condition is satisfied though. In other words, the sum of prices of the traded state contingent contracts should be exactly equal to the payoff of the winning contr act (Chen, Fine and Huberman 2001). For example, in case of binary contracts, if the winning contract pays off a $100, the sum of prices of the two traded contracts must be equal to a 100 (e.g. Yes $40, No $60).

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28 Iowa Electronic Markets (IEM), a well kno wn real money prediction market, used winner take all contracts to predict the outcomes of the 2008 U.S. presidential elections ( Table 2 take all prediction market opened in June 2006. The founder of election, prices indicated a 90 percen t probability that the Democratic candidate would win the popular vote (IEM press release, Nov 5, 2008). Table 2 : IEM 2008 US Presidential Election Winner Takes All Contracts Code Contract Description DEM08_WTA $1 if the Democratic Party nominee receives the majority of popular votes cast for the two major parties in the 2008 U.S. Presidential election, $0 otherwise REP08_WTA $1 if the Republican Party nominee receives the majority of popular votes cast for the two major parties in the 2008 U.S. Presidential election, $0 otherwise Figure 5 : IEM 2008 US Presidential Election Winner Takes All Market ( Source: http://iemweb.biz.uiowa.edu/graphs/graph_PRES08_WTA.cfm )

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29 In support for Professor Rietz statement, Figure 5 shows that for more than two years the democratic contract price never once dropped below the republican. Prices were exceptionally responsive to unfolding events on the campaign trail, and fluctuated around primary, caucus, and major party convention dat es. When forecasted outcomes are numbers or percentages, such as sales in dollars, vote count, or percentage of vote share, index contracts can be used that pay off proportionately to the outcomes (Wolfers and Zitzewitz, 2004). IEM vote share contracts ( Table 3 ) are examples of index contract. Table 3 : IEM 2008 US Presidential Election Vote Share Contracts Code Contract Des cription UDEM08_VS $1.00 times two party vote share of unnamed Democratic nominee in 2008 election UREP08_VS $1.00 times two party vote share of unnamed Republican nominee in 2008 election Prices on the IEM's Vote Share Market ( Figure 6 ) predicted the percentages received of the two party presidential popular vote to within half percentage point: the market predicted 53.55 perc ent for Barack Obama, and 46.45 percent for John McCain. After the ballots were counted, Obama received 53.2 percent of the vote, and McCain received 46.8 percent (IEM press release, Nov 24, 2008).

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30 Figure 6 : IEM 2008 US Presiden tial Election Vote Share Market ( Source: http://iemweb.biz.uiowa.edu/graphs/graph_PRES08_VS.cfm ) The price of index contract represents the market mean expectation of the outcome. On the other hand, a spread contract with even money bet represents the exceed a certai n cutoff point, such as a candidate receiving more than a certain vote share (Wolfers and Zitzewitz, 2004). Table 4 summariz es the discussed contract types. Table 4 : Information Markets Contract Types Contract Type Payoff Parameter Winner take all Pays $1, $0 otherwise Probability Index Proportionate to outcome Mean Spread Double money if outcome exceeds cutoff point; $0 otherwise Median

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31 Trading Mechanism The choice of market trading mechanism is another important aspect of market design. The dominant market trading mechanism is the continuous double auction (CDA), where bids, submitted by buyers, and asks, submitted by sellers, wait in queues to be executed. Bids are sorted by prices in de scending order and then by posting time in ascending order; while asks are sorted by prices then by time, both in ascending order to facilitate matching with pending bids. The continuous double aucti on (CDA) mechanism poses no risk on the market institution, provides incentives for continuous incorporation of information and offers the option of cashing out by selling shares at the currently offered bid price. However, CDA might suffer from illiquidi ty due to market thinness, or wide bid ask spread (Pennock, 2004). Continuous double auction with market maker (CDAwMM) are the bookie mechanisms used for sports betting This trading mechanism guarantees liquidity by transferring the risk involved to the market institution. Pari mutuel mechanism also guarantees liquidity without posing any risks on the market institution; however, unlike CDAwMM, it does not continuously incorporate information into the price, but rather wait s until the event can be identi fied with certainty (Pennock, 2004). Market scoring rule (MSR), invented by Hanson (2003, 2007), can elicit forecasts over many combination s of outcomes and from both individuals and groups. MSR c ombines the advantages of inform ation markets and scori ng rules while solving the thin market and irrational betting problems of standard information markets, as well as the

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32 information pooling problems of simple scoring rules. MSR is currently used at Inkling Markets, the Washington Stock Exchange, BizPredict and several other markets David Pennock (2004) developed a novel market mechanism called dynamic pari mutuel market (DPM) that is used at Yahoo! Tech Buzz Game. DPM combines some of the advantages of both Pari mutuel and CDA markets, yet like all other mechanisms has its own limitations. Table 5 summarizes the pros and cons for the various available market mechanisms as discussed by Pennock (2004). Table 5 : Market Mechanisms Pros and Cons Market Mechanisms Advantages Disadvantages Continuous Double Auction (CDA) 2,3,4 Fails 1 Continuous Double Auction with Market Maker (CDAwMM) 1,3,4 Fails 2 Pari Mutual (PM) 1,2 Fails 3 and 4 Dynamic Pari Mutual (DPM) 1,2,3,4 5,6 Market Scoring Rule (MSR) 1,3,4 Fails 2, but risk is bounded Bookie (Bookmaker) 1,3,4 Fails 2 1. Guaranteed liquidity 2. No risk for the market institution 3. Continuous incorporation of information 4. Ability to cash out by selling before the market closes 5. Pay off depends on the price at the time, and final pay off per share 6. One sided nature (only accept buy order) Information Markets Applications While research on information markets has witnessed an exponential gr owth in the number of published articles in the last ten years (Tziralis and Tatsiopoulos, 2007),

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33 prediction markets have been around for a long time. Betting on political outcomes has a long tradition in the United States, with large and formal markets, s uch as the New York betting market, operating for over three quarters of a century (Rhode and Strumpf, 2004). These markets h ave h ad a very large volume of activity and a notable predictive accuracy (Rhode and Strumpf, 2004). Today, the Iowa Electronic Market (IEM), the most well known application of information markets, is offering markets in which traders can bet on a wide variety of events ranging from the outcomes of presidential elections, to the periodic interest rate decisions of the Federal Reser Since 1988, prices on the IEM have proved more accurate than traditional polls in forecasting elections more than 75 percent of the time, with an average absolute error of only 1.5 percentage point, comp ared to 2.1 percentage points for polls ( Berg, Forsythe, Nelson and Rietz, 2003; Forsythe et al. 1992; Hahn and Tetlock, 2006). Market forecasts can be used to inform decisions made by political parties, such as nominating presidential candidates that ar e likely to win, as well as decisions made by the candidates themselves regarding their campaigns strategy such as what issues to focus on. The idea of using markets for decision support was fi rst introduced by Hanson (1999) when he used the concept of dec ision markets, or conditional markets, to illustrate how market forecasts can be used to inform decisions about an event, given market predictions of another. Berg and Rietz (2003) provided an elaborate analysis of the 1996 presidential election market, an d described how market prices can be used to support decisions; for

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34 example, market forecasts suggested that Dole was not the strongest candidate in the set, so the Republican Party could have used market prediction to support a stronger candidate with a b etter chance of beating Clinton (Berg and Rietz, 2003) The Hollywood Stock Exchange (HSX) is another successful application of information markets. Traders in the HSX buy and sell shares of their favorite actors or se or fall. Traders evaluate movies by collecting with fan communities to form beliefs about movies potential prospects. Prices of securities are used to predict Oscar, Emmy, and Grammy award winne rs and movie box office returns. The predictions have proved to be highly correlated with actual outcomes. In 2009, players correctly predicted 29 of 37 Oscar nominees for the 81st Annual Academy Awards, a 78.4% success rate, b s 11 year average to an impressive 82.1% (HSX press release, Jan 22, 2009) The HSX is being used as a market research instrument where movies box office prerelease forecasts are used to determine marketing budget, the number of movie screens, and related promotional activities (Eliashberg and Sawheny, 1996; Spann and Skiera, 2003). Spann and Skiera (2003) analyzed the HSX forecasting accuracy f or 152 also analyzed the market performance in many other areas, such as predicting the number of movie visitors, and chart position of pop music singles in Germany, and eve n in predicting the usage of different mobile phone services of a large German mobile phone

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35 operator. Market predictions were fairly accurate. Results showed that markets work well under different incentives structures and with small number of participants There are many other successful Web based implementation of information markets designed to aggregate information and forecast events in many areas such sports, politics, finance, law, entertainment, and even the weather. Some examples of real money inf ormation markets include Intrade, TradeSports, Nadex and BetFair. Other examples of play money markets are NewsFutures, Inkling markets, and the Foresight Exchange. In 2006, over 25 companies in the United States had started to experiment with information markets (King, 2006). Today the numbe r has at least doubled and companies have moved beyond the experimentation stage. Microsoft is using the market to predict software quality issues, such as the number of bugs in new software application, Google is usin g it to predict dates of product lunches and GE is using it to choose the best new research ideas (Schonfeld, 2006). AT&T, Yahoo, Corning and Best Buy are just a few examples of the many F ortune 500 companies that have begun to seriously use the market in various areas. In a series of experiments at Hewlett Packard laboratories, markets outperformed official HP forecasts 75% of the time in predicting printer sales and the DRAM microchip prices (Chen and Plott, 2002; Schonfeld, 2006). Ortner (1997, 1998) co nducted an experiment using information markets at Siemens Austria to forecast delays and reveal information about software project progress. Results showed that market prices anticipated delays long before the official release of information, proving the

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36 usefulness of using markets in the software project management arena. The Milestone Market ( www.milestonemarket.org ) at the University of South Florida is being deployed for software cost estimation and software project management where market contracts are defined for each set of mil e stones, and are tied to defined cost and time estimates (Berndt, Jones and Finch, 200 6 ) Intel integrated an information market designed to forecast demand into the market forecasts are stable, responded well to demand fluctuations, and were at least as accu rate as the official forecasts, with 75% of market forecasts falling within 2.7% of actual sales (Hopman, 2007). In addition to aggregating information, and forecasting events, markets can be used to study how organizations process information (Cowgill, Wo lfers, and Zitzewitz 2008). The how markets can be used to track information flow within the organization and how it responds to external events. Information Aggregation Methods Organizations employ vari ous methods to elicit forecasts and aggregate information held by members of a group. When the issues at hand are purely factual, statistical groups can be used by aski ng a large group of individuals and calculating the statistical mean or median of their answers ( Sunstein, 2005 )

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37 However when the group is anchored by a misleading number or the group members are ignorant to the issue at hand, the likelihood that the group will decide correctly decreases as the size of the group increases (Sunstein, 2005). Alternatively, deliberation can be used to improve group decision making through discussions and debates, especially when the issues are normative rather than factual (Sunstein, 2005). Armstrong (2006) presented the case against face to face meetings, demonstrating how ineffective and inefficient traditional group meetings are at aggregating information. Groups often produce inaccurate outcomes because of informational and social influences (Sunstein, 20 05). Sunstein ( 2005 ) argued that i nformational influence occurs when group members announce their information by conduct, conclusions or by reason giving; influencing other group members not to disclose any information to the contrary On the other hand, social influence leads individuals to conform to higher status group members fearing disapproval, or social sanctions of various sorts. These influences impair group judgment by emphasizing shared information, creating hidden profiles, cascade effects, and group polarization (Sunstein, 2005). Additionally, individual group members have limited info rmation processing capabilities and therefore rely on heuristics such as representativeness, availability, framing, anchoring and adjustment to reduce the cognit ive load of predicting values or assessing probabilities (Tversky and Kahneman, 1974). The use of heuristics reduces

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38 complex tasks to much simpler judgmental tasks, creating biases and errors in individual judgments that are propagated, and often amplified in group settings. The Delphi method is utilized to diminish the informational and social influences of deliberative groups. The Delphi technique us es a self administered questionnaire and a system of controlled feedback where in a group of experts pa rticipate in anonymous rounds of estimates and feedback until the degree of convergence reach es a desired threshold. Members are allowed to communicate their judgments and conclusions anonymously in the form of summary statistics along with their justifica tion and reasoning behind them. Experts can then respond to the forecas ts and justifications of others and revise their own based on the feedback they receive. Finally, individual judgments are statistically aggregated (Armstrong, 2001). Rowe and Wrigh t (1999) reviewed 25 empirical studies that evaluated the effectiveness of the Del phi method in terms of forecast accuracy and quality. Their review showed that Delphi outperformed both statistical and interactive groups roughly over 80% of the time. Altho ugh the Delphi technique proved to improve forecasting and decision making, it has its own limitations. In addition to the possible difficultly of recruiting experts in any area of interest, Delphi does not have an incentive structure to motivate experts t o reveal their true beliefs. Also, Delphi does not allow incorporation of additional information into the forecasts because it offers results only at a certain point in time ( Green, Armstrong, and Graefe 2007)

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39 Information M arkets Advantages Much of the enthusiasm for using information markets as a method of forecastin g and information aggregation co me s from the inadequacy of existing methods to accomplish this task. Information markets are being used to overcome the limitations of the various aforeme ntioned methods. Green et al. (2007) discussed how information markets can avoid the drawbacks of Delphi. First of all, markets are not restricted by their pr ivate information is not yet incorporated into the market price. Second, markets offer incentives for true revelation of beliefs. Monetary incentives eliminate group pressure to conform, where traders can only benefit by trading according to their own beli efs. Third, unlike Delphi, markets are dynamic and responsive to changing circumstances. Prices in information markets incorporate new information almost instantly, providing continuous and up to date forecasts of events. Information markets offer many ot her advantages over existing methods ( Table 6 ). First, Web based implementations of information markets are not restricted by location or time. Traders can participate from around the globe, 24 7. Second, markets are more cost effective and time efficient than other information aggregation methods. The process of price formation and discovery collect s disparate information sc attered around the organization or around th e world in a matter of hours, and at relatively little to no cost. Third, market trading is anonymous. Anonymity plays a pivotal role in reducing social and informational influences that prevail in group settings. Fourth, trading

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40 dynamics in a market setti ng cancel out i ndividual biases and errors preventin g cascading effects from impact forecasts (Forsythe et al., 1992; Forsythe et al., 1999; Oliven and Rietz, 2004). The substantial body of experimental research on information aggregation (e.g. Forsythe and Lundholm, 1990; Sunder, 1992, 1995; Forsyth et al., 1992; Plott, 2000; Plott and Sunder, 1982; Plott and Sunder, 1988) suggest s that markets seem to work fairly wel l in a wide variety of settings. Empirical studi es on information markets prove the feasibility of using the market in a business setting to forecast a variety of events (Chen and Plott, 2001; Ortner, 1997, 1998). Further, research has shown that markets a re robust to manipulation and insider trading (Hanson and Opera, 2004; Hanson, Opera, and Porter, 2006), and produce forecasts that are at least as accurate as existing alternatives, such as opinion polls and experts predictions (Berg, Nelson and Rietz, 2 003; Chen and Pennok, 2005; Forsythe et al., 1992; Servan Schreiber et al., 2004). Table 6 : Information Markets Advantages Why Information Markets ? Web based Robust to manipulation No time or place restrictions Anonymous No experts required Save time and money Offer continuous up to date forecasts Biases and errors proof Versatile Dynamic and responsive to unfolding events Offer Incentives for honesty High forecasting accuracy business world. Studies that test the usefulness of information markets in various areas of business are greatly needed.

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41 Future Research Directions Research on how information mar kets are used inside organizations is still in its infancy. Little is known about the impact of the business environment on market design, incentive structure, and types of questions asked in the market, or more simply put, what works and what does not. Li ttle is also known about the impact of the market on work processes, corporate culture, and formal and informal reporting mechanisms in the organization. Future research should investigate the impact of different incentives structures and the type of mark et mechanism used (e.g. pari mutuel, continuous double auction, decisions to adopt the market different trading mechanisms have different associated learning curves which may affect market. It may al so require traders to employ different trading strategies that involve a greater cognitive effort to analyze information and to participate in market trading; thus discouraging them from participating in the market. Moreover, future research should empi rically compare information markets to other methods of information aggregation, such as the Delphi method, not only in terms of forecasting accuracy but also on multiple other dimensions, such as the nature of forecasting problems appropriate for each met hod, sources of relevant information (e.g.

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42 external, internal, or a mix of both), the availability of public information to attract participants, the availability of experts in certain areas, and the costs involved in recruiting experts, acquiring the mark et, training, trading time, incentives, etc. curiosity, and help put everything in perspective. One might argue that the value of new innovations can be better appreciated r elatively rather than in absolute terms. However, we caution against using forecasting accuracy as the sole basis for comparison between markets and other existing methods. It is important to keep in mind when evaluating the effect iveness of information ma rkets what made them attractive in the first place. Available methods of forecasting and information aggregation such as polls, surveys and the Delphi method have their own limitations, and produce inaccurate forecasts all the time. So are we really doing markets justice by comparing them to error prone benchmarks? Further, unintended uses of markets might emerge that bring additional benefits to organizations, rendering them incomparable to other methods. Markets bring about a unique mix of involvement a nd enjoyment that other methods do not provide. By promoting democratic participation in decision making and idea generation, organizations Research is needed to study suc h questions. and on their relationships with employees, customers, partners, and strategic allies might

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43 change the way business is done forever. These unanticipated benefits mig ht create a stronger motivation to adopt information markets than their predictive accuracy. Information markets are innovative tools to harness the collective intelligence buried in organizations. They hold great promises for business that are only limite d by our own innovation to realize them.

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44 Chapter Three A Foundation for the Stud y of Organizational Information Markets Introduction human societies such as bacteria, insects and animals. Perhaps human pride has deterred individuals from communication technologie s, the World Wide Web, and the I nternet have made this fact evident to the world (Servan Schreibe r, 2008). Google, Wikipedia and information markets are three examples of human collective intelligence enabled by the Web that are designed to aggregate existing information to enhance existing knowledge. However, information markets have the additional benefit of generating new reliable knowledge about the future (Servan Schreiber, 2008). Information markets, also known as prediction/decision markets, are a form of futures markets designed to aggregate disparate information and intuitions about the likelihood of uncertain future events. Traders bet on the chances of the event by buying shares if they believe the event is going to happen and selling shares if they believe otherwise. The price of the traded shares in the event can be interpreted as the market

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45 according to the actual outcome. The most well known application of i nformation markets is the Iowa Electronic Market (IEM), established at the University of Iowa in 1988, to predict the outcomes of the U.S. presidential elections. Since its inception, IEM has demonstrated an impressive predictive performance with an averag e absolute error of only 1.5 percentage points compared to 2.1 percentage points for Gallup polls ( Berg, Forsythe, Nelson, and Rietz, 2003). Over the long run, the market predictions were closer to the actual election result 74% of the time when compared t o 964 polls over the five Presidential elections since 1988 and outperformed the polls in every election when forecasting more than 100 days in advance ( Berg, Nelson, and Rietz, 2008). The Hollywood Stock Exchange (HSX) is another successful application o f information markets used to predict Oscar, Emmy, and Grammy award winners and movie box office returns. In 2009, Hollywood Stock Exchange announced a 78.4% success rate in predicting the 81st Annual Academy Awards nominations, bringing its 11 years average to a remarkable 82.1% (HSX press release, Jan 22, 2009). Market forecasts can be used to inform decisions about forecasted events. For example, IEM forecasts can be used to inform decisions made by political parties, such as nominating presidential candidates that are likely to win, as well as decisions made by the candidates themselves reg arding their campaigns strategy and the issues to focus on (B erg and Rietz, 2003 ) Similarly, HSX forecasts can be used by movie production

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46 companies to determine marketing budget, the number of movie screens, and related promotional activities (Eliashberg and Sawheny, 1996; Spann and Skiera, 2003) Information mar kets outstanding performance in predicting future eve nts such as elections outcomes and other issues of public interest, coupled with an increasing interest in finding more efficient alternatives for information aggregation, has inspired the corporate wor ld to start experimenting with information markets. Yahoo, Google, Mi crosoft, GE, HP, Intel and many other fortune 500 companies are now using information markets to forecast business related issues, such as product delivery dates, product sales, market de mand, and software quality issues. Although the number of companies adopting information market technology is on the raise, it is still less than 1% of the target audience (Gartner, 2008) and d espite the enthusiasm for using information markets for busi ness forecasting, research on information markets used inside organizations is still in its infancy. It is expected that information markets will reach main stream adoption within 5 to 10 years (Gartner, 2008) and yet l ittle is known about the impact of th e business environment on market design, incentive structure, and types of questions asked in the market, or more simply put, what works and what does not. Little is also known about the impact of the market on work processes, corporate culture, and formal and informal reporting mechanisms in the organization. Information markets are, in essence, IT artifacts. To make the best out of this innovative technology, we must first theor ize about the technology itself and about the

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47 reciprocal relationship between markets and their environment to develop an understanding of how information markets use impact s organizations, how the business setting impacts market des ign, and how design impacts use and consequently the market objectives. As a first step to systema tically investigate the design and use processes of markets inside organizations, this chapter theorizes about information markets from an in formation systems perspective. The n ext section presents an information systems research framework for information markets, and re conceptualizes markets as IT artifacts. Section three employs systems thinking concepts to develop a systems theory of information markets to facilitate investigation of the relationships and interactions between markets as systems and thei r context of use. n the information systems field and defines information markets from a structuration perspective. Section five proposes a structuration model for design and use o f IT artifacts in organizations and applies it to the study of information markets. A closer look at information markets design and use is presented in the following two sections, where a framework of market users is proposed to guide market design to satisfy motivational and informational needs. Our conceptualization of the structuration pro cess of IT artifacts in general and information markets in particular is summarized in the structuration model of technology induced organization development, that e xtends Giddens structuration theory by

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48 considering technology as a catalyst for orga nization change and development and the structuration process as a continuous change process that objectifies changeability as an organizational permanent structure that leads to organization development. Conclusions and future directions conclude this chapter. Markets as IT Artifacts I nformation markets are at the frontier of predictive futures and collective intelligence research. Their impressive performance holds great potentials for the business world in areas such as forecasting, decision making and risk management. However, the r elationship between information markets and organizations has not been fully investigated The information systems research framework ( Figure 7 ) and the design science research guidelines suggested by Hevner et al. (2004) can be used to structure the methods and activities performed by IS researchers designing/studying organizational information markets. The information systems research framework encom passes two complimentary, however distinct paradigms: the behavioral science and the design science paradigms. The behavioral justify theories that explain or predict organizational and human behavior invo lved in the et al. 2004, p. 76).

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49 The design science paradigm is a problem solving paradigm that seeks to develop innovative technological solutions (i.e. IT artifacts) t o identified business problems that exist in the problem space as defined by its surrounding environment (Simon, 1996). IT artifacts can be constructs, models, methods, or instantiations that provide utili ty in addressing those problems and are produced vi a two design processes: build and evaluate evaluation, and are developed following the arti implementation and use to explain their impacts on the environment (Hevner et al., 2004). Figure 7 : Information Systems Research Framework for Information Markets (Adapted from Hevner et al., 2004) Information markets are fundamentally IT artifacts designed to provide more effective and efficient solutions to identified business problems such as infor mation Application in the Appropriate Environment Additions to the Knowledge Base Environment Information aggregation Business f orecasting Decision making Risk assessment Idea generation Project management IS Research Releva n ce Design Information Markets Design Market Interfaces Design Visualizations for Market Info Develop Markets related IS s pecific theories Evaluate Design Justify Theories Business Needs Applicable Knowledge Assess Refine Knowledge Base Finance Economics Psychology Political science Cognitive science Experimental economics Behavioral economics Computer science Rigor

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50 aggregation, forecasting and decision making under uncertainty. However, the build and evaluate loops used to produce the information market are informed by foundational theories and methodologies rooted in reference disciplines such as economics (experimental and behavioral), fi nance, psychology, and political science. As a result, current studies tend to view information markets through reference disciplines lens: as a financial market, or an economic entity (e.g. Forsythe, Nelson, Neumann and Wright, 1992). The tendency to stud y the IT artifact, and its intimately related issues, through varied reference disciplines lens is particularly concerning in the IS field. Orlikowski and Iacono (2001) argue that although the information systems field is premised on the centrality of info rmation technology i n everyday life, IS research does not live up to this premise. The authors observed that IS researchers tend to under subject matter, the IT artifact, and instead give central theoretical significance to the context where the technology is absent or black boxed, to the processing capabilities of the technology abstracted from its socioeconomic context, or to the deterministic impact of the technology on some dependent variable. IS studies that investigate the design and use processes of organizational information markets and their interactions with the business environment are greatly needed. However, existing literature on information markets and its current knowledge base might tempt IS researchers to bla ck box the market, undermine the importance of its interaction with the environment, or downplay the impacts of its technological and

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51 structural aspects on the effectiveness and efficiency of organizations adopting information markets. Although markets ar e socially constructed, focusing too much on the socioeconomic context, or treating the market as either an independent or a dependent variable, rather than focusing on the technology itself, moves us away from our main role of investigating IS specific ph enomena, and makes it easy to substitute the IS in our research with anything else ; making our contributions indistinct from those of other disciplines (Benbasat and Zmud, 2003). Thus, the first step in studying organizational information markets is to rec onceptualize markets as technology enabled information systems (i.e. IT artifact). Technology is limited to the hardware and the software components of the market, and the information system encompasses the design, development, implementation and use proc esses of the market, as well as the dynamic interaction between the market, people es the market, in the sense that it clears some of the doubts surrounding information ma rkets that are mainly due to the black box nature of markets and organization s lack of general understanding of its internal workings. It also serves as grounds for theorizing about information markets from an information systems perspective.

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52 A Systems Theory of Information Markets Systems thinking framework (Checkland, 1981) is a useful theoretical lens through which markets as systems can be defined, and the structures underlying these systems and their emergent properties can be understood. It can also be employed to investigate the relationship between IT artifacts and their context of use such as the organization. Systems thinking framework is being applied to study organizations, analyze organizational problems, and develop solutions by vi ewing organizations as systems operating within a bigger sy stem (e.g. industry) and in continuous interaction with their external environment (e.g. competitors) and internal subsystems (e.g. departments) (Checkland, 1981; Davis and Olson, 1985; Senge, 1990 ). picture that helps them solve complex problems effectively (Senge, 1990). Instead of isolating the problematic parts of the system, systems thinkers examine interaction patterns and interrelationships between systems and subs ystems which allow them to unc over dependencies among actions and to understand how problems, as well as solutions, propagate from one system to the other. As a result, systems thinkers choose actions that result in better long terms solutions, instead of those that result in temporary desirable effects that may, over the long run, worsen the problem (Checkland, 1981; Senge, 199 0). (Checkland, 1999) which can be useful in understanding the relationship between IT

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53 artifacts, such as information markets, and their context of use. An a daptive whole is an entit sum of its parts. It can be part of a larger whole, or contain smaller wholes, each with its adaptive whole survive s in a changing environment by having automatic or man made changes and adapt accordingly (Checkland, 1999). Figure 8 : A Systems Theory of Organizational Information Markets A systems perspective on organizational information markets views the market as an adaptive whole organized as part of a layered structure of adaptive wholes

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54 encapsulating each other ( Figure 8 ). An information market is a subsystem of the organization system in which it is used. The organization in turn operates within an industry, all of which operates in the lar gest system of all: the world. Recent research has attempted to reshape current thinking about information markets, and called for investigating markets from a business intelligence perspective. the spirit of business intel ligence lies at the heart of information markets and that markets used within organizations are in essence business intelligence tools that aggregate and summarize intelligence from multiple sources to enable accurate forecast ing about future market trends and potential risks, and consequently make better informed decisions. xecution of business ered by p.1032). The market aggregation mechanism (e.g. continuous double auction, pari mutual, scoring rules) does not only collect and aggregate int elligence from multiple sou rces but also determines h ow the information is collected, which makes it an adaptive whole that has its own structures and properties ( Figure 8 ). An information mar ket encapsulates the aggregation system and its emergent properties (e.g. intelligence), along with the market incentives and contracts structures, and produces an emergent property that makes the market l arger than the sum of its parts; collective intelli gence in form of equilibrium price. An organization then analyzes the

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55 intelligence stored in the market such as historical price trends, trading volume, buying and selling transactions, in addition to the collective intelligence produced by the market (i.e equilibrium price) to dra w inferences and make interpretations and predictions about future events, industry trends, and potential risks. Each system engages in a process of cybernetic informatio n exchange with its environment and ha s its own ways of re sponding to and communicating with the system in which it operates, as well as with other systems. For example, an information market communicates information to traders, to decision makers and to the organization in form of demand and supply cues and tra ding prices. It also controls participation by means of incentives offered and contracts used in the market. The o rganizati on impacts market participation s in the events being forecast through industry reports, official forecasts, proj ect status reports, and the feedback it receives from the industry regarding its performance relative to competitors. Similarly, market information can be used to measure organization performance by comparing market forecasts to official forecasts. Thus, a systems theory of information markets facilitates theorizing about the relationship between markets and organizations and about the impact of the business environment on market design and use by focusing on the big picture and analyzing interactions between systems subsystems and their emergent properties.

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56 Structuration Theory in Information Systems Structuration theory (Giddens, 1979, 1984) is another useful theoretical lens through which markets as IT artifacts can be defined and the relationship between the structuration theory has received substantial attention in the information systems field due to its rejec tion of traditional dualistic views of social phenomena as either determined by society (structure) or individuals (agency). This rejection of both positivism and strong interpretivism is seen in the IS literature as a rejection of both subjective and obj ective views of o rganizations (Orlikowski, 1992) and that of technological and social determinism (Jones and Karsten, 2008). It was also seen as an opportunity to resolve inconsistent definitions of technology ( i.e. technology scope), and those of the inte raction between technology and organizations (i.e. technology role) (Orlikowski, 1992). Giddens attempted to reconcile the dichotomous perspectives of social systems (society vs. individual, structure vs. agency, objective vs. subjective) by focusing on t he social processes or individual actions that are based on social structures, but at the same time serve to produce and reproduce social struc tures. The duality of structure or the dynamic conceptualization of structure as both a medium and an outcome of interaction

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57 Although technology is completely absent in structuration theory, its focus on structures and the dynamic processes by which humans use and modify struc tures through situated practice is o f particular interest to IS researchers seeking to understand structures as properties of technology, work groups and organizations and how an individual s use of technology is shaped by its features and yet reshapes them (Poole and DeSanctis, 1990, 1992, 1994). More than 330 IS papers have employed structuration concepts either to offer insight into IS phenomena, to explore its limitation s in comparison to other theoretical perspectives, or as a source for developing IS specific structuration theories that take structuration theory; the structuration model o f tec hnology (Orlikowski, 1992) and adaptive structuration the ory (DeSanctis and Poole, 1994) were developed to facilitate investigation of the relationship between technology and organizations. The structuration model of technology is premised on a recursi ve notion of technology called the duality of technology ; that technology is the outcome of human actions, yet is used by h umans to accomplish some action and thus is both structurally and socially constructed (Orlikowski, 1992). In other words, t echnolo gy in and of itself has no significance; it is only through ongoing appropriation by humans that it gains significance. In practice, technology use is conditioned by its material properties and built in structures H owever, this conditioning is both enabli ng and constraining (Orlikowski,

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58 1992) and although use is shaped by technology properties and structures, it also reshapes them causing new structures to emerge (Orlikowski, 2000). Therefore technology design, use and interpretations are rather flexible. The degree to which a user can exercise influence over technology construction either and it depends on the characteristics of the technology, human agents involved, and the institutional properties of organizations (Orlikowski, 1992). which they have no contr ol. Orlikowski (1992) argued that researchers tend to view technology as either objective or subjective depending on the temporal stage the studying the design of a technolo gy recognize its dynamic and constructed nature and view it as a product of human action. On the other hand researchers investigating ignoring the ongoing process of physica l and social construction (Orlikowski, 1992). The time space discontinuity between design and use of technology, which typically occur s at different organizations, is to blame for the conceptual dualism of technology dominating the IS literature (Orlikow ski, 1992). However, the structuration model of technology posits that this disjuncture between design and use is artificial and assumes that technology is designed and used recursively where design and use stages are tightly coupled. In other words, techn ology is potentially modifiable through use

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59 ongoing interaction with it and development of technology, users can redesign technology at any point in time by means of the different ways they interpret, appropriate, and manipulate it (Orlikowski, 1992). Thus, understanding the technology action relationship is critical in confronting structuration central paradox of why technologies with identical structures cause different o utcomes that lead to differ ent effects on organizations (Orlikowski, 1992; DeSanctis and Poole, 1994). Adaptive structuration theory extends Giddens structuration t heory by considering the recursive relationship between technology and action, where technology social structures and the social structures that emerge in human actions iteratively shape each other. Techn ology social structures include features and capabilities provided by the general intent with regard to values and goal f eatures (DeSanctis and Poole 1994, p.126). Other sources of social structures that enable and constraint the appropriation process of technology are the nature of the task s performed using the technology such as task complexity and interdependence and the organizational setting such as hierarchy, corporate information, and cultural beliefs The two central processes in adaptive structuration theory are appropriations and structuration processes. Appropriations are the immediate, visible actions that evidence deeper structuration processes Structuration is the proc ess by which social structures within technology, tasks, organization al environment or their outputs are produced and reproduced in social life ( i.e. their rules and res ources

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60 are brought into action) which causes new social structures to emerge. The use and reuse of existing and new emergent social structures lead over time to their acce ptance and institutionalization; bringing organizational change (DeSanc tis and Poole, 1994) Outcomes and changes brought about by technology use are contingent on many human agents, the faithfulness of their actions to the spirit and structura l features of the technology, the reasons for bringing the technology or other structures into action and their attitudes towards using the technology (DeSanctis and Poole, 1994) Although adaptive structuration theory has been mainly applied to the study of group (decis ion) support systems (GDSS/GSS) and computer mediated communications (CMC), it has established a legitimate link between main stream IS research and social theories in general and structuration in particular (Jones and Karsten, 2008) Thus, it can be applied to investigate the social processes involved in appropriating any class of advanced information technologies in organizations. Market s as IT Artifacts: A Structuration Perspective As defined above, information markets are technology en abled information systems. Thus, from a structuration perspective, an information market can be defined in terms of its social structures: spirit and feature set. An information market is a consensus making system that provides information about the degree beliefs about the likelihood of uncertain future events. It seeks to measure, quantify and

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61 probabilities (i.e. trading price constrained betwe en 0 100). Figure 9 : Infographic for Information Markets Consensus Making Mechanism on Design and Use of IT Artifacts Traders express their beliefs in form of market transactions (e.g. buying and selling). Each transaction has two quantifiable properties: strength and direction. Strength is the amount of money offered, and direction is positive for bids (the event is likely to occur), or negative for asks (the event is unlikely to occur) ( Figure 9 A). As positive transactions get stronger, or demand increases, contract price increases signaling a higher

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62 ( Figure 9 B). Similarly, as negative transactions get stronger or supply increases, price out the likelihood of future events ( Figure 9 C). An information market surrounding environment and the context in which it operates shape the market objectives and its statement of purpose, also known as the ( Figure 10 ). Organizations adopting the market should first and foremost create a mission statement and li st of objectives for the market and accordingly develop instruments to measure market performanc e over time. Further, organizations should create an information sharing channel between market traders and executive management to share infor mation about market performance, how its predictions are being used, and the benefits both gained and expected fr om its predictions. This will give the market a heightened sense of purpose and will consequently encourage market participation. Information Markets Design It is only after defining market objectives, setting forecasting goals and formulating forecastin g problem s in form of questions that markets can be properly designed ( Figure 10 ). The business environment imposes unique challenges on all aspect s of information markets design; design of the market itself, design of market interfaces, and design of visualizations for market information. For example, markets designed for business forecasting might involve estimating sales figures fo r a range of diffe rent

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63 products and thus the contracts used in those markets are more complex than those used in presidential election markets where outcomes are usually binary. Figure 10 : A Structuration Model for Design and Use of Information Technology Artifacts Further, interest in using markets to aggregate information dispersed among a group of people came out of the desperate need for a mechanism that eliminates judgment biases and other social and informational influences that are commonly present in a group setting ( Sunstein, 2005 ) to generate an honest consensus ( Hanson, 1992 ). Markets have an inherent advantage over traditional information aggregation and group consensus making methods by offering incentives for true revelation of beliefs; market participants put their money where their mouths are. To utilize this valuable f eature, an adopting organization must pay special predicting issues of public interest such as election outcomes or sports events, Context Design Objectives Use 1 2 2 3 3 3

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64 organizational markets are usually t hin with a relatively small number of trades and require a well designed incentives structure to attract traders and to motivate active participation and information gathering especially when information relevant to the forecasted events is not readily ava ilable, or easy to find. Other design elements of the market itself include: the trading mechanism, anonymity of traders, composition of initial traders portfolios, the use of real money or play money, duration of the market, trading hours, and whether pa rticipation is open or restricted to certain individuals. These design features of the market are shaped by the context of use and the market objectives. For example, gambling laws in certain states or countries might restric t the use of real money trading and depending on th e questions asked in the market and the expected amount of participation, a trading mechanism that ensures liquidity (e.g. scoring rules) might be used instead of a one that does not (e.g. continuous double auction). The business envir onment and market objectives shape the design of market interfaces and the various visualizati ons used for market information in addition to shaping the design of the market itself. Similar to other information and communication technologies, information m arkets design effectiveness depends on its ability to satisfy of information markets, market interfaces and visualizations be driven by thre e factors (Shown in Table 7 ) : ( 1) Market users Who; ( 2) Use motivation Why; and ( 3) Market information What.

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65 Table 7 : Guiding Aspects for Design of Information Markets Market Aspect Question to Ask Examples Market users Who is using the market? Employees, customers, partners decision makers Use motivation Why do users use the market? Focus on goals and motivations Entertainment, profit, inform decision Market information What information do users need to accomplish their goals/satisfy their needs? Trading volume, price trends, pending offers Market Users We propose a multidimensional framework for information markets users ( Figure 11 ) that classifies users according to three dimensions: 1) knowledge level in the issues being forecasted, as informed or uninformed users; 2) participation level in market trading, as active or passive users; and 3) externality level to the department/organization at which the market operates, as internal or external users. Informed users are those who are directly involved in the issues being forecasted or hold add itional information to t hat which is publicly available about them. Uninformed users are those whose knowledge about the issues does not exceed what is publicly available. Active market users are those who submit one or more orders du ring a specific time window (e.g. hour, day, week), and passive users are market readers who do not submit any orders. While users might exhi bit varying levels of knowledge or activity, the proposed framework focuses on the two main levels in each dimensio n to simplify

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66 depa and external users are those who are not employed in the department/organization at which the market operates (e.g. custom ers, partners). Figure 11 : A Framework for Information Market Users Use Motivation Understanding what causes be havior and why that behavior varies in its intensity is the ultimate goal of motivation studies (Reeve, 2005). Although there are a wide variety of motivation theories, they generally focus on id entifying sources of motivation and explaining their impact s on behavior (Reeve, 2005). According to affordance theory (Gibson, 1977), humans perception of the environment drives their behavior, as they possibilities for action. Affordance theory has contributed to our understanding of human computer interaction processes and of what constitute s a good design. For example, good design make s the range of possible actions, or ways of interaction (i.e. affordances), visible and readily perceivable (Norman, 1999). Design the ories inform design by emphasizing goals to be achieved and actions that might help achieve them (Malone, 1985). There are a number of theoretical Participation Level Active Passive Active Passive Knowledge Level Informed 1 3 5 7 Uninformed 2 4 6 8 Internal External Externality Level

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67 perspectives for designing organizational interfaces, such as information processing, economic, political and motivational perspectives (Malone, 1985). Utilizing afford ance theory of human perception as well as motivati onal theories of human behavior to understand technolo gy use behavior, allows us to develop motivational design principles technologies (Zhang, 2008a). Information markets with high motivational affordances fulfill the motivational needs of market users. Each group of users in the framework proposed above ( Figure 11 ) has its distinct motivational needs and goals that require different designs, information or information visualizations to be fulfilled. Informed active users (Groups 1 and 5) are motivated by either extrinsic rewards such as money or prizes or by intrinsic rewards such as recognition. Unin formed active traders ( Groups 2 and 6) are risk loving individuals who are mainly motivated by the thrill of the game and the entertaining aspects of betting on the future. In case of active users, market designs should conti expectations and fulfill their inf ormational needs to at least sustain their activity level. However, the real design challenge comes in case of passive market users; because organizational infor mation markets are usually thin and might suffer from illiquidity issues due to low activity le vels. Thus, markets should be properly designed to turn passive users into active ones involvement and participation level. Special attention must be given to three types of

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68 passive user as each typ e has different informational needs and can be influenced, targeted or attracted by different aspects of market design: I. Internal and external informed users (Groups 3 and 7). II. Internal and exte rnal uninformed users (Groups 4 and 8). III. Internal informed and uninformed decisions makers (Groups 3 and 4). Type I users are interested market readers who do not participate in market trading mainly because they are risk averse. Type I users are valuable because they hold information that can improve t he accuracy of market forecasts and generate significant trading activity. They can be attracted by offering an anonymous trading option, a well designed incentive structure that, for example, allows them to cash out of the market at any point in time or by using play mo ney instead of real money. Type II users are also risk averse market readers who feel they do not h ave enough information to trade and read the market out of curiosity. Type II users are vital for information markets to work due to their role in executing informed trades. Since type II users are likely to be motivated by non economic factors, finding ways to attract them is still an open question in the information markets literature (Wolfers and Zitzewitz, 2006). We propose a design based solution to gen erate sufficient uninformed trades. Market designs should be intuitive, simple and easy to use to attract uninformed trades. They should also be attractive to induce positive emotions that affect users desire t o use

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69 the system (Norman, 2004) and importa ntly they should be perceived as fun, decrease percei ved riskiness of market trading and give it a fun game like feeling. Malone (1982) argued that for interfaces to be en joyable, they should provide performance feedback to users, be emotionally appealing, and capitalize on users desire to have a well informed knowledge structure. Thus, enjoyable market interfaces should keep t and display relative and historical performance evaluation to traders. It should introduce new information when users feel their information is incomplete or inconsistent (Malone, 1982) by displaying updates, announcements or links to potential sources of information such as meeting minutes and the department bulletin board. Motivating market interfaces also support social and psychological needs for relatedness (Zhang, 2008b) by providing the ability to communicate with other market tr aders through market chat rooms or market blogs. designers do not seek to turn them into active users. Type III users are decision makers who use the market for the sole purpo se of informing their decis ions and thus the ed in the market and the collective intelligence produced by the market ; how to turn it int o business intelligence

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70 capacity in making intelligence actionable, special attention must be paid to the informational needs of decision makers to create managerial dashboards that provide them with greater control and visibility of what is going on in the market and allow them to act in a timely manner. Market Information T here are an infinite number of ways of processing, aggregating, manipulating, and visualizing market information. Thus, there are an infinite number of ways of designing market interfaces. Although the design of markets, markets interfaces, and information visualizations can be guided by various theoretical perspectives, the optimal set of information or information visualization to display on a market interface can only be identified through the accumulation of empirical evidence. The main piece of inform ation needed by market users is the price of the last traded contract in the outcome being forecasted. The last trade price represents the degree interpreted as the outcom 4 ). Other price related information that can be useful to market users include: historical price trends, contract prices offered by other market traders, and the average, max and min prices over a s pecified trading period. It is important to note, however, that price, and price related information are noisy signals that might not aggregate and transfer all the available information in the market (Grossman and Stiglitz 1976; Noeth, Camerer, Plott, a nd Webber, 1999; Plott, 2000),

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71 may suffer manipulation (Hansen, Schmidt and Strobel, 2004; Hanson, Oprea and Porter, 2006; Rhode and Strumpf, 2006) and bubbles ( Plott, 2000), and thus might not, at some points in time, be an accurate representation of tra ders beliefs Therefore, it is important to supplement prices with other non price information, such as volume weighted price ave rage and trading volume both in terms of money and number of shares, when making judgments about market conditions. Further, i t is important to monitor the amount of trading activity r egardless of the trading volume in a particular event because it signals the rele ase of updates about its status and gives traders as well as decision makers an indicati ce and degree of controversialit y. needs for competition, competence, achievement, and reco gnition (Malone 1985; Zhang, 2008b) This also motivates othe r traders to gather information and engage in future trading. To satisfy social and psychological needs for relatedness and cooperation, market designs should facilitate human human interact ion (Malone 1985; Zhang, 2008b) by allowing traders to post comments and chat with other traders in the market. As for decision makers, additional market information can be utilized to allow for greater visibility of market activity. In an attempt to identify ways of making market information more useful to managers, Yassin (2009) proposed a novel decision heuristic

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72 transactions in the market. Pending transactions are valuable because they contain information that is not yet incorporated into market forecasts. The goal of forecasts i s to enable managers to see ahead and take appropriate actions in advance. However, the accuracy of market forecasts cannot be judged until the market closing date or until the outcomes can be determined with certainty. Information that supplements market forecasts is important because it improves the quality of input to the decision process and allows managers to act in a timely manner. A managerial dashboard on the market allows managers to filter trading volu me by departments or user group and to create traders and rank traders according to their activity level, money inv ested, historical performance, and other available data Managers can use this capability to identify influential trades and information sources; thus judging their credibilit y. Information Market Use An information market is em bedded in conditions of its use and that in turn is embedded in an organizational environment. There is a recursive relationship between market design and use, between use and the market context of u se, and between use and the market intended objectives ( Figure 10 ), each shaping the other iteratively until new physical and social structures emerge. In other words, markets are designed purposefully ac cording to a list of objectives which are created based on an analysis of users needs M arkets are designed with a set of intended uses in mind. Use is shaped by current

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73 organizational practices, communication channels and hierarchy of control existing in However, continued use of the market can uncover unattended needs and create new ones causing new technological features to be added to the market, thus, altering the design of the marke t interfaces and the information visualizations used. Continued use can also generate a wave of redistribution of power in adopting organizations where market participants at all levels in the organizational hierarchy contribute to the decision making process and consequently influence the decisions being made. Further, continued use can alter formal and informal reporting mechanism in the organization, create new communication channels, empower informal leaders, and form info rmal information generating and sharing groups of market participants These factors may cause new social structures to emerge which over time become institutionalized structural properties of the organization. Also, market users might appropriate th e mark et in unconventional ways through their different interpretations of market objectives and the diffe rent meanings they assign to it; creating unintended uses for the market which over time can become parts of the market objectives. Structuration Model of Technology Induced Organization Development The dynamic interactions between organizations, market participants and the market, as well as among participants themselves will keep redefining the market design objectives in a continuous cycle of define d esi gn use. E xisting structures are used and reused c ausing new structures to emerge and these in turn will be used and reused until

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74 change becomes an organizational habitual routine and the ability to adapt to change, or organizational changeability, becomes the only objectified and institutionalized organizational structural property ( Figure 12 ). Figure 12 : Structuration Model of Technology Induced Organization Development The structuration model of technology induced organization development ( Figure 12 ) extends the two IS versions of Giddens structuration theory: adaptive structuration theory (AST) (DeSanctis and Poole, 1994) and the structuration model of technology (Orlikowski, 1992) by moving beyond the traditional structuration process via a recursive relationship between technology and action This model defines the relationship betwe en technology and organizations to consider technology as a catalyst for orga nization change and development and the structuration cycle as a continuous change process that objectifies changeability as an organizational permanent structure that leads to the ultimate goal of the structuration process of IT artifacts: organization development (OD).

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75 The structuration model of technology induced organization developm ent ( Figure 12 ) posits that: 1. Effective structuration process of IT artifacts in organizations does not produce permanent structures. 2. Existing and emerging physical and social structures involved in the spirit objectives) are temporary and potentially modifiable. 3. Effective structuration process of IT artifacts in organizations produce s habit ual routines. 4. Nurtured technology induced habitual routines become over time reified and institutionalized organization structures. 5. Reified organization structures lead to permanent structuration outcomes. 6. The ultimate goal of the structuration process of IT artifacts in organizations is organization development. 7. Technology induced change should be nurtured as a habitual routine by organizations seeking development and growth. 8. Nurtured habit of change causes organizational changeability to become inst itutionalized organization structure. 9. Changeability leads to long lasting and continuous organizational development and growth.

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76 wide, and managed from the top, to increase organizatio n effectiveness and health through planned interventions in the organization's processes, using behavioral science interv entions (French and Bell, 1990) through a cyclical change process of planning, action and fact finding (Lewin, 1946). Action research cycles of behavioral intervention and evaluation has moved traditional behavioral science research from being reactive with respect to technology to b eing a proactive prob lem solving paradigm where IT artifacts, such as information markets, can be adopted and used as interventions to improve organization effectiveness and efficiency. However, it is important to note that although the decision to adopt a nd use an IT artifact as a solution is a behavioral intervention, the subsequent group of of which technology to adopt, is a design science intervention. Design as a G roup of Decisions Organizations faced with a problem can develop in house solutions, buy custom made solutions developed by other organizations, or buy commercial off the shelf (COTS) IT artifacts. The effectiveness of the structuration process of IT artif acts (define design use) depends in some part on how much influence the users have over the developed in eans

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77 of the different ways they interpret, appropriate, and manipulate it. We extend design even before they have any interaction with it. Conceptualizing design as a group of decisio ns and the design process as a use of IT artifacts in the sense that users can still choose among alternative so lutions available in the market and betw een various configurations and settings provided by each solution. For example, organizations seeking to improve their sales forecasts can choose from a variety of information market solutions available in the market place without having to develop one in h ouse and yet retain a sufficient amount of control over their design to ensure an effective structuration process. Some market platforms allow users full control over their design by providing them the option to choose from a range of trading mechanisms, contract types, incentive structures, anonymity levels, trading hours and many other market design features. Each group of settings constitutes a unique IT artifact design that can be evaluated using common de sign science evaluation methods and the impact s of existing structures, such organization policies and culture, on the decision making process can be analyzed as a surrogate for the analysis of the design and development processes for in house developed solutions. The structuration process of IT artif acts ( Figure 12 ) combines both design science design evaluate loops with proactive behavioral science adopt/use evaluate loops to

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78 create an occasion for an ongoing pro cess of organization change and development. The traditional views on the structuration process of technology acknowledge the change caused by the technology action relationship and its interaction with organizations (DeSanctis and Poole, 1994). However, t his change is not planned but rather a natu ral result of situated practice and unless managed its effects on people, group s, and organizations are random and may or may not lead to organization development. The change resulting from the structuration proc ess of IT artifacts ( Figure 12 ) is planned in the sense that technology i s designed or adopted as an intervention to induce change. However, the structuration pr ocess itself takes its own path and progresses in unplanned manner. For example, we do not instruct people how to appropriate the technology. But we do manage the process by first encouraging users to explore and experiment with the different ways of using the t echnology; second, by designing or choosing to adopt IT artifacts that are malleable and can be redesigned or modified as needed ; a nd third, by creating flexible organizations rules and policies that give some degree of freedom to technology users to expe riment allowing for change to eventually take place. It is important to note though that change is not the aspired for outcome but rather the planned continuous change that leads to organization development. Conclusions and Future Directions Conceptualizi ng information market s as an IT arti fact using a structuration lens and placi ng it in a business environment as a system within a bigger system is an important first step towards building information systems theories about organizational

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79 information market s to describe, explain and predict their behavior and impacts on organizations. Attaining a better understanding of the design, implementation and use processes of information markets in organizations is vital to devise design, implementation and use gu idelines and procedures that promote an effective structuration process that leads to organization development. Future research should investigate the structuration and appropriation processes of info rmation markets in organization where markets are used as an intervention to induce organizational change and development. Future research should also characterize the decision making and cognitive processes involved in analyzing/using market information from both the trader and the decision maker perspectives to design effective market interfaces that meets users motivational and informational needs. icacy in satisfying users needs by cognitive walkthroughs, focus groups, surveys or experiments will provide valuable feedback into the design and will add to our knowledge base by providing a better understanding of the design and use process es of markets inside the organization. It will also improve our understanding of the decision making and cognitive proces ses of various market users when analyzing market information. The design of information markets, market interfaces and information visualization should fit the task at hand to accomplish market objectives. However, fit is moderated by traders and organiz ational factors. The accumulation of empirical evidence will provide guidance on how to design highly motivating information ma rkets that

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80 and will suggest the optimal feature set that best fits the problem at hand in order to result in desirable outcomes.

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81 Chapter Four Information Markets for Software Projects Risk Management Introduction Software projects are characterized by high failure rates. In 2006, 19 percent of initiated software projects in the US were outright failures; c anceled before completion or not deployed. 46 percent of projects failed to meet user requirements, had cost overruns, or were not delivered according to schedule (Rubinstein, 2007). In 2007, an independent market research firm surveyed 800 IT managers acr oss eight countries. The results demonstrated that failure rates are universal; 62 percent of IT projects failed to meet their schedules, 49 percent exceeded their budget, and 41 percent failed to deliver the expected business value and return on investmen t (Dynamic Markets Limited, 2007). inability to manage the risks in the early stages of the software development process (Boehm, 1991). Software project risk is an uncertain event th at may have negative effects on the processes and/or outcomes of software projects, such as software quality, scope, costs and schedule (Project Management Institute, 2004). In order to guard against or mitigate the negative effects of the various risks fa cing software projects, management must first identify relevant risk factors, assess their likelihood of occurrence, and their potential impacts on project objectives (Boehm, 1991). A risk matrix can then be

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82 constructed that assigns a risk score to each fa ctor; which is the product of its likelihood and impact (Charette, 1989). objectives have been proposed, such as brainstorming, interviewing, the Delphi method, and scenari o analysis (Project Management Institute, 2004). However, these methods require expert participation and are time and resource intensive. In addition, getting objective and accurate estimation of risk probability and impact at the beginning of software dev elopment projects is very difficult. Thus, recent research has proposed using fuzzy logic and software metrics to assess risks (Liu, Kane and Bambroo, 2006). Although software metrics, such as requirement volatility and cyclomatic complexity, can lead to more objective assessment of risks, they are difficult to measure and expensive to c ollect and update periodically particularly in small organizations with limited resources. Checklist analysis is another popular method for identifying risk factors that has received much attention in the literature due to its simplicity and low cost rel ative to other methods (Iversen, Mathiassen and Nielsen, 2004). Checklist analysis relies on historical data and knowledge of similar projects to create a list of potential risks and their likelihood of occurrence. Several lists of risk factors have been p ublished in the software project management literature (Bohem and Ross, 1989; Barki, Rivard, and Talbot, 1993; Keil, Cule, Lyytinen, and Schmidt, 1998; Moynihan, 1996; Ropponen and Lyytinen, 2000). Other approaches such as risk action list (Alter and Ginzb erg, 1978;

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83 Bohem, 1991; Jones, 1994), risk portfolio model (McFarlan, 1981), and requirements risk analysis (Davis, 1982) have also been popular among software development managers. Each approach has its limitations (Lyytinen, Mathiassen and Ropponen, 199 8; Moynihan, 1997) and thus hybrid methods have been proposed to provide a more comprehensive, context sensitive risk management approach (Lyytine n et al., 1998). However, t t is important to note that although current risk management approaches can be usef ul in identifying and prioritizing risks, assessing risks probabilities and impacts, as well as in suggesting mitigation strategies, none of them addresses the fundamental problem behind software projects failure; communication. Further, the initial risk assessments provided by current approaches are ineffective in reducing software project chances of failure unless there are methods that continuously provide complete, current, and accurate information about the status of project objectives as events unfo ld. Otherwise managers are left with unrealistic, dated assessments of project risks, and as a result fail to take appropriate actions to mitigate them. Many large scale software disasters have been attributed to inaccurate status reporting, such as the c ase of the CONFIRM project (Oz, 1994). Reluctance to transmit bad news (Kiel, Smith, Pawlowski and Jin, 2004), status misperception, deliberate misrepresentation by software developers and project managers (Snow and Keil, 2002), and escalation of commitmen t; where resources are continued to be expended on software projects destined for failure (Keil, 1995), are some of the reasons that lead to inaccurate status reports, and consequently, inaccurate assessments of risks and eventually project

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84 failure. These issues call for creative approaches to improve communication of project status information in order that senior management can terminate failing projects, salvage or redirect valuable resources in a timely manner. This chapter introduces information marke ts to the software project management domain as an approach to risk management. Markets may prove to be invaluable in minimizing software projects chances of failure. By aggregating status information from all levels of the organization and providing early warning signals about risks, markets can design science research paradigm (Hevner et al., 2004) to design an experimental information market solution for software pr oject risk assessment. We evaluate the two controlled experiment s This chapter is organized as follows: section two reviews the literature on software project risk assessment and discusses the ch allenges faced by software project managers that justify the need for the proposed information market approach. We then propose a theoretical framework along with propositions for the determinants of software project risks assessment accuracy. Section thr ee introduces the research approach and research questions. Section four focuses on artifact design and addresses the first two research questions by proposing an information market solution and research hypotheses about its expected utility for software p rojects risk assessment. Section five describes two controlled experiments that used a role playing scenario to evaluate the proposed information

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85 market design and answer the design evaluation research questions. Section six describes data analysis, scale validation and results. A discussion of the findings and their implications for theory and practice are described next. This chapter ends with conclusions and future directions. Challenges to Software Projects Risk Assessment The dynamic nature of the software industry and the high volatility of software project requirements add complexity to the inherently complex task of risk assessment. The intangible nature of software and the lack of visible signs of progress make it hard for management to ascertain true project status or to uncover problems until the project is well over budget or has passed schedule deadlines (Zmud, 1980; Abdel Hamid and Madnick, 1991). Further, traditional project management and control techniques for a cquiring status information to assess project risks, such as meetings, surveys and status reports, have been proven to be ineffective at revealing risks. Abdel Hamid, Sengupta and Ronan (1993) showed that project managers tend to anchor on initial percepti ons of status that affects their decisions to re adjust project plans down the road, even when the situation requires readjustment. Also, Snow and Keil (2002) showed that software project managers make significant errors in assessing status and may not fai thfully report their true beliefs causing reported status to be very different from reality.

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86 In many organizations valuable information that could potentially save millions of dollars is distributed at lower levels of the hierarchy and oftentimes fails to be communicated to project sponsors who have the power to change the direction of the by their sense of personal responsibility to report the bad news which is influe nced by their perception of whether bad news ought to be reported or not (Dozier and Miceli, 1985). true status information are organizational climate and information asymmetr y (Keil et al., 2004). Unhealthy organizational climate can produce the so employees refrain from reporting unpleasant information to management because they fear penalties of various sorts. Research has shown that in organization s where there is reluctance to either reporting and/or hearing negative information, silence will prevail even when an employee is an auditor or assumes a formal role of reporting problems (Keil and Robey, 2001). Organizational culture that does not encou rage open communication creates an news because the interests of employees are no longer aligned with the interests of the organization (Keil et al., 2004). Similarly, w hen perceived information asymmetry between management and employees is high and where individuals think that negative information can be hidden from management, they will be less likely to perceive negative

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87 information as ought to be reported and eventual ly their reluctance to report it will increase (Keil et al., 2004). The central whistle blowing decision model (Dozier and Miceli, 1985; Smith, Keil and Depledge, 2001) assumes that reporting an observed organizational wrongdoing is a choice that is lef t to an individual judgment and depends on whether or not s/he perceives the wrongdoing as ought to be reported and so assumes the responsibility for reporting it. However, in software development projects, as in many organizations, reporting project statu s information is an obligation not a choice. And is generally part of In organizations where all information ought to be reported and each employee is personally responsible for report ing what s/he knows, factors that directly impact individuals reluctance to report bad news become of central focus. Further, there are many other problems that lead to ineffective communication of project status information other than reluctance to repor t bad news, such as status misperception, individual biases, deliberate misrepresentation, reporting incomplete or dated status information, and organizational silence (Park and Keil, 2009). These problems contribute to inadequate assessment of software pr oject risks that causes escalation of commitment to a failing billions of dollars every year. Thus, organizations are in desperate need for information gathering and sha ring mechanisms that adjust for subjectivity in individual judgment, cancel individual biases

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88 out, offer incentives for faithful revelation of status information, and are capable of rapidly moving project status information from those who have it to those who need it to assess risks and make decisions. Research Framework and Research Questions The project status report is a key element in the software project risk assessment process. Current studies have focused on the accuracy of reported status informati on and bad news reporting in the context of IT projects (Snow and Keil, 2001; Keil et al., 2004). However, accuracy is only one attribute of project status information. Little research attention has been given to factors that impact other attributes of inf ormation, and consequently the accuracy of risk assessment. For example, accurate information can be incomplete and does not reflect the whole picture, or not up to date and does not incorporate t he latest development progress updates or problems. Thus, w e propose a theoretical framework to explain the variance in accuracy of software projects risk assessment ( Figure 13 ). We incorporate the factors identified in the literature that are proven to impact the accuracy of reported status in the proposed model. Table 8 summarizes the model propositions. There are three main factors that determine the accuracy of risk assessment: ( 1) currency of reported status information ( 2) completeness of reported status information and ( 3) accuracy of reported status information

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89 Figure 13 : Theoretical Framework for the Determinants of Software Projects Risk Assessment Accuracy Table 8 : Theoretical Framework Propositions Propositions P1: More current status information leads to higher accuracy of risk assessment P2: Higher accuracy of status information leads to higher accuracy of risk assessment P3: More complete status information leads to higher accuracy of risk assessment P4: Higher individual willingness to report bad news leads to higher accuracy of status information P5: Lower individual errors of perception of project status leads to higher accuracy of status information As currency, accuracy, and completeness of report ed status information increases, the accuracy of risk assessment will also increase. The accuracy of status information depends on ( bad news and is positively correlated with it, and ( errors of perception of true project status and is negatively correlated with it (Snow and Keil, 2001; Keil and Robey, 2001; Kiel et al., 2004). + + + + Currency of Sta tus Information Individual Willingness to Report Bad News Accuracy of Risk Assessment Accuracy of Status Information Individual Errors of Perception of Project Status Completeness Of Status Information P 1 P 2 P 3 P 4 P 5

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90 Based on the proposed framework ( Figure 13 ) the greatest improvement in software risk management will come from tools that increase the accuracy of risk assessment by improving the currency, accuracy, and completeness of reported status information Informatio n accuracy can be improve d by adjusting for individual errors in perception of the project true status due to having access to only partial knowledge about the project and by increasing willingness to report negative status information Existing tools for identifying and assessing risks are only effective in reducing ( 1) efficiently collects and combines information from around the organization to provide complete assessment about the status of different project objectives, such as scope, quality, cost and schedule, ( 2) responds to unfolding events by rapidly incorporating new information into the assessment to provide current and up to date assessment of risks, ( 3) adjusts for individual errors in perception of project status and risk assessment, and ( 4) motivates those who are involved in the project or have access to information about its progress to faithfully report status information. The design scie nce paradigm (Hevner et al., 2004) is concerned with the design and evaluation of technological solutions, or IT artifacts, to fulfill an identified business need. Thus, we are utilizing the design science research paradigm to design an experimental Web ba sed information aggregation mechanism, known as an information market, to aid organizations and project managers in assessing software project risks

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91 ( Figure 14 ). Market design is informed by existing theories, methodologies, and empirical evidence in the information market and software project management literatures. The proposed market design and its expected utility in the area of software project risk assessment are evaluated using controlled experiments. Experimental results can be used to refine market design and will contribute back to our knowledge base. Figure 14 : Design Science Approach for Designing and Evaluating an Information Market Solution for Software Project Risk Assessment Following the design science research guidelines proposed by Hevner et al. (2004), and our proposed research approach (discussed in chapter 2) for designing and evaluating IT artifacts developed to fulfill an identified business need, our research questions are organized into two sets: IT artifact design and IT artifact design evaluation. IT Artifact Design RQ 1 : What is the design of the information market solution for software projects risk assessment ? RQ 2 : What is the expected utility of the proposed information markets solution? IT Artifact Design Evaluation RQ 3 : What is the information market efficacy in providing hypothesized utility? Business Need Software Project Risk Assessment Knowledge Base Relevant literature Justify Inform Apply Add Evaluate Refine

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92 IT ar tifact design research questions are: RQ1 What is the design of an information market solution for software projects risk assessment? RQ2 What is the expected utility of the designed information market for software projects risk assessment? IT artifa ct design evaluation research questions are: RQ3 What is the efficacy of an information market in providing hypothesized utility for software projects risk assessment? Information Markets Design An information market is a form of futures markets where individuals trade contracts whose payoff depends on the outcomes of uncertain future event. According to rational expectations theory (Muth, 1961), individuals take all available information into account in forming expectations about future events. In stro ngly efficient markets (Fama, 1970) prices of traded assets reflect all available information about future prospects of the asset. Since prospects are analogous to events, prices in efficient information markets reflect all available information about the likelihood of the events. Information markets utilize market efficiency and the information aggregation property of prices (Hayek, 1945) to harness the collective knowledge of participants about the likelihood of future events. Although information markets differ in many

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93 respects, such as trading mechanism, payoff function, composition of initial portfolio, and incentive structure, they generally consist of one or more events for which you would like a reliable forecast. The standard contract in the market is the binary contract, aka winner take all. It costs a certain amount and pays off, for instance, $1 if and only if the event occurs and nothing otherwise. Traders buy and sell contracts of future events based on their beliefs in the events likelihood of occurrence. The higher the likelihood of the event the higher its contract price and vice versa. The result is a trading price that tracks the consensus opinion (Hanson, 1992) and can be interpreted as market aggregated forecast of the event probability ( Wolfers and Zitzewitz, 2004). For example, if a contract price is selling for $60 that means there is a 60% chance of the event happening. In addition to forecasting events probability, the type of contract used in the market and its payoff function can e licit the collective expectations of a range of different parameters such as the mean or median value of an outcome (Wolfers and Zitzewitz, 2004). For example, the price of index contract with payoff proportionate to the outcome represents the market mean expectation of the outcome and the price of a spread contract Experimental research on information aggregation suggest that markets can aggregate and disseminate information fai rly well (Forsythe and Lundholm, 1990; Plott and Sunder, 1988) and many successful implementations of information markets demonstrate their ability to aggregate information and generate reasonably accurate

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94 forecasts about a wide variety of events, such as presidential election outcomes ( Forsythe, Nelson, Neumann, and Wright, 1992) project delivery dates (Ortner, 1997, 1998), product sales (Chen and Plott, 2002; Hopman, 2007), and movie box office returns (Spann and Skiera, 2003). We propose a Web based in formation market solution to help organizations in assessing risks facing software development projects. Table 9 summarizes the major design decisions that organizations must consider before implementing an information market. Table 9 : Information Markets Major Design Aspects Design Decisions Market forecasting goal Contract payoff function Trader composition of initial portfolios/endowment Incentive mechanism Trading mechanism Trading anonymity Trading synchronicity Trading duration Following a design science research approach, market design is refined iteratively based on evaluation results. So organizations can experiment with various design configurations, such as implementing different incentive structures, payoff functions, and t rading durations, until a design that suits their needs and provides the expected utility is achieved.

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95 In the project management literature, project failure has generally been associated with not meeting four main objectives; cost, time, quality and scope (Atkinson, 1999; Lyytinen and Hirschheim, 1987; Project Management Institute, 2004; Shenhar, Levy and Dvir, 1997). Consequently, any factor that causes the project to go over one or more of its planned objectives is a risk that should be mitigated. T he higher the number of unmet objectives, the higher the project overall riskiness level and its chances of failure. Information markets can be used to monitor the status of the software projects main objectives and the overall riskiness level of the proje ct. The questions asked in the market are directly related to its forecasting goal and are designed to reveal the true status of the project, or in other word s its riskiness level. An information market for each project objective can be launched to predic t how likely each objective is to go over its planned limit, and another information market can be used to predict the riskiness level of the project or how likely it is that one or more of its objectives are currently unmet. The more unmet objectives the higher the riskiness level of the project. Questions asked in the markets take into account the impact definition of risks on major project objectives and seek to assess the collective forecast of the likelihood of these risks. Figure 15 provides some examples of risk impact definitions on cost, time, scope and quality objectives. Organizations can choose to keep track of only high or medium impact risks on the four main project objectives. For example, an information market designed to monitor high impact risks on the status of a project cost objective will predict the likelihood of 20

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96 40% cost increase. Another market designed to monitor medium impact r isks on the status of the time objective will predict the likelihood of 5 10% time increase. Same applies to scope and quality objectives. Project Objective Impact Scales of a Risk on Major Project Objectives Very low ( 0.05 ) Low ( 0.10 ) Medium ( 0.20 ) High ( 0.40 ) Very High ( 0.80 ) Cost Insignificant cost increase < 10% cost increase 10 20% cost increase 20 40% cost increase >40% cost increase Time Insignificant time increase <5% time increase 5 10% time increase 10 20% time increase >20% time increase Scope Scope decrease barely noticeable Minor areas of scope affected Major areas of scope affected Scope reduction unacceptable to sponsor Project end item is effectively useless Quality Quality degradation barely noticeable Only very demanding applications are affected Quality reduction requires sponsor approval Quality reduction unacceptable to sponsor Project end item is effectively useless Figure 15 : Definition of Impact Scales for Four Project Objectives (from PMBOK Guide) Market generated probabilities of high or medium impact risks on different project objectives can then be used to assess the status of objectives using a risk matrix setup with risk impact definitions numeric scales ( Figure 16 ). Risk definitions and interpretations can vary from one organization or project to the other. For example, if the market generated probability of a high impact risk (0.40) (such as having 20% cost increase) reaches 50%, the cost objective is considered unmet and warrants immediate managerial attention.

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97 Probability Risk Score 0.90 0.05 0.09 0.18 0.36 0.72 0.70 0.04 0.07 0.14 0.28 0.56 0.50 0.03 0.05 0.10 0.20 0.40 0.30 0.02 0.03 0.06 0.12 0.24 0.10 0.01 0.01 0.02 0.04 0.08 Impact 0.05 0.10 0.20 0.40 0.80 Figure 16 : Risk Matrix The forecasting goal of the proposed experimental information marke t ( Table 10 ) is the project riskiness level. The status of the project main objectives can be used to make an assessment of the project overall riskin ess level using a simple status reporting 2001). For example, if all four main project objectives are currently met, the project is considered low risk or Thus, there are three possible outcom es to the question asked in the market ( High Risk Medium Risk and Low Risk ). The market implements winner takes all payoff function. So after the market closing date, market prices can be interpreted as outcomes probabilities, and when the project true st atus can be determined with certainty, each contract bought in the actual outcomes will pay off a $100 virtual dollar and all others will pay off nothing. Low Risk Medium Risk High Risk

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98 sufficiently large amount of virtual money to guarantee liquidity and sustain trading activity as events unfold. Contracts are cashed out when the market closes, and incentives endowment. T he trading mechanism used in the proposed market design is automated market maker (AMM). Automated market maker has several advantages over its widely used counterpart; continuous double auction (CDA) that makes it particularly suitable to use in organizat ional markets. Markets used in organizations tend to be thin with a relatively small number of traders which can cause liquidity problems that negatively impact market forecasts. Unlike CDA, AMM guarantees liquidity because it does not require matching sel lers to buyers but instead it let traders buy and sell contracts directly from the market, and as a result, transfer some of the financial risk to the market institution. Web based implementations of information markets are not restricted by location or t ime and thus allow for both synchronous and asynchronous trading. Asynchronous trading can be particularly useful for organizations because employees, developers, customers and other project stakeholders can participate in trading or have access to the mar ket from anywhere and at anytime. Synchronous trading via the web in multiple sessions is chosen because design evaluation experiments are conducted in a controlled environment where experimental task requires all subjects to be in the same place at the sa me time to facilitate training and distribution of information. Further, synchronous

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99 trading in a controlled environment allows us to simulate real events at a more expedited pace than what a field study would allow and yet be able to achieve the same desi red effects. Table 10 : Experimental Information Market Design for Software Project Risk Assessment Design Aspect Selected Experimental Design Forecasting goals Project riskiness level (Low, M edium or H igh ) Payoff function Winner takes all ($100 if true, $0 if not) Composition of initial portfolios/endowment No shares; $10,000 virtual money Incentive mechanism Reward highest (Net worth $10,000) Trading mechanism Automated market maker Trading anonymity Anonymous Trading synchronicity Synchronous Trading duration 8 rounds 3 minutes each Information Markets Expected Utility The second IT artifact design research question focuses on the expected utility of the proposed information market solution for software projects risk assessment. Since project status information is the main input used by project sponsors to assess risks f acing software projects, an information market is expected to provide utility by improving the currency, accuracy, and completeness of reported status information that will in turn increase the accuracy of project risk assessment. The proposed information market is expected to improve the completeness of status information by aggregating information about project objectives from all individuals involved in the project or who have information or even intuition about

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100 project progress, regardless of their form al role or level at the organizational hierarchy. Information markets disseminate gathered information in form of prices that can be interpreted as a status report or collective assessment of project risks. Thus, in a properly designed information market, price or market generated risk assessment should be equal to the reported status or assessment of a hypothetical person who has access to all project information. H1 : An information will approximate the report ed assessment of a single person in possession of all the information. The information aggregation property of market prices provides a cost effective alternative to existing methods of information gathering such as surveys, periodic status reports an d meetings. Further, information markets are dynamic and responsive to changing circumstances. Prices in information markets prove to incorporate new information almost instantly ( Forsythe et al., 1992) and, therefore, can improve the currency of aggregate d status information and provide continuous and up to date assessment of risks. Thus, information market price is expected to quickly move up or down in response to new information and so provide up to date assessment of risks. Individuals often mispercei ve the true status of the project due to having partial information about its progress which biases their assessments of risks. The process of price formation and discovery provides a solution to the complex task of aggregating individual assessments of risks. Trading dynamics in a market setting cancel individual

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101 biases and errors out, preventing them from impacting predictions (F orsythe et al., 1992; Forsythe, Rietz, and Ross, 1999; Oliven and Rietz, 2004) and therefore can improve the accuracy of aggregated status information. H2 will be more accurate than any indivi dual reported assessment of project risk Thus, in an organization where disparate project status information is dispersed among many people, a well designed information market can collect this information bringing about, in form of prices, a complete and up to date collective assessment of project risks purified from individual biases and errors. However, prior research has identified several factors that impact the accuracy of reported status information, such as deliberate misrepresentation of status i nformation (Snow and Keil, 2002). Although a well designed aggregation mechanism, such as an information market, can adjust for individual errors caused by inaccurate perceptions of project progress, accounting for information misrepresentation, or individ uals reluctance to report accurate information remains a challenging task. In the context of IT projects, research adopting the whistle blowing theoretical perspective (Dozier and Miceli, 1985) has identified situational, organizational and personal va negative information. Those factors are useful in predicting communication effectiveness

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102 i nformation. However, some situational factors such as project risk (Smith et al., 2001) and impact of information technology failure (Park, Keil and Kim, 2009), organizational factors such as organization climate (Keil et al., 2004), and personal factors s uch as individual morality, ethics, and wi llingness to communicate (Park et al., 2009) cannot be easily adjusted or controlled. Research that aims to identify factors that can be controlled is critical because it enables organizations to target these fact ors to improve communication effectiveness, and factors that can be controlled by organizations seeking to improve communication and increase individual willingness to report accurate status information, and consequently increase the accuracy of project risk assessment ( Figure 17 ). In the context of software f retribution contribute to the problem negative status information (Keil and Robey 1999, 2001). Keil et al. (2004) extended the basic whistle blowing model (Dozier and Miceli, 1985, Smith and Kiel, 2003; Smith et al., 200 reluctance to report bad news: organizational climate and information asymmetry. They found that when organizational climate is not conducive to openness about problems,

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103 individ uals have an incentive to shirk and their reluctance to report bad news will increase. Figure 17 : Conceptual Model: Willingness to Report Bad News Table 11 : Conceptual Model Propositions Propositions P 6 : Higher perceived anonymity of reporting mechanism increases individual willingness to report bad news P 7 : Higher perceived self interest in truthful reporting increases individual willingness to report bad news P 8 : Lower perceived information asymmetry between employees and management /clients increase individual willingness to report bad news According to agency theory, agents are risk averse and will avoid any encounters that might jeopardize their jobs (Harrell and Harrison, 1994). Establishing an organizational climate that promotes open ness might provide a long term solution. However, it is not always possible and is certainly not an easy task. Thus we propose that higher perceived anonymity of communication mechanisms increases individual Perceived Anonymity Perceived Information Asymmetry P6 P7 P8 + + Individual Willingness to Report Bad News Perceived Self Interest

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104 willingness to report negative status informatio n regardless of the organizational climate ( Table 11 ), and is a factor that can be easily adjusted or controlled by organizations. Anonymity is a complex and influential aspect of communications medium that has received much attention in the study of collaborative technologies and group support systems (GSS) (Valacich, Leonard, Dennis and Nunamaker, 1992). An evaluation of 54 case and field studies of organizat ions using group support systems (GSS) technology to improve decision making, identified anonymity as a characteristic of successful GSS implementations (Fjermestad and Hiltz, 2001). Anonymity features of the communication medium improves the communication process, and the overall group satisfaction with the technology compared to face to face meetings where group members are identified (Fjermestad and Hiltz, 2001), broadens participation and encourages diversity of thought (Bikson, 1996), improves the effe ctiveness of the communication process (Dennis, Heminger, Nunamaker and Vogel, 1990), and increases group meetings quality (Dennis, Tryan, Vogel and Nunamaker, exposed will pr ovide employees with a sense of security and consequently will increase the accuracy of their reports. Employees participating in an information market report status information through their market trades. The proposed information market design allows for anonymous trading, where participants post bids or asks and perform market transactions

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105 using pseudo names. Thus, it is expected to increase their perceived anonymity of the market reporting mechanism ( Figure 18 ). H3 : An information market in which trading is anonymous will anonymity Figure 18 : Research Model: Information Market Impact on Willingness to Report Bad News Additionally, based on agency theory, employees are utility maximizers and seek their self interest. So if employees feel that hiding information or remaining silent is in their best interest, they will shirk from reporting bad news. We propose that a higher perceived self willingness to report bad news ( Table 11 ). Thus organizations should focus on factors that interest, and at the same time, can be H3 Perceived Anonymity + + Individual Willingness to Report Bad News Perceived Self Interest H4 H5 Perceived Information Asymmetry Information Market H6 +

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106 easily controlled. Incentives improve goal congruence between employees and organizations (Eisenhardt, 1989). Therefore we propose that a communication mechanism that offers incentives to employees for revealing true status information will increase the ir perception of self interest and as a result their willingness to report negative status information ( Figure 17 ). An information market offers incentives for faithful trading since contracts payoff depends on the outcomes of the forecasted events. So if e mployees have negative information about project progress, it is in their best interest to trade based on this information because they will benefit when events eventually occur ( Figure 18 ). H4 : An information market that provides incentives for faithful self interest in reporting true status information In addition to perceived anon ymity and perceived self interest, we propose that adjusting perceived information asymmetry between employees and management can Figure 17 ). When reluctance to report bad news will increase (Keil et al., 2004). We propose that a communication mechanism t asymmetry (by making them feel that they cannot hide negative information from management) will increase their willingness to report bad news ( Table 11 ).

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107 Monitoring projects progress reduces privately percep tion of information asymmetry. An organizational informa tion market acts like a project monitoring tool that facilitate s identification of risks early enough to mitigate them. Further, an i nformation market encourages employees to seek their self interest (because money is involved), so employees will soon realize that they are better off utilizing their information advanta ge by trading on what they know because if they do not, others will, and consequently the market will reveal this information to management or the client In other words, an information market acts as a control mechanism and will decrease employees perceiv ed information asymmetry between them and management/client ( Figure 18 ). H5 information asymmetry between them and management/client Ineffective monitoring and failing to manage goal conflict, shirking, and privately held information are among the primary reasons for software development projects failure (Mahaney and Lederer, 2003). Organizations can design communication mechanisms, such as information market, that allow for anonymous reporting, offer incentives, and act as a monitoring tool of the project that creates low perceived information asymmetry in the organization reports by increasing their willingness to report negative information.

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108 H6 : An information market in which trading is anonymous and provides incentives for truthful revelation of information will Now we describe design evaluation researc h questions and the experiments conducted to evaluate the proposed information market design and to test hypotheses about its expected utility for software projects risk assessment. Information Markets Design Evaluation details of the information aggregation and dissemination process are no t yet fully understood (Plott and Sunder, 1982; 1988; Forsythe and Lundholm, 1990). And although the results of laboratory experiments on security markets are useful in informing information markets design, information aggregation tasks used in lab experim ents lack realism and their results are difficult to interpret and generalize to business settings. The results of pilot studies in the field are encouraging by their demonstration of the feasibility of using information markets in organizations, but they do not provide sufficient levels of internal validity and control required to advance a rigorous theory of organizational information markets. There is a need for more controlled experimental studies on the use of information markets for business problem s that use business related tasks and scenarios. Such experimental studies are needed to advance the theory of organizational information

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109 market s and to improve our understanding of their utility to organizations. Experiments should provide sufficient degr ee of control that allows us to draw conclusions about manipulation effects and causality which, in turn, will allow us to build theoretical models to explain and predict the impact of various information markets designs on key business related dependent v ariables, and to explain and predict information markets performance in specific business settings. Experimental results are important to build a fundamental understanding of how information markets work, what are their expected impacts and benefits, and why they are expected to work well in some organizations but not as well in others. Such an understanding will allow organizations to better utilize information markets. Field studies can then be used to test developed theories and research models. Thus, to answer design evaluation research question we conducted a laboratory experiment using the proposed experimental information market ( Table 10 ) to test the market efficacy in providing complete, current and accurate information about software project risks. We used Inkling prediction markets platform ( www.inklingmarkets.com ) to setup the proposed risk assessment market. Gi ven the developed theoretical framework ( Figure 13 ) and hypotheses outline d in the previous section, we developed preliminarily experimental materials that include a business case, five different information structures that include different software development progress updates, and five different versions of a software project risk assessment survey.

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110 The surveys included a section in which the subjects were asked to provide comments and suggestions to improve the clarity and understandability of the case and the survey. Each survey included a different information structure, or in other words, different development progress updates that give information about the sta tus of the four main project objectives (functionality, quality, cost and schedule). It also included four manipulation check questions that asked participants to evaluate whether each project objective is currently met or not. The manipulation check quest ions tested the participants understanding of the case and the progress updates. The preliminarily case and surveys were administered to a group of 25 graduate students and their responses, comments and suggestions were used to strengthen the manipulations and improve the clarity of the case. Seven doctoral students pilot tested the risk assessment experiment using the information market. The result s were used to improve several d esign aspects of the experiment; i ncluding trading sessions duration, incentive structure, and the distributed experimental materials (progress updates) The reminder of the section describes final experiment s and instruments. Information Market Experiment The final business scenario asked participants to play the role of a member of the design and development team in a large consulting firm that is developing a new reservation system for an association of hotels and car rental corporations (the client). The scenario and development updates are inspired by the events of a real software

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111 development project; the CONFIRM project (Oz, 1994). The scenario described four main objectives for the development project in terms of functionality, performance, budget and schedule. It also described conditions under which these objectives are considered unmet. Appendix A shows the information markets experimental scenario. Five different information structures were created that include software development progress updates to help participants verify whether project objectives are currently met or not, and to help them assess the riskiness level of the project. Appendix B shows the information structure s Each information structure was manipulated to provide information abou t the status of two or more of project objectives ( Table 12 ). Table 12 : Experimental Information Structure s Group N Information Advantage A 7 Functionality and schedule objectives are unmet B 8 Schedule and budget objectives are unmet C 11 Functionality and performance objectives are unmet D 6 Public information All four project objectives are met E 10 Public information an d groups A, B and C information advantage Information structures were created to simulate the case of a real software development project. Groups A, B and C represent groups of people who have private information about different aspects of the project an d thus have only partial knowledge about the project overall status. Group D represent those who are not directly involved in the project and have access only to information that is publicly available which does not

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112 always reflect the true status. Group E represents the hypothetical person (that H1 refers to) who possesses all available information about the project. Five versions of the risk assessment survey were created and administered to a different group of participants. Each survey included the busi ness scenario shown in appendix C, and one of the developed information structures that include the development progress updates ( Table 12 ). The survey had four manipulation check questions that asked about the status of the four main objectives. It also included the risk assessment question that asked participants to assign a p robability score to each of the three risk states outlined in Table 13 to describe the project riskiness level based on the information they have about the status of the project objectives. Participants were told that the sum of three probabilities should be equal to 1. Table 13 : Risk Assessment Question Project Riskiness Level Probability% L ow risk: All four objectives are met to date M edium risk: Two or three objectives are met to date H igh risk: One or no objectives are met to date Sum 100% The risk assessment survey question is identical to the question asked in the proposed experimental information market ( Table 10 ). The market forecasting goal was to predict the riskiness level of the software project described in the same business case described above. Seven graduate students participated in market trading. Table 14 shows the market participant s d emographics. The experiment lasted 24 minutes. Development

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113 progress updates were distributed in 6 of the 8 t rading sessions. Each session lasted around 3 minutes. Participants were randomly assigned to one of four groups (Group D had one participant). Group s A, B C, and D received identical development progress updates to the updates provided to the participants who completed the surveys. Table 14 : Market Participants Demographics Subjects Demographics N Min Max Mean S.D. Age (Years) 5 22 38 27.6 6.23 Work Experience (Years) 7 0 26 11 3 6 10 .4 5 Experience in Software Projects (Years) 7 0 14 3 14 4 95 N Male Female Gender (%) 7 86% 14% The true riskiness level of the project described in the experimental business case scenarios was where all project objectives are currently unmet. Each participant in the market had access to only partial knowledge about the true status of the project ( Table 12 ) in addition to the predictions of four information markets each designed to monitor the status of one of the project four main objectives ( s hown in Appendix C ). Market participants were expected to use their private information and the information they learn ed from markets to trade in the risk assessment market. At the end of trading, the market was expected to aggregate the private information distributed to all participants to reveal the true status of the project.

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114 Publishing private information in form of market predictions allows participants to benefit from their information advantage and at the same time accounted for internal communication channels among them I n organizations private information about the status of different pr oject objectives becomes known to others as project due date approaches, or simply because employees choose to share it with others or report it to management. This practice of making private information p ublic was proven not to detract from information ma rkets effectiveness in aggregating private information. To the contrary it was shown to outperform settings where private information is not disclosed or where all information is publicly available ( Almenberg Kittlitz and Pfeiffer 2009) Also this practice suggests the information market usefulness in organizations that foster transparency and encourages open communications about issues and problems. The goal of the experiment was to test H1 and H2 by ( 1) comparing the market generated assessment of project risk to the average assessment of group E who received all available information about the project, and ( 2) comparing the accuracy of market generated assessment of project risk to the accuracy of ave rage assessment of groups A, B, C, and D. news, and as a result improve the accuracy of their status reports, we administered a survey to a sample of 72 graduate and undergra duate business students enrolled in information systems classes in a large metropolitan university in the United States. Table

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115 15 Participants work experience suggests that they are appropriate subjects for this type of experiment since the manipulations and treatment conditions are associated with organizational dynamics and decision making. Table 15 : S ubjects Demographics Subjects Demographics N Min Max Mean S.D. Age (Years) 65 21 44 28.31 5.99 Work Experience (Years) 71 0 26 8.46 7.04 Experience in Software Projects (Years) 71 0 20 2.80 5.17 N Male Female Gender (%) 70 76% 24% The subjects were told that the survey is part of a study that examines business decision making, and that it consisted of two parts. The subjects were informed that the survey is anonymous and their participation is completely voluntary. The first part of the survey described a business scenario and asked the participants to play the role of a member of the design and development team in a consulting firm involved in the development of a transaction processing system for a department store (the client). Th e scenario described negative project status information that according to the signed agreement between the company and the client allows the client to break out of their contract with the company. Appendix D shows the survey experimental scenario. The sc enario was manipulated to reflect conditions of high information asymmetry, low self interest in reporting negative information, and non anonymous reporting mechanism in the organization. For the condition of high information

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116 asymmetry between the client a nd the organization, the subjects were informed that unless employees report negative status information, the client will not become aware of them until the project due date. For conditions of low self interest in reporting negative information, the subjec ts were informed that employees are expected not to mention problems in their status reports because management shares them with the clients, and those who mention problems in their reports get in trouble. For the non anonymous reporting condition, the sub jects were informed that status reports must include the After reading the case, subjects were asked to express how strongly they agree or disagree with a series of manipulation check statements that measured their percei ved information asymmetry, perceived self interest and perceived anonymity of reporting mechanism in the organization. Then they were asked to express how likely they would report the negative status information. The second part of the survey introduced ad ditional information to the case. The subjects were told that the client decided to use an information market to track the development progress of its transaction processing system. Subjects were informed that information markets are known for their abilit y to quickly incorporate new updates and information to provide up to date assessment of the status of project objectives. This property is expected to bring negative status information to the client attention very quickly. Subjects were also informed that trading in the information market is anonymous, and all transactions, bids and asks are maintained by

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117 an independent third party organization. Employees can report negative status information or system problems in an information market without being ident ified. The market offers incentives for true revelation of status information. So if employees are reporting honestly they will benefit financially. All profits will be directly deposited by ect their identities. All individuals involved in the design and development of the system, or have any information about its progress, are participating in market trading. Subjects were then asked to respond to the same questions they answered in the firs t part to test the market impact on their perceived information asymmetry, perceived self interest in reporting bad news, perceived anonymity of reporting mechanism in the organization, and their willingness to report bad news. The four constructs of int erest were measured using multiple item scales using pre validated instruments wherever possible. Appendix E shows all measurement scales organized by construct. Perceived information asymmetry was measured using two likert scaled items developed and valid ated by Kiel et al. (2004). Items were reworded to fit the context of the scenario. Perceived self interest was measured using three likert scaled items designed specifically for this study. Perceived anonymity was measured using two likert scaled items wh ich were also designed specifically for this study. Willingness to report bad news was measured using a modified version of the three likert scaled items developed and validated by Kiel et al. (2004) and Park and Kiel (2009).

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118 Data Analysis and Results Data analysis was performed in two phases. In the first phase, the reliability and construct validity of all measurement scales were tested using confirmatory factor analysis (CFA). Confirmatory factor analysis was chosen over alternative statistical techn iques such as exploratory factor analysis because a priori theory about the number of factors and the relationships between factors and indicator variables exists. Amos 18 M d items were modeled as reflective indicators of their corresponding factors. Scale Validation Scale validity can be demonstrated through measures of convergent and discriminan t validity. Fornell and Larcker (1981) recommended three measures to assess convergent validity. ( 1) Standardized item to factor loadings ( ) should exceed 0.70. However, item loadings of 0.5 or 0.6 may still be acceptable if other items have high loa dings on the same factor (Chin, 1998). ( 2) Composite reliability for each construct should exceed 0. (Bearden Netemeyer and Mobley 1993) and ( 3) average variance extracted (AVE) for each construct should exceed 0.50, meaning that 50% of variance of the indicators is accounted for by the construct. Composite reliability scores are calculated using the following formula (Chin 1998, p.320) where is the standardized loading of the item (i) on the factor.

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119 Average variance extracted (AVE) scores are calculated using the following formula (Fornel and Larcker, 1981) where is the standardized loading of the item (i) on the factor. As seen in Table 16 standardized item to construct loadings for all scale items exceeded 0.70 except for the first anonymity item which has a 0.56 loading. However, the second item within the same block has a very high loading of 1. In addition, the composite reliability for perceived anonymity construct is higher than 0.70 threshold value, and its average variance extracted is higher than the recommended value of 0.50. Therefore, the first anonymity item loading was deemed acceptable. Table 16 : Item to Construct Standardized Loadings Construct Item Item Loading Perceived information asymmetry (IA) IA1 0.71 IA2 0.92 Perceived self interest (SI) SI1 0.83 SI2 0.78 SI3 0.82 Perceived anonymity(AN) AN1 0.56 AN2 1.00 Willingness to report bad news (WL) WL1 0.93 WL2 0.80 WL3 0.85

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120 reliability or the internal consistency of each constructs items. The recommended threshold is 0.70 for and 0.80 for the composite reliability However, a score of 0.70 or higher is sufficient to demonstrate extensive evidence of construct reliability. As shown in Table 17 and composite reliability of 0.70 or higher and the a verage variance extracted for all construct is higher than the recommended threshold of 0.50. Thus, all three conditions of convergent validity were met. Table 17 : Constructs Reliability Construct Composite Reliability Alpha Average Variance Extracted (AVE) Perceived information asymmetry (IA) 0.80 0.79 0.68 Perceived self interest (SI) 0.85 0.84 0.66 Perceived anonymity (AN) 0.78 0.70 0.66 Willingness to report bad news (WL) 0.90 0.90 0.74 To assess the constructs discriminant validity, we used Fornell and Larcker (1981) recommendation that the average variance extracted for each construct exceeds the square of correlations between that construct and all other constructs. As shown in Table 18 the highest square of correlations is 0.48 between perceived self interest and willingness to report bad news and is lower than the lowest average variance extracted of 0.66 for perceived self interest. Thus, the recommended condition for discriminant validity was met.

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121 Table 18 : Discriminant Validity Construct Average Variance Extracted (AVE) Squares of Correlations Between Constructs IA SI AN WL IA 0.68 -0.09 0.17 0.07 SI 0.66 0.09 -0.07 0.48 AN 0.66 0.17 0.07 -0.05 WL 0.74 0.07 0.48 0.05 -Hypotheses Testing The market generated assessment of the project riskiness level was ( High Risk 86.23%, Medium Risk 8.46% and Low Risk 5.30%). These probabilities are equal to the average price for the transactions posted in the last minute of trading in each of the three states Figure 19 s hows the price curves of the project three riskiness states for the entire high risk f the project, the rest of Figure 19 : Price Curves of the Project Riskiness States 0 10 20 30 40 50 60 70 80 90 100 0 5 10 15 20 25 H M L Time (Minutes) P R I C E

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122 All three risk states started with equal probabilities (33.33%) of being the actual state at the beginning of the experiment. The price curve fluctuate d according to the development progress updates. The updates were manipulated in such a way as to test the market responsivenes s to negative status information. At the beginning of the experiment all updates and market predictions indicated that the project is within planned objectives. At the beginning of the third trading session updates probability went up. Around minute 15 (beginning of trading session 6) updates started to show that other project objectives are going over their planned goals, and consequently t well over its planned objectives until it reached a near certain probability. It is worth noting that trading slowed down during the second and fifth trading sessio ns where no updates were distributed to participants, and speeded back up in the following sessions where updates indicated a change in project status. This demonstrates the market responsiveness to updates and its ability to provide current information ab out project risks. To test H1, a t test was conducted to compare the market generated assessment of high risk = 0.8623) to the mean assessment of participants in group E who received all available information about the project.

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123 H1 Statistical Hypotheses H 0 : E = P m H 0 : E = 0.8623 Ha: E <> P m Ha: E <> 0.8623 We assume that the population from which all samples in the five groups are randomly drawn is normal ly distributed Although the t test is fairly robust against violation of normality assumption, we will not be able to test the assumption because of the relatively small sample size in each of the groups Thus, we also report the results of the non parametric equivalent to the t test : one sample Wilcoxon test (also known as Wilcoxon signed rank test ) as a comp le mentary test The one sample Wilcoxon test does not make any assumptions about the sampling distribution and is used to test whether the sample median is equal to a specified value or not Table 19 Table 19 : Groups Assessment of High Risk Probability Groups N Mean (High Risk %) S.D. Median ( High Risk %) Group A 7 0. 2214 0 .20587 0.2500 Group B 8 0.0 438 0 .09039 0.0000 Group C 11 0.2 318 0 .36351 0.0000 Group D 6 0.0983 0 .14148 0.0250 Group E 10 0.9500 0 .12693 1.0000

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124 Given the sample data from Group E the t observed value (2.185) was less than the critical value (2.262). Thus, we fail to reject the null at 5% significance level ( p value = 0.057). In other words, the results of the t test failed to reveal a statistically reliable difference between the market assessment and the true mean assessment of project risk made by individuals in possession of all the information. The power of the t test is 0. 747 indicating that given our sample data, the probability of detecting a mean significantly different from the market assessment given such a difference actually exists is reasonably high. Since no significant difference was detected in the t test, the result is much more likely to be due to a zero difference (supporting H1) rather than to a Type II error In addition a t 5% signi ficant level t he result s of Wilcoxon test have also failed to reveal a statistically reliable difference between the market assessment (test value = 0.8623) and the true median assessment of project risk made by individuals in group E (p value = 0.59) Thus, H1 was supported. To test H2, a series of t tests were conducted to compare the accuracy of the market to the accuracy of the groups (A, B, C, and D) mean assessment of the project H2 Statistical Hypotheses H 0 : (A i ) <= A m H 0 : (A i ) <= 0.0877 Ha: (A i ) > A m Ha: (A i ) > 0.0877 i = A, B, C or D The accuracy of the groups and the market assessment equals the absolute

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125 the mean assessment made by group E (Assuming P E = E ). Table 20 shows the market vs. groups risk assessment accuracy. Table 20 : Market vs. Groups Risk Assessment Accuracy Groups A B C D E Market i 0. 2214 0.0 438 0.2 318 0.0983 0.9500 0.8623 Mean Accuracy A i =|P E P i | 0.7286 0.9063 0.7182 0.8517 0.0877 Median i 0.2500 0.0000 0.0000 0.0250 1.0000 0.8623 Median Accuracy A i =|P E P i | 0.7500 1.0000 1.0000 0.9750 0.1377 Table 21 shows the results of the t tests. The t critical values for all the groups are less than the observed t values the P values are less than 5% significance level, and the upper and lower bound of all confidence intervals are positive. Thus, we reject the null hypothesis and accept the alternative at 5% significance level. We conclude that the market assessment accuracy of the project actual riskiness level is greater than the true m ean assessment accuracy of any group of individuals with only partial knowledge about the project. Table 21 : Groups Risk Assessment Accuracy T Tests Test Value Information Market Accuracy = 0.0877 t observed t critical df P value (2 tailed) Mean Difference 95% Confidence Interval of the Difference Lower Upper Group A 8.207 1.943 6 .000 .63857 .4482 .8290 Group B 25.543 1.894 7 .000 .81625 .7407 .8918 Group C 5.732 1.812 10 .000 .62818 .3840 .8724 Group D 13.187 2.015 5 .000 .76167 .6132 .9101

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126 The one sample Wilcoxon test results have also found sufficient evidence to reject the null at 5% significance level ( Table 22 ) indicating that the market assessment accuracy of the project actual riskiness level is greater than the median assessment accuracy of any of the four group s (assuming that group E median as sessment of risk is equal to true population median). Table 22 : Groups Risk Assessment Accuracy Wilcoxon tests Test Value Information Market Accuracy = 0. 13 77 P value Group A 0.018 Group B 0.008 Group C 0 .003 Group D 0.026 Table 23 shows descriptive statistics of survey items. The mean values for the three manipulated variables (IA High, SI Low and AN Low) in the first part of the survey indicate that manipulations were effective. Table 23 : Scale Properties Construct Item N Min Max Mean S.D. Mean S.D. Traditional Market Perceived information asymmetry (IA) IA1 72 1 7 4.29 2.21 1.81 1.10 IA2 72 1 7 4.43 2.13 2.17 1.20 Perceived self interest (SI) SI1 72 1 7 2.88 2.03 5.67 1.44 SI2 72 1 7 2.38 1.60 5.28 1.58 SI3 72 1 7 3.28 2.16 5.35 1.60 Perceived anonymity(AN) AN1 72 1 7 1.85 1.12 5.43 1.69 AN2 72 1 7 2.07 1.49 5.82 1.49 Willingness to report bad news(WL) WL1 72 1 7 3.44 2.03 5.58 1.44 WL2 72 1 7 3.18 1.86 5.44 1.50 WL3 72 1 7 3.44 1.91 5.06 1.56

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127 Also, the mean values for all the variables move in the expected direction from the first part of the survey where employees used traditional status reporting mechanisms to the second part of the survey where employees used the information market mechanism to report project status. Mean perceived information asymmetry is lower in the information market condition than in the traditional reporting condition. Perceived self interest, perceived anonymity and willingness to report bad news are higher in the mark et condition than in the traditional condition. To test, H3, H4, H5 and H6, a series of paired t tests were conducted. Our sample size (n=72) is large enough to assume that mean differences are normally distributed because f or large samples (n > 30), the central limit theorem ensures the t test robust ness against violations of the normality assumption Table 24 shows the results of the paired test s Support of the hypotheses was determined by examining the sign of the mean difference, t values and the p values at 5% significance level. Statistical Hypotheses H3 H 0 : IA MIA <= 0 Ha: IA MIA > 0 H4 H 0 : MSI SI <= 0 Ha: MSI SI > 0 H5 H 0 : MAN AN <= 0 Ha: MAN AN > 0 H6 H 0 : MWL WL <= 0 Ha: MWL WL > 0

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128 For the first pair, the mean difference as well as the upper and lower bound of the confidence interval are positive. The t value is positive as well and greater than the critical value at 5% significance level indicating that the mean perceived informatio n asymmetry in the information market condition (MIA) is lower than the mean perceived information asymmetry in the traditional reporting condition (IA). Thus, H3 was supported. For pairs 2, 3, and 4, the mean difference is positive, the upper and lower bo und of the confidence interval are positive, and the t values are positive and greater than the critical value at 5% significance level indicating that the mean perceived self interest (MSI), mean perceived anonymity (MAN) and mean willingness to report ba d news (MWL) in the market condition are greater than their corresponding means in the traditional condition. Thus, H4, H5 and H6 were supported. Table 24 : Paired Samples Test Paired Differences t o bs t crt df P value (2 ta iled) Mean S.D 95% Confidence Interval of the Difference Lower Upper Pair 1 IA MIA 2.458 2.101 1.96 5 2.952 9.928 2.66 71 .000 Pair 2 MSI SI 2.822 2.077 2.334 3.310 11.528 2.66 71 .000 Pair 3 MAN AN 3.625 2.040 3.14 6 4.104 15.076 2.66 71 .000 Pair 4 MWL WL 2.00 5 2.137 1.502 2.50 7 7.959 2.66 71 .000 Discussion and Implications The variance in risk assessment accuracy, according to the proposed theoretical framework, depends on the completeness, currency and accuracy of reported status

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129 information where accuracy of status information depends in turn on misperceptions of project status and their willingness to report bad news. Figure 20 shows a summary of the framework propositions. Figure 20 : Summary of Theoretical Framework Propositions The results of the experiment provide empirical evidence on information markets efficacy in improving risk assessment accuracy by aggregating information from all participants in the m arket to provide more complete and accurate assessment of risks than any individual group of participants. Table 25 provides a summary of the hypotheses, results and implications. The information market assessment approximated the mean assessment of individuals who have access to all available information about the project. Those individuals rarely exist in organizations. Otherwise, an information market, or any o ther information aggregation and reporting mechanism, will not be needed. + + Currency of Status Information Individual Willingness to Report Bad News Accuracy of Risk Assessment Accuracy of Status Information Individual Errors of Perception of Project Status Completeness of Status Information P 1 + P 2 + P 3 + P 4 + P 5 Perceived Anonymity Perceived Self Interest Perceived Information Asymmetry P 6 + P 7 + P 8

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130 Table 25 : Summary of Results As is the case with most software development projects, status information are distributed among all individuals involved in the project and does not exist in Hypothesis Result Implications H1: reported assessment of project risks will approximate the reported assessment of a single person in possession of all the information Supported Demonstrate s information markets efficacy in aggregating information about project status from all market assessment of project risk H2: reported assessment of project risks will be more accurate than any in dividual reported assessment of project risk Supported Demonstrate s information markets misperceptions of project risk due to partial knowledge about project status and as a result improve risk assessment accuracy H3: An information market in which trading is anonymous will anonymity Supported Demonstrate the effects of a major design aspect of information markets; anonymity of trades, on employees perce ptions of the anonymity of the market as a reporting mechanism which in turn is proposed to increase their willingness to report bad news H4: An information market that provides incentives for faithful revelation of information will perceived self interest in reporting true status information Supported Demonstrate the effects of a major design aspect of information markets; incentive structure, on employees perceptions of self interest in truthful reporting of status information which is proposed to increase their willingness to report bad news H5: An information market will of information asymmetry between them and management/client Supported Demonstrate an additional benefit for information markets; decrease employees perception of information asymmetry, or their ability to hide information from management or clients, which is proposed to increase their willingness to report bad news H6: An information market in which trading is anonymous and provides incentives for truthful revelation of information will incre to report bad news Supported Demonstrate information markets efficacy in increasing individuals willingness to report negative status information and as a result improve risk assessment accuracy

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131 concentrated form. Management as well as the clients relies on traditional project management tec hniques such as status reports and periodic meetings to monitor the status of the project and to check on its progress. However, traditional monitoring and reporting techniques have proven ineffective time and time again due to employees misperc eptions of true project status and their reluctance to report negative information. The results of the experiment prove that information markets can adjust for the project. Market assessment of project risk proved to be more accurate than any individual group of people with access to incomplete information about the project. Additionally, the results provide evidence on information markets efficacy in increasing individual willingness to report negative status information via the market, and consequently improving the accuracy of the market generated assessment of project risks. Information markets ability to increase individual willingness to report bad news can be attributed to major design features of information markets such as anonymity of trades and incentive structures. Ma rkets offer anonymity and provide incentives for honest reporting. The results of the experiment showed a significant increase in interest in reporting true status information and in their perceived anonymity of the market repor ting mechanism. information asymmetry, or in other words, their perceived ability to hide information from management/clients. Information markets efficiency in responding to up dates and

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1 32 their proven ability to collect all available information about an event are believed to be information asymmetry. These results have important theoretic al and practical implications. At the conceptual level, the decreased information asymmetry suggest that regardless of information markets predictive accuracy, their mere existence in the organization might have a psychological impact that levels the play ing field between management or clients willingness to report bad news via other more traditional reporting mechanisms, and consequently improve risk assessment accuracy. Perh aps information markets indirect positive effects on transparency of communications might encourage some organizations to adopt them more than the minimizing software project reporting of negative status information are not encouraged. By providing early warning challenged projects. Li mitations Although laboratory experiments provide high degree s of internal validity and control, they provide lower degrees of external validity compared to field studies. To

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133 improve generalizability of the results, the experimental information aggregation task used in this study was based on a realistic business scenario. However, the scenario and the progress updates that were distributed to participants throughout the experiment were manipulated to achieve high degree of control over the information stru cture that will allow us to test the market efficacy in aggregating information, and to investigate its effect on the market assessment of risk. In organizations the actual distribution of information among employees might not be as clear, and there might be other context specific or extraneous variables, such as internal communication sharing channels between market participants that affect the market generated assessment that have not been investigated or accounted for in this study. Additionally, t he survey measured behavioral intentions rather than actual status information under certain conditions. The focus on few variables allowed us to investigate the impact of c consequently their behavioral decision to report negative information. The goal was to shed light on some important factors that can improve the accuracy of risk assessment by increasing employ controlled by organizations, such as anonymity and incentives. However, there might be other factors that can be controlled by organizations that we did not investigate here.

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134 Control of tre atment conditions provided high internal validity that allowed us to information asymmetry, anonymity and self interest caused by the information market treatment. Ano anonymity of the reporting mechanism. However, in organizations, markets might not be perceived as anonymous reporting mechanisms even when trading is. Depending on the forecasting goal and the size of the organization, traders in the market might not feel that their identities are protected because of the specialized knowledge they have about the project. So if small number of employees has access to status information about a certain o bjective, their trades in the market might be identified even when their real names are not attached to their trades. Thus, caution must be taken when generalizing this result to some organizations because perception of anonymity might be moderated by the size of the organization and employees job responsibilities. Having said that, the market can still improve their willingness to report negative information because of the incentives it offers for truthful reporting, and the market effects on their percep tions of information asymmetry. Contributions and Future Directions This research makes several contributions to the software project risk management literature. First, it develops a theoretical framework for the determinants of risk assessment accuracy. This framework broadens our perspective by focusing on

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135 important but under investigated attributes of information that directly impact the accuracy of risk assessment, such as informa tion currency and completeness. Second, it proposes an innovative techno logy ba sed information market solution to risk assessment problems to improve the accuracy, currency and completeness of reported project status information and consequently the accuracy of risk assessment. Third, it evaluates the efficacy of the proposed solution by conducting two controlled experiments. The risk assessment experiment provides a closer look at information aggregation and dissemination in information markets by using a realistic information structure and business scenario. The results of the experiments highlight an additional benefit for information markets besides their anonymity and incentives, which is the ability to influence organizations if utiliz ed properly. The results also provide evidence to the market effectiveness in improving software risk assessment accuracy, by improving the currency, accuracy and completeness of reported status information, which will consequently reduce software projects chances of failure and save organizations billions of dollars. Fourth, this research develops and validates measures for several important constructs such as perceived self interest in reporting bad news and perceived anonymity of reporting mechanism. It also re validates modified versions of existing measures such as willingness to report bad news and perceived information asymmetry.

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136 Finally, this research highligh ts the importance and impacts of three variables willingness to report bad news. These variables are information asymmetry, self interest and anonymity. The difference between our proposed conceptual model of willingness to report bad news ( Figure 17 ) and existing models in the literature is that it focuses our attention on factors that not only impact willingness but also can be adjusted and controlled by organizations. The proposed information market solution is pro ven to decrease information asymmetry and to increase their perception of the anonymity of the reporting mechanism and their perceived self interest in reporting negative status information Future research should investigate the impact of these three factors individually factors that can be adjusted by organizations or influenced by the use of technology. Fu ture research should investigate the impact of different information structures on market generated assessment of risk, and then test information market effectiveness in improving risk assessment accuracy in the field.

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137 Chapter Five Summary and Futu re Directions I nformation markets are a form of futures markets whose primary purpose is to aggregate disparate information which is expensive to collect using other commonly used methods. Participants in the market trade contracts that payoff depending on the outcomes of future event Contract prices can be interpreted as a forecast of the event probabilit y and can be used by organizations to support a wide variety of decisions. Despite the corporate world enthusiasm for information markets, the relation ship between markets and organizations has not been fully investigated yet. There are many open questions and unknowns when it comes to the design and use of markets in a business environment. Markets are fundamentally technology enabled information system s designed to provide efficient and effective solutions to identified business problems, such as forecasting, information aggregation and decision making under uncertainty. Technology is limited to the hardware and the software components of the market, and the information system encompasses the design, development, implementation, and use processes of the market, as well as the dynamic interaction between the market, people, and its environment to accomplish a certain task This

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138 dissertation employs two theoretical perspectives to investigate the relationship between information markets as IT artifacts and their context of use Systems thinking framework (Checkland, 1981) is employed to develop a systems theory of information markets to facilitate investigation of the relationships and interactions between markets as systems and their context of use. An information market is viewed as a subsystem of the organization system in which it is used. The organization in turn operates within an industry, all of which operates in the largest system of all: the world An information market encapsulates the aggregation system and its emergent al ong with the market incentives and contracts structures, and produces an emergent property that makes the market larger than the sum of its parts; collective intelligence in form of equilibrium price. Each system engages in a process of cybernetic informat ion exchange with its environment and has its own ways of responding to and communicating with the system in which it operates, as well as with other systems. A systems theory of information markets allow us to choose design and use processes that result i n better long term benefits to organizations in light of existing interactions and interrelationships between the market and its subsystems, such as the aggregation mechanism and the incentives structure, and the bigger system(s) in which it operates, such as the organization and its various department s and the industry.

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139 The second theoretical perspective is structuration theory (Giddens, 1979, 1984) This research proposes a structuration model for design and use of IT artifacts in organizations and appl ies it to the study of information markets. The context in which the market operates shapes the market objectives and all aspects of market design. There is a recursive relationship between market objectives, design, use and context of use, each shaping th e other iteratively. Just like any other information and communication technology, market s uccess to effectively use it, and on the market to satisfy es on the market design. Thus, we propose that the design of information markets, market interfaces, and visualizations be driven by three factors : ( 1) Market users Who; ( 2) Use motivation Why; and ( 3) Market information What T his dissertation develo ps a multidimensional framework of market users to guide The framework classifies users according to three dimensions: 1) knowledge level in the issues being forecasted, as informed or uninformed users; 2) participation level in market trading, as active or passive users; and 3) externality level to the department/organization at which the market operates, as internal or external users. Each group of market users has its own motivationa l needs and goals that can be satisfied using different information and market designs. Thus, information markets, market interfaces, and information visualizations can be designed specifically to target

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140 and attract any group of users depending on careful analysis of their motivations and needs. Thus, uninformed traders who are needed for markets to function properly can be attracted using markets designs that are intuitive, enjoyable induce positive emotions that o use the system, and most importantly, they should be perceived as (Giddens, 1979, 1984), adaptive structuration theory (AST) (DeSanctis and Poole, 1994), and the structuratio n model of technology (Orlikowski, 1992), by moving beyond the tra ditional structuration process and t he recursive relationship between technology and action that defines the relationship between technology and organizations, to consider technology as a ca talyst for organization change and development. The structuration cycle is viewed as a continuous change process that objectifies changeability as an organizational permanent structure that leads to the ultimate goal of the structuration process of IT arti facts: organization development (OD). A well designed information market can generate several benefits to organizations which contribute to their growth and development Software development organizations are in desperate need of better risk management tools due to their role in reducing software project chances of failure. This dissertation develops a theoretical framework for the determinants of software project risk assessment accuracy and proposes an information market design solution to help organizations better assess

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141 software project risks. It evaluates the information market efficacy in increasing risk assessment accuracy using two controlled experiments. The first experiment compares the market generated assessment of ri sk for a given software project to the mean assessment of a group of individuals with access to all available information about the project. The results showed that the market assessment of risks approximated the mean assessment of the group demonstrating the market efficacy in aggregating available information about the project from all market participants to leads to higher accuracy of risk assessment. It also compares t he market generated assessment of risk to the mean assessment of four groups of individuals each of whom has access to partial information about the project status. The results showed that the market assessment of risk is more accurate than the assessment generated by any of the groups demonstrating the market efficacy in information about its status. The second experiment focuses on three factors derived from agency th eory that a result, the accuracy of reported status and risk assessment. These fac tors are information asymmetry between employees and management/clients, anonymity of the reporting mechanism, and self interest in truthful reporting.

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142 The results of the experiment demonstrated the effectiveness of major design features of information ma rkets, such as the incentive structure and anonymity of trades, management/clients, (2) market anonymity as a reporting mechanism, and (3) self interest in truthful repo rting. The results also demonstrated the market efficacy in mation, and as a result increasing the accuracy of reported status and risk assessment. Future research should investigate the i mpact of these three fact ors idependently willingness to report bad news. It should also seek to identify other factors that can be adjusted by organizations or influenced by the use of technology. Future research should investigate the impact of different contracts, incentive structures and market mechanism s such as pari mutuel, continuous double auction, and market scoring rules assessment accuracy. It should also investigate the impact of different information structur es on market generated assessment s of risk, and then test information market effectiveness in improving risk assessment accuracy in the field. This dissertation suggests other fruitful areas of research. There is a great need for studies that empirically compare information markets to other methods of information aggregation, such as the Delphi method, not only in terms of forecasting accuracy but also on multiple other dimensions, such as the nature of the forecasting problems appropriate for each method, sources of relevant information (e.g. external, internal, or a

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143 mix of both), the availability of public information to attract participants, the availability of experts in certain areas, and the costs involved in recruiting experts, acquiring the market, training, trading time and incentives Further, there is a need for studies that investigate the structuration and appropriation processes of information markets in organization where markets are used as an intervention to induce organizational change and development Additionally, there is a need for research that seek s to characterize the decision making and cognitive processes involved in analyzing and using market information from both the trader and the decision maker perspectives Researc h is also needed on the design of effect ive market interfaces that meet

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159 A ppendices

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160 Appendix A: Information Markets Experimental Scenario Innovations & More Corporation (IMC) Information Markets for Software Project Risk Management You are a member of the design and development team in a large consulting firm; Innovations & More Corporation (IMC). Your firm is developing a new reservation system for an association of hotels and car rental corporation s (the client). Your firm and the client signed an agreement describing the four main objectives for the development project in terms of functionality, performance, budget and schedule. It also describes conditions under which these objectives are consider ed unmet. Project Objective Objective is considered UNMET if Functionality Integrate airline, rental car and hotel information in a central database. System fails integration test Performance Transaction response time is 1 second Transaction response time exceeds 2 seconds Budget $55 million Cost exceeds budget by 10% ($5.5 million) Schedule Design phase: 12 months (1 year) Development phase: 48 months (4 years) Schedule exceeds deadline by 15% (9 months)

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161 Appendix A: (Continued) Your firm and the client agreed to set up 5 information markets to track the development progress of the reservation system. One market is created to monitor the status of each project objective (total of 4 markets), and the fifth market to monitor the project overall status (riskiness level). The project riskiness level depends on whether project objectives are met or not: Low risk: All four objectives substantially met to date Medium risk: Two or three objectives substantially met to date High risk: One or ze ro objectives substantially met to date Market Forecasting Goal Price (%) 1 Will the project meet its functionality objective? i.e. System pass integration test Yes 50% No 50% Sum 100% 2 Will the project meet its performance objective? i.e. Transaction response time is less than 2 seconds Yes 50% No 50% Sum 100% 3 Will the project meet its budget objective? i.e. Budget increase is less than 10% Yes 50% No 50% Sum 100% 4 Will the project meet its schedule objective? i.e. Schedule increase is less than 15% Yes 50% No 50% Sum 100% Market Forecasting Goal 5 Which state best describes the project riskiness level? Price (%) Low risk: All four objectives substantially met to date 33.3% Medium risk: Two or three objectives substantially met to date 33.3% High risk: One or zero objectives substantially met to date 33.3% Sum 100%

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162 Appendix A: (Continued) You will be provided with development progress updates to help you verify whether project objectives are currently met or not. Progress updates provide information to help you better assess the riskiness level of the project. You will also be provided with the predictions of the four information markets that monitor the status of the project objectives. Based on progress updates and the market predictions provided to you, you will participate in an information market designed to predict the riskiness level of the project.

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163 Appendix B: Information Structure s GROUP A Update 0 The project is going great. Currently there is no reason to believe that the project will not meet any of its objectives. Update1 4 months after signing the agreement, base design is completed and presented to the client. Base design describes expected functionality in general terms, and does not provide sufficient details for developers to understand what the user is expecting. Up date2 1 year after signing the agreement, the design phase is completed. However, the quality of the specification is questionable, and might cause serious delays down the road. Update3 IMC circulated a preliminary development plan. The client request ed some revisions. Update4 Development plan was revised and sent to the client. Revisions to development plan were unexpected and delayed the project by at least 10 months (resulting in more than 15% schedule overrun). Update5 IMC admits some technica l difficulties, and that the system failed integration tests.

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164 Appendix B: (Continued) GROUP B Update 0 The project is going great. Currently there is no reason to believe that the project will not meet any of its objectives. Update1 4 months after signing the agreement, base design is completed and presented to the client. Update2 1 year after signing the agreement, the design phase is completed. However, the quality of the specification is questionable, and might cause serious de lays down the road. IMC circulated a preliminary development plan. The client requested some revisions. Update3 Development plan was revised and sent to the client. Update4 Revisions to development plan were unexpected and delayed the project by at le ast 10 months (resulting in more than 15% schedule overrun). Update5 IMC guaranteed that the project will deliver expected functionality and performance. However, the firm hired some experts to help with technical problems. This increased the budget by a t least 15%.

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165 Appendix B: (Continued) GROUP C Update 0 The project is going great. Currently there is no reason to believe that the project will not meet any of its objectives. Update1 4 months after signing the agreement, base design is completed an d presented to the client. Update2 1 year after signing the agreement, the design phase is completed. However, the quality of the specifications is questionable. IMC circulated a preliminary development plan. The client requested some revisions. Update3 The requested modifications to the development plan increased transaction response time to more than 2.0 seconds. Update4 Development plan modifications did not affect the project budget or schedule. Update5 The technical team found that the airli ne, rental car and hotel databases cannot be integrated. A major functionality cannot possibly be delivered.

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166 Appendix B : (Continued) GROUP D (PUBLIC INFORMATION) Update 0 The project is going great. Currently there is no reason to believe that the project will not meet any of its objectives. Update1 4 months after signing the agreement, base design is completed and presented to the client. Your firm (IMC) guaranteed t he client that the final specifications will on time. Update2 1 year after signing the agreement, the design phase is completed on time. IMC circulated a prel iminary development plan. Client requested some revisions. Update3 6 months later, development plan is revised and sent to the client. Update4 IMC guaranteed that the project will still be delivered on time and with promised functionality. Update 5 Two months later, IMC admits some technical difficulties, but is confident that it will deliver the project within budget and with expected performance.

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167 Appendix B: (Continued) INFORMATION MARKET PREDICTIONS Updates Market Outcomes 0 1 2 3 4 5 1 Yes 65% 55% 45% 40% 40% 5% No 35% 45% 55% 60% 60% 95% 2 Yes 65% 70% 70% 60% 25% 1% No 35% 30% 30% 40% 75% 99% 3 Yes 65% 65% 70% 65% 40% 5% No 35% 35% 30% 35% 60% 95% 4 Yes 65% 65% 50% 45% 25% 1% No 35% 35% 50% 55% 75% 99%

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168 Appendix C: Risk Assessment Survey Innovations & More Corporation Business Case and Risk Assessment Survey INSTRUCTIONS: The following business case is part of a study that examines software project risk assessment. The case describes four main objectives for a software development project in terms of functionality, performance, budget and schedule. It also describes conditi ons under which these objectives are considered unmet. You will be provided with development progress updates to help you verify whether project objectives are currently met or not. Progress updates provide information to help you better assess the riskine ss level of the project. Please read the following case and development progress updates and complete the survey that follows. Innovations & More Corporation (IMC) You are a member of the design and development team in a large consulting firm; Innovatio ns & More Corporation (IMC). Your firm is developing a new reservation system for an association of hotels and car rental corporations (the client). Your firm and the client signed an agreement describing the four main objectives for the development projec t.

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169 Appendix C: (Continued) Risk Assessment Survey Based on all the information and updates provided to you Yes/No Does the project currently meet its functionality objective? Does the project currently meet its performance objective? Does the project currently meet its budget objective? Does the project currently meet its schedule objective? The client asked your firm to conduct a survey to assess the overall riskiness level of the project using discrete reporting scale (high risk, medium risk and low risk). Riskiness level is defined in terms of the number of unmet objectives. W hen all projec t objectives are met to date the project is considered low risk. When only two or three objectives are met to date, the project is considered medium risk. When one or no objectives are met, the project is considered high risk. Project Objective Objective is considered UNMET if Functionality Integrate airline, rental car and hotel information in a central database. System fails integration test Performance Transaction response time is 1 second Transaction response time exceeds 2 seconds Budget $55 million Cost exceeds budget by 10% ($5.5 million) Schedule Design phase: 12 months (1 year) Development phase: 48 months (4 years) Schedule exceeds deadline by 15% (9 months)

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170 Appendix C: (Continued) Depe nding on the information you have about project status, assign a probability score to the state that best describes the project riskiness level. In other words, how likely the project is to achieve its objectives? For example, if your information indicates that all four project objectives are met to date, you will assign a 100% to low risk, 0% to medium risk, and 0% to high risk Project Riskiness Level Probability% Low risk : All four objectives are met to date Medium risk: Two or three objectives are met to date High risk : One or no objectives are met to date Sum 100%

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171 Appendix D: Survey Experimental Scenario INSTRUCTIONS: This business case is part of a study that examines business decision making. Please read the following case and answer the questions that follow based on the information presented in the case. Digit Dash & Beyond Corporation You are a member of the design and development team in a major consulting firm; Digit Dash & Beyond Corporation (DDB). For the last year you have be en involved in the development of a transaction processing system for a large department store; Chars.com. DDB and Chars signed an agreement stating project objectives in terms of The agreement also stated that the client can withdraw when two or more objectives are unmet during the first year of system development. The system has been under development for almost a year. The project is over budget, over schedule, system has perfor mance issues and initial integration tests showed that the system will fail to deliver expected functionality. In other words, the project four main objectives are currently unmet. Unless employees report the status of project objectives the client will not become aware of these issues until the project due date. Y our firm has an implicit policy of not reporting negative status information to clients to keep them from withdrawing, and instead tries to arrange new agreement with the client before the project due date.

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172 Appendix D: (Continued) Employees are required to submit a periodic status report to management. Management shares these reports with the client signature Employees are expected not to mention problems in their status reports beca use clients will see them. Employees who mention problems in their reports get in trouble In the past an employee reported performance issues in his formal report and got reprimanded by the project manager. Later he was denied a promotion, and lost his jo b. Rumor has it that his negative status report is behind it. NOTE: The above scenario represents the treatment used to manipulate high information asymmetry, high anonymity and low self interest in reporting negative information. The scenario that follows was used in the second part of the survey to introduce the information market treatment. Digit Dash & Beyond Corporation (continued) The client decided to use a risk assessment tool to track the development progress of its transaction processing system. This tool is known as information market. An information market main goal is to collect information about the status of project objectives from all over the company to reveal whether or not they are being met. The more unmet objectives, the higher the r iskiness level of the project. Information markets are known for their ability to quickly incorporate new updates and information to provide up to date assessment of the status of project objectives.

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173 Appendix D: (Continued) This property is expected to bri ng system problems, performance issues or negative status information to the client attention very quickly. Trading in the information market is anonymous and all transactions, bids and asks are maintained by an independent third party organization. Emplo yees can report negative status information or system problems in an information market without being identified. The market offers incentives for true revelation of status information. So if employees are reporting honestly they will benefit financially. All profits will be directly deposited by All individuals involved in the design and development of the system, or have any information about its progress, are participa ting in market trading.

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174 Appendix E: Constructs and Measures Perceived information asymmetry (7 point likert scale, 1 = strongly disagree, 4 = neutral or unsure, 7= strongly agree) IA1: Negative status information will become apparent to the client ver y quickly (Reversed) IA2: Whether or not I report negative status information, the client will become aware of it very soon anyway (Reversed) Perceived self interest in reporting bad news (7 point likert scale, 1 = strongly disagree, 4 = neutral or unsure, 7= strongly agree) SI1: It is in my interest NOT to report negative status information in my report (Reversed) SI2: I will benefit from reporting negative status information in my report SI3: I have nothing to gain from reporting negative status information in my report (Reversed) Perceived anonymity (7 point likert scale, 1 = strongly disagree, 4 = neutral or unsure, 7= strongly agree) AN1: If I mention negative status information in my status reports, management will know my name (Reversed) AN2: Project status reports at my firm are anonymous (i.e. reports have no names attached to them)

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175 Appendix E: (Continued) Willingness to report bad news (7 point likert scale, 1 = very unlikely, 4 = neutral or unsure, 7= very likely) WL1: How likely are you to report negative status information in your status report? WL2: How likely are you to report negative status information to client? WL3: How likely it is that you would avoid reporting negative s tatus information to client? (Reversed) NOTE: The questions asked in the second part of the survey under the treatment market.

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About the Author Areej M. Yassin received her B.S. degree in Computer Science with a minor in Business Administration from Yarmouk University in Jordan where she was on the Dr. Yassin earned both her M.S. in Management Information Systems and MBA degrees from the University of South Florida, where she maintained a 4.0 GPA. She is member of Phi Kappa Phi and Beta Gamma Sigma honor societies. Before pursuing her academic career, Dr Yassin held several positions in industry. She is an Oracle Certified Professional (OCP), Cisco Certified Network Associate (CCNA), and Microsoft Certified Office User Specialist (MOUS Master).