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Comparison of Multicriteria and Prediction Market Approaches for Technology Foresight


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We present and compare two original approaches for technology assessment and foresight based on opposite paradigm: a management science approach (Multi-Criteria Decision-Making) versus a participatory approach (Prediction Market). These approaches are intended to support the management of a technology portfolio and the assessment of new technology by an IT organization. In order to explore the relevance of the research, we conducted several experiments in real environments. The results demonstrated that the rigor of management science and the participation of the Web 2.0 approach are complementary strengths for technology foresight. Furthermore, a framework has been established to compare the two approaches.

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Comparison of Multicriteria and Prediction Market Approaches for Technology Foresight

  1. 1. 13th AIM Conference 2008 - Paris Comparison of Multicriteria and Prediction Market Approaches for Technology Foresight Cédric Gaspoz, Faculty of Business and Economics
  2. 2. Introduction One of the critical issues in IT management is to “situate the challenges facing the IT managers regarding emerging technology…”. McKeen and Smith (2003) This requires companies to adopt a systematic process to stay up-to-date and assess new technology for a potential integration into modern organizations. 17th June 2008 2 | 13th AIM Conference 2008
  3. 3. How to choose the best approach? We propose to establish a comparison framework based on characteristics derived from past research previously presented (MCDM and PM). – Presentation of the Approaches – Design of the Artifacts – Settings of the Experiments – Analysis of the Results This framework aims at helping us to compare our two approaches and identify their key success factors. – Comparison of the Methods – Conclusions – Future Work 17th June 2008 3 | 13th AIM Conference 2008
  4. 4. Presentation of the Approaches MCDM PM A Management Science An Emerging Approach Approach • uses either quantitative or • aggregates automatically qualitative criteria the information simultaneously and disseminated among all concurrently actors in a corporate crowd • determines the solution • determines the consensual approaching the “optimal” equilibrium price of the in regards of several underlying solution criteria or among existing solutions 17th June 2008 4 | 13th AIM Conference 2008
  5. 5. Design of the Artifacts MCDM PM A Group Decision e-Trading Market Support System PylaDESS MarMix 17th June 2008 5 | 13th AIM Conference 2008
  6. 6. Settings of the Experiments MCDM PM Visiting Swiss Experts Gathering the Crowd Selected Experts Who Master Students (crowd) Individual interviews with One group meeting to each company followed by start the market and some a roundtable for all the Where trading activities. Later, experts to meet and the participants continue to discuss the results. trade alone anytime. 6 month When 1 month Several month for setup, Few days for setup and How interviews and analysis analysis 17th June 2008 6 | 13th AIM Conference 2008
  7. 7. Analysis of the Results MCDM PM Ranking and Outranking Price of Contracts 1. SmartCard 1. NFC 2. NFC 2. SmartCard 3. Contactless Card 3. Contactless Card 4. Magnetic Card 4. Phone proximity 5. Phone proximity 5. Phone remote 6. Phone remote 6. Magnetic Card 17th June 2008 7 | 13th AIM Conference 2008
  8. 8. Comparison of the Methods (1/5) A Framework of Comparison Organizational Organizational Factors Factors Technology Data IN Data OUT Forecasting Method Data Assessment Attributes Properties Assessment properties 17th June 2008 8 | 13th AIM Conference 2008
  9. 9. Comparison of the Methods (2/5) Organizational factors MCDM PM • organizations with formal • organizations with and less participatory participatory and informal decision-making processes decision-making style • relies mainly on relevant • community of players experts driven by the game and its financial profits • experts need a good • does not require in depth knowledge of the method knowledge of the method 17th June 2008 9 | 13th AIM Conference 2008
  10. 10. Comparison of the Methods (3/5) Assessment Properties MCDM PM • gives a posteriori results • longitudinal studies for to support the resolution assessments requiring of a decision problem frequent or permanent update • detailed snapshots taken • movies shot over a at certain times period of time 17th June 2008 10 | 13th AIM Conference 2008
  11. 11. Comparison of the Methods (4/5) Data Attributes MCDM PM • Endogenous Data • Exogenous Data Collection Collection • External Validation • Internal Validation Process Process • Extended Outcome • Aggregated Outcome 17th June 2008 11 | 13th AIM Conference 2008
  12. 12. Comparison of the Methods (5/5) Key Success Factors • Experts vs Crowd • Hired Facilitator vs Motivated Crowd • Valid Data vs Validated Data • Explicit Outcome vs Implicit Outcome 17th June 2008 12 | 13th AIM Conference 2008
  13. 13. Conclusions MCDM approach brought PM provide a synthetic an analytic explanation of aggregation of numerous the phenomenon by a individual beliefs, constan- controlled and criteria- tly adjusted and made based evaluation available for everyone The combined strengths of the MCDM approach and prediction markets could be exploited for technology assessment and foresight to improve IT investment decisions. 17th June 2008 13 | 13th AIM Conference 2008
  14. 14. Future Work • Expand the framework to a tool to choose the right Computer Aided Technology Foresight Tool based on the forecasting context • Use our framework with other forecasting methods 17th June 2008 14 | 13th AIM Conference 2008
  15. 15. The research presented in this slideshow is available as a research paper on the website of the author: Cédric Gaspoz University of Lausanne Faculty of Business and Economics Information Systems Institute CH-1015 Lausanne Cédric Gaspoz's research focuses on information aggregation, primarily to support decision making. He explores ways of aggregating disseminated information to structure it and increase it's significance. His research covers a broad range of topics like prediction markets, group decision support systems (GDSS), negotiation support systems (NSS), semantic search and Mashup. His actual focus is on using prediction markets to support portfolio management of research projects in mobile information and communication systems. 17th June 2008 15 | 13th AIM Conference 2008