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Andreas Graefe

Personal Details

First Name:Andreas
Middle Name:
Last Name:Graefe
Suffix:
RePEc Short-ID:pgr243
http://www.andreas-graefe.org

Affiliation

Institut für Kommunikationswissenschaft und Medienforschung, LMU München (Department of Communication Science and Media Research, LMU Munich)

http://www.en.ifkw.uni-muenchen.de/index.html
Munich, Germany

Research output

as
Jump to: Working papers Articles

Working papers

  1. Armstrong, J. Scott & Graefe, Andreas, 2009. "Predicting Elections from Biographical Information about Candidates," MPRA Paper 16461, University Library of Munich, Germany.
  2. Graefe, Andreas & Armstrong, J. Scott, 2008. "Forecasting Elections from Voters’ Perceptions of Candidates’ Positions on Issues and Policies," MPRA Paper 9829, University Library of Munich, Germany.
  3. Green, Kesten C. & Armstrong, J. Scott & Graefe, Andreas, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," MPRA Paper 4663, University Library of Munich, Germany.

Articles

  1. Andreas Graefe & J. Scott Armstrong, & Randall J. Jones & Alfred G. Cuz‡n, 2013. "Combined Forecasts of the 2012 Election: The PollyVote," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 28, pages 50-51, Winter.
  2. Andreas Graefe & Randy Jones & Scott Armstrong & Alfred Cuzán, 2012. "The PollyVote’s Year-Ahead Forecast of the 2012 U.S. Presidential Election," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 24, pages 13-14, Winter.
  3. Graefe, Andreas & Armstrong, J. Scott, 2011. "Conditions under which index models are useful: Reply to bio-index commentaries," Journal of Business Research, Elsevier, vol. 64(7), pages 693-695, July.
  4. Graefe, Andreas & Armstrong, J. Scott, 2011. "Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task," International Journal of Forecasting, Elsevier, vol. 27(1), pages 183-195.
  5. Andreas Graefe, 2011. "Prediction Markets and the “Trough of Disillusionment”," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 23, pages 43-46, Fall.
  6. Armstrong, J. Scott & Graefe, Andreas, 2011. "Predicting elections from biographical information about candidates: A test of the index method," Journal of Business Research, Elsevier, vol. 64(7), pages 699-706, July.
  7. Andreas Graefe, 2010. "Prediction Markets for Forecasting Drug Development," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 17, pages 8-12, Spring.
  8. Andreas Graefe, 2010. "Are Prediction Markets More Accurate than Simple Surveys?," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 19, pages 39-43, Fall.
  9. Andreas Graefe & J. Scott Armstrong & Alfred G. Cuzán & Randall J. Jones, Jr., 2009. "Combined Forecasts of the 2008 Election: The Pollyvote," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 12, pages 41-42, Winter.
  10. Andreas Graefe, 2008. "Prediction Markets – Defining Events and Motivating Participation," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 9, pages 30-32, Spring.
  11. Andreas Graefe & Christof Weinhardt, 2008. "Long-Term Forecasting with Prediction Markets - A Field Experiment on Applicability and Expert Confidence," Journal of Prediction Markets, University of Buckingham Press, vol. 2(2), pages 71-91, September.
  12. Kesten Green & J. Scott Armstrong & Andreas Graefe, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 17-20, Fall.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Armstrong, J. Scott & Graefe, Andreas, 2009. "Predicting Elections from Biographical Information about Candidates," MPRA Paper 16461, University Library of Munich, Germany.

    Mentioned in:

    1. How to select presidential candidates based on their biography
      by Economic Logician in Economic Logic on 2009-09-14 19:58:00

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Kesten Green & J. Scott Armstrong & Andreas Graefe, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 17-20, Fall.

    Mentioned in:

    1. Delphi method in Wikipedia (English)
    2. デルファイ法 in Wikipedia (Japanese)
    3. Metoda Delphi in Wikipedia (Romanian)

Working papers

  1. Armstrong, J. Scott & Graefe, Andreas, 2009. "Predicting Elections from Biographical Information about Candidates," MPRA Paper 16461, University Library of Munich, Germany.

    Cited by:

    1. Voss, Kevin E., 2011. "Voss wins the Presidency! A commentary essay on "Predicting elections from biographical information about candidates: A test of the index method"," Journal of Business Research, Elsevier, vol. 64(4), pages 345-347, April.
    2. Cote, Joseph A., 2011. "Predicting elections from biographical information about candidates: A commentary essay," Journal of Business Research, Elsevier, vol. 64(7), pages 696-698, July.
    3. Graefe, Andreas & Armstrong, J. Scott, 2011. "Conditions under which index models are useful: Reply to bio-index commentaries," Journal of Business Research, Elsevier, vol. 64(7), pages 693-695, July.

  2. Graefe, Andreas & Armstrong, J. Scott, 2008. "Forecasting Elections from Voters’ Perceptions of Candidates’ Positions on Issues and Policies," MPRA Paper 9829, University Library of Munich, Germany.

    Cited by:

    1. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    2. Graefe, Andreas, 2015. "Improving forecasts using equally weighted predictors," Journal of Business Research, Elsevier, vol. 68(8), pages 1792-1799.
    3. Armstrong, J. Scott & Graefe, Andreas, 2009. "Predicting Elections from Biographical Information about Candidates," MPRA Paper 16461, University Library of Munich, Germany.
    4. Graefe, Andreas & Armstrong, J. Scott, 2011. "Conditions under which index models are useful: Reply to bio-index commentaries," Journal of Business Research, Elsevier, vol. 64(7), pages 693-695, July.
    5. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.

  3. Green, Kesten C. & Armstrong, J. Scott & Graefe, Andreas, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," MPRA Paper 4663, University Library of Munich, Germany.

    Cited by:

    1. Graefe, Andreas & Armstrong, J. Scott, 2011. "Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task," International Journal of Forecasting, Elsevier, vol. 27(1), pages 183-195, January.
    2. Kerr, Norbert L. & Tindale, R. Scott, 2011. "Group-based forecasting?: A social psychological analysis," International Journal of Forecasting, Elsevier, vol. 27(1), pages 14-40, January.
    3. Keyvanfar, Ali & Shafaghat, Arezou & Abd Majid, Muhd Zaimi & Bin Lamit, Hasanuddin & Warid Hussin, Mohd & Binti Ali, Kherun Nita & Dhafer Saad, Alshahri, 2014. "User satisfaction adaptive behaviors for assessing energy efficient building indoor cooling and lighting environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 277-295.
    4. Robert J. MacCoun, 2010. "Comment on "Rethinking America's Illegal Drug Policy"," NBER Chapters, in: Controlling Crime: Strategies and Tradeoffs, pages 281-289, National Bureau of Economic Research, Inc.
    5. Milan Daus & Katharina Koberger & Kaan Koca & Felix Beckers & Jorge Encinas Fernández & Barbara Weisbrod & Daniel Dietrich & Sabine Ulrike Gerbersdorf & Rüdiger Glaser & Stefan Haun & Hilmar Hofmann &, 2021. "Interdisciplinary Reservoir Management—A Tool for Sustainable Water Resources Management," Sustainability, MDPI, vol. 13(8), pages 1-21, April.
    6. Angela Dalton & Alan Brothers & Stephen Walsh & Paul Whitney, 2010. "Expert Elicitation Method Selection Process and Method Comparison," Labsi Experimental Economics Laboratory University of Siena 030, University of Siena.
    7. Liu, Yaqin & Zhao, Guohao & Zhao, Yushan, 2016. "An analysis of Chinese provincial carbon dioxide emission efficiencies based on energy consumption structure," Energy Policy, Elsevier, vol. 96(C), pages 524-533.
    8. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    9. Joshua Becker & Abdullah Almaatouq & EmH{o}ke-'Agnes Horv'at, 2020. "Network Structures of Collective Intelligence: The Contingent Benefits of Group Discussion," Papers 2009.07202, arXiv.org, revised Mar 2021.
    10. Geoff Woolcott & Dan Chamberlain & Zachary Hawes & Michelle Drefs & Catherine D. Bruce & Brent Davis & Krista Francis & David Hallowell & Lynn McGarvey & Joan Moss & Joanne Mulligan & Yukari Okamoto &, 2020. "The central position of education in knowledge mobilization: insights from network analyses of spatial reasoning research across disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2323-2347, December.
    11. Ricardo Gomes & Alfeu Marques & Joaquim Sousa, 2013. "District Metered Areas Design Under Different Decision Makers’ Options: Cost Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(13), pages 4527-4543, October.
    12. Palma, David & Dios Ortuzar, Juan de & Casaubon, Gerard & Rizzi, Luis I. & Agosin, Eduardo, 2013. "Measuring consumer preferences using hybrid discrete choice models," Working Papers 164855, American Association of Wine Economists.
    13. Omid Bozorg-Haddad & Mohammad Delpasand & Sarvin ZamanZad-Ghavidel & Xuefeng Chu, 2024. "Developing a novel social–water capital index by gene expression programming," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(11), pages 28187-28217, November.
    14. Maria Jose Marques & Gudrun Schwilch & Nina Lauterburg & Stephen Crittenden & Mehreteab Tesfai & Jannes Stolte & Pandi Zdruli & Claudio Zucca & Thorunn Petursdottir & Niki Evelpidou & Anna Karkani & Y, 2016. "Multifaceted Impacts of Sustainable Land Management in Drylands: A Review," Sustainability, MDPI, vol. 8(2), pages 1-34, February.
    15. Kerr, Norbert L. & Tindale, R. Scott, 2011. "Group-based forecasting?: A social psychological analysis," International Journal of Forecasting, Elsevier, vol. 27(1), pages 14-40.
    16. Samir Mili & Maria Bouhaddane, 2021. "Forecasting Global Developments and Challenges in Olive Oil Supply and Demand: A Delphi Survey from Spain," Agriculture, MDPI, vol. 11(3), pages 1-25, February.
    17. Bloem da Silveira Junior, Luiz A. & Vasconcellos, Eduardo & Vasconcellos Guedes, Liliana & Guedes, Luis Fernando A. & Costa, Renato Machado, 2018. "Technology roadmapping: A methodological proposition to refine Delphi results," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 194-206.
    18. Vicente Coll-Serrano & Salvador Carrasco-Arroyo & Olga Blasco-Blasco & Luis Vila-Lladosa, 2012. "Design of a Basic System of Indicators for Monitoring and Evaluating Spanish Cooperation’s Culture and Development Strategy," Evaluation Review, , vol. 36(4), pages 272-302, August.
    19. Robert Reig & Ramona Schoder, 2010. "Forecasting Accuracy: Comparing Prediction Markets And Surveys – An Experimental Study," Journal of Prediction Markets, University of Buckingham Press, vol. 4(3), pages 1-19.
    20. Soyeon Caren Han & Yulu Liang & Hyunsuk Chung & Hyejin Kim & Byeong Ho Kang, 2016. "Chinese trending search terms popularity rank prediction," Information Technology and Management, Springer, vol. 17(2), pages 133-139, June.
    21. Shin, Dong-Hee, 2015. "Effect of the customer experience on satisfaction with smartphones: Assessing smart satisfaction index with partial least squares," Telecommunications Policy, Elsevier, vol. 39(8), pages 627-641.
    22. Lang, Mark & Bharadwaj, Neeraj & Di Benedetto, C. Anthony, 2016. "How crowdsourcing improves prediction of market-oriented outcomes," Journal of Business Research, Elsevier, vol. 69(10), pages 4168-4176.
    23. Sungchul Kim & Dongsik Jang & Sunghae Jun & Sangsung Park, 2015. "A Novel Forecasting Methodology for Sustainable Management of Defense Technology," Sustainability, MDPI, vol. 7(12), pages 1-17, December.

Articles

  1. Andreas Graefe & J. Scott Armstrong, & Randall J. Jones & Alfred G. Cuz‡n, 2013. "Combined Forecasts of the 2012 Election: The PollyVote," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 28, pages 50-51, Winter.

    Cited by:

    1. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.

  2. Graefe, Andreas & Armstrong, J. Scott, 2011. "Conditions under which index models are useful: Reply to bio-index commentaries," Journal of Business Research, Elsevier, vol. 64(7), pages 693-695, July.

    Cited by:

    1. Graefe, Andreas, 2015. "Improving forecasts using equally weighted predictors," Journal of Business Research, Elsevier, vol. 68(8), pages 1792-1799.
    2. Loock, Moritz & Hinnen, Gieri, 2015. "Heuristics in organizations: A review and a research agenda," Journal of Business Research, Elsevier, vol. 68(9), pages 2027-2036.
    3. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.

  3. Graefe, Andreas & Armstrong, J. Scott, 2011. "Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task," International Journal of Forecasting, Elsevier, vol. 27(1), pages 183-195.

    Cited by:

    1. Prommer, Lisa & Tiberius, Victor & Kraus, Sascha, 2020. "Exploring the future of startup leadership development," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
    2. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    3. Katherine A Smith & Segolame Setlhare & Allan DeCaen & Aaron Donoghue & Janell L Mensinger & Bingqing Zhang & Brennan Snow & Dikai Zambo & Kagiso Ndlovu & Ryan Littman-Quinn & Farhan Bhanji & Peter A , 2019. "Feasibility and preliminary validity evidence for remote video-based assessment of clinicians in a global health setting," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-13, August.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Litsiou, Konstantia & Polychronakis, Yiannis & Karami, Azhdar & Nikolopoulos, Konstantinos, 2022. "Relative performance of judgmental methods for forecasting the success of megaprojects," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1185-1196.
    6. Tommaso Ciarli & Alex Coad & Ismael Rafols, 2015. "Quantitative Analysis of Technology Futures: A review of Techniques, Uses and Characteristics," SPRU Working Paper Series 2015-23, SPRU - Science Policy Research Unit, University of Sussex Business School.
    7. Kopyto, Matthias & Lechler, Sabrina & von der Gracht, Heiko A. & Hartmann, Evi, 2020. "Potentials of blockchain technology in supply chain management: Long-term judgments of an international expert panel," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    8. Muhammad Ridhuan Tony Lim Abdullah & Saedah Siraj & Zulkipli Ghazali, 2021. "An ISM Approach for Managing Critical Stakeholder Issues Regarding Carbon Capture and Storage (CCS) Deployment in Developing Asian Countries," Sustainability, MDPI, vol. 13(12), pages 1-23, June.
    9. Rengarajan, Srinath & Moser, Roger & Narayanamurthy, Gopalakrishnan, 2021. "Strategy tools in dynamic environments – An expert-panel study," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    10. Bolger, Fergus & Rowe, Gene & Belton, Ian & Crawford, Megan M & Hamlin, Iain & Sissons, Aileen & Taylor Browne Lūka, Courtney & Vasilichi, Alexandrina & Wright, George, 2020. "The Simulated Group Response Paradigm: A new approach to the study of opinion change in Delphi and other structured-group techniques," OSF Preprints 4ufzg, Center for Open Science.
    11. Keller, Jonas & von der Gracht, Heiko A., 2014. "The influence of information and communication technology (ICT) on future foresight processes — Results from a Delphi survey," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 81-92.
    12. Wright, George & Rowe, Gene, 2011. "Group-based judgmental forecasting: An integration of extant knowledge and the development of priorities for a new research agenda," International Journal of Forecasting, Elsevier, vol. 27(1), pages 1-13, January.
    13. Kauko, Karlo & Palmroos, Peter, 2014. "The Delphi method in forecasting financial markets— An experimental study," International Journal of Forecasting, Elsevier, vol. 30(2), pages 313-327.
    14. Christoph Markmann & Alexander Spickermann & Heiko A. von der Gracht & Alexander Brem, 2021. "Improving the question formulation in Delphi‐like surveys: Analysis of the effects of abstract language and amount of information on response behavior," Futures & Foresight Science, John Wiley & Sons, vol. 3(1), March.
    15. Marcin Kozak & Olesia Iefremova, 2014. "Implementation Of The Delphi Technique In Finance," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 10(4), pages 36-45, May.
    16. Winkler, Jens & Kuklinski, Christian Paul Jian-Wei & Moser, Roger, 2015. "Decision making in emerging markets: The Delphi approach's contribution to coping with uncertainty and equivocality," Journal of Business Research, Elsevier, vol. 68(5), pages 1118-1126.
    17. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    18. Hanea, A.M. & McBride, M.F. & Burgman, M.A. & Wintle, B.C. & Fidler, F. & Flander, L. & Twardy, C.R. & Manning, B. & Mascaro, S., 2017. "I nvestigate D iscuss E stimate A ggregate for structured expert judgement," International Journal of Forecasting, Elsevier, vol. 33(1), pages 267-279.
    19. Julia A. Minson & Jennifer S. Mueller & Richard P. Larrick, 2018. "The Contingent Wisdom of Dyads: When Discussion Enhances vs. Undermines the Accuracy of Collaborative Judgments," Management Science, INFORMS, vol. 64(9), pages 4177-4192, September.
    20. Apreda, Riccardo & Bonaccorsi, Andrea & dell'Orletta, Felice & Fantoni, Gualtiero, 2019. "Expert forecast and realized outcomes in technology foresight," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 277-288.
    21. Zeng, Michael A. & Koller, Hans & Jahn, Reimo, 2019. "Open radar groups: The integration of online communities into open foresight processes," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 204-217.
    22. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
    23. Pennings, Clint L.P. & van Dalen, Jan & Rook, Laurens, 2019. "Coordinating judgmental forecasting: Coping with intentional biases," Omega, Elsevier, vol. 87(C), pages 46-56.
    24. Jaemyung Ahn & Olivier L. de Weck & Martin Steele, 2014. "Credibility Assessment of Models and Simulations Based on NASA’s Models and Simulation Standard Using the Delphi Method," Systems Engineering, John Wiley & Sons, vol. 17(2), pages 237-248, June.
    25. Jukrin Moon & Dongoo Lee & Taesik Lee & Jaemyung Ahn & Jindong Shin & Kyungho Yoon & Dongsik Choi, 2015. "Group Decision Procedure to Model the Dependency Structure of Complex Systems: Framework and Case Study for Critical Infrastructures," Systems Engineering, John Wiley & Sons, vol. 18(4), pages 323-338, July.
    26. Merfeld, Katrin & Wilhelms, Mark-Philipp & Henkel, Sven & Kreutzer, Karin, 2019. "Carsharing with shared autonomous vehicles: Uncovering drivers, barriers and future developments – A four-stage Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 66-81.
    27. Nikolopoulos, Konstantinos & Litsa, Akrivi & Petropoulos, Fotios & Bougioukos, Vasileios & Khammash, Marwan, 2015. "Relative performance of methods for forecasting special events," Journal of Business Research, Elsevier, vol. 68(8), pages 1785-1791.
    28. Bonaccorsi, Andrea & Apreda, Riccardo & Fantoni, Gualtiero, 2020. "Expert biases in technology foresight. Why they are a problem and how to mitigate them," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    29. Christoph Diermann & Arnd Huchzermeier, 2017. "Case Article—Canyon Bicycles: Judgmental Demand Forecasting in Direct Sales," INFORMS Transactions on Education, INFORMS, vol. 17(2), pages 58-62, January.
    30. Bo Cowgill & Eric Zitzewitz, 2015. "Corporate Prediction Markets: Evidence from Google, Ford, and Firm X," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1309-1341.
    31. Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael, 2014. "Collaborative forecasting in the food supply chain: A conceptual framework," International Journal of Production Economics, Elsevier, vol. 158(C), pages 120-135.
    32. Lian Jian & Rahul Sami, 2012. "Aggregation and Manipulation in Prediction Markets: Effects of Trading Mechanism and Information Distribution," Management Science, INFORMS, vol. 58(1), pages 123-140, January.
    33. Tiberius, Victor & Gojowy, Robin & Dabić, Marina, 2022. "Forecasting the future of robo advisory: A three-stage Delphi study on economic, technological, and societal implications," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    34. Spickermann, Alexander & Zimmermann, Martin & von der Gracht, Heiko A., 2014. "Surface- and deep-level diversity in panel selection — Exploring diversity effects on response behaviour in foresight," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 105-120.
    35. Laura Studen & Victor Tiberius, 2020. "Social Media, Quo Vadis? Prospective Development and Implications," Future Internet, MDPI, vol. 12(9), pages 1-22, August.
    36. Cary Deck & David Porter, 2013. "Prediction Markets in the Laboratory," Working Papers 13-05, Chapman University, Economic Science Institute.
    37. Griffiths, Frances & Cave, Jonathan & Boardman, Felicity & Ren, Justin & Pawlikowska, Teresa & Ball, Robin & Clarke, Aileen & Cohen, Alan, 2012. "Social networks – The future for health care delivery," Social Science & Medicine, Elsevier, vol. 75(12), pages 2233-2241.
    38. Sung, Ming-Chien & McDonald, David C.J. & Johnson, Johnnie E.V. & Tai, Chung-Ching & Cheah, Eng-Tuck, 2019. "Improving prediction market forecasts by detecting and correcting possible over-reaction to price movements," European Journal of Operational Research, Elsevier, vol. 272(1), pages 389-405.
    39. Steffen Keck & Wenjie Tang, 2021. "Elaborating or Aggregating? The Joint Effects of Group Decision-Making Structure and Systematic Errors on the Value of Group Interactions," Management Science, INFORMS, vol. 67(7), pages 4287-4309, July.
    40. Winkler, Jens & Moser, Roger, 2016. "Biases in future-oriented Delphi studies: A cognitive perspective," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 63-76.

  4. Armstrong, J. Scott & Graefe, Andreas, 2011. "Predicting elections from biographical information about candidates: A test of the index method," Journal of Business Research, Elsevier, vol. 64(7), pages 699-706, July.

    Cited by:

    1. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    2. Graefe, Andreas, 2015. "Improving forecasts using equally weighted predictors," Journal of Business Research, Elsevier, vol. 68(8), pages 1792-1799.
    3. Philippe Jacquart & J. Scott Armstrong, 2013. "The Ombudsman: Are Top Executives Paid Enough? An Evidence-Based Review," Interfaces, INFORMS, vol. 43(6), pages 580-589, December.
    4. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzan, Alfred G., 2017. "Assessing the 2016 U.S. Presidential Election Popular Vote Forecasts," MPRA Paper 83282, University Library of Munich, Germany.
    5. Armstrong, J. Scott, 2011. "Illusions in Regression Analysis," MPRA Paper 81663, University Library of Munich, Germany.
    6. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
    7. Cote, Joseph A., 2011. "Predicting elections from biographical information about candidates: A commentary essay," Journal of Business Research, Elsevier, vol. 64(7), pages 696-698, July.
    8. Graefe, Andreas, 2023. "Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020)," International Journal of Forecasting, Elsevier, vol. 39(1), pages 170-177.
    9. Woike, Jan K. & Hoffrage, Ulrich & Petty, Jeffrey S., 2015. "Picking profitable investments: The success of equal weighting in simulated venture capitalist decision making," Journal of Business Research, Elsevier, vol. 68(8), pages 1705-1716.
    10. David Stadelmann & Marco Portmann & Reiner Eichenberger, 2018. "Military Service of Politicians, Public Policy, and Parliamentary Decisions," CESifo Economic Studies, CESifo Group, vol. 64(4), pages 639-666.
    11. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.
    12. Andreas Graefe & Kesten C Green & J Scott Armstrong, 2019. "Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-14, January.
    13. Marco Portmann & David Stadelmann, 2013. "Testing the Median Voter Model and Moving Beyond its Limits: Do Characteristics of Politicians Matter?," CREMA Working Paper Series 2013-05, Center for Research in Economics, Management and the Arts (CREMA).

  5. Andreas Graefe & J. Scott Armstrong & Alfred G. Cuzán & Randall J. Jones, Jr., 2009. "Combined Forecasts of the 2008 Election: The Pollyvote," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 12, pages 41-42, Winter.

    Cited by:

    1. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzan, Alfred G., 2017. "Assessing the 2016 U.S. Presidential Election Popular Vote Forecasts," MPRA Paper 83282, University Library of Munich, Germany.
    2. Graefe, Andreas, 2019. "Accuracy of German federal election forecasts, 2013 & 2017," International Journal of Forecasting, Elsevier, vol. 35(3), pages 868-877.
    3. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.

  6. Andreas Graefe, 2008. "Prediction Markets – Defining Events and Motivating Participation," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 9, pages 30-32, Spring.

    Cited by:

    1. Andreas Heusler & Dominik Molitor & Martin Spann, 2019. "How Knowledge Stock Exchanges can increase student success in Massive Open Online Courses," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-17, September.

  7. Andreas Graefe & Christof Weinhardt, 2008. "Long-Term Forecasting with Prediction Markets - A Field Experiment on Applicability and Expert Confidence," Journal of Prediction Markets, University of Buckingham Press, vol. 2(2), pages 71-91, September.

    Cited by:

    1. Patrick Buckley & Fergal O’Brien, 0. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 0, pages 1-13.
    2. Buckley, Patrick, 2016. "Harnessing the wisdom of crowds: Decision spaces for prediction markets," Business Horizons, Elsevier, vol. 59(1), pages 85-94.
    3. Patrick Buckley & Fergal O’Brien, 2017. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 19(3), pages 611-623, June.

  8. Kesten Green & J. Scott Armstrong & Andreas Graefe, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 17-20, Fall.
    See citations under working paper version above.

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NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-FOR: Forecasting (3) 2007-09-09 2008-08-14 2009-08-02
  2. NEP-CBE: Cognitive and Behavioural Economics (2) 2007-09-09 2008-08-14
  3. NEP-CDM: Collective Decision-Making (2) 2008-08-14 2009-08-02
  4. NEP-POL: Positive Political Economics (2) 2008-08-14 2009-08-02
  5. NEP-ECM: Econometrics (1) 2009-08-02

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