IDEAS home Printed from https://ideas.repec.org/a/spr/decisn/v48y2021i3d10.1007_s40622-021-00288-4.html
   My bibliography  Save this article

Smart advice for better governance: applying expert methods to high-stakes decisions

Author

Listed:
  • Dušana Dokupilová

    (Slovak Academy of Sciences)

  • Vladimíra Kurincová Čavojová

    (Slovak Academy of Sciences)

  • Vladimír Baláž

    (Slovak Academy of Sciences)

  • Eva Ballová Mikušková

    (Slovak Academy of Sciences)

  • Dagmar Gombitová

    (Slovak Academy of Sciences)

Abstract

The main aim of this paper was to examine the consistency of experts (N = 71) in evaluation in high-stakes real-life decision-making, and how their consistency relates to other psychological constructs such as cognitive reflection and overconfidence. A pool of top Slovak experts was assembled, and the AHP method for eliciting policy priorities was applied. Moreover, the cognitive reflection and overconfidence of experts were measured. The consistency of experts tended to improve over time and this improvement occurred also in exercises with increased cognitive demand. Improved consistency may have resulted both from the learning effect and from better comprehension of one’s preferences. However, there was no correlation between the consistency of experts and their cognitive reflection or overconfidence. The results suggest that for technological and economic development of any state it is beneficial for real experts to decide these issues. However, experts are not perfect and free from mistakes; therefore, attention should be paid to the selection process of future experts and their learning environment.

Suggested Citation

  • Dušana Dokupilová & Vladimíra Kurincová Čavojová & Vladimír Baláž & Eva Ballová Mikušková & Dagmar Gombitová, 2021. "Smart advice for better governance: applying expert methods to high-stakes decisions," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 48(3), pages 285-293, September.
    • Handle: RePEc:spr:decisn:v:48:y:2021:i:3:d:10.1007_s40622-021-00288-4
    DOI: 10.1007/s40622-021-00288-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40622-021-00288-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40622-021-00288-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fligstein, Neil & Brundage, Jonah S & Schultz, Michael, 2014. "Why the Federal Reserve Failed to See the Financial Crisis of 2008: The Role of “Macroeconomics” as a Sense making and Cultural Frame," Institute for Research on Labor and Employment, Working Paper Series qt97k6t78z, Institute of Industrial Relations, UC Berkeley.
    2. Hoppe, Eva I. & Kusterer, David J., 2011. "Behavioral biases and cognitive reflection," Economics Letters, Elsevier, vol. 110(2), pages 97-100, February.
    3. Britta Herbig & Andreas Glöckner, 2009. "Experts and Decision Making: First Steps Towards a Unifying Theory of Decision Making in Novices, Intermediates and Experts," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2009_02, Max Planck Institute for Research on Collective Goods.
    4. Gary Klein, 1999. "Sources of Power: How People Make Decisions," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262611465, December.
    5. Wagenaar, Willem A. & Keren, Gideon B., 1985. "Calibration of probability assessments by professional blackjack dealers, statistical experts, and lay people," Organizational Behavior and Human Decision Processes, Elsevier, vol. 36(3), pages 406-416, December.
    6. Shane Frederick, 2005. "Cognitive Reflection and Decision Making," Journal of Economic Perspectives, American Economic Association, vol. 19(4), pages 25-42, Fall.
    7. Wolfgang Ossadnik & Stefanie Schinke & Ralf H. Kaspar, 2016. "Group Aggregation Techniques for Analytic Hierarchy Process and Analytic Network Process: A Comparative Analysis," Group Decision and Negotiation, Springer, vol. 25(2), pages 421-457, March.
    8. Leonard Lee & On Amir & Dan Ariely, 2009. "In Search of Homo Economicus: Cognitive Noise and the Role of Emotion in Preference Consistency," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 36(2), pages 173-187.
    9. Darius Danesh & Michael J. Ryan & Alireza Abbasi, 2017. "A systematic comparison of multi-criteria decision making methods for the improvement of project portfolio management in complex organisations," International Journal of Management and Decision Making, Inderscience Enterprises Ltd, vol. 16(3), pages 280-320.
    10. Bernasconi, Michele & Choirat, Christine & Seri, Raffaello, 2014. "Empirical properties of group preference aggregation methods employed in AHP: Theory and evidence," European Journal of Operational Research, Elsevier, vol. 232(3), pages 584-592.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chavez, Daniel E. & Palma, Marco A. & Nayga, Rodolfo M. & Mjelde, James W., 2020. "Product availability in discrete choice experiments with private goods," Journal of choice modelling, Elsevier, vol. 36(C).
    2. Alós-Ferrer, Carlos & Hügelschäfer, Sabine, 2016. "Faith in intuition and cognitive reflection," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 64(C), pages 61-70.
    3. Corgnet, Brice & DeSantis, Mark & Porter, David, 2020. "The distribution of information and the price efficiency of markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    4. Jinrui Pan & Jason Shachat & Sijia Wei, 2020. "Cognitive reflection and economic order quantity inventory management: An experimental investigation," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(6), pages 998-1009, September.
    5. Laila Oubahman & Szabolcs Duleba, 2022. "A Comparative Analysis of Homogenous Groups’ Preferences by Using AIP and AIJ Group AHP-PROMETHEE Model," Sustainability, MDPI, vol. 14(10), pages 1-18, May.
    6. Ray Saadaoui Mallek & Mohamed Albaity, 2019. "Individual differences and cognitive reflection across gender and nationality the case of the United Arab Emirates," Cogent Economics & Finance, Taylor & Francis Journals, vol. 7(1), pages 1567965-156, January.
    7. Kai Duttle & Keigo Inukai, 2015. "Complexity Aversion: Influences of Cognitive Abilities, Culture and System of Thought," Economics Bulletin, AccessEcon, vol. 35(2), pages 846-855.
    8. Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2022. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Management Science, INFORMS, vol. 68(7), pages 5216-5232, July.
    9. Mohammad Noori, 2016. "Cognitive reflection as a predictor of susceptibility to behavioral anomalies," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(1), pages 114-120, January.
    10. Daniel J. Benjamin & Sebastian A. Brown & Jesse M. Shapiro, 2013. "Who Is ‘Behavioral’? Cognitive Ability And Anomalous Preferences," Journal of the European Economic Association, European Economic Association, vol. 11(6), pages 1231-1255, December.
    11. Lauber, Arne & March, Christoph & Sahm, Marco, 2023. "Optimal and fair prizing in sequential round-robin tournaments: Experimental evidence," Games and Economic Behavior, Elsevier, vol. 141(C), pages 30-51.
    12. Ruffle, Bradley J. & Wilson, Anne E., 2019. "Tat will tell: Tattoos and time preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 566-585.
    13. Antonio Mastrogiorgio & Enrico Petracca, 2014. "Numerals as triggers of System 1 and System 2 in the ‘bat and ball’ problem," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 13(1), pages 135-148, June.
    14. Chavez, Daniel E. & Palma, Marco A. & Nayga Jr., Rodolfo M., 2017. "When does real become consequential in non-hypothetical choice experiments?," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266327, Southern Agricultural Economics Association.
    15. Benjamin Enke & Uri Gneezy & Brian Hall & David Martin & Vadim Nelidov & Theo Offerman & Jeroen van de Ven, 2020. "Cognitive Biases: Mistakes or Missing Stakes?," CESifo Working Paper Series 8168, CESifo.
    16. Joshua Zonca & Giorgio Coricelli & Luca Polonio, 2020. "Gaze patterns disclose the link between cognitive reflection and sophistication in strategic interaction," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(2), pages 230-245, March.
    17. Ji Yong Lee & Rodolfo M. Nayga & Cary Deck & Andreas C. Drichoutis, 2020. "Cognitive Ability and Bidding Behavior in Second Price Auctions: An Experimental Study," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(5), pages 1494-1510, October.
    18. Brañas-Garza, Pablo & Kujal, Praveen & Lenkei, Balint, 2019. "Cognitive reflection test: Whom, how, when," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 82(C).
    19. Cueva, Carlos & Iturbe-Ormaetxe, Iñigo & Mata-Pérez, Esther & Ponti, Giovanni & Sartarelli, Marcello & Yu, Haihan & Zhukova, Vita, 2016. "Cognitive (ir)reflection: New experimental evidence," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 64(C), pages 81-93.
    20. Benjamin Enke & Uri Gneezy & Brian Hall & David Martin & Vadim Nelidov & Theo Offerman & Jeroen van de Ven, 2023. "Cognitive Biases: Mistakes or Missing Stakes?," The Review of Economics and Statistics, MIT Press, vol. 105(4), pages 818-832, July.

    More about this item

    Keywords

    High-stakes decision-making; Analytical hierarchy process; Consistency; Government;
    All these keywords.

    JEL classification:

    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • D78 - Microeconomics - - Analysis of Collective Decision-Making - - - Positive Analysis of Policy Formulation and Implementation
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:decisn:v:48:y:2021:i:3:d:10.1007_s40622-021-00288-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.