IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v155y2020ics004016251930246x.html
   My bibliography  Save this article

Individual inconsistency and aggregate rationality: Overcoming inconsistencies in expert judgment at the technical frontier

Author

Listed:
  • Funk, Patrick
  • Davis, Alex
  • Vaishnav, Parth
  • Dewitt, Barry
  • Fuchs, Erica

Abstract

Commercialization of a new material or process invention can take decades. A predominance of tacit knowledge, information asymmetries, and insufficient human capital with knowledge in the field can contribute to this delay. Focusing on an emerging technology which offers an extreme example of such issues, we seek to capture what expert decision-making looks like at the technological frontier and opportunities for interventions to accelerate the commercialization of technologies with these issues. We elicit implicit and explicit knowledge of experts about the feasibility of producing parts with metal additive manufacturing (MAM), then recruit 27 of 65 experts from industry, academia, and government to complete the survey. We find that no two experts make the same judgments about the feasibility of producing jet engine parts with MAM. Further, the majority of experts exhibit some internal inconsistency (intransitivity) in their judgments. Aggregate expert knowledge has greater internal consistency, suggesting that relying on one or two experts could cause considerable divergence from aggregate knowledge. Through resampling the experts, we show the degree of this divergence decreases as the number of experts in the sample increases. The results suggest that capturing, pooling, and scaling aggregate expert knowledge could accelerate commercialization of new materials and processes.

Suggested Citation

  • Funk, Patrick & Davis, Alex & Vaishnav, Parth & Dewitt, Barry & Fuchs, Erica, 2020. "Individual inconsistency and aggregate rationality: Overcoming inconsistencies in expert judgment at the technical frontier," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    • Handle: RePEc:eee:tefoso:v:155:y:2020:i:c:s004016251930246x
    DOI: 10.1016/j.techfore.2020.119984
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S004016251930246X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2020.119984?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. repec:cup:judgdm:v:8:y:2013:i:1:p:25-28 is not listed on IDEAS
    2. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    3. Colson, Abigail R. & Cooke, Roger M., 2017. "Cross validation for the classical model of structured expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 109-120.
    4. Jacob Marschak, 1959. "Binary Choice Constraints on Random Utility Indicators," Cowles Foundation Discussion Papers 74, Cowles Foundation for Research in Economics, Yale University.
    5. Michel Regenwetter & Clintin P. Davis-Stober, 2008. "There Are Many Models of Transitive Preference: A Tutorial Review and Current Perspective," Springer Optimization and Its Applications, in: Tamar Kugler & J. Cole Smith & Terry Connolly & Young-Jun Son (ed.), Decision Modeling and Behavior in Complex and Uncertain Environments, pages 99-124, Springer.
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, January.
    7. An, Hyoung Joon & Ahn, Sang-Jin, 2016. "Emerging technologies—beyond the chasm: Assessing technological forecasting and its implication for innovation management in Korea," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 132-142.
    8. Jiang, Ruth & Kleer, Robin & Piller, Frank T., 2017. "Predicting the future of additive manufacturing: A Delphi study on economic and societal implications of 3D printing for 2030," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 84-97.
    9. J. Kruskal, 1964. "Nonmetric multidimensional scaling: A numerical method," Psychometrika, Springer;The Psychometric Society, vol. 29(2), pages 115-129, June.
    10. Dražen Prelec & H. Sebastian Seung & John McCoy, 2017. "A solution to the single-question crowd wisdom problem," Nature, Nature, vol. 541(7638), pages 532-535, January.
    11. Sara Abdollahi & Alexander Davis & John H Miller & Adam W Feinberg, 2018. "Expert-guided optimization for 3D printing of soft and liquid materials," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-19, April.
    12. Bohn, Roger E., 2005. "From Art to Science in Manufacturing: The Evolution of Technological Knowledge," Foundations and Trends(R) in Technology, Information and Operations Management, now publishers, vol. 1(2), pages 1-82, October.
    13. repec:cup:judgdm:v:13:y:2018:i:4:p:322-333 is not listed on IDEAS
    14. Bonnín Roca, Jaime & Vaishnav, Parth & Morgan, M.Granger & Mendonça, Joana & Fuchs, Erica, 2017. "When risks cannot be seen: Regulating uncertainty in emerging technologies," Research Policy, Elsevier, vol. 46(7), pages 1215-1233.
    15. Tversky, Amos & Kahneman, Daniel, 1986. "Rational Choice and the Framing of Decisions," The Journal of Business, University of Chicago Press, vol. 59(4), pages 251-278, October.
    16. Stephen T. Goddard, 1983. "Ranking in Tournaments and Group Decisionmaking," Management Science, INFORMS, vol. 29(12), pages 1384-1392, December.
    17. de Leeuw, Jan & Mair, Patrick, 2009. "Multidimensional Scaling Using Majorization: SMACOF in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 31(i03).
    18. Amos Tversky & Itamar Simonson, 1993. "Context-Dependent Preferences," Management Science, INFORMS, vol. 39(10), pages 1179-1189, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Andrew Weng & Omar Y. Ahmed & Gabriel Ehrlich & Anna Stefanopoulou, 2024. "Higher labor intensity in US automotive assembly plants after transitioning to electric vehicles," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Marić, Josip & Opazo-Basáez, Marco & Vlačić, Božidar & Dabić, Marina, 2023. "Innovation management of three-dimensional printing (3DP) technology: Disclosing insights from existing literature and determining future research streams," Technological Forecasting and Social Change, Elsevier, vol. 193(C).

    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. Bonnín Roca, Jaime & Vaishnav, Parth & Morgan, Granger M. & Fuchs, Erica & Mendonça, Joana, 2021. "Technology Forgiveness: Why emerging technologies differ in their resilience to institutional instability," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    2. Kazagli, Evanthia & de Lapparent, Matthieu, 2023. "A discrete choice modeling framework of heterogenous decision rules accounting for non-trading behavior," Journal of choice modelling, Elsevier, vol. 48(C).
    3. Marić, Josip & Opazo-Basáez, Marco & Vlačić, Božidar & Dabić, Marina, 2023. "Innovation management of three-dimensional printing (3DP) technology: Disclosing insights from existing literature and determining future research streams," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    4. Emerson Melo, 2021. "Learning in Random Utility Models Via Online Decision Problems," Papers 2112.10993, arXiv.org, revised Aug 2022.
    5. Axel C. Mühlbacher & Anika Kaczynski & Peter Zweifel & F. Reed Johnson, 2016. "Experimental measurement of preferences in health and healthcare using best-worst scaling: an overview," Health Economics Review, Springer, vol. 6(1), pages 1-14, December.
    6. Hammon, Angelina & Zinn, Sabine, 2020. "Multiple imputation of binary multilevel missing not at random data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 69(3), pages 547-564.
    7. Regenwetter, Michel & Marley, A. A. J. & Grofman, Bernard, 2002. "A general concept of majority rule," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 405-428, July.
    8. Hensher, David A. & Ho, Chinh, 2015. "The role of perceived acceptability of alternatives in identifying and assessing choice set processing strategies in stated choice settings: The case of road pricing reform," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 225-237.
    9. A. Kamakura, Wagner & Afonso Mazzon, Jose & De Bruyn, Arnaud, 2006. "Modeling voter choice to predict the final outcome of two-stage elections," International Journal of Forecasting, Elsevier, vol. 22(4), pages 689-706.
    10. Ng'ombe, John, 2019. "Economics of the Greenseeder Hand Planter, Discrete Choice Modeling, and On-Farm Field Experimentation," Thesis Commons jckt7, Center for Open Science.
    11. Bonnin Roca, Jaime & O'Sullivan, Eoin, 2020. "Seeking coherence between barriers to manufacturing technology adoption and innovation policy," International Journal of Production Economics, Elsevier, vol. 230(C).
    12. Stefanie Heinzle, 2012. "Disclosure of Energy Operating Cost Information: A Silver Bullet for Overcoming the Energy-Efficiency Gap?," Journal of Consumer Policy, Springer, vol. 35(1), pages 43-64, March.
    13. Bechler, Georg & Steinhardt, Claudius & Mackert, Jochen & Klein, Robert, 2021. "Product line optimization in the presence of preferences for compromise alternatives," European Journal of Operational Research, Elsevier, vol. 288(3), pages 902-917.
    14. Paolo Crosetto & Alexia Gaudeul, 2011. "Do consumers prefer offers that are easy to compare? An experimental investigation," Jena Economics Research Papers 2011-044, Friedrich-Schiller-University Jena.
    15. Benjamin Polak & Rupert Stadler & Mark Heitmann & Andreas Herrmann & Marc Cäsar & Jan Landwehr, 2010. "Aufpreise oder Gesamtpreise? Wirkung der Preisdarstellung auf das individuelle Entscheidungsverhalten," Schmalenbach Journal of Business Research, Springer, vol. 62(8), pages 911-932, December.
    16. Guilhem Lecouteux & Ivan Mitrouchev, 2023. "The view from Manywhere : normative economics with context-dependent preferences," Post-Print hal-04551021, HAL.
    17. Pinger, Pia & Ruhmer-Krell, Isabel & Schumacher, Heiner, 2016. "The compromise effect in action: Lessons from a restaurant's menu," Journal of Economic Behavior & Organization, Elsevier, vol. 128(C), pages 14-34.
    18. Engel, Christoph & Zamir, Eyal, 2024. "Is transparency a blessing or a curse? An experimental horse race between accountability and extortionary corruption," International Review of Law and Economics, Elsevier, vol. 78(C).
    19. Amel Awadelkarim & Arjun Seshadri & Itai Ashlagi & Irene Lo & Johan Ugander, 2023. "Rank-heterogeneous Preference Models for School Choice," Papers 2306.01801, arXiv.org.
    20. Brad R. Taylor, 2020. "The psychological foundations of rational ignorance: biased heuristics and decision costs," Constitutional Political Economy, Springer, vol. 31(1), pages 70-88, March.

    More about this item

    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:eee:tefoso:v:155:y:2020:i:c:s004016251930246x. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.