IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v10y2023i1d10.1057_s41599-023-01542-z.html
   My bibliography  Save this article

A brief history of heuristics: how did research on heuristics evolve?

Author

Listed:
  • Mohamad Hjeij

    (HHL Leipzig Graduate School of Management)

  • Arnis Vilks

    (HHL Leipzig Graduate School of Management)

Abstract

Heuristics are often characterized as rules of thumb that can be used to speed up the process of decision-making. They have been examined across a wide range of fields, including economics, psychology, and computer science. However, scholars still struggle to find substantial common ground. This study provides a historical review of heuristics as a research topic before and after the emergence of the subjective expected utility (SEU) theory, emphasising the evolutionary perspective that considers heuristics as resulting from the development of the brain. We find it useful to distinguish between deliberate and automatic uses of heuristics, but point out that they can be used consciously and subconsciously. While we can trace the idea of heuristics through many centuries and fields of application, we focus on the evolution of the modern notion of heuristics through three waves of research, starting with Herbert Simon in the 1950s, who introduced the notion of bounded rationality and suggested the use of heuristics in artificial intelligence, thereby paving the way for all later research on heuristics. A breakthrough came with Daniel Kahneman and Amos Tversky in the 1970s, who analysed the biases arising from using heuristics. The resulting research programme became the subject of criticism by Gerd Gigerenzer in the 1990s, who argues that an ‘adaptive toolbox’ consisting of ‘fast-and-frugal’ heuristics can yield ‘ecologically rational’ decisions.

Suggested Citation

  • Mohamad Hjeij & Arnis Vilks, 2023. "A brief history of heuristics: how did research on heuristics evolve?," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-15, December.
  • Handle: RePEc:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-01542-z
    DOI: 10.1057/s41599-023-01542-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-023-01542-z
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-023-01542-z?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. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    2. Herbert A. Simon & Allen Newell, 1958. "Heuristic Problem Solving: The Next Advance in Operations Research," Operations Research, INFORMS, vol. 6(1), pages 1-10, February.
    3. Frantz, Roger, 2003. "Herbert Simon. Artificial intelligence as a framework for understanding intuition," Journal of Economic Psychology, Elsevier, vol. 24(2), pages 265-277, April.
    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. Suresh P. Sethi & Sushil Gupta & Vipin K. Agrawal & Vijay K. Agrawal, 2022. "Nobel laureates’ contributions to and impacts on operations management," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4283-4303, December.
    2. Marco Sahm & Robert K. von Weizsäcker & Robert K. von Weizsäcker, 2014. "Reason, Intuition, and Time," CESifo Working Paper Series 5134, CESifo.
    3. Daniele Schilirò, 2018. "Economic Decisions and Simon’s Notion of Bounded Rationality," International Business Research, Canadian Center of Science and Education, vol. 11(7), pages 64-75, July.
    4. Michelle Baddeley, 2020. "Hoarding in the age of COVID-19," Journal of Behavioral Economics for Policy, Society for the Advancement of Behavioral Economics (SABE), vol. 4(S), pages 69-75, June.
    5. Wierenga, Berend, 2011. "Managerial decision making in marketing: The next research frontier," International Journal of Research in Marketing, Elsevier, vol. 28(2), pages 89-101.
    6. Torgler, Benno & Schneider, Friedrich & Schaltegger, Christoph A., 2007. "With or Against the People? The Impact of a Bottom-Up Approach on Tax Morale and the Shadow Economy," Berkeley Olin Program in Law & Economics, Working Paper Series qt6331x6vz, Berkeley Olin Program in Law & Economics.
    7. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    8. Christina Leuker & Thorsten Pachur & Ralph Hertwig & Timothy J. Pleskac, 2019. "Do people exploit risk–reward structures to simplify information processing in risky choice?," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 76-94, August.
    9. Jae Wook Yoo & Richard Reed & Shung Jae Shin & David J. Lemak, 2009. "Strategic Choice and Performance in Late Movers: Influence of the Top Management Team's External Ties," Journal of Management Studies, Wiley Blackwell, vol. 46(2), pages 308-335, March.
    10. Giovanni Calice & Levent Kutlu & Ming Zeng, 2021. "Understanding US firm efficiency and its asset pricing implications," Empirical Economics, Springer, vol. 60(2), pages 803-827, February.
    11. Westerhoff, Frank H. & Dieci, Roberto, 2006. "The effectiveness of Keynes-Tobin transaction taxes when heterogeneous agents can trade in different markets: A behavioral finance approach," Journal of Economic Dynamics and Control, Elsevier, vol. 30(2), pages 293-322, February.
    12. José Castro Caldas & Helder Coelho, 1999. "The Origin of Institutions: Socio-Economic Processes, Choice, Norms and Conventions," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 2(2), pages 1-1.
    13. Nagler Matthew G., 2007. "Understanding the Internet's Relevance to Media Ownership Policy: A Model of Too Many Choices," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 7(1), pages 1-28, June.
    14. Ranganathan, Kavitha & Lejarraga, Tomás, 2021. "Elicitation of risk preferences through satisficing," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    15. Westerhoff Frank H., 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 195-227, April.
    16. Andrew Caplin & Mark Dean & Daniel Martin, 2011. "Search and Satisficing," American Economic Review, American Economic Association, vol. 101(7), pages 2899-2922, December.
    17. Shi, Yi & Deng, Yawen & Wang, Guoan & Xu, Jiuping, 2020. "Stackelberg equilibrium-based eco-economic approach for sustainable development of kitchen waste disposal with subsidy policy: A case study from China," Energy, Elsevier, vol. 196(C).
    18. Lawrence Bunnell & Kweku-Muata Osei-Bryson & Victoria Y. Yoon, 0. "RecSys Issues Ontology: A Knowledge Classification of Issues for Recommender Systems Researchers," Information Systems Frontiers, Springer, vol. 0, pages 1-42.
    19. da Silveira, Jaylson Jair & Lima, Gilberto Tadeu, 2021. "Wage inequality as a source of endogenous macroeconomic fluctuations," Structural Change and Economic Dynamics, Elsevier, vol. 56(C), pages 35-52.
    20. Nathan N. Cheek & Jacob Goebel, 2020. "What does it mean to maximize? “Decision difficulty,†indecisiveness, and the jingle-jangle fallacies in the measurement of maximizing," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(1), pages 7-24, January.

    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:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-01542-z. 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: https://www.nature.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.