IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0275339.html
   My bibliography  Save this article

A simple satisficing model

Author

Listed:
  • Erlend Dancke Sandorf
  • Danny Campbell
  • Caspar Chorus

Abstract

Economic theory is built on the assumption that people are omniscient utility maximizers. In reality, this is unlikely to be true and often people lack information about all alternatives that are available to them; either because the information is unavailable or that the cost of searching for and evaluating that information is high. In this paper, we develop a simple and tractable model that captures satisficing behavior. We show that the model can retrieve consistent parameters under a large range of experimental conditions. We test our model on synthetic data and present an empirical application. We discuss the implications of our results for the use of satisficing choice models in explaining choice.

Suggested Citation

  • Erlend Dancke Sandorf & Danny Campbell & Caspar Chorus, 2022. "A simple satisficing model," PLOS ONE, Public Library of Science, vol. 17(10), pages 1-30, October.
    • Handle: RePEc:plo:pone00:0275339
    DOI: 10.1371/journal.pone.0275339
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0275339
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0275339&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0275339?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
    ---><---

    References listed on IDEAS

    as
    1. Guth, Werner, 2007. "Satisficing in portfolio selection--Theoretical aspects and experimental tests," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 36(4), pages 505-522, August.
    2. Huber, Joel & Train, Kenneth, 2000. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Department of Economics, Working Paper Series qt7zm4f51b, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    3. John D. Hey & Yudistira Permana & Nuttaporn Rochanahastin, 2018. "When and how to satisfice: an experimental investigation," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 5, pages 121-137, World Scientific Publishing Co. Pte. Ltd..
    4. Tyson, Christopher J., 2008. "Cognitive constraints, contraction consistency, and the satisficing criterion," Journal of Economic Theory, Elsevier, vol. 138(1), pages 51-70, January.
    5. Charles F. Manski, 2017. "Optimize, satisfice, or choose without deliberation? A simple minimax-regret assessment," Theory and Decision, Springer, vol. 83(2), pages 155-173, August.
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, November.
    7. Tyson, Christopher J., 2008. "Cognitive constraints, contraction consistency, and the satisficing criterion," Journal of Economic Theory, Elsevier, vol. 138(1), pages 51-70, January.
    8. Weitzman, Martin L, 1979. "Optimal Search for the Best Alternative," Econometrica, Econometric Society, vol. 47(3), pages 641-654, May.
    9. Danny Campbell & Seda Erdem, 2015. "Position Bias in Best-worst Scaling Surveys: A Case Study on Trust in Institutions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(2), pages 526-545.
    10. Gilles Laurent & Eric Lapersonne & Jean-Jacques Le Goff, 1995. "Consideration sets of size one: An empirical investigation of automobile purchases," Post-Print hal-00458463, HAL.
    11. David Hensher & Andrew Collins & William Greene, 2013. "Accounting for attribute non-attendance and common-metric aggregation in a probabilistic decision process mixed multinomial logit model: a warning on potential confounding," Transportation, Springer, vol. 40(5), pages 1003-1020, September.
    12. Chorus, Caspar G. & Arentze, Theo A. & Timmermans, Harry J.P., 2008. "A Random Regret-Minimization model of travel choice," Transportation Research Part B: Methodological, Elsevier, vol. 42(1), pages 1-18, January.
    13. Joel Huber and Kenneth Train., 2000. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Economics Working Papers E00-289, University of California at Berkeley.
    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. Erlend Dancke Sandorf & Danny Campbell, 2019. "Accommodating satisficing behaviour in stated choice experiments," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 46(1), pages 133-162.
    2. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    3. Boeri, Marco & Scarpa, Riccardo & Chorus, Caspar G., 2014. "Stated choices and benefit estimates in the context of traffic calming schemes: Utility maximization, regret minimization, or both?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 121-135.
    4. Villas-Boas, Sofia B & Taylor, Rebecca & Krovetz, Hannah, 2016. "Willingness to Pay for Low Water Footprint Food Choices During Drought," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt9vh3x180, Department of Agricultural & Resource Economics, UC Berkeley.
    5. Kim, Junghun & Seung, Hyunchan & Lee, Jongsu & Ahn, Joongha, 2020. "Asymmetric preference and loss aversion for electric vehicles: The reference-dependent choice model capturing different preference directions," Energy Economics, Elsevier, vol. 86(C).
    6. Valentino Dardanoni & Paola Manzini & Marco Mariotti & Christopher J. Tyson, 2020. "Inferring Cognitive Heterogeneity From Aggregate Choices," Econometrica, Econometric Society, vol. 88(3), pages 1269-1296, May.
    7. Daniele Pacifico, 2012. "Fitting nonparametric mixed logit models via expectation-maximization algorithm," Stata Journal, StataCorp LLC, vol. 12(2), pages 284-298, June.
    8. Byun, Hyunsuk & Shin, Jungwoo & Lee, Chul-Yong, 2018. "Using a discrete choice experiment to predict the penetration possibility of environmentally friendly vehicles," Energy, Elsevier, vol. 144(C), pages 312-321.
    9. Valentino Dardanoni & Paola Manzini & Marco Mariotti & Christopher J. Tyson, 2020. "Inferring Cognitive Heterogeneity From Aggregate Choices," Econometrica, Econometric Society, vol. 88(3), pages 1269-1296, May.
    10. Shin, Jungwoo & Park, Yuri & Lee, Daeho, 2018. "Who will be smart home users? An analysis of adoption and diffusion of smart homes," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 246-253.
    11. Stefanie Lena Heinzle & Rolf Wüstenhagen, 2012. "Dynamic Adjustment of Eco‐labeling Schemes and Consumer Choice – the Revision of the EU Energy Label as a Missed Opportunity?," Business Strategy and the Environment, Wiley Blackwell, vol. 21(1), pages 60-70, January.
    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. Xiaoxue Sherry Gao & Glenn W. Harrison & Rusty Tchernis, 2023. "Behavioral welfare economics and risk preferences: a Bayesian approach," Experimental Economics, Springer;Economic Science Association, vol. 26(2), pages 273-303, April.
    14. Hoyos, David, 2010. "The state of the art of environmental valuation with discrete choice experiments," Ecological Economics, Elsevier, vol. 69(8), pages 1595-1603, June.
    15. Mørkbak, Morten Raun & Olsen, Søren Bøye & Campbell, Danny, 2014. "Behavioral implications of providing real incentives in stated choice experiments," Journal of Economic Psychology, Elsevier, vol. 45(C), pages 102-116.
    16. Mandy Ryan & Nicolas Krucien & Frouke Hermens, 2018. "The eyes have it: Using eye tracking to inform information processing strategies in multi‐attributes choices," Health Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 709-721, April.
    17. Lee, Daeho & Shin, Jungwoo & Lee, Sangwon, 2015. "Network management in the era of convergence: Focusing on application-based quality assessment of Internet access service," Telecommunications Policy, Elsevier, vol. 39(8), pages 705-716.
    18. Hye-Jeong Lee & Beom Jin Chung & Sung-Yoon Huh, 2023. "Consumer Preferences for Smart Energy Services Based on AMI Data in the Power Sector," Energies, MDPI, vol. 16(9), pages 1-20, May.
    19. repec:ebl:ecbull:v:30:y:2010:i:1:p:437-449 is not listed on IDEAS
    20. Kyuho Maeng & Sungmin Ko & Jungwoo Shin & Youngsang Cho, 2020. "How Much Electricity Sharing Will Electric Vehicle Owners Allow from Their Battery? Incorporating Vehicle-to-Grid Technology and Electricity Generation Mix," Energies, MDPI, vol. 13(16), pages 1-25, August.
    21. Arne Risa Hole & Hong Il Yoo, 2017. "The use of heuristic optimization algorithms to facilitate maximum simulated likelihood estimation of random parameter logit models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(5), pages 997-1013, November.

    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:plo:pone00:0275339. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.