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Improving out-of-sample predictions using response times and a model of the decision process

Citations

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Cited by:

  1. Sangil Lee & Chris M. Glaze & Eric T. Bradlow & Joseph W. Kable, 2020. "Flexible Utility Function Approximation via Cubic Bezier Splines," Psychometrika, Springer;The Psychometric Society, vol. 85(3), pages 716-737, September.
  2. Hébert, Benjamin & Woodford, Michael, 2023. "Rational inattention when decisions take time," Journal of Economic Theory, Elsevier, vol. 208(C).
  3. Shen Li & Yuyang Zhang & Zhaolin Ren & Claire Liang & Na Li & Julie A. Shah, 2024. "Enhancing Preference-based Linear Bandits via Human Response Time," Papers 2409.05798, arXiv.org, revised Jan 2025.
  4. Federico Echenique & Alireza Fallah & Baihe Huang & Michael I. Jordan, 2026. "Response Time Enhances Alignment with Heterogeneous Preferences," Papers 2605.06987, arXiv.org.
  5. Guangzhong Hu & Yuming Liu & Kai Liu & Xiaoxu Yang, 2023. "Research on Data-Driven Dynamic Decision-Making Mechanism of Mega Infrastructure Project Construction," Sustainability, MDPI, vol. 15(12), pages 1-25, June.
  6. Valdes Salvador & Gonzalo ValdesEdwards, 2023. "Microfoundations of Expected Utility and Response Times," Papers 2302.09421, arXiv.org.
  7. Carlos Alós-Ferrer & Ernst Fehr & Michele Garagnani, 2022. "Identifying nontransitive preferences," ECON - Working Papers 415, Department of Economics - University of Zurich, revised Jan 2023.
  8. Duarte Gonc{c}alves, 2024. "Speed, Accuracy, and Complexity," Papers 2403.11240, arXiv.org, revised May 2026.
  9. Ryan Webb, 2019. "The (Neural) Dynamics of Stochastic Choice," Management Science, INFORMS, vol. 65(1), pages 230-255, January.
  10. Konrad Grabiszewski & Alex Horenstein, 2022. "Profiling dynamic decision-makers," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-22, April.
  11. Clithero, John A., 2018. "Response times in economics: Looking through the lens of sequential sampling models," Journal of Economic Psychology, Elsevier, vol. 69(C), pages 61-86.
  12. Lohse, Johannes & Rahal, Rima-Maria & Schulte-Mecklenbeck, Michael & Sofianos, Andis & Wollbrant, Conny, 2024. "Investigations of decision processes at the intersection of psychology and economics," Journal of Economic Psychology, Elsevier, vol. 103(C).
  13. John A. Clithero & Jae Joon Lee & Joshua Tasoff, 2019. "Supervised Machine Learning for Eliciting Individual Demand," Papers 1904.13329, arXiv.org, revised Feb 2021.
  14. Shuo Liu & Nick Netzer, 2023. "Happy Times: Measuring Happiness Using Response Times," American Economic Review, American Economic Association, vol. 113(12), pages 3289-3322, December.
  15. Dewan, Ambuj & Neligh, Nathaniel, 2020. "Estimating information cost functions in models of rational inattention," Journal of Economic Theory, Elsevier, vol. 187(C).
  16. Fadong Chen & Yingshuai Zhao & Ulrich Thonemann, 2023. "The Value of Response Time Information in Supply Chain Bargaining," Manufacturing & Service Operations Management, INFORMS, vol. 25(1), pages 19-35, January.
  17. Carlos Alós-Ferrer & Ernst Fehr & Nick Netzer, 2021. "Time Will Tell: Recovering Preferences When Choices Are Noisy," Journal of Political Economy, University of Chicago Press, vol. 129(6), pages 1828-1877.
  18. David J. Cooper & Ian Krajbich & Charles N. Noussair, 2019. "Choice-Process Data in Experimental Economics," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 1-13, August.
  19. Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Aldo Rustichini, 2023. "Multinomial Logit Processes and Preference Discovery: Inside and Outside the Black Box," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(3), pages 1155-1194.
  20. Aleksandr Alekseev, 2019. "Using response times to measure ability on a cognitive task," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 65-75, August.
  21. Andrew Schotter & Isabel Trevino, 2021. "Is response time predictive of choice? An experimental study of threshold strategies," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 87-117, March.
  22. Fadong Chen & Gideon Nave & Lei Wang, 2025. "Calculated Punishment," Journal of Business Ethics, Springer, vol. 200(3), pages 715-731, September.
  23. Carlos Alós-Ferrer & Michele Garagnani, 2022. "Strength of preference and decisions under risk," Journal of Risk and Uncertainty, Springer, vol. 64(3), pages 309-329, June.
  24. Ayush Sawarni & Sahasrajit Sarmasarkar & Vasilis Syrgkanis, 2025. "Preference Learning with Response Time: Robust Losses and Guarantees," Papers 2505.22820, arXiv.org, revised Oct 2025.
  25. S. Cerreia-Vioglio & F. Maccheroni & M. Marinacci & A. Rustichini, 2017. "Multinomial logit processes and preference discovery: inside and outside the black box," Working Papers 615, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  26. Sophie Bavard & Erik Stuchlý & Arkady Konovalov & Sebastian Gluth, 2024. "Humans can infer social preferences from decision speed alone," PLOS Biology, Public Library of Science, vol. 22(6), pages 1-27, June.
  27. Sullivan, Nikki & Breslav, Alexander & Doré, Samyukta & Bachman, Matthew & Huettel, Scott A., 2025. "The golden halo of defaults in simple choices," LSE Research Online Documents on Economics 126086, London School of Economics and Political Science, LSE Library.
  28. Hebert, Benjamin & Woodford, Michael, 2018. "Information Costs and Sequential Information Sampling," Research Papers 3751, Stanford University, Graduate School of Business.
  29. Shuhua Si, 2026. "Is Complexity the Problem? Testing Random Choice with Heterogeneity," Papers 2605.01850, arXiv.org.
  30. Huseynov, Samir & Palma, Marco A. & Ahmad, Ghufran, 2021. "Does the magnitude of relative calorie distance affect food consumption?," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 530-551.
  31. Benjamin Hébert & Michael Woodford, 2021. "Neighborhood-Based Information Costs," American Economic Review, American Economic Association, vol. 111(10), pages 3225-3255, October.
  32. Vriens, M. & Vidden, C. & Schomaker, J., 2020. "What I see is what I want: Top-down attention biasing choice behavior," Journal of Business Research, Elsevier, vol. 111(C), pages 262-269.
  33. Cary Frydman & Ian Krajbich, 2022. "Using Response Times to Infer Others’ Private Information: An Application to Information Cascades," Management Science, INFORMS, vol. 68(4), pages 2970-2986, April.
  34. Alós-Ferrer, Carlos & Mihm, Maximilian, 2025. "A characterization of the Luce choice rule for an arbitrary collection of menus," Journal of Economic Theory, Elsevier, vol. 223(C).
  35. Carlo Baldassi & Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Marco Pirazzini, 2020. "A Behavioral Characterization of the Drift Diffusion Model and Its Multialternative Extension for Choice Under Time Pressure," Management Science, INFORMS, vol. 66(11), pages 5075-5093, November.
  36. Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci, 2020. "Multinomial logit processes and preference discovery: outside and inside the black box," Working Papers 663, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
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