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Ryan Webb

Personal Details

First Name:Ryan
Middle Name:
Last Name:Webb
Suffix:
RePEc Short-ID:pwe241
[This author has chosen not to make the email address public]
http://www.ryan-webb.com
Terminal Degree:2011 Economics Department; Queen's University (from RePEc Genealogy)

Affiliation

Rotman School of Management
University of Toronto

Toronto, Canada
http://www.rotman.utoronto.ca/
RePEc:edi:smtorca (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Kenneth I. Carlaw & Richard G. Lipsey & Ryan Webb, 2007. "Has the ICT Revolution Run its Course?," Discussion Papers dp07-18, Department of Economics, Simon Fraser University.

Articles

  1. Ryan Webb & Paul W. Glimcher & Kenway Louie, 2021. "The Normalization of Consumer Valuations: Context-Dependent Preferences from Neurobiological Constraints," Management Science, INFORMS, vol. 67(1), pages 93-125, January.
  2. Webb, Ryan & Mehta, Nitin & Levy, Ifat, 2021. "Assessing consumer demand with noisy neural measurements," Journal of Econometrics, Elsevier, vol. 222(1), pages 89-106.
  3. Stephanie M. Smith & Ian Krajbich & Ryan Webb, 2019. "Estimating the dynamic role of attention via random utility," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 97-111, August.
  4. Ryan Webb, 2019. "The (Neural) Dynamics of Stochastic Choice," Management Science, INFORMS, vol. 65(1), pages 230-255, January.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Kenneth I. Carlaw & Richard G. Lipsey & Ryan Webb, 2007. "Has the ICT Revolution Run its Course?," Discussion Papers dp07-18, Department of Economics, Simon Fraser University.

    Cited by:

    1. Kenneth I. Carlaw & Richard G. Lipsey, 2021. "The Funding of Important Emerging and Evolving Technologies by the Public and Private Sectors," Discussion Papers dp21-04, Department of Economics, Simon Fraser University.
    2. Дементьев В.Е., 2013. "Структурные Факторы Технологического Развития," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 49(4), pages 33-46, октябрь.
    3. Christiaan Hogendorn & Brett Frischmann, 2020. "Infrastructure and general purpose technologies: a technology flow framework," European Journal of Law and Economics, Springer, vol. 50(3), pages 469-488, December.
    4. Federico Biagi, 2013. "ICT and Productivity: A Review of the Literature," JRC Working Papers on Digital Economy 2013-09, Joint Research Centre.
    5. Dov Samet & David Schmeidler, 2023. "Desirability relations in Savage’s model of decision making," Theory and Decision, Springer, vol. 94(1), pages 1-33, January.

Articles

  1. Ryan Webb & Paul W. Glimcher & Kenway Louie, 2021. "The Normalization of Consumer Valuations: Context-Dependent Preferences from Neurobiological Constraints," Management Science, INFORMS, vol. 67(1), pages 93-125, January.

    Cited by:

    1. Wan-Yu Shih & Hsiang-Yu Yu & Cheng-Chia Lee & Chien-Chen Chou & Chien Chen & Paul W. Glimcher & Shih-Wei Wu, 2023. "Electrophysiological population dynamics reveal context dependencies during decision making in human frontal cortex," Nature Communications, Nature, vol. 14(1), pages 1-24, December.
    2. Benjamin Enke & Cassidy Shubatt, 2023. "Quantifying Lottery Choice Complexity," CESifo Working Paper Series 10644, CESifo.
    3. Guo, Julie & Tymula, Agnieszka, 2021. "Waterfall illusion in risky choice – exposure to outcome-irrelevant gambles affects subsequent valuation of risky gambles," European Economic Review, Elsevier, vol. 139(C).
    4. Choi, S. Chan & Turut, Ozge, 2023. "National brand’s competition with premium private labels: The role of context-dependent preferences," Journal of Business Research, Elsevier, vol. 165(C).
    5. Chernulich, Aleksei, 2021. "Modelling reference dependence for repeated choices: A horse race between models of normalisation," Journal of Economic Psychology, Elsevier, vol. 87(C).
    6. Glimcher, Paul W. & Tymula, Agnieszka A., 2023. "Expected subjective value theory (ESVT): A representation of decision under risk and certainty," Journal of Economic Behavior & Organization, Elsevier, vol. 207(C), pages 110-128.

  2. Stephanie M. Smith & Ian Krajbich & Ryan Webb, 2019. "Estimating the dynamic role of attention via random utility," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 97-111, August.

    Cited by:

    1. Pirrone, Angelo & Gobet, Fernand, 2021. "Is attentional discounting in value-based decision making magnitude sensitive?," LSE Research Online Documents on Economics 108608, London School of Economics and Political Science, LSE Library.
    2. Molter, Felix & Thomas, Armin W. & Heekeren, Hauke R. & Mohr, Peter N. C., 2019. "GLAMbox: A Python toolbox for investigating the association between gaze allocation and decision behaviour," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 14(12), pages 1-23.
    3. Fiedler, Susann & Hillenbrand, Adrian, 2020. "Gain-loss framing in interdependent choice," Games and Economic Behavior, Elsevier, vol. 121(C), pages 232-251.
    4. 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.

  3. Ryan Webb, 2019. "The (Neural) Dynamics of Stochastic Choice," Management Science, INFORMS, vol. 65(1), pages 230-255, January.

    Cited by:

    1. Aleksandr Alekseev, 2018. "Using Response Times to Measure Ability on a Cognitive Task," Working Papers 18-16, Chapman University, Economic Science Institute.
    2. Uwe Sunde & Dainis Zegners & Anthony Strittmatter, 2022. "Speed, Quality, and the Optimal Timing of Complex Decisions: Field Evidence," CESifo Working Paper Series 9546, CESifo.
    3. Mogens Fosgerau & Emerson Melo & André de Palma & Matthew Shum, 2017. "Discrete Choice and Rational Inattention: a General Equivalence Result," Discussion Papers 17-26, University of Copenhagen. Department of Economics.
    4. Carlos Alós-Ferrer & Johannes Buckenmaier, 2021. "Cognitive sophistication and deliberation times," Experimental Economics, Springer;Economic Science Association, vol. 24(2), pages 558-592, June.
    5. Jose Apesteguia & Miguel Ángel Ballester, 2020. "Separating predicted randomness from residual behavior," Economics Working Papers 1757, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Yukalov, V.I., 2021. "A resolution of St. Petersburg paradox," Journal of Mathematical Economics, Elsevier, vol. 97(C).
    7. Brocas, Isabelle & Carrillo, Juan D., 2021. "Value computation and modulation: A neuroeconomic theory of self-control as constrained optimization," Journal of Economic Theory, Elsevier, vol. 198(C).
    8. Ryan Webb & Paul W. Glimcher & Kenway Louie, 2021. "The Normalization of Consumer Valuations: Context-Dependent Preferences from Neurobiological Constraints," Management Science, INFORMS, vol. 67(1), pages 93-125, January.
    9. Fedor Sandomirskiy & Omer Tamuz, 2023. "Decomposable Stochastic Choice," Papers 2312.04827, arXiv.org.
    10. Alejandro Hirmas & Jan Engelmann, 2022. "Impulsiveness moderates the effects of exogenous attention on the sensitivity to gains and losses in risky lotteries," Tinbergen Institute Discussion Papers 22-046/I, Tinbergen Institute.
    11. 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.
    12. Carlos Alós-Ferrer & Ernst Fehr & Nick Netzer, 2018. "Time will tell: recovering preferences when choices are noisy," ECON - Working Papers 306, Department of Economics - University of Zurich, revised Jun 2020.
    13. Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Aldo Rustichini, 2020. "Multinomial logit processes and preference discovery: inside and outside the black box," Papers 2004.13376, arXiv.org, revised Jan 2021.
    14. Webb, Ryan & Mehta, Nitin & Levy, Ifat, 2021. "Assessing consumer demand with noisy neural measurements," Journal of Econometrics, Elsevier, vol. 222(1), pages 89-106.
    15. Carlos Alós-Ferrer & Michele Garagnani, 2019. "Strength of preference and decisions under risk," ECON - Working Papers 330, Department of Economics - University of Zurich, revised Feb 2022.
    16. Pirrone, Angelo & Gobet, Fernand, 2021. "Is attentional discounting in value-based decision making magnitude sensitive?," LSE Research Online Documents on Economics 108608, London School of Economics and Political Science, LSE Library.
    17. Geoffrey Fisher, 2023. "Measuring the Factors Influencing Purchasing Decisions: Evidence From Cursor Tracking and Cognitive Modeling," Management Science, INFORMS, vol. 69(8), pages 4558-4578, August.
    18. 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.
    19. Duffy, Sean & Smith, John, 2020. "An economist and a psychologist form a line: What can imperfect perception of length tell us about stochastic choice?," MPRA Paper 99417, University Library of Munich, Germany.
    20. V. I. Yukalov, 2021. "A Resolution of St. Petersburg Paradox," Papers 2111.14635, arXiv.org.
    21. Taro Ohdoko & Satoru Komatsu, 2023. "Integrating a Pareto-Distributed Scale into the Mixed Logit Model: A Mathematical Concept," Mathematics, MDPI, vol. 11(23), pages 1-22, November.
    22. Chernulich, Aleksei, 2021. "Modelling reference dependence for repeated choices: A horse race between models of normalisation," Journal of Economic Psychology, Elsevier, vol. 87(C).
    23. Linda Q. Yu & Jason Dana & Joseph W. Kable, 2022. "Individuals with ventromedial frontal damage display unstable but transitive preferences during decision making," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    24. Emerson Melo, 2021. "Learning In Random Utility Models Via Online Decision Problems," CAEPR Working Papers 2022-003 Classification-D, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    25. D. Pennesi, 2016. "Intertemporal discrete choice," Working Papers wp1061, Dipartimento Scienze Economiche, Universita' di Bologna.
    26. Michel Wedel & Rik Pieters & Ralf Lans, 2023. "Modeling Eye Movements During Decision Making: A Review," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 697-729, June.
    27. D. Pennesi, 2016. "Deciding fast and slow," Working Papers wp1082, Dipartimento Scienze Economiche, Universita' di Bologna.
    28. 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.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ICT: Information and Communication Technologies (1) 2007-12-01

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