Prof. Ido Erev

Behavioral Science and Management

Overview

 

Ido Erev (PhD: University of North Carolina, 1990, Cognitive/Quantitative Psychology).

Ido joined the Faculty of Industrial Engineering and Management in 1990 as a Lecturer. He was promoted to Full Professor in 2004, and holds the “Women’s Division—ATS Academic Chair” since 2006. He presently serves as the Vice Dean for the MBA programs, the Head of the Behavioral Science Area, the head of the Technion section of the Max Wertheimer Minerva Center for Cognitive Research, and the head of the Technion group in the ICORE for Empirical Legal Studies of Decision Making

Ido has been a visiting research associate in Economics at the University of Pittsburgh; a Michael A. Gould fellow at Columbia Business School; a Marvin Bower Fellow at Harvard Business School; a fellow in the Israel Center of Advanced Studies; a visiting professor at Erasmus School of Economics; a visiting professor at the Interdisciplinary center (IDC) in Herzliya; and a research environment professor at Warwick Business School.

Ido and his co-workers focus on three related lines of research.  The first line centers on the observation of a large difference between decisions that are made based on a description of the incentive structure, and decisions that are made based on experience: People tend to exhibit oversensitivity to rare events in decisions from description, and the opposite bias in decisions from experience.  This observation, initially documented by Barron & Erev (2003) and now known as the experience-description gap (Hertwig & Erev, 2009), is important as mainstream behavioral economic research (e.g., Kahneman & Tversky, 1979) focus on decisions from description, and most of the application effort involve decisions from experience.  Ido and his co-workers address this problem by systematic study of decisions from experience. 

A second line of research focuses on the difference between anomalies and forecasts.  The leading models of choice behavior tend to focus on interesting anomalies.  Since each model focuses on few isolated anomalies, it is not easy to use these models to derive clear forecasts.  That is, it Is not clear which of the leading models should be used to address a new choice problem. Ido and his co-workers try to address this problem by developing general models, and then organizing international choice prediction competitions in which they challenge other researchers to propose better models that can capture all the classical anomalies and allow ex ante predictions of behavior

(for example, see http://departments.agri.huji.ac.il/economics/teachers/ert_eyal/competition.htm).

A third line of research centers on the practical implications of the basic research summarized above.  The experience-description gap, and the models that best capture it, suggest that economic incentives are most effective when they insure that the socially desirable behavior maximizes payoff, and also minimizes the probability of regret.  Ido and his co-authors use this observation to address distinct social and organizational problems.  For example, they demonstrate that gentle rule enforcement methods are more effective in improving safety in industrial settings than traditional policies (see Erev & Roth, 2014). 

 

Selected Publications

 

 Papers

Book Chapters

  • Erev, I. (1992), "The effect of explicit probability estimates on violations of subjective expected utility theory in the Allais paradox". In: Decision Making under Risk and Uncertainty: New models and empirical finding, J. Geweke (Ed.). Dordecht: Kluwer Academic Publisher.
  • Rapoport, A. & Erev, I. (1994), "Provision of step-level public goods: Effects of different information structures". In: U. Schulz, W. Albers & U. Mueller (Eds.), Social Dilemmas and Cooperation (pp 147-171). New York: Springer-Verlag.
  • Erev, I. (1994), "Convergence in the orange grove: Learning processes in a social dilemma setting". In: U. Schulz, W. Albers & U. Mueller (Eds.), Social Dilemmas and Cooperation (pp. 187-206). New York: Springer-Verlag.
  • Erev, I., Maital, S. & Or-Hof, O. (1997), "Melioration, adaptive learning and the effect of constant re-evaluations of strategies". In: G. Antoniedes, F. van Raaij & S. Maital (Eds.), Advances in Economic Psychology. Sussex, England: John Wiley & Sons.
  • Erev, I. & Gopher, D. (1999), "A cognitive game theoretic analysis of attention strategies, ability and incentives". In: D. Gopher & A. Koriat (Eds.), Attention and Performance XVII: Cognitive Regulation of Performance: Interaction of Theory and Applications. Cambridge, MA: MIT Press.
  • Erev, I. & Roth, A.E. (1999), "On the role of reinforcement learning in experimental games: The cognitive game-theoretic approach". In: D. Budescu, I.
  • Erev & R. Zwick (Eds.), Games and Human Behavior: Essays in Honor of Amnon Rapoport. LEA
  • Zwick, R., Erev, I. & Budescu, D. (1999), "Can psychologists and economists cooperate in the study of human decisions in social and interactive contexts?" In: D. Budescu, I. Erev & R. Zwick (Eds.), Games and Human Behavior: Essays in Honor of Amnon Rapoport. LEA.
  • Erev, I. & Roth, A.E. (2001), "On simple reinforcement learning models and reciprocation in the prisoner dilemma game". In Gigerenzer, G. and Selten, R. (Eds.), The Adaptive Toolbox. Cambridge, MA: MIT Press.
  • Mellers, B.A., Erev, I., Fessler, D.M.T., Hemelrijk, C.K., Hertwig, R., Laland, K.N., Scherer, K.R., Seeley, T.D., Selten, R. & Tetlock, P.E. (2001). "Effects of emotions and social processes on bounded rationality." In Gigerenzer, G. and Selten, R. (Eds.), The Adaptive Toolbox. Cambridge, MA: MIT Press.
  • Haruvy, E. & Erev, I. (2002), On the Application and Interpretation of Learning Models. In Zwick R. and Rapoport A. (Eds.), Experimental Business Research. Kluwer Academic Publishers.
  • Hertwig, R. Barron, G., Weber, E. and Erev, I. (2006), Risky Prospects: When Valued Through A Window of Sampled Experiences. In K. Fiedler, & P.Juslin (Eds.), Information sampling and adaptive cognition (pp. 72-91). Cambridge, England: Cambridge University Press.
  • Erev, I., & Livne-Tarandach, R. (2005)."Experiment-based exams and the difference between the behavioral and the natural sciences". In Zwick R. and Rapoport A. (Eds.), Experimental Business Research, Vol 3. Dordrecht, The Netherlands: Springer.
  • Erev, I. (2007). On the weighting of rare events and the economics of small decisions. In: S. H. Oda (Ed.), Advances in Experimental Economics, Lecture Notes in Economics and Mathematical Systems, Vol. 590. Dordrecht, The Netherlands: Springer.
  • Parush, A., Ahuvia, S. & Erev, I. (2007). "Degradation in spatial knowledge Acquisition when using automatic navigation systems". In S. Winter, M. Duckham, L. Kulik & B. Kuipers (eds). (2007). Spatial Information Theory. 8th International Conference, COSIT 2007. (pp. 238–254). Berlin: Springer-Verlag.
  • Erev, I., Shinovich, D., Schurr, A., & Hertwig, R. (2008). "On the effect of base rates in perception studies, and base rate neglect in judgment studies". In: H. Plessner, C Betsch and T. Betsch (Eds.). Intuition in Judgment and Decision Making. (pp. 135-148). LEA.
  • Erev, I., Haruvy, E. (in press). "Learning and the economics of small decisions". Invited chapter submitted to Kagel, J.H. and Roth, A.E. (Eds.), The Handbook of Experimental Economics. Princeton University Press.
  • Erev, I. and Grainer, B. (in press). On Psychology, Economics, and the Prediction of Human Behavior. Invited chapter submitted to Guillaume F. and Schotter A. (Eds.) The handbook on Methods of Modern Experimental Economics. Oxford University Press.

Books

  • Budescu, D., Erev, I. & Zwick, R. (1999), Games and Human Behavior: Essays in Honor of Amnon Rapoport. LEA.

 

 

Teaching

Thinking and decision-making (undergraduate and graduate)

Behavioral implications of game theory (graduate and MBA)

Cognitive psychology (undergraduate and graduate)

Introduction to psychology (undergraduate)

Experimental psychology (undergraduate)

Negotiation (MBA)

Behavioral statistics (undergraduate)

Research

Decisions from experience
• Descriptive models of choice behavior, and choice prediction competitions
• The economics of small decisions
The Laboratory of Behavioral Research

Contact Info

Room 405 Bloomfield Building
+972-4-829-4501