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Dr. Joseph G. Johnson, Director Department of Psychology Division of Brain and Cognitive Science Miami University Oxford, OH 45056 (513) 529-2475 
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| Research interests: | Judgment and decision making, mathematical and computational modeling of cognitive processes, dynamic systems, time perception, experimental methodology, parameter estimation and model fitting, individual differences |
| Current projects: | Measuring attention and information acquisition. In conjunction with Ana Franco-Watkins, I am interested in exploring the use of new technologies (i.e. eye-tracking) to reveal processes of attention and information use in deliberation. That is, rather than simply examining indvidual's overt decisions, I feel it is important to understand the underlying processes that give rise to these decisions. We are developing new metrics and analyses for considering such "process-tracing" data, as well as new methods for quantitative model comparison using process and RT data. |
| Motivation and decision making. This line of research, initiated by graduate student Daniel DeCaro, investigates the influence that various types of motivation have on deliberation and decision making. This project includes the development of a new psychometric scale to measure six distinct types of motivation, and an application of this scale to an experimental choice task. The results of this experiment will be used to incorporate motivational influences formally into models of decision making. | |
| Reference-dependent valuation. Perhaps the most popular descriptive theory of risky choice, prospect theory, is characterized by the notion that individuals use a reference point to evaluate outcomes. This reference point, often assumed to reflect the "status quo," suggests valuation is relative rather than absolute. In this collaborative effort with Dr. X.T. Wang, we propose that multiple reference points in fact determine valuation of outcomes. Specifically, in addition to the status quo, we propose that individuals simultaneously consider minimum requirements and goals. This theory makes strong testable predictions regarding valuation and choice, which we have formalized in a mathematical model and are testing empirically. | |
| Modes of thought. In many domains in psychology, a common (and usually controversial) supposition is that there are distinct and qualitatively different modes of thought; in cognitive psychology this suggests different modes of processing information, and decision making researchers have proposed "intuitive" and "analytic" dichotomies for arriving at a decision. We conjecture that a single information sampling model can more parsimoniously describe decision making behavior, and that behavior attributed to "intuitive" or "analytic" processes can arise from specific parameterization of this common model. | |
| Decision making in sports. We have a longstanding collaboration with Dr. Markus Raab, investigating various aspects of athletes' decision processes. This research has provided an applied setting for testing the theoretical models we have developed, including a model for how people generate options in real, dynamic situations, and how they select from among them. We have also developed methods for incorporating personality variables into formal models, and have detailed the relationship between learning styles and subsequent behavior. Currently, we are working on efforts that use athletes' dynamic streams of attention, as measured by eye-tracking, to predict their choices. | |
| Age and risk-taking. We have collaborated with various researchers in studying risk-taking by two guiding principles: (1) that risk-taking is domain specific, and (2) that risk-taking can be conceptualized in a cost-benefit framework. Current research extends our past work on risk taking to focus specifically on older adults, using experimental tasks and survey instruments. An application of this work studies the decisions of older adults to participate in clinical research varying in potential success and potential risk. | |
| Representative publications: | Raab, M., & Johnson, J. G. (2007). Expertise-based differences in search and option generation strategies. Journal of Experimental Psychology: Applied, 13, 158-170. |
| Raab, M., & Johnson, J. G. (2007). Implicit learning as a means to intuitive decision making in sports. In H. Plessner, C. Betsch, & T. Betsch (Eds.), A new look on intuition in judgment and decision making, 119-133. Mahwah, NJ: Lawrence Erlbaum | |
| Johnson, J. G., & Busemeyer, J. R. (2006). A unified computational modeling approach to decision making. In D. Fum, F. Del Missier, & A. Stocco (Eds.), Proceedings of the Seventh International Conference on Cognitive Modeling, 154-159. | |
| Hanoch, Y., Johnson, J. G., & Wilke, A. (2006). Domain specificity in experimental measures and participant recruitment: An application to risk-taking behavior. Psychological Science, 17, 300-304. | |
| Busemeyer, J. R., Jessup, R. K., Johnson, J. G., & Townsend, J. T. (2006). Building bridges between neural models and complex decision making behavior. Neural Networks, 19, 1047-1058. | |
| Busemeyer, J. R., Johnson, J. G., & Jessup, R. K. (2006). Preferences constructed from dynamic micro-processing mechanisms. In P. Slovic & S. Lichtenstein (Eds.), The Construction of Preference. | |
| Johnson, J. G. (2006). Cognitive modeling of decision making in sports. Psychology of Sport and Exercise, 7, 631-652. | |
| Johnson, J. G., & Busemeyer, J. R. (2005). A dynamic, stochastic, computational model of preference reversal phenomena. Psychological Review, 112, 841-861. | |
| Johnson, J. G. & Busemeyer, J. R. (2005). Rule-based Decision Field Theory: A dynamic computational model of transitions among decision-making strategies. In Betsch, T., & Haberstroh, S. (Eds.), The Routines of Decision Making, 3-20. Mahwah, NJ: Lawrence Erlbaum Associates. | |
| Busemeyer, J. R. & Johnson, J. G. (2004). Computational models of decision making. In D. Koehler & N. Harvey (Eds.), Blackwell Handbook of Judgment and Decision Making. Oxford, UK: Blackwell Publishing Co. 133-154. | |
| Raab, M. & Johnson, J. G. (2004). Individual differences of action-orientation for risk-taking in sports. Research Quarterly for Exercise and Sport, 75(3), 326-336. | |
| Johnson, J. G., Wilke, A. & Weber, E. U. (2004). Beyond a trait view of risk-taking: A domain-specific scale measuring risk perceptions, expected benefits, and perceived-risk attitude in German-speaking populations. Polish Psychological Bulletin, 35(3), 153-163. | |
| Johnson, J. G. & Raab, M. (2003). Take the first: Option generation and resulting choices. Organizational Behavior and Human Decision Processes, 91(2), 215-229. | |
| Johnson, J. G. (2003). Incorporating motivation, individual differences, and other psychological variables in utility-based choice models. Utility Theory and Applications. Dipartimento di Matematica applicata Bruno de Finetti, Universitą di Trieste, Italy. 123-142. | |
| Johnson, J. G. & Busemeyer, J. R. (2001). Multiple-stage decision-making: The effect of planning horizon length on dynamic consistency. Theory and Decision, 51(2-4), 217-246. | |
| Links of interest: | Society for Judgment and Decision Making |
| Society for Mathematical Psychology | |
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