Journal of Dynamic Decision Making


The Journal of Dynamic Decision Making (JDDM) offers a peer-reviewed interdisciplinary open-access publication outlet for research on cognitive and behavioral processes involved in dynamic decision making. It is free of charge for both authors and readers. Contributions are expected primarily from the field of psychology but also from other disciplines like economics, philosophy, cognitive science, or system dynamics. Please refer to our Focus and Scope as well as our Author Guidelines, if you are interested in making a contribution to JDDM. For further information you may also refer to our Editorial Statement.

 

Recent Articles

 
Michael Engelhart, Joachim Funke, Sebastian Sager
The question “How can humans learn efficiently to make decisions in a complex, dynamic, and uncertain environment” is still a very open question. We investigate what effects arise when feedback is given in a computer-simulated microworld that is controlled by participants. This has a direct impact on training simulators that are already in standard use in many professions, e.g., for flight simulators for pilots, and a potential impact on a better understanding of human decision making in general. ... (more)
JDDM doi: 10.11588/jddm.2017.1.34608
Alexander Nicolai Wendt
Empirical methods of self-description, think aloud protocols and introspection have been extensively criticized or neglected in behaviorist and cognitivist psychology. Their methodological value has been fundamentally questioned since there apparently is no suficient proof for their validity. However, the major arguments against self-description can be critically reviewed by theoretical psychology. This way, these methods’ empirical value can be redeemed. Furthermore, self-descriptive methods can be updated by the use of contemporary media technology. In order to support the promising perspectives for future empirical research ... (more)
JDDM doi: 10.11588/jddm.2017.1.33724
Natassia Goode, Jens F Beckmann
Many situations require people to acquire knowledge about, and learn how to control, complex dynamic systems of inter-connected variables. Numerous studies have found that most problem solvers are unable to acquire complete knowledge of the underlying structure of a system through an unguided exploration of the system variables; additional instruction or guidance is required. This paper examines whether providing structural information following an unguided exploration also improves control performance, and the extent to which any improvements are moderated by problem solvers’ fluid intelligence. ... (more)
JDDM doi: 10.11588/jddm.2016.1.33346
Miriam Sophia Rohe, Joachim Funke, Maja Storch, Julia Weber
In this paper, we bring together research on complex problem solving with that on motivational psychology about goal setting. Complex problems require motivational effort because of their inherent difficulties. Goal Setting Theory has shown with simple tasks that high, specific performance goals lead to better performance outcome than do-your-best goals. However, in complex tasks, learning goals have proven more effective than performance goals. ... (more)
JDDM doi: 10.11588/jddm.2016.1.28510
Cleotilde Gonzalez, Varun Dutt
Before making a choice we often search and explore the options available. For example, we try clothes on before selecting the one to buy and we search for career options before deciding a career to pursue. Although the exploration process, where one is free to sample available options is pervasive, we know little about how and why humans explore an environment before making choices. This research contributes to the clarification of some of the phenomena that describe how people perform search during free sampling ... (more)
JDDM doi: 10.11588/jddm.2016.1.29308

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