Submission deadline: July 15, 2022
The DAS Student Paper Award is given annually to the best decision analysis paper by a student author(s), as judged by an award selection committee.
For this award, decision analysis is defined as a prescriptive approach to provide insight for decision-making based on axioms that are logically consistent with the axioms of von Neumann and Morgenstern and of Savage. Key constructs of decision analysis are utility to quantify one's risk preferences and probability to quantify the state of one's knowledge.
The intent of the award is to recognize the best publication in decision analysis, by a student. This includes, but is not limited to, theoretical, methodological, and procedural contributions to decision analysis, descriptions of applications and experimental studies. Publications addressing behavioral aspects of decision-making are eligible if the relevance to the theory or practice of prescriptive decision analysis is clear. Nominated publications will be judged for significance, relevance, originality, and readability.
Students who did not complete their Ph.D. prior to May 1, 2021 are eligible for the 2022 competition.
The majority of work, including writing, must be that of the student, though faculty members or other mentors can be co-authors if appropriate. Papers need not be published; but published, peer-reviewed, papers will be given careful consideration. Unpublished manuscripts should be 30 pages or fewer (double spaced and 11-point font) and in the standard format of the Decision Analysis journal.
The award includes an honorarium of $500 and a plaque.
To be considered for this year's competition, please email both committee co-chairs, at the address given below, by the deadline of July 15, 2022 with your final submission of:
- An electronic version of your paper in PDF format, and
- A letter in PDF format from one faculty co-author (if any) articulating your role in writing this paper.
2022 INFORMS Decision Analysis Society (DAS) Student Paper Award Co-Chairs
Mehmet Ayvaci
Associate Professor, Information Systems
Jindal School of Management, University of Texas at Dallas
Email: mehmet.ayvaci@utdallas.edu
Saša Zorc
Assistant Professor, Quantitative Analysis
Darden School of Business, University of Virginia
Email: ZorcS@darden.virginia.edu
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Mehmet Ayvaci
Associate Professor
The University of Texas at Dallas
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