From the Editor: Belated Recognition for the 2021 Clemen–Kleinmuntz Decision Analysis Best Paper Award Winner and Finalist

Abstract

Free AccessAboutSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked InEmail Go to SectionFree Access HomeDecision AnalysisAhead of Print From the Editor: Belated Recognition for the 2021 Clemen–Kleinmuntz Decision Analysis Best Paper Award Winner and FinalistVicki M. BierVicki M. BierPublished Online:9 May 2023https://doi.org/10.1287/deca.2023.0477The winning paper for 2021 was “Friction and Decision Rules in Portfolio Decision Analysis,” by Gary J. Summers (Summers 2021). To put this paper in context, the practice of decision analysis typically involves identifying performance objectives and managerial preferences, quantifying uncertainties, and then using them as inputs to assess alternatives. An exhaustive theory-driven literature in decision analysis provides foundations for this practice, assuming that objectives, preferences, and uncertainties are well understood and available to quantify. The award-winning paper by Summers highlights that this quantification may not be accurate in practice, leading to “friction” in decision analysis models. This friction can systematically lead to a loss in decision quality. The article provides examples from multiple domains, and new analysis to illustrate this friction. As such, the article underscores the importance of calibrating the inputs to decision analysis models. It promises to be a springboard for future research on understanding the causes of friction in decision analysis models, its implications, and mitigation methods.I congratulate Gary J. Summers on this excellent paper and am especially glad that Decision Analysis was able to help a full-time practitioner bring forth important and insightful ideas in a manner that is compelling to both academics and practitioners.The finalist for 2021 was “Preference-Approval Structures in Group Decision Making: Axiomatic Distance and Aggregation,” by Yucheng Dong, Yao Li, Ying He, and Xia Chen (Dong et al. 2021). Although decision analysis commonly focuses on decision making by an individual or a group acting as an individual, this paper focuses on group decision making. It combines two popular approaches for aggregating individual preferences, ranked voting and approval voting, which have compensating strengths and weaknesses. Ranked voting leverages the preference ranking central to the decision analysis approach, but is subject to strategic manipulation (where individuals misrepresent their preferences); approval voting is immune to strategic manipulation, but does not provide the complete ranking required by decision analysis. The article shows that combining them leads to superior performance. Future empirical research and practice is likely to significantly benefit from the rigorous foundational treatment provided by this article.Congratulations to Dong et al. for this excellent and pragmatic contribution to the challenging topic of group decision making.Thanks also to committee members Saurabh Bansal (Pennsylvania State University) and Robert Bordley (University of Michigan) for cochairing the award committee for 2021, and for providing extensive input to the paper descriptions given above. My sincere apologies for this belated recognition to all.ReferencesDong Y, Li Y, He Y, Chen X (2021) Preference–approval structures in group decision making: Axiomatic distance and aggregation. Decision Anal. 18(4):273–295. https://doi.org/10.1287/deca.2021.0430.Link, Google ScholarSummers GJ (2021) Friction and decision rules in portfolio decision analysis. Decision Anal. 18(2):101–120. https://doi.org/10.1287/deca.2020.0421.Link, Google Scholar Previous Back to Top Next FiguresReferencesRelatedInformation Articles In Advance Article Information Metrics Information Published Online:May 09, 2023 Copyright © 2023, INFORMSCite asVicki M. Bier (2023) From the Editor: Belated Recognition for the 2021 Clemen–Kleinmuntz Decision Analysis Best Paper Award Winner and Finalist. Decision Analysis 0(0). https://doi.org/10.1287/deca.2023.0477 PDF download