Free AccessAboutSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked InEmail Go to SectionFree Access HomeDecision AnalysisAhead of Print From the Editor and Chair of the Award Committee: 2022 Clemen–Kleinmuntz Decision Analysis Best Paper AwardVicki M. Bier, Gilberto Montibeller Vicki M. Bier, Gilberto Montibeller Published Online:9 May 2023https://doi.org/10.1287/deca.2023.0476In this issue, we present the 2022 Clemen–Kleinmuntz Decision Analysis Best Paper Award. The author of the best paper will receive a $2,000 prize. This prize is supported by an endowment established by the Kleinmuntz Family Foundation and administered by INFORMS. The goal of the Best Paper Award is to draw attention to the high quality of work published in the journal and encourage the journal’s continuing growth and success.All papers published during 2022 in the journal were assessed against three main criteria: The paper is foundationally based on Decision Analysis; the paper makes an important contribution to theory and/or practice; and the paper is broadly interesting and influential to a wide portion of the Decision Analysis community. We wish to thank Kara Morgan (of Quant Policy Strategies) and Jason Merrick (of Virginia Commonwealth University), who were members of the award committee, chaired by Gilberto Montibeller (of Loughborough University and the University of Southern California).We are pleased to announce that the winning paper for 2022 is “Cutoff Threshold Decisions for Classification Algorithms with Risk Aversion,” by Andrea C. Hupman (Decision Analysis, vol. 19, no. 1, 2022, pp. 63–78; Hupman 2022). A critical decision in the design of machine learning algorithms for classification is the cutoff threshold for the classes. Andrea has proposed innovative analytic results for the selection of an optimal cutoff threshold for a classification algorithm that is used to inform a two-action decision in the cases of risk aversion and risk neutrality. The results provide insight into how the optimal cutoff thresholds relate to the associated costs and the sensitivity and specificity of the algorithm for different types of risk attitudes.The winning paper highlights the important contribution that Decision Analysis can make to machine learning in modeling the kinds of judgments that often are required in such algorithms, employing a clear and explicit normative framework. We congratulate Andrea Hupman for the excellent paper and encourage our community to develop further research on the interface between artificial intelligence and Decision Analysis.Two papers were finalists for the Clemen–Kleinmuntz Decision Analysis Best Paper Award. The first finalist paper was “Modeling Ethical and Operational Preferences in Automated Driving Systems,” by William N. Caballero, Roi Naveiro, and David Ríos Insua (Decision Analysis, vol. 19, no. 1, 2022, pp. 21–43; Caballero et al. 2022). The paper deals with an important development in transportation technology: automated driving systems. The use of these systems, given their revolutionary nature, brings novel challenges related to both operational and ethical concerns that are relevant to numerous stakeholders (e.g., governments, manufacturers, and passengers). When considering any such problem, the decision-making calculus of the automated driving system is always a central component.In the paper, the authors propose a general decision-analytic framework tailorable to distinctive stakeholders involved in the design, regulation, and use of an automated driving system. They developed and validated a generic tree of management objectives for the system, explored potential attributes for their measurement, and provided multiattribute utility functions for implementation. Furthermore, they explored how each of the components can be tailored following the stakeholder’s desired ethical perspective and tested it via a simulated environment. We congratulate William N. Caballero, Roi Naveiro, and David Ríos Insua for the application of decision analysis to this important topic in transportation science.The second finalist paper for the Clemen–Kleinmuntz Decision Analysis Best Paper Award was “Model Complexity and Accuracy: A COVID-19 Case Study,” by Colin Small and J. Eric Bickel (Decision Analysis, vol. 19, no. 4, pp. 354–383; Small and Bickel 2022). There has been intensive modeling effort in epidemiology during the COVID-19 pandemic, with the development of several sophisticated and large-scale predictive models, in the belief that higher-fidelity models are more accurate than simpler ones. This thoughtful paper analyzed the performance of models that submitted COVID-19 forecasts to the U.S. Centers for Disease Control and Prevention and evaluated them against a simple two-equation model specified using simple linear regression. They found that their simple model was comparable in accuracy to highly publicized models and had among the best-calibrated forecasts.This research result may be surprising, given the complexity of many COVID-19 models and their support by large forecasting teams. However, the result is consistent with the body of research that suggests that simple models often perform well in a variety of settings. Even more importantly, the authors emphasize how a decision-making focus can help in developing predictive models that are requisite in supporting policymakers dealing with emerging health threats. The paper is an excellent example of research in Health Decision Analysis and was part of the special issue on this topic in the December 2022 issue of Decision Analysis (Long et al. 2022). Dillon et al. (2023) also cite Small and Bickel (2022) in regard to the potential and challenges of Decision Analysis in supporting policymaking during future pandemics. We congratulate Colin Small and J. Eric Bickel for the creative and thought-provoking paper for health security decision making.Concluding this letter, we would like to thank all the authors that published papers in 2022 in the journal and were considered for the award. We encourage our Decision Analysis community to continue submitting high-quality manuscripts that can be strong contenders for the Clemen–Kleinmuntz Decision Analysis Best Paper Award in future years.ReferencesCaballero WN, Naveiro R, Insua DR (2022) Modeling ethical and operational preferences in automated driving systems. Decision Anal. 19(1):21–43.Link, Google ScholarDillon RL, Bier VM, John, RS, Althenayyan A (2023) Closing the gap between decision analysis and policy analysts before the next pandemic. Decision Anal., ePub ahead of print February 28, https://doi.org/10.1287/deca.2023.0468.Link, Google ScholarHupman AC (2022) Cutoff threshold decisions for classification algorithms with risk aversion. Decision Anal. 19(1):63–78.Link, Google ScholarLong EF, Montibeller G, Zhuang J (2022) Health decision analysis: Evolution, trends, and emerging topics. Decision Anal. 19(4):255–264.Link, Google ScholarSmall C, Bickel JE (2022) Model complexity and accuracy: A COVID-19 case study. Decision Anal. 19(4):354–383.Link, Google Scholar Back to Top Next FiguresReferencesRelatedInformation Articles In Advance Article Information Metrics Information Published Online:May 09, 2023 Copyright © 2023, INFORMSCite asVicki M. Bier, Gilberto Montibeller (2023) From the Editor and Chair of the Award Committee: 2022 Clemen–Kleinmuntz Decision Analysis Best Paper Award. Decision Analysis 0(0). https://doi.org/10.1287/deca.2023.0476 PDF download