Webinars

DAS/SDP Joint Seminar

Date: December 13th, 12pm EST

Speaker: Ali Abbas,

Title: Ethical Decision Quality: Building an Ethical Decision Culture

Date: January 24th, 12pm EST 

Speaker: Michael Lee (Irvine) 

TITLE: Using decision-making models to improve the wisdom of the crowd 

DAS Seminar

Date: November, TBD

Speakers: Robert Meyer and Erwann Michel-Kerjan 

Moderator: Robin Dillon-Merrill  

Title: Why We Under-prepare for Disasters: The Enduring Legacy of Howard Kunreuther  



A Replication Study of Operations Management Experiments in Management Science

Event Info

icon_calendar.jpgThursday, September 28th, 2023 
icon_clock.jpg12:00 PM EST
icon_stopwatch.jpgDuration: 1 hour

Speaker


 

Blair Flicker is an assistant professor of management science at the Moore School. He holds a doctoral degree in management science and an MBA from the University of Texas, Dallas. Flicker’s research is focused on understanding how to best integrate human and algorithmic decision making. Specific interests include behavioral operations management, judgmental forecasting, human-computer interaction and machine learning.

Kyle B. Hyndman is a professor at the Naveen Jindal School of Management at the University of Texas at Dallas. His main research interests are behavioural and experimental economics, though he has done research in industrial organisation, auctions, bargaining and behavioural operations management.

Abstract: Over the last two decades, researchers in operations management have increasingly leveraged laboratory experiments to identify key behavioral insights. These experiments inform behavioral theories of operations management, impacting domains including inventory, supply chain management, queuing, forecasting, and sourcing. Yet, until now, the replicability of most behavioral insights from these laboratory experiments has been untested. We remedy this with the first large-scale replication study in operations management. With the input of the wider operations management community, we identify 10 prominent experimental operations management papers published in Management Science, which span a variety of domains, to be the focus of our replication effort. For each paper, we conduct a high-powered replication study of the main results across multiple locations using original materials (when available and suitable). In addition, our study tests replicability in multiple modalities (in-person and online) due to laboratory closures during the COVID-19 pandemic. Our replication study contributes new knowledge about the robustness of several key behavioral theories in operations management and contributes more broadly to efforts in the operations management field to improve research transparency and reliability.
Between-prospects comparisons: Regret Theory and Probability Dominance

Event Info

icon_calendar.jpgJune 16, 2023 
icon_clock.jpg12:00 PM EST
icon_stopwatch.jpgDuration: 1 hour
Watch replay here.

Speaker

Enrico Diecidue is a Professor of Decision Sciences at INSEAD. In 1996 he obtained his degree in Economics, with a specialisation in Mathematical Economics, from Bocconi University, Italy. He then joined the CentER (Center for Economic Research), Tilburg University, the Netherlands, where he received his PhD in 2001.

His research focuses on decision making under uncertainty. He is interested in the role of regret, aspiration levels, and time in individual decisions. His current research is also addressing the role of groups in complex decisions. Enrico’s research has appeared in leading journals including Decision AnalysisInternational Economic ReviewJournal of Economic TheoryJournal of Mathematical PsychologyJournal of Risk and UncertaintyManagement ScienceMathematical Social SciencesTheory and Decision. He serves on the Editorial Board of Decision and of Journal of Risk and Uncertainty, and is an Associate Editor for Decision Analysis and for Management Science.

Enrico Diecidue is directing the 
International Directors Programme and is director for the Strategic Decision Making for Leaders Program Strategic Decision Making for Leaders Program.

Abstract: The most popular models of decision under uncertainty such as expected utility (EU, von Neumann and Morgenstern 1947), and cumulative prospect theory (CPT; Tversky and Kahneman 1992) – assume that the decision maker evaluates each prospect separately and then chooses the prospect with the highest EU (or the highest CPT value). Regret theory (Bell 1982; Fishburn 1982; Loomes and Sugden 1982) is a bold exception in that the forgone alternative does influence the decision maker; hence this theory allows also for between-prospects interactions.

 

In this talk: I present a review of some of the advancements in regret theory (behavioral foundation, quantitative measurement, and empirical performance); I then introduce Probability Dominance. This is an heuristic (choosing the alternative that maximizes the probability of being ahead) that also captures the effects of the forgone alternative, yet considers between-prospects interactions in a way that differs from regret theory. The final part of the talk focuses on evaluating the empirical performance of probability dominance relative to EU, CPT, and regret theory.

 SDP-DAS Webinar-The Multivariate Metalog Distributions: An Introduction With Application to Strategic Decision-Making in Golf

Event Info

icon_calendar.jpgMay 17, 2023 
icon_clock.jpg8:00 AM PT, 11:00 AM ET
icon_stopwatch.jpgDuration: 1 hour

Link here to the paper mentioned by Tom Keelin during the webinar. 

Speaker

TOM KEELIN | Managing Partner, Keelin Reeds Partners
Tom Keelin is a founder and Managing Partner of Keelin Reeds Partners, a firm that provides strategy, decision analysis, and education services. Previously, over two decades with the Strategic Decisions Group (SDG), Tom co-developed the definition of "decision quality”, led dozens of strategy engagements for leading companies, founded SDG’s life sciences practice, and served as Board Member and Worldwide Managing Director. Later, Tom invented the metalog distributions. Tom is a Fellow and Board Member of the Society of Decision Professionals and a founder and Director of the Decision Education Foundation. He holds three Stanford degrees: BS in Economics and MS and PhD in Engineering-Economic Systems. 
 
Tom has also been an avid amateur golfer since childhood. He was Captain of the Stanford Golf Team as an undergraduate and has maintained a longstanding interest in golf strategy.
Abstract: Continuous multivariate probability distributions are highly relevant to many important decisions, such as how to best allocate resources across a portfolio of correlated financial or R&D assets; which of multiple oil fields to develop; and choice of aim point in sports, military, or space-exploration applications. Traditionally, however, many of us have avoided such distributions because they have been impractical to parameterize, validate, and/or simulate. Here we introduce new practical methods and apply them in a new application area: strategic decision-making in golf.

Because of their desirable properties, quantile-parameterized distributions (QPDs), which include the metalogs, are being used increasingly instead of traditional distributions (normal, student-t, beta, etc.) for practical applications of probability. Application areas include not only decision analysis but diverse fields ranging from environmental conservation to astrophysics.
The metalog distributions and other QPDs give rise to improved multivariate methods -- enabling such distributions to be more accurately specified, easier to elicit, easier to determine from data, easier to validate, and easier to simulate. We illustrate these features with an easy-to-understand practical application: in golf, choosing the best aimpoint can make the difference between winning and losing. 
SDP-DAS Webinar - Thinking about Process, Elicitation and Modelling in Decision Analysis 

Event Info

icon_calendar.jpgApril 26, 2023 
icon_clock.jpg8:00 AM PT, 11:00 AM ET
icon_stopwatch.jpgDuration: 1 hour
Register  here

Listen to replay here

Speaker

Simon French joined the Department of Statistics in August 2011. He moved here from Manchester Business School, where he was Professor of Information and Decision Sciences to take up the Directorship of RISCU, the department's Risk Initiative and Statistical Consultancy Unit. At the beginning of 2017, he handed over the Directorship to Martine Barons and at the same time RISCU was renamed, the Applied Statistics and Risk Unit (AS&RU), of which he remains a member.

Simon's research career began in Bayesian statistics and he was one of the first to apply hierarchical modelling, particularly in the domain of protein crystallography. Nowadays he is better known for his work on decision making, which began with his early work on decision theory and saw several papers on the mathematical foundations of rational decision making and the publication of his 1986 text on Decision Theory. That strand of work still continues in the background: e.g. his book on Statistical Decision Theory, co-authored with David Rios Insua. However, his work has generally become more applied; looking at ways of supporting real decision makers facing major strategic and risk issues.

In 2017 Simon was awarded the Ramsey Medal by the INFORMS Decision Analysis Society for his research in and applications of risk and decision analysis.

Abstract: Decision analysis is much more than maximising an expected utility or value function: we all know that. Nonetheless, we may not reflect as much as we should on the wider, more qualitative processes that surround the analytical and quantitative steps. For instance:

• How and where are different types of knowledge drawn into the process?
• How do we work with and elicit not just numerical subjective probabilities, values and utilities, but softer more structural issues such as the context, models, available data, and appropriate computational methods?
• How do we recognise and address all the uncertainties that relate to a decision and its context?
• How do we report and archive details so that necessary information is available for audit?
• How do we recognise and reflect the wider political and Political processes surrounding the decision?

In discussing these and related questions, I will draw on several other disciplines and schools of thought than usually associated with (Bayesian) decision analysis. It is through the softer, qualitative process steps that we recognise, address and communicate those issues and uncertainties that are not modelled in the quantitative decision analysis, but still need communicating to the decision-makers so that they have a full understanding of the issues when they take their decision.

Multi-Multi-Attribute Utility: the Prettiest Axiomatization of Expected Utility You ever Saw & the Million-$ Question: Row-First or Column-First Aggregation?  

Event Info

icon_calendar.jpgApril 14, 2023 
icon_clock.jpg12:00 PM ET  
icon_stopwatch.jpgDuration: 1 hour
Register here

Speaker

Peter Wakker is professor of decision under uncertainty at Behavioral Econ. of Erasmus School of Econ. (ESE). He works in behavioral economics and on risk/ambiguity. He has published in leading journals in economics, business, medicine, psychology, statistics, and mathematics. He was the best-publishing Dutch economist in 1994, 1998, 2003, and 2007, and collaborated with three Nobel-prize winners. He is the 157th most influential economist, and the 20463th most influential researcher over all disciplines (Ioannidis, Boyack, & Baas 2020 Table 6). Köbberling & Wakker (2005) is among the 50 most influential papers in Journal of Economic Theory (Shell, Borgers, & Pavan (2020). Wakker received a Medical Decision Making Career Achievement Award (2007), the Frank P. Ramsey Medal (2013; highest award of INFORMS Decision Analysis Society), and an Honorary doctorate in economics (University of St. Gallen 2016). He frequently gives advices on insurance in the media. He is a director of the research group Behavioral Economics. Personal website.

Abstract:

Keeney & Raiffa’s (1976) multiattribute utility aggregates U(X1,…,Xn). Here Xj can refer to persons (welfare), timepoints (time preference), events (decision under uncertainty), commodities (consumer theory), etc. In applications one often has to aggregate over two or more kinds of attributes: risk & time, persons & commodities, etc. In classical models with complete separability the order of aggregation then does not matter. This gives our first result: the prettiest axiomatization of discounted expected utility you ever saw. Paradox 1: this is too simple to be true?

Modern behavioral generalizations relax complete separability (= sure-thing principle = time separability etc.) but maintain weak separability (= stochastic dominance = Pareto optimality etc.). Paradox 2: for two or more kinds of attributes this is just impossible.

A century-old forgotten theorem from macro-economics resolves our two modern paradoxes: Nataf (1948). He provided diagnoses and remedies for many ongoing debates, on ex-ante/ex-post fairness, incentive compatibility of random incentives, hedging in ambiguity measurements, equity in Harsanyi’s veil of ignorance, monotonicity in Anscombe-Aumann’s framework, etc. They all amount to the same million-$ question: “row-first or column-first aggregation?” Nataf resolved! 

CO-AUTHORS: Chen Li & Kirsten Rohde

 

Watch replay here

SDP/DAS joint webinar
Decision Making for Enhanced Health Security

Event Info

icon_calendar.jpgFebruary 15, 2023 
icon_clock.jpg11:00 AM ET  
icon_stopwatch.jpgDuration: 1 hour

Watch replay HERE

Speaker

Gilberto Montibeller is a Professor of Management Science and Director of Executive Education at Loughborough University (UK). He is also a Senior Research Fellow at the Center for Risk and Economic Analysis of Threats and Emergencies at the University of Southern California (USA), an Associate Editor of the INFORMS Decision Analysis Journal, and a member of the SDP Executive Board. Dr. Montibeller is an expert in Behavioral Decision Analysis and Multi-Criteria Decision Analysis with an application focus on Health Decision Analysis and Health Operations. He provides decision consulting for private and public organizations, such as WHO, FAO, Roche, Novartis, DEFRA, the UK Department of Health, among others. In his spare time, he enjoys riding his motorbike along beautiful European roads.

SUMMARY:
Emerging and re-emerging health threats have always been a central theme of our history; the recent COVID-19 pandemic being the latest of these unfortunate events and certainly not the last. The pandemic once again reminded us of the importance of reasoned decision making and responsible leadership for health security. (In fact, did you know the very first decision analysis was conducted on a health security decision problem in the 18th century?)
In this talk I argue that decision analysis has much to contribute to this important category of decision problems, which has specific challenges that must be addressed to support high-quality decisions. I propose a framework for supporting health security decision making that can address competing priorities and key uncertainties, mitigate critical risks in a cost-effective manner and maximize societal value.
Join us to learn about the fascinating true story of the first health security decision analysis and to jointly reflect on how we can improve the decision quality of private and public organizations which are confronted by health threats. Together we, the decision professionals, can help to enhance the health security of our societies.

MODERATOR
EYAS RADDAD is a seasoned drug discovery and development researcher, strategist, and innovator. Since he joined Eli Lilly and Company in 2001, he applied sophisticated data analytics and strategic frameworks to improve decision making in drug discovery and development process.
Over his career, he implemented Decision Analytic techniques in drug development applications. In 2017, Eyas established and led Research Decision Analytics function in Lilly Research Laboratories, with a mission that includes portfolio management, decision consulting and decision education. More recently, he has been serving a COO of multiple early development programs at Eli Lilly, as well as portfolio management role in Diabetes Research.

DAS presents - Frank P. Ramsey Medal winner Professor Ahti Salo, from Aalto University

Addressing Uncertainties through Advances in Scenario and Decision Analysis

Event Info

icon_calendar.jpgFebruary 10, 2023 
icon_clock.jpg12:00 PM ET  
icon_stopwatch.jpgDuration: 1 hour

Speaker

Ahti Salo is a Professor of Systems Analysis at Aalto University, Finland. He received his MSc and DSc degrees in systems and operations research from the Helsinki University of Technology in 1987 and 1992, respectively. He has worked at the Nokia Research Center and the Technical Research Centre of Finland, and he has been a Visiting Professor at the London Business School, Université Paris-Dauphine, and the University of Vienna. His research interests include topics in decision analysis, risk management and foresight methodologies, with applications in energy, healthcare, and safety-critical systems. He has supervised 190 MSc Theses and 27 Doctoral Dissertations, and published more than 180 scientific publications, including 100 refereed papers in leading international journals.

Abstract: In this talk, I first summarize experiences based on my role as a member of the COVID-19 Science Panel which was appointed by the Prime Minister’s Office in Finland to provide science-based support for managing the pandemic. Second, I discuss uses of scenario analysis in setting the stage for strategic decisions, noting that it can be beneficial to employ quantitative approaches to build scenarios that are diverse and comprehensive. Third, I present advances in solving influence diagrams for problems in which the usual ‘no-forgetting’ assumption does not hold or in which cross-cutting logical, resource and risk constraints must be accounted for. Such problems can be solved through Decision Programming (Salo et al., Eur J Oper Res 299:2, 2022) by building the equivalent mixed-integer linear programming formulation which can be solved through standard solvers. 

Listen to replay here

Innovations in the Science and Practice of Decision Analysis: The Role of Management Science

Event Info

icon_calendar.jpgApril 6, 2022
icon_clock.jpg12 PM ET  
icon_stopwatch.jpgDuration: 1 hour

Speaker

johannes

James S. Dyer is the Fondren Foundation Centennial Chair in Business in the Department of Information, Risk, and Operations Management at the McCombs School of Business at The University of Texas at Austin. His research and teaching interests include risk management, multiple criteria decision making, and capital budgeting. Dyer is the 2002 winner of the Frank P. Ramsey Medal for distinguished contributions in decision analysis.

johannes

James E. Smith is the Jack Byrne Distinguished Professor in Decision Science at the Tuck School of Business at Dartmouth College. His research and teaching interests include decision analysis and operations research, particularly related to dynamic decisions and dynamic programming. Smith is the 2008 winner of the Frank P. Ramsey Medal for distinguished contributions in decision analysis.

In this talk, we reflect on research in decision analysis that has appeared in Management Science and its impact on decision analysis practice and applications. We consider professional applications of decision analysis in business and government settings as well as everyday conversational applications. This is a reprise of a talk given in May 2019 at the Conference in celebration of the 65th Anniversary of Management Science. The corresponding paper (see link below) was published in the September 2021 issue of Management Science.

Listen to replay here

Slides from presentation 
Innovations in the Science and Practice of Decision Analysis: The Role of Management Science

NUDGE YOURSELF TO MAKE BETTER DECISIONS: Developing the Necessary Foundation to Make A Quality Decision

Event Info

icon_calendar.jpgMarch 16, 2022
icon_clock.jpg12 PM ET  
icon_stopwatch.jpgDuration: 1 hour

Speaker

johannes

Johannes Siebert teaches Decision Sciences and Behavioral Economics at MCI | THE ENTREPREUNRIAL SCHOOL®, Innsbruck, Austria. His research objective is to contribute to better informed decision-making of individuals and organizations.

He has published papers in leading international journals such as Operations Research and European Journal of Operational Research. Johannes also works as a business consultant for both public and private organizations in the US and Europe. Three times, he was acknowledged as a finalist in the practice award of the Decision Analysis Society (INFORMS). More details can be found on his personal website JohannesSiebert.com.



The only way that you can purposefully influence anything in your life or business is by your decisions. Ralph Keeney and Johannes Siebert provide practical concepts and useful procedures to appropriately structure any decision that you want to face. This structure guides you to make some decisions worthy of thought directly and indicates the information needed to resolve more complex decisions. This empowers you to make better decisions and improve your life.

Followed by a PANEL DISCUSSION with Ralph Keeney
Ralph L. Keeney is a consultant on decision making and a speaker and author on making smart decisions. His main professional interest is helping individuals, organizations, and governments make smarter decisions.

Previously, he has been a professor at MIT, the University of Southern California, and Duke University and created and managed the decision and risk analysis group at a major consulting firm. He is a member of the U.S. National Academy of Engineering and an author of several books, including Give Yourself a Nudge, which is directly relevant to the seminar.

MODERATOR
Gilberto Montibeller
is a Professor of Management Science and Director of Executive Education at Loughborough University (England) and a Visiting Senior Research Fellow at the University of Southern California. He is an expert on multi-criteria decision analysis and behavioral decision analysis. Dr. Montibeller has provided decision analysis consultancy to both private and public organizations in the USA, Britain, Continental Europe, and South America. He has published widely in decision science journals and is Associate Editor of the Informs Decision Analysis journal.

Register here

Decision Analysis for Diversity Equity and Inclusion

Event Info

icon_calendar.jpgMarch 3, 2022
icon_clock.jpg10:30 ET  
icon_stopwatch.jpgDuration: 1 hour

Speaker

DeVries__002_.jpg

Catherine E. De Vries is a professor of political science at Bocconi University, a Research Associate at the Dondena Centre for Research on Social Dynamics and Public Policy, the CLEAN Unit for the Economic Analysis of Crime of the BAFFI-CAREFIN research center and the Bocconi COVID crisis lab. Catherine's work examines the key challenges facing the European continent today, such as Euroscepticism, political fragmentation, migration and corruption. Her my current project examines the conditions under which economic hardship affects support for socially conservative political agendas. This research project (LOSS) is funded through a Consolidator grant by the European Research Council.

Her first book Euroscepticism and the Future of European integration (Oxford University Press) received the European Union Studies Association Best Book in EU Studies Award, and was listed in the Financial Times top-5 books to read about Europe’s future. Her second book Political Entrepreneurs: The Rise of Challenger Parties in Europe, co-authored with Sara Hobolt (LSE), was published with Princeton University Press in 2020. It was featured in the Washington Post Monkey Cage Blog and Politico.

Next to books, Catherine has published numerous articles on topics spanning the fields of political behaviour, comparative European politics and political economy in journals including the American Political Science Review, Annual Review of Political Science, the Journal of Politics and International Organization. Together with Seth Jolly (Syracuse), Catherine hosts the European Politics Online Workshop: www.europw.com

For my societal impact, Catherine was selected a Young Global Leader in the World Economic Forum in 2013. In 2014, She was awarded the Emerging Scholar Award from the Elections, Voting Behavior and Public Opinion Section of the American Political Science Association. For more information see: www.catherinedevries.eu

The values of Diversity, Equity and Inclusion play a central role in academia and in society broadly. In December 2021, the Decision Analysis Society of INFORMS formed a permanent Diversity, Equity and Inclusion (DEI) Committee. The DEI Committee will champion the Diversity, Equity and Inclusion values through explorations on: 1) how to actively promote initiatives that afford an equal playing field for people from historically marginalized groups? 2) how to enhance cultural competence for DEI values to ensure equitable access to society opportunities? We invite all INFORMS community to join us  to learn from internationally renowned experts Catherine De Vries, Professor of Political Science at Bocconi University, Anahita Khojandi (University of Tennessee) and Susan Martonosi (Harvey Mudd College). INFORMS DEI Representatives and DAS-DEI committee members Allison Reilly (University of Maryland), Andrea Hupman (University of Missouri), Gül Okudan Kremer (Iowa State University), and Jun Zhuang (University of New York) will also partake as panelists in the session illustrating DEI values, and the INFORMS viewpoint and the first initiatives of the DAS.  

Listen to replay here

Event Info

icon_calendar.jpgJanuary 27, 2022
icon_clock.jpg12pm ET  
icon_stopwatch.jpgDuration: 1 hour

Speaker

Professor Yael Grushka-Cockayne's research and teaching activities focus on data science, forecasting, project management and behavioral decision-making. Her research is published in numerous academic and professional journals, and she is a regular speaker at international conferences in the areas of decision analysis, project management and management science. She is also an award-winning teacher, winning the Darden Morton Leadership Faculty Award in 2011, the University of Virginia's Mead-Colley Award in 2012 and the Darden Outstanding Faculty Award and Faculty Diversity Award in 2013. In 2015, she won the University of Virginia All University Teaching Award. Grushka-Cockayne teaches the core "Decision Analysis" course, an elective she designed on project management and an elective on data science. She is the leader of the open enrollment courses "Project Management for Executives" and "The Women's Leadership Program."

Before starting her academic career, she worked in San Francisco as a marketing director of an Israeli ERP company. As an expert in the areas of project management, she has served as a consultant to international firms in the aerospace and pharma industries. She is a UVA Excellence in Diversity fellow and a member of INFORMS, the Decision Analysis Society, the Operational Research Society and the Project Management Institute (PMI). She is an associate editor at Management Science and Operation Research and the secretary/treasurer of the INFORMS Decision Analysis Society.

In 2014, Grushka-Cockayne was named one of "21 Thought-Leader Professors" in Data Science. Her recent "Fundamentals of Project Planning and Management" Coursera MOOC had over 100,000 enrolled, across 200 countries worldwide.

This webinar is co-sponsored with the Society of Decision Professionals

This webinar will present the story of the rescue of the soccer team of twelve boys and their coach from the Tham Luang Caves in Thailand in July 2018.  The A case focuses on the first 9 days of the search, from when the boys went missing to when they were found. The B case focuses on the planning and execution of the rescue mission. Through our discussion of the cases, we will debate the role of leadership and communications, decision making in moments of crisis, the efficiency of ad hoc teams, the project planning and execution strategies in high-risk situations with low chances of success. This unbelievable rescue story will showcase some key decision making tendencies and strategies, and demonstrate how cultural, experience, and language differences can be bridged when working to accomplish a mutual goal.

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Webinar slides


Multivariate almost stochastic dominance: review and current work

Event Info

icon_calendar.jpgDecember 2, 2021
icon_clock.jpg12pm ET  
icon_stopwatch.jpgDuration: 1 hour

Speaker

DAS

Ilia M. Tsetlin is a Professor of Decision Sciences at INSEAD. His teaching and research interests are in prescriptive decision making emerging from normative analysis. Two recent research focuses are generic properties of preferences (multiattribute utility and stochastic dominance) and search, deadlines, and the role of uncertainty. Other research streams are related to negotiation, auction theory and collective choice. His work has been published in a number of academic journals including Management Science, Operations Research, Journal of Risk and Uncertainty, Journal of Economic Theory, Psychological Review, Games and Economic Behavior, and Social Choice and Welfare. He currently serves as a Department Editor in Management Science.

Stochastic dominance (SD) is a useful concept, especially in a multivariate context, where assessing multiattribute utility is challenging and different stakeholders might have divergent views. However, applying multivariate SD is difficult for three reasons: First, often distributions, even if fully known, cannot be ranked (e.g., by first-order SD).  Second, easily verifiable integral conditions for multivariate SD often do not exist. Third, full information about multivariate distributions (including dependence structure) is difficult (and often impossible) to obtain.  We will discuss how the concept of almost SD helps to overcome these challenges.

Co-authors: Alfred Müller, Marco Scarsini, Robert Winkler

Listen to replay here

Paper: Decisions with Several Objectives under Uncertainty: Sufficient Conditions for Multivariate Almost Stochastic Dominance

 
 
 

Event Info

icon_calendar.jpgOctober 5, 2021
icon_clock.jpg9am EDT  
icon_stopwatch.jpgDuration: 1 hour

Speaker

DAS

Galit Shmueli is Tsing Hua Distinguished Professor and Institute Director at the Institute of Service Science, College of Technology Management, National Tsing Hua University, Taiwan. Earlier she was Associate Professor at University of Maryland's Smith School of Business, and then the SRITNE Chaired Professor of Data Analytics and Associate Professor of Statistics & Information Systems at the Indian School of Business.

Prof. Shmueli’s research focuses on statistical and machine learning methodology with applications in information systems and healthcare, and an emphasis on human behavior. Since her 2010 Statistical Science paper “To Explain or To Predict?” (2000+ citations), she's been investigating how predictive methodology can enhance causal explanatory goals, and how causal explanatory methodology can enhance predictive goals. Prof. Shmueli authors multiple books, including the popular textbook Data Mining for Business Analytics and has over 100 publications in peer-reviewed journals and books. 

Prof. Shmueli teaches courses on data mining, forecasting analytics, interactive visualization, research methods, and other business analytics topics. Her online teaching videos are highly subscribed, and she has won multiple teaching awards.

Prof. Shmueli is the inaugural Editor-in-Chief of the INFORMS Journal on Data Science, and has served on editorial boards of top journals in statistics and information systems. She is an IMS Fellow and ISI elected member.

Many internet platforms that collect behavioral big data use it to predict user behavior for internal purposes and for their business customers (e.g., advertisers, insurers, security forces, governments, political consulting firms) who utilize the predictions for personalization, targeting, and other decision-making. Improving predictive accuracy is therefore extremely valuable. Data science re- searchers design algorithms, models, and approaches to improve prediction. Prediction is also improved with larger and richer data. Beyond improving algorithms and data, platforms can stealthily achieve better prediction accuracy by “pushing” users’ behaviors towards their predicted values, using behavior modification techniques, thereby demonstrating more certain predictions. Such apparent “improved” prediction can unintentionally result from employing reinforcement learning algorithms that combine prediction and behavior modification. This strategy is absent from the machine learning and statistics literature. Investigating its properties requires integrating causal with predictive notation. To this end, we incorporate Pearl’s causal do(.) operator into the predictive vocabulary. We then decompose the expected prediction error given behavior modification, and identify the components impacting predictive power. Our derivation elucidates implications of such behavior modification to data scientists, platforms, their customers, and the humans whose behavior is manipulated. Behavior modification can make users’ behavior more predictable and even more homogeneous; yet this apparent predictability might not generalize when customers use predictions in practice. Outcomes pushed towards their predictions can be at odds with customers’ intentions, and harmful to manipulated users.

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Event Info

icon_calendar.jpg May 20, 2021
icon_clock.jpg12noon ET
icon_stopwatch.jpgDuration: 1 hour

Speaker

DAS Yan Chen is the Daniel Kahneman Collegiate Professor in the School of Information at University of Michigan, and Distinguished Visiting Professor of Economics at Tsinghua University. Her research interests are in behavioral and experimental economics, market and mechanism design, information economics, and public economics. She conducts both theoretical and experimental research. She is a former president of the Economic Science Association, an international organization of experimental economists. Chen has published in leading economics and management journals, such as the American Economic Review, Journal of Political Economy, Journal of Economic Theory, and Management Science, and general interest journals such as the Proceedings of the National Academy of Sciences. She serves as a Department Editor of Management Science

Utility over Risky Payoff Streams: Normative and Descriptive Approaches

Event Info

icon_calendar.jpg March 23, 2021
icon_clock.jpg12noon ET
icon_stopwatch.jpgDuration: 1 hour

Speaker

DAS Manel Baucells teaches Quantitative Analysis courses in Darden’s MBA and Executive Education programs. Manel research focuses on incorporating psychological realism into consumer behavior models by considering factors such as anticipation, reference price comparison, mental accounting, range effects, and satiation. He serves as department editor for the journal Management Science and associate editor for Operations Research.

Co-authors: Manel Baucells, Michal Lewandowski, and Krzysztof Kontek

 Abstract: We provide behavioral foundations of a preference model for risky payoff streams, a broad domain having timed lotteries, income streams under certainty, and repeated lotteries as special cases. Following expected utility and the notion that time is perceived as inherently uncertain, we inadvertently rediscover Bell's (1974) model. To this bedrock, we add the notion that preferences are affected by range effects. The result is a behavioral model with a broad domain and consistent with a plethora of phenomena (bias towards short payback periods, the four-fold patterns for risk and time, preference reversals for risk and time, temporal patterns of decreasing or increasing impatience, and magnitude effects).

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Properties of Utility Functions for Money

Event Info

icon_calendar.jpg January 29, 2021
icon_clock.jpg12noon EST
icon_stopwatch.jpgDuration: 1 hour

Speaker

David Bell Professor David Bell

David E. Bell is a Baker Foundation Professor at Harvard Business School.  He has a BA degree from Oxford University in Mathematics and a PhD from MIT in Operations Research.

In 2001 he was awarded the Ramsey Medal, the highest distinction of the Decision Analysis Society of INFORMS.

This talk is intended as the first of many in which decision analysts give casual talks on topics of interest to them. I will review, in a non-detailed way, three papers that I have written (during my career, i.e. not recently, and for the most part uncelebrated) that concern utility functions for money. An appropriate audience would be decision analysts with some research interest in the properties of utility functions. Though most of my published work has concerned multiattribute utility, this talk will not, except tangentially. It will also not be a general review of decision analysis.