Research Seminars

Title: Enhancing and Optimizing Resilience of Port-Hinterland Container Transportation Networks

Speaker: Nan Liu

Date/Time: May 02, 2018 – 17:30

Location: RTH 211

Abstract: Within the entire maritime logistic chain, the landside portion between ports and hinterlands, namely, the port-hinterland container transportation network (PHCTN), serves as an essential link. However, under the risk of unconventional emergency events (UEEs), the ability of PHCTNs being robust against and adaptive to potential disruptions is a prerequisite to ensure the efficiency of the international container transportation. Specifically, we carried out two studies. The first study aims to investigate the strategic investment of players in a PHCTN to enhance network resilience to man-made UEEs in the pre-event period by reducing network vulnerability. Given the complexity of the involvement of multiple players and their interactin g complementary and competitive business relationships, network game theory is adopted. Results show that the complementary influence Bonacich centrality of players plays a critical role in determining their investment decisions and serves as basis for useful managerial insights. The second study constructs an integer programming model to investigate the influence of immediate recovery activities on the improvement of PHCTN resilience from the perspective of shippers by focusing on the post-event period of UEEs. The validity and reliability of the model is tested by using a numerical simulation based on the specific case of Gothenburg Port and part of its hinterland. Some useful implications to improve the resilience of PHCTN in the post-event period are provided.
 
Bio: Dr. Nan Liu is currently a professor in the Department of Data Science and Management Engineering, and Director of Institute of Logistics and Decision Optimization, in School of Management at Zhejiang University. He received his B.S. in mathematics from Nankai University, M.S. in urban systems and policy planning from Northwestern University, and Ph.D. in economics from the University of Illinois at Chicago. His research interests include logistics and supply-chain management, transportation economics and management, port/marine logistics, and humanitarian/emergency logistics management. Professor Liu has conducted six national-level research grants, including four from the National Natural Science Foundation of China and two from the National Social Science Foundation of China. He has published numerous academic papers in leading international journals such asTransportation Research-Part B/Part E,International Journal of Production EconomicsJournal of Urban Economics,Regional Science and Urban Economics,Maritime Policy and Management,Computers & Industrial Engineering.

Title: After Great Disasters

Speaker: Robert Olshanky

Date/Time: September 07, 2017 – 14:00

Location: RTH 324

Major natural disasters are rare, but their aftermath can change the fortunes of a city or region forever. This book and its companion Policy Focus Report  (co-authored with Laurie Johnson) identify lessons from different parts of the world to help communities and government leaders better organize for recovery after future disasters. The authors consider the processes and outcomes of community recovery and reconstruction following major disasters in six countries: China, New Zealand, India, Indonesia, Japan, and the United States. Post-disaster reconstruction offers opportunities to improve construction and design standards, renew infrastructure, create new land use arrangements, reinvent economies, and improve governance. If done well, reconstruction can help break the cycle of disaster-related impacts and losses, and improve the resilience of a city or region.

Bio: Robert B. Olshansky, Ph.D., FAICP, is Professor of Urban and Regional Planning, University of Illinois at Urbana-Champaign. Professor Olshansky has studied recovery planning and management after numerous major disasters around the world, including ones in the U.S., Japan, China, Taiwan, India, Indonesia, and Haiti. His research has been funded by the National Science Foundation and Lincoln Institute of Land Policy, and in 2004-05 and 2012-13 he was a Visiting Professor at the Disaster Prevention Research Institute at Kyoto University. Along with Laurie Johnson he co-authored Opportunity in Chaos: Rebuilding after the 1994 Northridge and 1995 Kobe Earthquakes (available online), Clear as Mud: Planning for the Rebuilding of New Orleans (APA Press, 2010), and After Great Disasters: An In-depth Analysis of How Six Countries Managed Community Recovery (Lincoln Institute, 2017). He is also the editor of Urban Planning after Disasters (4 volumes) (Routledge, 2016), and in 2014 he co-edited a special issue of the Journal of the American Planning Association on Planning for Disaster Recovery.

Title: Oil Consumption and Security

Speaker: Stephen P.A. Brown

Date/Time: February 13, 2017 – 14:00

Location: RTH 326

Formerly the director of energy economics at the Federal Reserve Bank of Dallas, Stephen has numerous published articles about energy markets and policy and microeconomic public policy.  He an editor for Energy Policy, on the advisory board for the journal Energy Economics, and a regular participant in meetings of the Stanford Energy Modeling Forum. He previously served on the American Statistical Association’s advisory board for the U.S. Energy Information Administration.  He developed MarketSim, an energy-market simulation model used by the U.S. Department of Interior to evaluate offshore oil and gas leasing.  He was honored as a senior fellow by the U.S. Association for Energy Economics in 2008, and his coauthored article, “What Drives Natural Gas Prices?" was recognized by the International Association for Energy Economics as the best article published in The Energy Journal during 2008.  His current research includes oil and energy security, the aggregate economic effects of world oil supply disruptions, natural gas markets, the economics of antibiotic effectiveness, and the role of public policy in a market economy.

Title: Informing Ex-Ante Event Studies With Macro-Econometric Evidence on the Structural Policy of Terrorism

Speaker: Dr. Jasson Nassios & Professor James A. Giesecke

Date/Time: December 02, 2016 – 14:00

Location: RGL 209

Economic consequence analysis is one of many inputs to terrorism contingency planning. Computable general equilibrium (CGE) models are being used more frequently in these analyses, in part because of their capacity to accommodate high levels of event-specific detail. In modeling the potential economic effects of a hypothetical terrorist event, two broad sets of shocks are required: (1) physical impacts on observable variables (e.g., asset damage); (2) behavioral impacts on unobservable variables (e.g., investor uncertainty). Assembling shocks describing the physical impacts of a terrorist incident is relatively straightforward, since estimates are either readily available or plausibly inferred. However, assembling shocks describing behavioral impacts is more difficult. Values for behavioral variables (e.g., required rates-of-return) are typically inferred or estimated by indirect means. Generally, this has been achieved via reference to extraneous literature or ex-ante surveys. In this talk we describe a new method. We elucidate the magnitude of CGE-relevant structural shifts implicit in econometric evidence on terrorist incidents, with a view to informing future ex-ante event assessments. Ex-post econometric studies of terrorism by Blomberg et al.(2004) yield macro econometric equations that describe the response of observable economic variables (e.g., GDP growth) to terrorist incidents. We use these equations to determine estimates for relevant (unobservable) structural and policy variables impacted by terrorist incidents, using a CGE model of the U.S. This allows us to: (i) compare values for these shifts with input assumptions in earlier ex-ante CGE studies; and (ii) discuss how future ex-ante studies can be informed by our analysis.

Bio: Dr. Jason Nassios is a Research Fellow at the Centre of Policy Studies (CoPS), based at Victoria University's Flinders Street campus in Melbourne. He holds a PhD in Applied Mathematics and Bachelor's Degrees in Commerce and Science from the University of Melbourne. Prior to joining CoPS in April 2015, Jason spent two years as an Investment Consultant at Mercer Australia. Jason's key areas of interest are applied economic modelling, applied mathematics, policy analysis and finance.

Bio: Professor James A. Giesecke is the Director of CoPS. His research is in the development of large-scale multi-regional and national computable general equilibrium (CGE) models, and the application of these models to the analysis of the determinants of economic growth and structural change, forecasting, and policy analysis.

Title: Economic Consequences of Terrorism and Natural Disasters: the Computable General Equilibrium Approach

Speaker: Peter B. Dixon

Date/Time: December 07, 2015 – 12:00

Location: RGL 100

Abstract: Peter Dixon’s presentation will start with a brief comparison of Input-Output and CGE modeling.  This will be followed by a description of USAGE and USAGE-TERM.  USAGE is a detailed national CGE model of the United States developed at the Centre of Policy Studies (CoPS), Victoria University, with support from the U.S. International Trade Commission and other Federal government agencies.  USAGE-TERM is a multi-region version of USAGE developed at CoPS with support from CREATE.  The third part of the presentation will be an illustrative application of USAGE-TERM demonstrating the relevance of the model in terrorism analysis.  The final part will focus on how the modeling capacity of USAGE-TERM can be made available in a timely fashion to decision makers.  The presentation will draw on the chapter with the same name authored by Dixon, Rimmer, Wittwer, Rose and Heatwole that will appear in a book edited by Abbas, von Winterfeldt and Tambe to be published by Cambridge University Press. 

Bio: Professor Dixon is known for his work in computable general equilibrium modelling.  Together with colleagues at the IMPACT Project and the Centre of Policy Studies, he created the ORANI model and its dynamic successor, MONASH.  These models have been prominent in the Australian economic debate for 35 years and have been used as templates for the development of other models throughout the world.  He is the principal author of the ORANI and MONASH books published in the North Holland Contributions series in 1982 and 2002.  In recent years he has led the development of the USAGE model of the U.S. which is being used by the U. S. International Trade Commission and the Departments of Agriculture, Commerce, Energy, Transportation and Homeland Security, and by the Canadian Embassy in Washington DC.  He is currently professor in the Centre of Policy Studies, Victoria University, Melbourne

Title: Asymmetric Impact of Competitive and Cooperative Environments on Decisions Involving Ambiguity

Speaker: Sule Guney

Date/Time: August 05, 2015 – 14:00

Location: RTH 306

Ambiguity aversion refers to a pattern of preferences favoring options with known winning probabilities (i.e. risky) over those with unknown winning probabilities (i.e. ambiguous), even though normative theories imply indifference. In a couple of studies, we aimed to explore how different strategic environments influence people’s beliefs about winning probabilities and hence their decisions under ambiguity. To do so, we changed the structure of the classic Ellsberg task into a two-player interactive game where the decision-making environment was explicitly made Cooperative (i.e., players’ financial interests were aligned), Competitive (players’ financial interests were opposite), or Non-Competitive (players’ financial interests were independent). In the study, two players were presented with a risky box (50 black and 50 yellow balls), and an ambiguous box (100 black and yellows balls in an unknown proportion); and asked to bet on a color to be drawn from their chosen box. To make the Ellsberg task interactive, one of the players was allowed to arrange the ambiguous box before the box/color choice stage, even though the exact proportion of colored balls remained unknown to both players. The highest level of ambiguity aversion was obtained in the Competitive condition, and the lowest in the Cooperative condition, with the Non-Competitive condition in between. Also, ambiguity attitudes were sensitive to who was in charge of box arrangement in the Competitive condition, but not in the Cooperative condition. Overall our findings indicate that the perceived competitiveness and cooperativeness of the decision-making environment alter attitudes toward ambiguity in opposing directions.

Bio: Sule Guney is a post-doctoral research associate at the U.S. Homeland Security Center for Risk and Economic Analysis of Terrorism Events (CREATE). She received her Ph.D. in Cognitive Psychology from University of New South Wales, Australia. Her primary area of interest is decision-making, with a specific focus on understanding how people make (i) individual decisions in the face of ambiguity and risk, and (ii) strategic decisions in interactive environments both in laboratory and real-life settings. She has publications on decision-making under ambiguity and in strategic games in top field journals, including Journal of Behavioral Decision Making, Behavioral and Brain Sciences, and Frontiers in Human Neuroscience. Using her expertise in behavioral and experimental techniques in the area of decision-making, she is currently working on various projects at CREATE, and studying decisions from a decision-analytic perspective, both in terrorism and non-terrorism contexts.

Title: Implementing High-Powered Contracts to Motivate Intertemporal Effort Supply

Speaker: Leon Yang Zhu

Date/Time: July 01, 2015 – 14:00

Location: RTH 306

We characterize the optimal contract between a principal and a risk-neutral, wealth-constrained agent when an adverse selection problem follows a moral hazard problem. The optimal contract in this setting often is more steeply sloped for the largest output levels than is the optimal contract in either the standard moral hazard setting or the standard adverse selection setting. The large incremental rewards for exceptional performance motivate the agent to deliver substantial effort both before and after he acquires privileged information about the production environment.

Bio: Leon Zhu is an associate professor of Data Sciences and Operations in the Marshall School of Business. He received his Ph.D. in Industrial and Systems Engineering and M.A. in Economics from the University of Florida and a Bachelor degree from Shanghai Jiaotong University. Before joining Marshall, he was a Postdoc and lectured at the University of California, Berkeley. His research interests include policy and mechanism design, game theory, and applied optimization. Professor Zhu's papers have appeared in the leading journals, including the American Economic Review, Journal of Economic Theory, Management Science, Manufacturing and Service Operations Management, Operations Research, and Rand Journal of Economics. Professor Zhu teaches the core operations management and an elective on operations forensics at Marshall School of Business.

Title: Location Privacy Preservation in Mobile Networks

Speaker: Miao Pan

Date/Time: June 24, 2015 – 15:00

Location: EEB 248

With over 770 million GPS-enabled smartphones, location Based Service (LBS) has begun to permeate the entire mobile space. Although LBS greatly benefits the daily life of mobile device users, it has introduced significant threats to privacy. In an LBS system, even under the protection of pseudonyms, users may become victims of inference attacks, where an adversary reveals a user’s real identity and complete moving trajectory with the aid of side information, e.g., accidental identity disclosure through personal encounters. To enhance privacy protection for LBS users, in this talk, I will present a centralized location privacy preservation scheme and a distributed approach for achieving k-anonymity, respectively. For the centralized scheme, a new metric to quantify the system's resilience against inferential attack is proposed and multiple mix-zone placement is introduced to tackle this problem. In the case that there is no trusted central authority, we will include extra fake location information associated with different pseudonyms, known as dummy users, and study the behaviors of self-interested users in terms of generating dummy users from a game-theoretic perspective. We model the distributed dummy user generation as Bayesian games in both static and timing-aware contexts, analyze the existence and properties of the Bayesian Nash Equilibria for both models, and propose a strategy selection algorithm to help users achieve optimized payoffs. I will also briefly discuss my most recent work on cybersecurity, cognitive radio networks and cyber-physical systems.

Bio: Dr. Miao Pan is an Assistant Professor in the Department of Computer Science at Texas Southern University. He was a recipient of NSF CAREER Award in 2014. Dr. Pan received Ph.D. degree in Electrical and Computer Engineering from University of Florida in August 2012. Dr. Pan's research interests include cognitive radio networks, cyber-physical systems, and cybersecurity. He has published over 50 papers in prestigious journals including IEEE/ACM Transactions on Networking, IEEE Journal on Selected Areas in Communications, IEEE Transactions on Mobile Computing, and IEEE Transactions on Smart Grid, or in top conferences such as IEEE INFOCOM, ICDCS, and IEEE IPDPS. Dr. Pan serves as a Technical Reviewer for many international journals and conferences. He has also been serving as a Technical Program Committee member of several top international conferences, e.g., IEEE INFOCOM 2014 and 2015. Dr. Pan is a member of IEEE and ACM.

Title: Correlation Between Anomalies and Theories of Mental Accounting

Speaker: Manel Baucells

Date/Time: June 17, 2015 – 14:00

Location: RTH 306

Several consumer choice models account for anomalies in consumption-payment decisions. We consider four such models, including Prelec and Loewenstein 1998 double-entry model and Koszegi and Rabin 2006 reference dependent model. We observe that these models make distinct predictions regarding how different anomalies ought to be related or unrelated. In a controlled experiment we elicit the participant's tendency towards five anomalies, namely, the sunk-cost effect, the reluctance to trade, the flat-rate bias, the preference for pre-pay, and the preference to be post-paid. The observed correlation between anomalies across individuals is consistent with the prediction of Baucells and Hwang 2014 model and, to a large extent, with that of Prelec and Loewenstein 1998. The evidence is partially consistent with Thaler 1985, and we find little support for Koszegi and Rabin 2006. The results suggest that the speed of adaptation of reference prices to current price information is a key explanatory factor.

Bio: Manel Baucells is Senior Economist at the USC Center for Economic and Social Research. Previously he was Senior Economist at the Rand Corporation (California), and full professor at the University Pompeu Fabra (Barcelona). He completed his Ph.D. on game theory, with applications to management, at the University of California, Los Angeles (UCLA) under the supervision of Steven Lippman and Lloyd Shapley (2012 Nobel Prize laureate in Economics). His research focuses on incorporating psychological realism into economic models by considering factors such as reference point formation, mental accounting, non-linear risk and time distance and satiation. He is department editor in the journal Management Science and associate editor of Operations Research. Manel and Rakesh Sarin (UCLA) have published the book Engineering Happiness (UC Press), that has received the 2014 best publication award by the Decision Analysis society. The book applies principles of behavioral economics to improve life outcomes.

Title: Meta-Model Choice and the Economic Modeling of Cyber-Security Investments

Speaker: Arunesh Sinha

Date/Time: June 02, 2015 – 11:00

Location: REB 248

The presentation links work on meta-model selection, such as that between a multi-attribute utility model and a benefit-cost analysis, with the finer grained development of an economics based model for cyber security investments.   The cyber-security model seeks to link a taxonomy of cyber attack types to micro-economic structures and economic damages broadly considered.  Both projects are in progress.

Bio: Scott Farrow is a Professor in the Department of Economics at UMBC and the Economics Coordinator for CREATE.   Since receiving his Ph.D. in economics from Washington State University in 1983, Dr. Farrow has served as a member of the faculty at Carnegie Mellon University and the Pennsylvania State University, twice in the Executive Office of the President under both Democratic and Republican administrations, in the Governmental Accountability Office (GAO) and the Department of the Interior.   He was the founding editor of the Journal of Benefit-Cost Analysis.  His research focuses on integration of risk and economics in the development and evaluation of government programs and policies.

Title: One Size Does Not Fit All: A Game-Theoretic Approach for Dynamically and Effectively Screening for Threats

Speaker: Arunesh Sinha

Date/Time: May 20, 2015 – 14:00

Location: RTH 306

An effective way of preventing attacks in secure areas is to screen for threats (people, objects) before entry, e.g., screening of airport passengers. However, screening every entity at the same level may be ineffective and undesirable. The challenge then is to find a dynamic approach for screening, allowing for more effective use of limited screening resources, leading to improved security. We address this challenge with the following contributions: (1) a threat screening game (TSG) model for screening domains; (2) an NP-hardness proof for computing the equilibrium of TSGs; (3) a scheme for decomposing TSGs into subgames to improve scalability; (4) a column generation approach to solve TSGs which includes a novel multidimensional knapsack slave formulation and heuristics for faster computation; and (5) a minimax regret-based trade-off analysis for handling uncertainty in the number of screenees and choosing a robust screening strategy. This talk will focus more on the model and we welcome any feedback that could improve the model or algorithmic techniques used in this ongoing work.

Bio: Dr. Arunesh Sinha is a postdoctoral scholar with Prof. Milind Tambe at the Computer Science Department of University of Southern California. He received his Ph.D. from Carnegie Mellon University in Aug 2014, where he was fortunate to be advised by Prof. Anupam Datta. He obtained his undergraduate degree in Electrical Engineering from IIT Kharagpur in India. He has industry research experience in form of internships at Microsoft Research, Redmond and Intel Labs, Hillsboro. He was awarded the Bertucci fellowship at CMU in appreciation of his novel research.

Dr. Sinha has conducted research at the intersection of cyber-security, machine learning and game theory. He introduced a novel game theoretic model of auditing for enforcement of policies in large organizations. He has also worked on the use of machine learning to learn and enforce access policies. His interests lie in the theoretical aspects of multi-agent interaction, machine learning, security and privacy, along with an emphasis on real-world applicability of the theoretical models

Title: Striving for integration in a Multi-Sector System: Lessons from the California Multi-Hazard Plan Process

Speaker: William Siembieda

Date/Time: May 20, 2015 – 09:30

Location: RTH 324

Multi-hazard mitigation planning crosses boundaries and requires participation from multiple actors, mostly from the public sector.  Cross-sector communications emerges as a powerful tool to foster the partnership needed for boundary crossing.   The end goal is integration of effort among actors at all scales.   The process of  designing and assembling a  FEMA standard and enhanced state level multi-hazard mitigation plan is a case study in striving for integration.  The nationally  acclaimed State of California multi-hazard mitigation plan  effort is the subject of this presentation.

Bio: William Siembieda is an internationally known disaster mitigation planner. His work bridges scholarship and practice. He was a key member of the team that prepared the highly acclaimed 2013 and 2010 State of California Multi-Hazard Mitigation Plan. His work on the legislative framework led to the first of its kind 2004 Federal District of Caracas (Venezuela) Mitigation and Preparedness Plan. In 2008 he conducted studies of long-term disaster recovery studies in Niigata (Japan) and pre-disaster planning studies in Nara Prefecture (Japan), and has continued to work on recovery plans for the Great East Japan Earthquake and Tsunami. His four-country Central America study of 15 poor communities demonstrates how communities chose a paradigm for disaster recovery and provides insight into viable long-term recovery.

Siembieda is Professor of City and Regional Planning and director of the College of Architecture and Environmental Design’s Resilient Communities Research Institute at California Polytechnic State University, San Luis Obispo, and CA.  He has held academic appointments at the University of New Mexico and at the University of California-San Diego. He has been visiting research professor at the Disaster Prevention Research Institute, Kyoto University, Research Scholar at the Joint Center for Disaster Research, Massey University, Wellington, NZ, and serves as an international advisor to Chile’s National Research Center for Integrated Disaster Management.  Research areas include disaster mitigation planning, recovery theory, resiliency planning, land use planning, and urban land market behavior.

Dr. Siembieda holds a Ph.D. in Urban Planning from the University of California, Los Angeles and an Economics B.A. and a MCRP (City Planning) from the University of California, Berkeley. 

Recent scholarship includes: “Towards a risk-based framework for land use reconstruction planning,” Journal of the American Planning Association, “The role of the built environment in the recovery of cities and communities from extreme events,” International Journal of Mass Emergencies and Disasters; “Rebuild fast but rebuild better: Chile’s initial recovery following the 27F earthquake and tsunami,” Earthquake Spectra; and “Transactions and friction as concepts to guide disaster recovery policy,” International Journal of Disaster Risk Science, and “Adaptation to seismic risk and climate change: San Francisco and Berkeley, CA,” in  Adapting to Climate Change: Lessons from Natural Hazards Planning, Policy for the ARkStorm Scenario (USGS), and “The Crisis Management System in Japan.” in Possible Futures for Japan (forthcoming, New York University Press).

Title: From Controversy to Consensus: Decommissioning California's offshore oil platforms

Speaker: Max Henrion

Date/Time: April 14, 2015 – 14:00

Location: PHE 333

Like many issues of energy and environment, there was much controversy about how to decommission California's 27 offshore oil platforms. Complete removal was required by the original leases, but would cost over a billion dollars, and destroy the rich marine ecosystems that have grown up around these platforms. A decision analysis provided stakeholders with insights that helped form consensus for a “rigs to reefs” option — removing the platform tops and retaining the supports as an artificial reef. An enabling law was passed by the California Statehouse with near unanimity.  This talk illustrates the practical value of: 

  • Using decision trees and influence diagrams to simplify the model
  • Examining different points of view with a multi-attribute decision model
  • Enabling stakeholders to explore the effects of changing assumptions and preferences with interactive decision software
  • Analyzing sensitivities to uncertainties and preferences
  • Creatively designing better decision options
  • Summarizing key insights on a single page

This project won the 2014 Decision Analysis Practice Award from the Society of Decision Professionals and INFORMS Decision Analysis Society.

Bio: Max Henrion is the Chief Executive Officer of Lumina Decision Systems, in Los Gatos, California. He has 30 years’ experience as a professor, practicing decision analyst, software designer, and entrepreneur. He is the originator of the Analytica software. He has been Professor at Carnegie Mellon, Vice President at Ask Jeeves (now Ask.com), and Consulting Professor at Stanford University. He is a Member of the Board of the Society for Decision Professionals. He is co-author of three books, including Uncertainty: A Guide to dealing with Uncertainty in Policy and Risk Analysis (Cambridge UP, 1990), and over 60 articles in decision and risk analysis, artificial intelligence, and energy and environmental policy. He has an MA from Cambridge University, M. Design from the Royal College of Art, London, and Ph.D. from Carnegie Mellon University.

Title: Adversary Bounded Rationality in Green Security Domains: Handling Payoff Uncertainty and Elicitation

Speaker: Than Nguyen

Date/Time: April 01, 2015 – 14:00

Location: RHE 333

Research on Stackelberg Security Games (SSG) has recently shifted to green security domains, e.g., protecting wildlife from illegal poaching. Previous research on this topic has advocated the use of behavioral (bounded rationality) models of adversaries in SSG. We, for the first time, provides validation of these behavioral models based on real-world data from a wildlife park. We next introduce the first algorithm to handle payoff uncertainty – an important concern in green security domains – in the presence of such adversary behavioral models. Finally, given the availability of mobile sensors such as Unmanned Aerial Vehicles in green security domains, we introduce new payoff elicitation strategies to strategically reduce uncertainty over multiple targets at a time.


Bio: Thanh Nguyen is a PhD student in the Dept. of Computer Science. She is working with Prof. Milind Tambe at the Teamcore research group. Her research interests include game-theoretic modeling, robust solution techniques, and behavioral modeling for real-world security applications. In particular, she has been focusing on developing efficient robust algorithms for handling worst-case cenario of uncertainties in Stackelberg Security Games. Furthermore, she is working on predicting decision-making of human adversaries based on their activity history and incorporate that model into computing the optimal protection strategy for security agencies or the defender.

Title: Cognitive and Motivational Biases in Decision and Risk Analysis

Speaker: Gilberto Montibeller/Detlof von Winterfeldt

Date/Time: March 25, 2015 – 14:00

Location: RTH 306

Behavioral decision research has demonstrated that judgments and decisions of ordinary people and experts are subject to numerous biases. Decision and risk analysis were designed to improve judgments and decisions and to overcome many of these biases. However, when eliciting model components and parameters from decision-makers or experts, analysts often face the very biases they are trying to help overcome. When these inputs are biased they can seriously reduce the quality of the model and resulting analysis. Some of these biases are due to faulty cognitive processes; some are due to motivations for preferred analysis outcomes. In this talk we identify the cognitive and motivational biases that are relevant for decision and risk analysis, because they can distort analysis inputs and are difficult to correct. We also review and provide guidance about the existing debiasing techniques to overcome these biases. In addition, we describe some biases that are less relevant, because they can be corrected by using logic or decomposing the elicitation task. We conclude the talk with an agenda for future research on this topic.

Bio: Dr. Gilberto Montibeller is a Tenured Lecturer in Management Science, in the Department of Management, at the London School of Economics, and Course Director of its MSc in Management Science. He is an expert on multi-criteria decision analysis.  His main research interests are on the links between behavioral decision research and decision analytic modeling and on the formal conceptualization of decision aiding practices. He is area editor of the Journal of Multi-Criteria Decision Analysis and is on the editorial boards of the Informs Decision Analysis and European Journal of Decision Processes journals. Dr Montibeller has published widely in key journals in the field, such as Risk Analysis, European Journal of Operational Research, Decision Support Systems, Technological Forecasting & Social Change, among others. He has held visiting scholar positions at the International Institute for Applied Systems Analysis (IIASA, Austria) and at the Massachusetts Institute of Technology (MIT), and is presently a visiting scholar at Create in the University of Southern California. He is also a visiting professor at CNRS Lamsade (Paris Dauphine University, France) and at the University of São Paulo (Brazil). Dr Montibeller has more than twenty years of experience in conducting decision analytic consultancy projects for private and public organizations, in Continental Europe, Britain, and Latin America. Partner organizations include the UK Department of Agriculture (Defra), World Health Organisation (WHO), Food and Agriculture Organization of the United Nations (FAO), Babcock International, Itaipu Binational (Brazil and Paraguay), and the Brazilian Centre for SMEs (SEBRAE), among others. Two of his main areas of applications are resource allocation against emerging threats, particularly health and terrorist ones, and multi-criteria health prioritizations.

Title: Cognitive Constraints on Valuing Annuities

Speaker: Arie Kapteyn

Date/Time: February 04, 2015 – 13:45

Location: RTH 306

This paper documents consumers' difficulty valuing life annuities (paper attached). We show that the prices at which people are willing to buy annuities are substantially below the prices at which they are willing to sell them, a finding we show is not attributable to an endowment effect. We also find that buy values are negatively correlated with sell values and that the sell-buy valuation spread is negatively correlated with cognition; the spread is larger for those with less education, weaker numerical abilities, and lower levels of financial literacy. Our evidence contributes to the emerging literature on heterogeneity in financial decision-making abilities.

Bio: Arie Kapteyn, Ph.D. is a Professor of Economics and the Executive Director of the Dornsife College of Letters Arts and Sciences Center for Economic and Social Research (CESR) at the University of Southern California. Before founding CESR at USC, Prof. Kapteyn was a Senior Economist and Director of the Labor & Population division of the RAND Corporation. Prof. Kapteyn's research expertise covers microeconomics, public finance, and econometrics. Much of his recent applied work is in the field of aging and economic decision making, with papers on topics related to retirement, consumption and savings, pensions and Social Security, disability, economic well-being of the elderly, and portfolio choice. At CESR he is the Principal Investigator of several projects for the National Institute on Aging. Dr. Kapteyn received an M.A. in econometrics from Erasmus University Rotterdam, an MA in agricultural economics from Wageningen University, and a Ph.D. from Leiden University, all in the Netherlands.

Title: Analyzing the Value-of-Information for Improving Biosurveillance

Speaker: Henry Willis

Date/Time: February 02, 2015 – 14:00

Location: RTH 324

Biosurveillance provides information that improves decisions about mitigating the effects of disease outbreaks and bioterrorism. Applying two standard risk and decision analysis tools to biosurveillance -decision trees and value-of-information analysis– I demonstrate an approach for evaluating strategies to enhance biosurveillance and to improve decisions about whether and how to act after detection of a biosurveillance signal.

Bio: Henry H. Willis is director of the RAND Homeland Security and Defense Center and a professor at the Pardee RAND Graduate School. Willis has applied risk analysis tools to resource allocation and risk management decisions in the areas of public health and emergency preparedness, homeland and national security policy, energy and environmental policy, and transportation planning. He is the author of dozens of publications, book chapters, and op-ed pieces and has testified before Congress as an expert on applying risk analysis to homeland security policy. Willis's recent research has involved assessing the costs and benefits of terrorism security measures like the Western Hemisphere Travel Initiative and evaluating the impact of public health emergency preparedness grant programs like the Cities Readiness Initiative. Willis earned his B.A. in chemistry and environmental studies from the University of Pennsylvania, his M.A. in environmental science from the University of Cincinnati, and his Ph.D. from the Department of Engineering and Public Policy at Carnegie Mellon University.

Title: System Design under Uncertainty: Scheduling and Incentive Policies

Speaker: Amy Ward

Date/Time: January 28, 2015 – 14:00

Location: RTH 306

We present several system design questions, and discuss their analysis.  Our purpose is to understand which types of models are most relevant for the applications of interest to CREATE.  We begin with a more classical network control problem, in which we must decide how to schedule jobs for processing at different stations in a network.  Although there is a broad literature on such problems, there has been less focus on networks in which there is both sequential and parallel processing of jobs, and this is where our interest lies.  Our next problem considers how to control congestion when processing resources are people, instead of machines, as is the case in many service systems.  The difference is that machines work at fixed rates (as is assumed in traditional queueing theory) whereas people may work faster or slower, depending on their incentives.  We want to understand how incentives influence system performance, and we do this by looking at a queueing game.  We end by very briefly summarizing some current research thoughts on emergency department design, and on capacity sizing when there is demand uncertainty.

 

Bio: Amy Ward is an Associate Professor of Data Sciences and Operations in the Marshall School of Business at USC.  She received her PhD from Stanford University in 2001, and then spent 4 years in the Industrial and Systems Engineering Department at Georgia Tech before coming to USC.  She is an associate editor for Operations Research, Manufacturing & Service Operations Management, and Operations Research Letters.  She is the vice-chair of the Applied Probability Society of INFORMS, and will become chair in 2016.  Her research focuses on the approximation and control of stochastic systems, with applications to the manufacturing and service industries.