Dr. Judit Lienert leads the cluster Decision Analysis in the Environmental Social Science Department of Eawag, the Swiss Federal Institute of Aquatic Science and Technology. Judit Lienert has around twenty years of research experience in inter- and transdisciplinary projects and has published more than 50 peer-reviewed papers. Her focus is on Multi-Criteria Decision Analysis (MCDA), integrating natural, engineering, and social science data in decision models to better address environmental decision problems. This work has gained increasing attention, including three recent best paper awards by EJOR, OMEGA, and the INFORMS Decision Analysis Society. Judit Lienert studied biology and environmental sciences at the University of Zürich, Switzerland, after a first career in nursing. She finished her PhD on habitat fragmentation of wetlands in 2001. At Eawag, until 2007 she was co-project leader of the large cross-cutting project Novaquatis on urine source separation, which won a prestigious Swiss transdisciplinary research award (td-net 2008), recognizing both interdisciplinary research integration and cooperation with non-academic partners. Building on this research at the interface of various scientific disciplines and society, Judit Lienert focused on participatory MCDA from 2007 onwards. To address complex environmental decision problems, all steps of MCDA are crucial, from problem structuring over making scientific predictions to preference elicitation, and modelling. A specific interest is the behavioral analysis of decision processes and a scientifically rigorous, but practicable integration of stakeholder preferences. Judit Lienert is lecturer for MCDA at ETH Zürich, and is on the managing board of the EURO working group on Behavioral OR.
Addressing Environmental Decision Problems with MCDA, Problem Structuring, and Behavioral OR
Environmental decisions share characteristics that make them difficult to tackle. Usually, many stakeholders are involved, including public authorities, NGO’s, local communities, or even future generations. Environmental decisions may have serious long-term consequences. Decision outcomes may be difficult to quantify and predictions highly uncertain. This talk draws on Swiss cases from river management and urban water infrastructure planning, and creating a flood alert system in West Africa. I will cover important steps of structured, participatory decision-making using Multi-Criteria Decision Analysis (MCDA; MAVT/MAUT), with a focus on behavioral aspects to integrate stakeholder preferences. Initial problem structuring is key, comprising stakeholder analysis, generating alternatives and objectives, and wise decisions on which minimal set of objectives to include. I will introduce experimental online surveys with serious games. Surveys potentially allow including a broader audience in participatory decision-making; e.g., for generating objectives, or eliciting stakeholder preferences. Uncertainty is another critical issue. Future uncertainty can be captured by combining scenario planning with MCDA. Predictive uncertainty is often addressed with probability theory, and stakeholder uncertainty about own preferences with sensitivity analyses. Recently, we proposed integrating the uncertainty of predictions and preferences using the neglected concept of expected expected utility (EEU). Moreover, timing can be decisive in environmental decisions, e.g., when choosing (wastewater infrastructure) alternatives in transition phases over time, or regarding stakeholder preferences over a series of decision workshops. Another neglected subject in practical MCDA is model building; a growing number of cases illustrate that the common additive aggregation (weighted mean) is often inadequate in capturing stakeholder preferences. I will introduce the ValueDecisions app, a new R-Shiny interface that allows addressing some of these specificities, including easy exploration of the MCDA-aggregation model. This talk invites the OR community to discover the exciting research opportunities provided by environmental decision problems, while contributing to tackling todays’ serious environmental challenges.