Eva Lieberherr: Catalogue data in Spring Semester 2020
|Name||Dr. Eva Lieberherr|
Gruppe Natural Resource Policy
ETH Zürich, SOL G 2
|Telephone||+41 44 632 93 36|
|Department||Environmental Systems Science|
|701-1562-00L||Cases in Environmental Policy and Decision Making |
Number of participants limited to 40.
|6 credits||4P||A. Patt, E. Lieberherr, M. Morosini, J. Wilkes-Allemann|
|Abstract||The course will proceed through a series of case studies, modeled after those often used in business and policy teaching curricula. Students will engage in individual and group work to practice the art of effective decision-making, recommending a course of action for the individual and organization that is the subject of each case, gaining valuable insights into environmental policy-making.|
|Objective||- Identify the facts, assumptions, theories, and social constructions guiding the decisions of different stakeholders to a range of environmental and natural resource policy problems.|
- Recognize key institutional and interpersonal challenges in decision-making situations.
- Design communication and decision-making processes that can work effectively in the context of stakeholder worldviews and perspectives.
- Conduct qualitative and quantitative analysis of value to decision-makers, and communicate that in a manner that is clear and effective.
- Consider broader policy issues applicable across the cases, such as the appropriate roles of public, non-profit, and private sector organizations, the decentralization of authority, and possible societal pathways towards sustainability.
|Content||The course will cover a range of environmental problem areas, include land conversion, water quality, air quality, climate change, and energy. Across these issues, cases will force students to confront particular decisions needing to be made by individuals and organizations, primarily in the public and non-profit sectors, but also in private sector firms.|
|Prerequisites / Notice||It would be desirable, but not essential, that students had already taken a course on policy analysis and modeling.|