G2TT
来源类型Report
规范类型报告
ISSN1862- 4804
System Analysis for Environmental Policy
Dr. Martin Hirschnitz-Garbers
发表日期2018
出版者Federal Environment Agency (UBA), Germany
出版年2018
语种英语
概述System thinking through system dynamic modelling and policy mixing as used in the SimRess projectSystems analysis could be an essential approach to shape resource efficiency policy in a sustainable long term perspective. In the SimRess project, we tested systems thinking to develop a system dynamic resource use simulation model and ii) to investigate policy mixes for resource conservation. The report, which is available for download, documents and summarizes the various results of the workshops and the systems analysis. The study was carried out by the SimRess project partners, with Martin Hirschnitz-Garbers from Ecologic Institute as lead-author.
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System thinking through system dynamic modelling and policy mixing as used in the SimRess project

Systems analysis could be an essential approach to shape resource efficiency policy in a sustainable long term perspective. In the SimRess project, we tested systems thinking to develop a system dynamic resource use simulation model and ii) to investigate policy mixes for resource conservation. The report, which is available for download, documents and summarizes the various results of the workshops and the systems analysis. The study was carried out by the SimRess project partners, with Martin Hirschnitz-Garbers from Ecologic Institute as lead-author.

Diverse and complex interactions as well as multi-actor systems characterise resource use and resource policy. This makes system analysis a relevant tool to orient resource policy towards the long term. Analysing such complex systems requires systemic thinking, consideration of causal loops as well as time-lags and delays in system responses.

In the SimRess project, system analysis encompassed participatory conceptual system modelling via involving external stakholders into identifying system boundaries and elements via causal loop diagrams (CLDs). The CLDs were than reflected in the parametrisation of simulation models and the development of policy mixes.

Only a limited number of stakeholders participated in two of the five workshops needed for a fully-fledged group modelling process. Therefore, the project team finalised internally the conceptual system model. Although this reduced ownership and transparency of the system model, the two workshops provided relevant system knowledge for further modelling work and policy mix development.

During policy mix development in SimRess, we needed to deviate from the theoretical concept of policy mixing based on available project capacities and stakeholder decisions. On the one hand, understanding and assessing cumulative effects of policy mixes challenged conceptual policy mix development and simulation capacities. On the other hand, stakeholder decisions impacted on the depth at which system analysis via simulation models could be undertaken.

目录Table of Contents: List of Abbreviations Zusammenfassung Summary 1 Systems thinking approach used in the SimRess modelling work 1.1 Conceptual modelling and systems analysis 1.1.1 Causal loop diagrams and group modelling process in SimRess project 1.1.2 Potentials and challenges of CLDs 1.2 System dynamics modelling and integrated scenario analysis 1.3 Dynamic modelling of the structures of complex system interdependencies – annotations from an applied econometrician’s perspective 1.4 How do two modelling approaches complement each other in terms of system analysis? 2 Policy mixing as a concept for systemic resource 2.1 The need for more systemic responses in resource policy 2.2 The concept of policy mixing for resource policy 2.3 Promises and challenges of policy mixing 2.4 Policy mixing for systemic resource policy in the SimRess project – approach, challenges and lessons learnt 2.4.1 A systemic resource policy mix approach tackling key drivers and trends 2.4.1.1 Setting objectives and targets 2.4.1.2 Underlying conceptual causal system model 2.4.1.3 Selecting promising policy instruments 2.4.1.4 Undertaking ex-ante assessments 2.4.2 A resource policy mix approach based on selected ProgRess II policy instruments 2.4.2.1 Setting objectives and targets 2.4.2.2 Underlying conceptual causal system model 2.4.2.3 Selecting promising instruments 2.4.2.4 Undertaking ex-ante assessments 2.4.3 A systemic resource policy mix approach aimed at contributing to more ambitious, longer-term resource policy targets 2.4.3.1 Setting objectives and targets 2.4.3.2 Underlying conceptual causal system model 2.4.3.3 Selecting promising instruments 2.4.3.4 Undertaking ex-ante assessments 2.5 Lessons learnt on policy mixing for systemic resource policy 2.5.1 Conceptual development of the policy mix approaches 2.5.2 Scientific assessment of the policy mix approaches 3 Main conclusions 4 References used 5 Appendix List of figures and tables Figure 1: Integrative systems science Figure 2: A sample Causal Loop Diagram (CLD) Figure 3: Two phases and six steps of the group modelling process Figure 4: Causal Loop Diagram with the theme of private household consumption Figure 5: With mining industry, various metal ores are provided to different metal industries to be processed into basic metals. Different fabricated metal industries then turn these basic metals into fabricated metals. Figure 6: Flow chart showing main services/industries using metal ore and basic metals Figure 7: Causal loop diagram showing cause effect relations, feedbacks and time delays in the metal sector Figure 8: Causal loop diagram showing the demand for cars and the production, and the causal linkages between these factors Figure 9: Heuristic concept for policy mix development Figure 10: CLD for the consumption area of food (Koca and Sverdrup 2014a, 24) Figure 11: Screenshot of the SimRess consistency matrix in EIDOS Table 1: Stakeholder categorisation Table 2: List of selected policy approaches from ProgRess strategic approaches and action areas Table 3: Snapshot of the option space created for the systemic resource policy mix tackling key drivers and trends (cf. section 2.4.1)
标签Report ; Policy Assessment ; Resources
关键词environmental policy system thinking policy mixing resource efficiency causal loop diagrams development models system analysis system dynamic modelling
URLhttps://www.ecologic.eu/15906
来源智库Ecologic Institute (Germany)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/36713
推荐引用方式
GB/T 7714
Dr. Martin Hirschnitz-Garbers. System Analysis for Environmental Policy. 2018.
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