The politics of green infrastructure: A discrete choice experiment with Flemish local decision-makers

Oijstaeijen, Wito Van; Passel, Steven Van; Back, Phil; Cools, Jan

doi:10.1016/j.ecolecon.2022.107493

Cited by 3 publications

(1 citation statement)

References 51 publications

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“…In recent years, DCE has been used more frequently in research concerning the energy transition to capture stakeholder preferences related to key components of this transition. These include different energy policies and energy technologies [17,18], the identification and selection of assessment indicators for energy systems [14,16], energy policies related to local energy communities and social acceptance [19] and green infrastructure [20]. The study by Azarova et al [19], for example, applied a choice experiment approach to analyse the attitude of local communities towards different configurations of renewable energy technologies within the local energy system in four European countries.…”

Section: Introductionmentioning

confidence: 99%

Weighting Key Performance Indicators of Smart Local Energy Systems: A Discrete Choice Experiment

et al. 2022

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The development of Smart Local Energy Systems (SLES) in the UK is part of the energy transition tackling the energy trilemma and contributing to achieving the Sustainable Development Goals (SDGs). Project developers and other stakeholders need to independently assess the performance of these systems: how well they meet their aims to successfully deliver multiple benefits and objectives. This article describes a step undertaken by the EnergyREV Research Consortium in developing a standardised Multi-Criteria Assessment (MCA) tool—specifically a discrete choice experiment (DCE) to determine the weighting of key performance indicators (KPIs). The MCA tool will use a technology-agnostic framework to assess SLES projects, track system performance and monitor benefit realisation. In order to understand the perceived relative importance of KPIs across different stakeholders, seven DCEs were conducted via online surveys (using 1000minds software). The main survey (with 234 responses) revealed that Environment was considered the most important criterion, with a mean weight of 21.6%. This was followed by People and Living (18.9%), Technical Performance (17.8%) and Data Management (14.7%), with Business and Economics and Governance ranked the least important (13.9% and 13.1%, respectively). These results are applied as weightings to calculate overall scores in the EnergyREV MCA-SLES tool.

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Section: Introductionmentioning

confidence: 99%

Weighting Key Performance Indicators of Smart Local Energy Systems: A Discrete Choice Experiment

et al. 2022

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The Nature Smart Cities business model: A rapid decision-support and scenario analysis tool to reveal the multi-benefits of green infrastructure investments

Oijstaeijen¹,

Silva²,

Back³

et al. 2023

Urban Forestry & Urban Greening

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Exploring Associations between Subjective Well-Being and Non-Market Values When Used in the Evaluation of Urban Green Spaces: A Scoping Review

Papastergiou

Latinopoulos

Evdou

et al. 2023

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Proximity and access to urban green spaces (UGSs) provide city dwellers with multiple benefits related to health and well-being. Understanding what (and how) characteristics of these spaces affect individuals’ perceived preferences and sense of well-being (subjective well-being) could be critical for relevant future planning interventions, policy design, and investments in green spaces. This scoping review aims to summarize, synthesize, and compare previous research findings about the application of (stated) preference-based methods, using non-market valuation techniques (e.g., willingness-to-pay methods), and non-preference-based measures of well-being (e.g., subjective well-being) to evaluate UGSs. By comparing these two methodologies, we aim to explore the differences and similarities among the determinants of benefits associated with UGS design and planning. We also seek to identify the most commonly used research approaches for measuring and/or projecting the impact of (new or rejuvenated) UGSs on people’s welfare and well-being. The review focuses on peer-reviewed empirical scientific work published during the period from 2010 to 2022.

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The politics of green infrastructure: A discrete choice experiment with Flemish local decision-makers

Cited by 3 publications

References 51 publications

Weighting Key Performance Indicators of Smart Local Energy Systems: A Discrete Choice Experiment

Weighting Key Performance Indicators of Smart Local Energy Systems: A Discrete Choice Experiment

The Nature Smart Cities business model: A rapid decision-support and scenario analysis tool to reveal the multi-benefits of green infrastructure investments

Exploring Associations between Subjective Well-Being and Non-Market Values When Used in the Evaluation of Urban Green Spaces: A Scoping Review

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