| Literature DB >> 35244894 |
Amelia Leavesley1, Alexei Trundle2, Cathy Oke2.
Abstract
City action is critical to achieving global visions for sustainability such as the UN's Sustainable Development Goals (SDGs). However, SDG 'localisation' is complex procedure, with divergent outcomes depending on context and diverse city processes. This paper considers the operational challenges faced by city actors in taking on the SDGs, and subsequent implications for initiating local (and global) sustainability transitions. We analyse emergent approaches to SDG localisation within the Asia-Pacific, using a policy analysis framework (transition management) to assess transformation potential. We find that SDG localisation can influence urban sustainability, but effective implementation requires sufficient data, resourcing, and guidance-which are not readily, nor equally available to all city governments. City-to-city peer learning can accelerate SDG uptake, but realising the transformative ambition set out by the SDGs will require an approach to localisation that clearly demonstrates why and how any city government can and should engage with global sustainability frameworks.Entities:
Keywords: City actors; Engagement; Local government; SDG localisation; Transition management
Mesh:
Year: 2022 PMID: 35244894 PMCID: PMC8895692 DOI: 10.1007/s13280-022-01714-2
Source DB: PubMed Journal: Ambio ISSN: 0044-7447 Impact factor: 5.129
Fig. 1Study sample: cities in the Asia–Pacific localising the SDGs.
(Source: author)
Success factors for managing sustainable transitions,
adapted from Loorbach (2010) and Frantzeskaki et al. (2012)
| Transition management spheres | Type of change | Policy success factors/analysis elements |
|---|---|---|
| Strategic | Cultural | Vision and objectives, goals and targets, leadership, internal buy-in (champions) |
| Tactical | Structural | External buy-in (alliances and partnerships), community engagement, policy integration |
| Operational | Practical | Technical skills, delivery mechanisms, resources for implementation |
| Reflexive | Temporal | Indicator sets, monitoring and evaluation, city to city learning |
Specific localisation ‘challenges’ identified by participants as part of the SDGs Cities Challenge programme (sourced from Connected Cities Lab 2020). Participants were asked to select a local project and relate it to one or more targets within SDG11
| City | SDG | City Challenge |
|---|---|---|
| Dehradun | 11.2 | Our proposal calls for a children friendly mobility plan for the city, with emphasis on providing access to safe and affordable mobility systems in their journey from home to school |
| Melbourne | 11.7 | The City of Melbourne’s challenge is using or modifying SDG targets and indicators to track and understand how well they are adapting the city to climate change impacts |
| Newcastle | 11 | Our challenge is to integrate SDG11 into our Indicator Framework |
| Warrnambool | 11 | …to find ways to effectively measure, report and track the impact of climate change and adaptation programmes in urban development within the city |
| Whitehorse | 11.1, 11.6 | …to develop a robust sustainable procurement process that measures the whole life-cycle sustainability of procured goods and services and incorporates an effective assessment and monitoring system |
| Woollahra | 11.6 | …to develop a framework to set community resource use and emissions reductions targets and to develop a strategy and system to monitor, track and report on our progress towards these targets |
VLR analysis, exploring synergies between the content involved with SDG localisation and the success factors for transition management
| City | VLR Year | # pages | Strategic | Tactical | Operational | Reflexive | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Vision, objectives | Goals, targets | Mayoral endorsement | Supporting strategies | Alliances, engagement | Dedicated resources | Delivery mechanisms | Monitoring, evaluation | City-to-city learning | |||
| Cauayan | 2017 | 7 | x | x^ | – | – | x | – | x | – | – |
| Kitakyushu+ | 2018 | 58 | xx | xx | x | xx | xx | x | xx | x | x |
| Shimokawa+ | 2018 | 60 | xx | xx | x | x | xx | x | x | xx | x |
| Toyama+ | 2018 | 56 | xx* | xx | x | xx | x | x | x | – | x |
| Hamamatsu+ | 2019 | 48 | xx* | x^ | x | xx | xx | – | x | x | x |
| Suwon+ | 2018 | 35 | x | xx | x | x | x | x | xx | x | x |
| New Taipei | 2019 | 131 | xx | x | x | x | x | x | x | x | x |
| Taipei | 2019 | 80 | xx | xx | x | x | x | x | xx | – | x |
- Not stated, x Included but with little detail, xx Detailed coverage, +Document co-created with partner organisation, *Vision beyond 2030, ^No targets specified
Fig. 2Overview image of analysis outcomes across fourteen cities within the Asia–Pacific region.
(Source: author)