https://orcid.org/0000-0001-8313-7755
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ABSTRACT
The volume of urban transportation sustainability assessments in academic literature has steadily increased over the last two decades. This paper targets these studies through the first systematic literature review to construct a synthesised and critical overview of how urban transportation sustainability is in fact assessed. The sample consists of 99 peer-reviewed articles retrieved via three scientific search engines. The results reveal a Europe-centric and single-case focus, a strong interest to introduce new indicator systems with limited references to previous work, and a lack of qualitative approaches and stakeholder diversity regarding the assessment methods. Nearly 2400 indicators are identified in the articles with significant variation in their use. Furthermore, the comprehensive accounting for sustainability is often overlooked, and the inconclusive assessment results are often noted by the authors of the sample articles themselves. Our findings signal that the research field is highly fragmented and to some extent fails to accumulate knowledge generated by past studies and to comprehensively operationalise the concept of sustainability. The identified shortcomings of the assessments and their implications for transportation policy-making and planning are highlighted, and based on our results recommendations to develop more reliable, comparable, and inclusive sustainability assessments for the urban transportation sector are made.
Acknowledgements
We thank the three anonymous reviewers for their valuable suggestions and comments.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 The annual sub-sample for 2019 is incomplete as the systematic searches were conducted early in the year. Therefore, the volume of publications for 2019 should be treated as incomplete in relation to publication trends.
2 The indicator regrouping was performed manually in Excel 2016 under thematically cohesive groups of indicators that emerged from the dataset. Similar indicators were merged together if they measured exactly the same phenomenon.