Temporal sustainability efficiency analysis of urban areas via Data Envelopment Analysis and the hypervolume indicator: Application to London boroughs. (1st December 2019)

• Record Type: Journal Article
• Authors: Pozo, C.; Limleamthong, P.; Guo, Y.; Green, T.; Shah, N.; Acha, S.; Sawas, A.; Wu, C.; Siegert, M.; Guillén-Gosálbez, G.
• Is Part Of: Journal of cleaner production. Volume 239(2019)
• Publication Date: 2019-12-01
• Subjects: Data envelopment analysis -- Hypervolume indicator -- Temporal analysis -- Sustainability -- London boroughs -- Urban systems; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2019.117839
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Transitioning towards a more sustainable society calls for systematic tools to assess the sustainability performance of urban systems. To perform this task effectively, this work introduces a novel method based on the combined use of Data Envelopment Analysis (DEA) and the hypervolume indicator. In essence, DEA is applied to (i) distinguish between efficient and inefficient urban systems through the identification of best practices; and to (ii) establish improvement targets for the inefficient urban systems that, if attained, would make them efficient. Meanwhile, the hypervolume indicator is employed in conjunction with DEA to evaluate how urban systems evolve with time. The capabilities of this approach are illustrated through its application to the sustainability assessment of London boroughs between 2012–2014. Results reveal that most boroughs tend to perform well in terms of the indicators selected, with 20–25 of the 32 boroughs found efficient depending on the year. Regarding the temporal assessment, a global improvement in sustainability performance was found, with a strong relationship between the boroughs' performances and their locations. The method proposed opens new pathways of social and environmental research for the application of advanced multi-criteria decision-support tools in the assessment and optimisation of urban systems.