The growing interest and debate on smart cities and the vast literature on this topic (Hollands, 2008; Caragliu et al., 2009, Nijkamp et al., 2011) led to the identification of a number of characteristic factors, such as economic development, environment, human capital, culture and leisure, and finally e-Governance. Factors that have been structured in a recent research conducted by the University of Vienna, Delft and Ljubljana (http://www.smart-cities.eu/) in some intangible indicators: smart economy, smart mobility, smart environment, smart people, smart living, smart governance; factors and indicators declined according to a hierarchical and unweighted framework. Having in mind the limits of the methodology used to define the concept of smartness and the resulting ranking of some European cities, the aim of our analysis is to use a more complex empirical model based on the concept of output maximizing. This method allows us to build a stochastic frontier to which decision makers can refer in order to assess the economic distance that separates them from being smart. The methodology, developed by Battese and Coelli (1995), allows to incorporate in the analysis peculiar (or rather structural or context) characteristics of each European city within the error that is called technical inefficiency. Moreover, this approach allows to distinguish the inputs from the factors of efficiency / inefficiency and to calculate the distance of every single city from the frontier of efficiency by splitting the error into a systematic component (which therefore depends on the structural characteristics of city) and in the error itself. The conclusion of the work is the construction of a ranking of European cities that find in the technical inefficiency a kind of weighting term.

Smart Cities and a Stochastic Frontier Analysis: A comparison among European cities

MUNDULA, LUIGI;
2012-01-01

Abstract

The growing interest and debate on smart cities and the vast literature on this topic (Hollands, 2008; Caragliu et al., 2009, Nijkamp et al., 2011) led to the identification of a number of characteristic factors, such as economic development, environment, human capital, culture and leisure, and finally e-Governance. Factors that have been structured in a recent research conducted by the University of Vienna, Delft and Ljubljana (http://www.smart-cities.eu/) in some intangible indicators: smart economy, smart mobility, smart environment, smart people, smart living, smart governance; factors and indicators declined according to a hierarchical and unweighted framework. Having in mind the limits of the methodology used to define the concept of smartness and the resulting ranking of some European cities, the aim of our analysis is to use a more complex empirical model based on the concept of output maximizing. This method allows us to build a stochastic frontier to which decision makers can refer in order to assess the economic distance that separates them from being smart. The methodology, developed by Battese and Coelli (1995), allows to incorporate in the analysis peculiar (or rather structural or context) characteristics of each European city within the error that is called technical inefficiency. Moreover, this approach allows to distinguish the inputs from the factors of efficiency / inefficiency and to calculate the distance of every single city from the frontier of efficiency by splitting the error into a systematic component (which therefore depends on the structural characteristics of city) and in the error itself. The conclusion of the work is the construction of a ranking of European cities that find in the technical inefficiency a kind of weighting term.
2012
stochastic frontier; smart cities; technical inefficiency
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/48525
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