The level of interest in smart cities has been growing during these last years. The academic literature (Holland, 2008;Caragliu et al., 2009, Nijkamp et al., 2011 and Lombardi et al., 2012) has identified a number of factors thatcharacterise a city as smart, such as economic development, business-friendly, environmental sustainability, socialinnovation, information and knowledge process, and human and social capital. Thus, the smartness concept is strictlylinked to urban efficiency in a multifaceted way as well as to citizens’ wellbeing through the use of appropriatetechnologies. Instead, from a “political perspective” smartness is mainly related to the ability of using ICT (Informationand Communication Technology) as instrument to strengthen economic growth. In this perspective, a research byGiffinger et al. (2007) to support European policy has defined the concept of smart city on the basis of severalintangible indicators (such as a smart economy, smart mobility, smart environment, smart people, smart living, andsmart governance) and has become a benchmark for European policy makers (European Parliament’s Committee onIndustry, Research and Energy, 2014). Following this influential research, the aim of our paper is to verify how muchthese smartness indicators can influence the efficiency and indirectly the growth of the same sample of European cities.Using the concept of output maximising, we built a stochastic frontier function in terms of urban productivity and/orurban efficiency by assessing the economic distance that separates cities from that frontier. Moreover, this approach,which distinguishes between inputs and efficiency, allows us to incorporate the smartness indicators into the systematiccomponent within the error term. As a result, our conclusions identify a different ranking of European cities withrespect to Giffinger et al. (2007) analysis, thereby highlighting the need for a better and more robust definition of theseindicators.
|Numero di pagine||36|
|Stato di pubblicazione||Published - 2015|