Smart Cities Ranking of European medium-sized cities, 2007

The first attempts to measure the smartness of cities proved unsuitable, since they combined criteria that did not collimate with each other and ultimately provided inaccurate assessments. Furthermore, these models did not highlight the strengths and weaknesses of the cities analysed, so as not to favour neither a change nor the identification of a successful trend.

Smart Cities Taxonomies

45 Smart cities Ranking of European medium-sized cities, 2007 was the first work that brought greater clarity in the classification of smart cities. Giffinger and the other scholars of the University of Vienna proposed a tool that did not give a univocal definition of what a smart city was. It instead analysed and evaluated the results that were achieved through six categories:

• Smart Economy: the smart economy refers to the circumstance according to which the inhabitants generate new ideas and work in order to optimize revenues with the least possible effort. This concept is called the maximum productivity cycle. Cities will have to take advantage of the opportunities created by the introduction of technological innovations and the use of ICT in order to increase competitiveness in the market and to grow the local economy. In fact, the process of innovation of processes and services allows to optimize times and costs and, consequently, to increase profits.

• Smart Mobility: the need for smart mobility is imposed by the rapid increase in population and urbanism that has upset the balance of cities. The main element on which smart mobility focuses is the increase in transport efficiency in urban and neighbouring areas, so as to be able to reduce energy consumption, pollution and traffic. An example is represented by GPS systems that provide the driver with real-time traffic information, thus also advising the optimal route to reach the destination. Another example of smart mobility is represented by the introduction of sharing mobility mechanisms (car sharing, bike sharing), that lead to a reduction in the number of vehicles on the road and the related CO2 emissions.

• Smart Environment: Environmental protection is the main concern of the last decades. In order to satisfy their needs, citizens have caused serious environmental damages through activities that do not comply with sustainability.

The smart environment involves the use of new technologies to offer more sustainable solutions, reducing the consumption of natural resources and reducing energy consumption, greenhouse gases and CO2 emissions. Functional for this purpose is the introduction of technological devices in the cities, such as sensors which allow to monitor air quality and pollution percentages in real time, so as to intervene to restore optimal conditions.

• Smart People: in addition to innovation and new technologies, a crucial role in the evolution of a city towards a smarter configuration is played by citizens and human capital. In fact, it is absolutely essential the collaboration between administrations and inhabitants, who are asked to be smarter in terms of capabilities, attitudes and skills. It is imperative for this transformation the active

Smart Cities Taxonomies

participation of citizens in the social sphere, which is favoured through initiatives, such as online consultation. In this way citizens, in addition to being users of goods and services offered by institutions, become protagonists of the transformation process of cities.

• Smart Living: this axis focuses on improving the quality of life of the citizen.

It starts from the assumption that cities and their inhabitants must be in a harmonious balance where technologies and innovations are used at the same time to meet the needs of citizens and improve the urban environment. In particular, the improvement of the quality of life of a citizen is ensured through intervention on various areas such as economic-social, safety and sustainability.

As regards security, for example, data collection and the transmission of these in real time have allowed the creation of devices capable of circumscribing areas with high probability of aggression, so that the police can, in a preventive perspective, work to reduce the incidence of such events.

• Smart Governance: Governments, as promoters and financiers of most smart initiatives, are an active part of the city change process. Smart Governance aims to operate in a transparent way and to involve citizens in the decision-making process, since with a greater participation of all the subjects of the city it is possible to start a process of improvement of urban areas.

For example, digital platforms have been created to offer citizens a series of information and data on the city in relation to different areas (environment, politics, safety, etc.) and which, at the same time, can be enriched and interpreted by the citizens themselves, leading to the development of high value-added services.

Giffinger believed that a medium-sized city could be considered intelligent when, based on the combination of local data and the activities carried out by politicians, by the economy and the inhabitants themselves, it presents a lasting development over time, of the six characteristics mentioned above.

The model envisaged using the 6 categories as a basis for city analysis, to then integrate more specific factors. In order to obtain a reliable measurement and ranking, a transparent hierarchical structure was used, where each level depended on the results obtained from the lower one.

The pyramid structure included 4 levels, the top of which was occupied by the target or the smart city, followed by the six categories, factors and indicators respectively (Figure 21).

The result of the first work was the identification of 31 factors and 74 indicators (Figure 22 and 23).

Smart Cities Taxonomies

47 The model proposed by Giffinger et alt revealed significant negative sides: indeed, it presented an undue mix of national and local indicators. In particular, while 65% of the indicators were based on local or regional data, 35% used national data and therefore could not be defined at an urban level. These critical issues have forced a rethinking of the model.

In the following years, in fact, scholars updated the proposed taxonomy, also trying to take into account the phenomenon of urbanization, arriving in 2015 with a model having 6 characteristics, 27 domains and 90 indicators.

Figure 21 - Giffinger et alt. (2007) taxonomy structure

Smart Cities Taxonomies

Smart Cities Taxonomies

49 Figure 23 - Giffinger et alt. taxonomy categories (2)

Smart Cities Taxonomies