1,720,973 research outputs found
Institutions, firms and environment in a framework of innovation
No full textThe aim of the paper is the analysis of innovation and institution as the key elements for reaching a higher social welfare and environmental quality. To determine a social optimum or a Pareto improvement, we consider the interaction between institution and firm in the short and in the medium/long run. Using a static comparative analysis, the interaction of these two agents, institution and market, is examined. Within the market an entrant and an incumbent firm are present, where the entrant firm represents the firm who radically innovates. Even if in the short run results show that the market alone is able to realize a Pareto improvement, however, whenever institution intervenes through an innovation adoption, both in short and in medium/long run a preferable solution with a better performance is reached. Our main results highlight that the strategic role of an innovating institution in each case considered consists in innovating towards green technology and in creating a competitive, attractive and environmentally sustainable milieu. From this point of view, technology innovation plays a central role in an economic and territorial development, orienting and optimizing the relationship between environmental quality and firm performance
Smart Cities and Eu growth strategy: a Comparison among European Cities
No full textThe 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 that
characterise a city as smart, such as economic development, business-friendly, environmental sustainability, social
innovation, information and knowledge process, and human and social capital. Thus, the smartness concept is strictly
linked to urban efficiency in a multifaceted way as well as to citizens’ wellbeing through the use of appropriate
technologies. Instead, from a “political perspective” smartness is mainly related to the ability of using ICT (Information
and Communication Technology) as instrument to strengthen economic growth. In this perspective, a research by
Giffinger et al. (2007) to support European policy has defined the concept of smart city on the basis of several
intangible indicators (such as a smart economy, smart mobility, smart environment, smart people, smart living, and
smart governance) and has become a benchmark for European policy makers (European Parliament’s Committee on
Industry, Research and Energy, 2014). Following this influential research, the aim of our paper is to verify how much
these 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/or
urban 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 systematic
component within the error term. As a result, our conclusions identify a different ranking of European cities with
respect to Giffinger et al. (2007) analysis, thereby highlighting the need for a better and more robust definition of these
indicators
Smartness, City Efficiency and Entrepreneurship Milieu
No full textThe definition of smart city and its measurement are not shared. Different characteristics define a city
as smart, which is strictly linked to urban efficiency and to entrepreneurship spirit in a multifaceted
way as well as to citizens’ well-being. On the basis of the comparison between city and entrepreneur
behaviour and on the definition of Giffinger et al. (2007) of smart city, this chapter verifies the efficiency
of a sample of European cities using a stochastic frontier approach. Departing from this analysis, the
chapter develops the relative smartness definition based on the efficient use of its own resources and
related to the different context. Moreover, as a city becomes close to the optimal value, the frontier will
shift upward because of the more attractiveness and a new adjustment mechanism should be followed
to become efficient again (virtuous cycle). Then, the concept of smartness becomes dynamic. This definition,
taking into account city’s performance, is able to sustain the entrepreneurship milieu of a city
Il contrasto all’economia sommersa: un’analisi comparata di policies
No full textSOMMARIO: 1. L’economia non osservata. – 2. Economia sommersa e corruzione. – 3. La
consistenza del sommerso. – 4. Le motivazioni e le dinamiche sociali collegate
all’economia sommersa. – 5. Gli approcci per la lotta al sommerso in Europa:
deterrenza e incentivo. – 6. Conclusioni
Defining Smart Cities: a relative and dynamic approach
No full textAlthough the level of interest in smart cities is growing, the main issue – the smart city concept – is still
open. The definition of smart city is not shared as well as the way to measure city’s smartness. The main
approach has developed the concept of an “ideal” city which every city should tend because it represents the
optimal standard.
In this context, the aim of our paper is to break with the traditional point of view in favour of a new concept
of smartness which identifies a city specific value of smartness, based on the efficient use of its own
resources and related to the different context in which a city is situated. Thus, in this way, the concept of
smartness becomes relative. Moreover when a city is very close to optimal value (i.e. maximum efficient
frontier) then the frontier will shift upward because of the more attractiveness of the city but after a while the
performance of the city goes down and a new adjustment mechanism should be followed to become efficient
again (virtuous cycle). The needed time to be close again to the frontier will be correlated to the degree of
inertia (reaction time) of urban government. So the smartness concept becomes dynamic as well as relative
because it depends on how long the city takes to react and change the direction of its own performance to
become smart again
Public Choices and Decision-Making Processes: a Case Study on Sustainable Mobility
Full text linkThe definition of a decision process, which implies the capacity to implement and realize an action involving all the actors interested, is crucial not only for taking adequate political decisions but even mainly for getting a democratic control of the decisions themselves.
From a strategic planning point of view, decision process on public issues should be essentially considered as a process of participation, which involves political decision-makers as well as all the administrative organizations which have to realize the decisions taken and citizens and more generally all the stakeholders who will be impacted in a positive or negative way by such decisions. If this is the case, important issues arise: which is the methodology that should be followed to assess all the alternative solutions to adopt? How are analyzed the effects and the impacts of political decisions? How are evaluated the consequences of a set of actions?
To answer to all these questions, Decision Support Systems (DSSs) have been developed. They include measurement tools such as cost-benefit analysis as well as relational methods of “rational analysis” such as multicriteria analysis. DSSs’ allow decision makers to implement the best choices and decisions with the aim of reaching a Pareto improvement for the territory considered. Though these tools may be implemented to any socio-political decisions, in these last years the democratic and, therefore, political pressure has led to adopt DSSs’ mainly for two specific themes: the environment and the sustainable mobility.
Moreover, in the agenda of European institutions and local and national administrative governments, sustainable mobility is become a high priority. In this framework, the methodology1 proposed combines two different approaches. On the one hand, the “classic” or top-down approach based on statistical data analysis is considered where the main target is the definition of some synthetic indicators, while on the other hand, the bottom-up approach is adopted, which is based on the Strategic Environment Assessment (SEA) framework and on citizens’ participation. This decision process as defined, should be followed for implementing specific and appropriate solutions at local level and for taking into consideration the peculiarities of the territory considered. Finally, a case-study regarding the ex-13th District of the Municipality of Rome is presented
Smart cities: a policy tool for city efficiency?
Full text linkThe level of interest in smart cities has been growing during these last years. The academic literature (Hollands, 2008; Caragliu et al., 2009, Nijkamp et al., 2011 and Lombardi et al., 2012) has identified a number of factors that characterise a city as smart, such as economic development, business-friendly, environmental sustainability, social innovation, information and knowledge process, and human and social capital. Thus, the smartness concept is strictly linked to urban efficiency in a multifaceted way as well as to citizens’ wellbeing through the use of appropriate technologies. Instead, from a “political perspective” smartness is mainly related to the ability of using ICT as instrument to strengthen economic growth. A research by Giffinger et al. (2007) to support European policy has defined the concept of smart city on the basis of several intangible indicators (such as a smart economy, smart mobility, smart environment, smart people, smart living, and smart governance) and has become a benchmark for European policy makers (European Parliament’s Committee on Industry, Research and Energy, 2014). Following this influential research, the aim of our paper is to verify how much that smartness definition can influence the efficiency and indirectly the growth of the cities. Using the concept of output maximising, we built a stochastic frontier function in terms of urban productivity and/or urban efficiency by assessing the economic distance that separates cities from that frontier. Our conclusions highlight that not all the six indicators defined in the Giffinger et al. (2007)’ analysis contribute to strength the city efficiency
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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