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In recent years, the term “smart city” has attracted a lot of attention from policy makers, business leaders and citizenship in general. Although there is not a unique definition of what a smart city is, it is generally accepted that “smart” urban policies refer to local governments’ initiatives that use information and communication technologies in order to increase the quality of life of their inhabitants while contributing to a sustainable development. So far, “smart city” approaches have generally been related to top-down processes of technology diffusion. The purpose of this paper is to present a broader view on “smart” initiatives to analyze both top-down and bottom-up dynamics in a smart city. The authors argue that these two perspectives are complementary and its combination can reinforce the collaboration between different city stakeholders. Top-down and bottom-up initiatives are not opposed forces but, on the contrary, can have a synergistic effect on the innovation capacity of the city. Both perspectives are illustrated by providing examples of different “smart” aspects in the city of Barcelona: smart districts, open collaborative spaces, infrastructures and open data.

To illustrate the arguments, the authors analyze the case of the city of Barcelona providing examples of top-down and bottom-up initiatives in four different smart city aspects: smart districts, open collaborative spaces, infrastructures and open data. The research method is based on a case study (Yin, 1984). The primary data consisted on interviews to city council representatives as well as managers of local public institutions, like economic development offices, and local organizations like for instance coworking spaces. The authors interviewed also specialists on the innovation history of the city in order to validate the data. In addition, the authors used secondary data such as reports on the 22@, and documentation on the Barcelona innovation policies, as well as doing a compilation of press articles and the online content of the institutional webpages. All together, the authors have followed a data triangulation strategy to seek data validation based on the cross-verification of the analyzed data sources.

The analysis suggests that the top-down and bottom-up perspectives are complementary and their combination can reinforce the collaboration between different city stakeholders. Top-down and bottom-up initiatives are not opposed forces but, on the contrary, can have a synergistic effect on the innovation capacity of the city. Both perspectives are illustrated by providing examples of different “smart” aspects in the city of Barcelona: smart districts, open collaborative spaces, infrastructures and open data.

Nevertheless, the analysis has its limitations. Even if the authors have emphasized the importance of the bottom-up initiatives, citizens do not have often the resources to act without governmental intervention. This is the case of services that require high-cost infrastructures or regulatory changes. Also, as it usually happens in the case of disruptive technology, it is hard for citizens to understand the possibilities of its use. In these cases, firms and institutions must play an important role in the first phases of the diffusion of innovations, by informing and incentivizing its use. It is also important to note that some of the emerging usages of technology are confronted to legal or regulatory issues. For instance, distributed and shared Wi-Fi networks might be in opposition to economic interests of internet providers, that often difficult its expansion. It is also the case of services of the sharing economy that represent a menace to established institutions (like the tensions between Uber and taxi companies, or Airbnb and hotels). In these cases, city halls like it is the case in Barcelona, tend to respond to these emergent uses of technology by regulating to ensure protection to existing corporate services.

In conclusion, the transformational process that leads a city to become a smart city has to take in consideration the complexity and the plurality of the urban reality. Beyond considering citizens as being users, testers or consumers of technology, local administrations that are able to identify, nourish and integrate the emerging citizens’ initiatives would contribute to the reinforcement of a smart city reality.

The contribution of the paper is to go beyond the generalized technologic discourse around smart cities by adding the layer of the citizens’ initiatives.

The purpose of this paper is to analyse how digital technologies trigger changes in the business process of manufacturing small and medium-sized enterprises (SMEs) in the Apulia Region (South Italy). As SMEs play an essential role in the process value creation of industries and countries, the article examines the enablers of Industry 4.0 in a regional contexts characterized by delay in research and development and innovation performances where the companies' competitiveness is based on limited knowledge and technological assets.

The case study of Smart District 4.0, an ongoing project aimed to promote the digitalization of SMEs operating in the Agri–Food, Clothing–Footwear and Mechanics–Mechatronics in the Apulia Region (South Italy) is analysed. The project has been financed by the Italian Ministry of Economic Development with the final aim to sustain the digital transformation of SMEs in South Italy.

The results introduce a four levels approach of engagement of SMEs in the adoption of digital technologies, namely, digital awareness, digital enquirement, digital collaboration and digital transformation. Furthermore, for each level of engagement the study describes and discusses some relevant variables that could be used by managers and entrepreneurs to assess the level of readiness for utilization of digital technologies and how to digitalize some processes.

Practical implications regard the definition of a roadmap useful to assess and manage the level of digital transformation of SMEs. Limitations of the study regarding the temporal dimension of the evidences associated to the Smart District 4.0 as well as to the regional context was analysed.

Originality resides in the definition of a roadmap for the digital transformation of SMEs in a region where the profile of companies' digital maturity is still low.

In this chapter, I unpack the idea of “smart community” conceived in relation to the first “smart district” in Italy, Milano 4 You, that will be realized in Segrate, one of the wealthiest municipalities of Italy located in the Milanese metropolitan area. Through the lenses of critical political economy, notably the work of Miranda Joseph and David Harvey, the chapter focuses on the economic rationality behind the “smart community,” that is, a community of production and consumption. In fact, the new residents are envisaged as self-entrepreneurs willing to re-appropriate their data and sell them for profit, while sharing a “smart” lifestyle. However, the chapter avoids a reductionist and negative reading, highlighting the potential for contestation and alternative rationalities to emerge.

The purpose of this paper is to introduce a critical framework to analyse how “smart” plays out in tourism places. Moving from a recognition of the strategies, expected impacts and imageries of Smart City, the authors engage with the mobilities literature to identify pitfalls in the quest of “smartening up” cities for hypermobile populations.

The study adopted a set of geoanalytical techniques to establish the potential relationship between the territorial upgrade of mobility and the socio-economic change processes the city of Barcelona is experiencing.

The paper suggests the effect of “smart” in cities could indeed be one of economic recovery; however, one triggering fundamental transformation of the social fabric of the city, whose most evident facet is the creation of globalised functional enclaves that may be forcefields of exclusion for the most vulnerable populations.

This paper contributes to a new stream of critical research on “smart” with a strong focus on the power of mobilities and mobility systems, whose digital enhancement plays out as a leveraging agent of new place connections and negotiations for short-term populations, but at the same time, may exclude disadvantaged subjects in their capacity to access and afford the system network.

The purpose of this paper is to understand the perceptions of visitors in terms of multiple aspects of smart cities to allow wise decisions to be made about smart tourist destinations by municipal governments and tourism authorities.

This study takes a sample of inbound visitors (n=205) from Hong Kong as an empirical questionnaire-based survey on visitors’ perceptions of these smart city attributes, which are collected from literature, and framed in Cohen’s Smart City Wheel.

This paper identifies the distinctive factors for branding Hong Kong as a smart city. The results from the factor analysis identify four factors for determining what a smart city is from the perspective of visitors, namely, the quality of a smart society: energy consumption in an urban environment, smart city governance and smart city livelihood. The first two factors further become the determinants of a successful smart city brand considered by visitors, which contribute to their locational decisions and thus the strategies and policies of smart destination branding.

The results obtained can serve as insights for tourism policy makers and destination marketers when considering significant information and communication technology, or other smart and sustainable attributes for city branding (e.g. Buhalis and Amaranggana, 2014; Marine-Roig and Anton Clavé, 2015), as well as common investment and resource allocation for shared benefits in similar metropolises.

The smartness factors represent important dimensions of urban smartness as prioritized areas for further development, innovation and marketing of tourism industries and enterprises in Hong Kong, as a mature urban destination incorporating the branding of a proposed smart district as a strategy of urban development.

Smart urban development and tourism development have increasingly become inseparable, especially when visitors utilize cities as tourist destinations but share other urban resources and spaces with local citizens. Unlike the development of smart tourist attractions, smart tourist destinations should have a wider scope of smartness. A smart tourist destination may carry similar and overlapping characteristics of smart cities, which may be interpreted by visitors and may eventually affect their perceived image of a city.

The purpose of this paper is to compare and contrast amenity mixes of innovation districts worldwide and to identify the types of amenities in the districts.

Urban amenity data were collected from Google Maps as 31,236 points of interest (POIs) in 24 innovation districts. The data were compared and categorised based on the density and diversity of amenity mixes using correspondence analysis. An overall amenity space of the 24 innovation districts was created using correlation and social network analyses.

This study found that innovation districts have broad ranges of diversity and density. Five groups were identified by correspondence analysis, including retail, foodie, balanced, emerging and health-care districts. The amenity space of innovation districts created using correlation and social network analyses categorised amenities into four broad types – necessary, anchor, vibrant and contextual amenities – based on eigenvector centrality scores and density.

To improve their innovation districts, managers are encouraged to create a foundation of innovations with anchor amenities, to ensure the “live-work-play” environment with necessary amenities, to foster buzz and vibes with vibrant amenities and to strengthen the identity and authenticity with contextual amenities.

Despite some understanding, no previous research has thoroughly analysed the amenities available in innovation districts. This study is the first to comprehensively explore the amenities in innovation districts using data from Google Maps. Place managers can use the method introduced in this research to analyse innovation districts and other kinds of places.