Spatial clustering of knowledge-based industries in the Helsinki Metropolitan Area

Chica, Juan Eduardo

doi:10.1080/21681376.2016.1189848

Cited by 9 publications

(7 citation statements)

References 26 publications

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“…In the last two decades, the analysis of KE has been tackled from segmented approaches based on quantitative and econometric analyses, such as indicators, composite indexes, OLS regressions, cluster or factorial analyses (Hall and Pain, 2006;Raspe and van Oort, 2006;Combes and Gobillon, 2015). However, in our attempt to achieve an integrated characterisation of the growth and spatial distribution of KE, we suggest a multistep method based on some of the previous partial analyses: (i) for assessing the effect of borrowed-sized, based on Meijer and Burger (2015) or Chica (2016), a regression model is proposed. Variables are nevertheless adjusted to the case study.…”

Section: Methodsmentioning

confidence: 99%

“…(ii) for characterising specialisation and diversity processes, following Méndez and Sanchez-Moral (2011) or Chica (2016), and based on an economic characterization of each city, a cluster analysis is suggested; and, finally, (iii) for assessing the path dependence effect on KE concentrations, we also suggest a regression model. In this model, the independent variables are, on the one hand, the location coefficient of skilled workers and knowledge-based activities concentrations (based on Volgmann and Münster, 2018) and, on the other hand, the Shannon-Wiener index of amenities/facilities (such as in Chong et al, 2020).…”

Section: Methodsmentioning

confidence: 99%

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Knowledge Economy Clustering at the Intrametropolitan Level: Evidence from Madrid

et al. 2021

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Despite the increasing relevance of knowledge-based activities in the global economy, their spatial distribution at the intrametropolitan scale has rarely been studied. The aim of this paper is to shed light on the intrametropolitan spatial localisation of knowledge-based activities by assessing some of its main causal mechanisms, paying special attention to agglomeration economies and borrowed size (both questioned in the era of Information and Communications Technologies because of the theorised 'death of distance'), the controversial role of industrial diversity and specialisation (traditionally considered exclusive processes) and path dependence.The empirical application refers to the case of the Madrid urban region for the period between 2012 and 2017. This study area proves particularly appropriate for two main reasons. First, the area is a main urban region in the European and global urban systems. Second, the area is a good example of a multicore urban region with a traditionally strong metropolis. The results show that the knowledge economy remains strongly dependent on the size of the city itself (agglomeration economies) and of the surrounding areas (borrowed size), that the specialisation and diversity processes are complementary and appear at different scales and that, in the specialisation of certain areas in some knowledge economy activities, the city's trajectory (path dependence) plays an important role. The results of the present study have various practical implications for policymakers when considering not only strategies (and investments) to coordinate land availability, worker training, connections between research centres and companies and amenities but also strategies to coordinate with the surrounding municipalities (e.g. in terms of mobility or joint public and private projects).

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Knowledge Economy Clustering at the Intrametropolitan Level: Evidence from Madrid

et al. 2021

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“…It is the largest and most powerful concentration of population and economic activity in Finland. While being rather small metropolitan area by European standards, it has been considered as one of the leading knowledge-intensive hubs even in global comparison, as exemplified by various international rankings and benchmarking studies [36,55]. For example, the Helsinki-Uusimaa Region is the most innovative region in the EU according to the European Commission's Regional Innovation Scoreboard of 2019.…”

Section: The Case Of Helsinki Metropolitan Areamentioning

confidence: 99%

City as a Growth Platform: Responses of the Cities of Helsinki Metropolitan Area to Global Digital Economy

2020

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The aim of this article is to shed light on how ongoing structural change towards the global digital economy condition urban economic development. Discussion starts with a brief reference to the growth machine thesis and its emphasis on the interests of local land and real estate owners. This theory serves as a contrasting point for the second element of our framework, the platform economy, which brings digital platforms and the transnational capitalist class into the picture. The transition from the urban growth machines of the industrial age to the digital growth platforms of the information age imply a radical change in the context of urban economic development. On this basis, we discuss cities’ need to adjust their growth strategies to the conditions of the emerging platform economy. Our illustrative case is the capital region of Finland. We interviewed officials and experts who hold key positions in the design of economic development policy in the three largest cities of this area. The empirical results show that the platform economy is rather vaguely conceptualized, and its challenges are ambiguously addressed. Cities have, however, started to adopt platform and ecosystem thinking in their strategies and established urban innovation platforms, talent and start-up attraction programs, and open data initiatives that reflect the gradual adoption of platform logic in urban economic development.

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“…In contrast, no consensus can yet be distilled from the literature on the role of KBIs in the reconfiguration of cities at the regional scale. For example, in his analysis of the spatial clustering of KBIs in the Helsinki region, Chica (2016) notes that geographical proximity to the CBD is also a key factor for the emergence of new KBI clusters. However, as Spencer (2015) as well as Münter and Volgmann (2014) observe, this does not apply to all KBI branches.…”

Section: Regional Studies Regional Sciencementioning

confidence: 99%

“…Regional StudieS, Regional Science knowledge intensities (Chica, 2016;Krätke, 2007;Muñiz & Garcia-López, 2010). EUROSTAT adopted this OECD definition of both KIS sectors 4 and technology-intensive industries/manufacturing industries 5 (NACE Rev.…”

Section: Systemizing Knowledge-based Industries (Kbis)mentioning

confidence: 99%

Specialization of and complementarities between (new) knowledge clusters in the Frankfurt/Rhine-Main urban region

Volgmann

Münter

2018

Regional Studies, Regional Science

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The spatial distribution of economic activities in urban regions in post-industrial countries can be interpreted as the result of the play of power between metropolization and regionalization processes. On the one hand, the globalization of the economy and the growing importance of the knowledge economy contribute to the metropolization of the global urban system, with metropolitan regions gaining in importance (

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Spatial clustering of knowledge-based industries in the Helsinki Metropolitan Area

Cited by 9 publications

References 26 publications

Knowledge Economy Clustering at the Intrametropolitan Level: Evidence from Madrid

Knowledge Economy Clustering at the Intrametropolitan Level: Evidence from Madrid

City as a Growth Platform: Responses of the Cities of Helsinki Metropolitan Area to Global Digital Economy

Specialization of and complementarities between (new) knowledge clusters in the Frankfurt/Rhine-Main urban region

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