Do software and video game firms share location patterns across cities? Evidence from Barcelona, Lyon and Hamburg

Méndez-Ortega, Carles; Arauzo‐Carod, Josep‐Maria

doi:10.1007/s00168-019-00917-y

Cited by 9 publications

(7 citation statements)

References 37 publications

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“…On the contrary, both advertising and IT companies were heavily concentrated in the inner cities and to a lesser extent also in the urban cores of Praha, Brno and Ostrava-despite significant differences in urban morphology: See Reference [51] for similar finding. This conclusion is different from the findings of Méndez-Ortega and Arauzo-Carod [21], who analyzed the localization of software and video games firms in Barcelona, Lyon and Hamburg. They found three different spatial patterns of firms that were probably shaped by the urban structures, local policies and path dependence.…”

Section: Discussioncontrasting

confidence: 98%

“…An extension of the above-mentioned method is addressed in more recently developed approaches (G, F or K functions). The K-function [21,[93][94][95] that considers all events and provides the standardized average number of events to the distance d from any event is used to provide greater detail on how the companies are clustered in space. Standardization is done by the intensity:…”

Section: Methodsmentioning

confidence: 99%

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Spatial Patterns of Knowledge-Intensive Business Services in Cities of Various Sizes, Morphologies and Economies

2020

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We compare intra-urban localization patterns of advertising and IT companies in three large Czech cities. The main aim of our analysis is an empirically-based contribution to the question to what extent do knowledge bases affect the spatial distribution of various knowledge-intensive business industries. The central research question is: To what extent is the localization of these two industries influenced by different modes of innovation/knowledge bases (symbolic vs. synthetic) and to what extent by contextual factors, such as urban size, morphology, position in the urban hierarchy and economic profile of the given city. We found that the urban contexts shape the localization patterns of advertising and IT companies more than differences in knowledge bases-both industries cluster primarily in the inner cities and urban cores. Formation of more suburban IT "scientific neighborhoods" is limited. significantly to the economic transformation of formerly industrial cities (considering IT, Brno is now the most specialized city in Czechia and Ostrava is the third) [13][14][15].Advertising is a representative of KIBS with a purely symbolic knowledge base. These companies should require tight geographical proximity to their customers, suppliers or rivals [16,17], and cluster in urban cores and dense inner cities, close to the headquarters of large corporations and public institutions. By contrast, services with a predominantly synthetic knowledge base (such as IT) rely primarily on knowledge sourcing and innovation collaboration with partners inside value chains, which are not necessarily local [18,19]. IT companies should, thus, exhibit more dispersed spatial patterns (However, Zook [20] documented clustering of internet companies in the inner city, close to the financial institutions, Spencer [12] also noted this possible location pattern), although they may cluster at the neighborhood level as well [12].Méndez-Ortega and Arauzo-Carod [21] stated that " . . . in addition to industry-specific characteristics that determine some external requirements by these firms (such as accessibility to skilled labour or specialized IT suppliers), there are some city-specific characteristics (e.g., urban policies, spatial distribution of economic activity) that also matter, and which shape the location decisions taken by these firms." We aim to analyze exactly these city-specific characteristics and their effects on the spatial distribution of firms. Our central research question is: To what extent are localization patterns of selected KIBS influenced by their distinct modes of innovation (knowledge bases) and to what extent by the city-specific characteristics?Funding: This research wJan Žas funded by the Ministry of Education, Youth and Sports through a research grant "SMART technologies to improve the quality of life in cities and regions" (no.

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Section: Discussioncontrasting

confidence: 98%

Section: Methodsmentioning

confidence: 99%

Spatial Patterns of Knowledge-Intensive Business Services in Cities of Various Sizes, Morphologies and Economies

2020

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“…Second, when we considered the technological heterogeneity of the industries, we found that high‐tech industries (80% of industries) are more often localized at short distances (up to 200 km) than low‐tech ones (50%). Although based on different methods, the evidence here is consistent with previous evidence presented by Audretsch and Feldman (1996) for the US, and more recently by Coll‐Martínez et al (2019) and Méndez‐Ortega and Arauzo‐Carod (2019, 2020) for the Metropolitan Area of Barcelona, Lyon, and Hamburg, about the tendency of knowledge‐intensive industries to cluster. We also observe that the pattern is consistent with the geographic configuration of large Brazilian urban areas and suggests that the agglomeration forces generated from geographic proximity can act more strongly in determining the spatial location of these industries.…”

Section: Discussionsupporting

confidence: 91%

“…The combination of these features and this overrepresentation at short distances appears consistent with the arguments associated with human capital spillovers in bigger urban areas (see, e.g., Ciccone & Hall, 1996; Dingel et al, 2019; Duranton, 2016; Fu, 2007; Moretti, 2004a, 2004b). This result is also in line with the recent evidence provided by Coll‐Martínez et al (2019) for creative industries (including some high‐tech industries) in the Metropolitan Area of Barcelona and by Méndez‐Ortega and Arauzo‐Carod (2019, 2020) for high‐tech industries in the Metropolitan Area of Barcelona, Lyon, and Hamburg.…”

Section: Location Of Brazilian Manufacturingsupporting

confidence: 91%

Manufacturing location patterns in Brazil

Almeida

Neto

Rocha

2022

Papers in Regional Science

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In this paper, we present a detailed and comprehensive analysis of the location patterns of manufacturing industries in Brazil using a distance‐based measure and micro‐geographic panel data for a 10‐year period. Our results show that 89.9% and 91% of manufacturing at the 3‐digit level have statistically significant localization for 2006 and 2015, respectively, and that these patterns remain high when we consider 4‐digit classification. High‐tech industries have location patterns at short distances, being localized mainly in large urban areas, while low‐tech industries are also localized at long distances. We also present evidence that agglomeration economies affect the degree of spatial concentration.

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“…For instance, as noted by Peck (2005) Moeller (2018) concentrates on Berlin, Germany, and points out that the location decisions of creative firms depends greatly on the location of creative employees and that such employees tend to locate in "amenity rich" urban places. Finally, Mendez-Ortega and Arauzo-Carod (2020) analyze the location decisions of firms in the software and video game (SVE) industry in Barcelona, Lyon, and Hamburg. Their results show that the urban cores of these three cities have a significant impact on the location decisions of creative firms even though other factors such as the "core-periphery distribution" of the SVE industry are also relevant.…”

Section: Empirical Perspectives On the Location Of Creative Industriesmentioning

confidence: 99%

The Response of Creative Class Members to Regions Vying to Attract Them With Subsidies

Batabyal

Beladi

2022

International Regional Science Review

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There are no theoretical studies in regional science that examine which region to locate in from the standpoint of a creative class member, given that the pertinent regional authorities (RAs) are competing among themselves to attract the creative class using subsidies. This gap provides the motivation for our paper. This paper’s contribution is that it is the first to theoretically study the regional location choice of creative class members when the RAs of the locations in which they might locate are using subsidies to attract them. Specifically, a knowledge good producing creative class member must decide which of two regions ( A or B) to locate his plant in. This good is produced using a Cobb–Douglas function with creative and physical capital. We analyze plant location in four cases. In the benchmark case, we show that the representative creative class member ought to locate his plant in the less expensive region B. Next, we show that a small subsidy to creative capital by region A switches the plant location decision from region B to A. Finally, when both regions grant identical subsidies to creative capital, the representative creative class member is indifferent between locating in regions A and B. So, for identical subsidies to affect the plant location decision, they are better targeted to physical and not to creative capital. JEL Codes: R11, R58

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Do software and video game firms share location patterns across cities? Evidence from Barcelona, Lyon and Hamburg

Cited by 9 publications

References 37 publications

Spatial Patterns of Knowledge-Intensive Business Services in Cities of Various Sizes, Morphologies and Economies

Spatial Patterns of Knowledge-Intensive Business Services in Cities of Various Sizes, Morphologies and Economies

Manufacturing location patterns in Brazil

The Response of Creative Class Members to Regions Vying to Attract Them With Subsidies

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