2009
DOI: 10.1111/j.1468-2257.2008.00461.x
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Spatial Effects in Website Adoption by Firms in European Regions

Abstract: The purpose of this paper is to provide empirical evidence on the neighboring effects of Internet adoption as measured by the percentage of firms with their own website in the European regions. This is the first study that explicitly analyzes the role played by spatial effects to explain website adoption for the European case. A set of instruments and techniques commonly used in the spatial econometrics framework is employed to test the hypothesis that proximity matters when explaining Internet adoption by fir… Show more

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Cited by 33 publications
(29 citation statements)
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References 69 publications
(114 reference statements)
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“…The indicators mentioned show the presence of a north-south geographical divide of ICT use at global/worldwide level and between the member states of the EU (Moroz, 2017;Cruz-Jesus et al, 2012;Schlichter and Danylchenko, 2014). In particular, for Europe, a spatial pattern of DD between the north, south and east of Europe is defined (Billon et al, 2009 and2016).…”
Section: The Measurement Of the Enterprise Dd In The Eumentioning
confidence: 99%
See 1 more Smart Citation
“…The indicators mentioned show the presence of a north-south geographical divide of ICT use at global/worldwide level and between the member states of the EU (Moroz, 2017;Cruz-Jesus et al, 2012;Schlichter and Danylchenko, 2014). In particular, for Europe, a spatial pattern of DD between the north, south and east of Europe is defined (Billon et al, 2009 and2016).…”
Section: The Measurement Of the Enterprise Dd In The Eumentioning
confidence: 99%
“…In May 2015, adopted a digital single market strategy (European Commission,2015) as one of its top 10 political priorities. In connection with this, the studies published on ICTs emphasise, above all, the economic effects and the inequalities of use according to countries (Bach, et al, 2013a;Billon et al, 2009) according to factors such as the GDP, the unemployment rate, the sectoral composition, the educational level, the agglomeration economies. The first studies were focused on bringing to light the spatial inequalities in the use of ICTs between the north and south of Europe (Billon et al 2008), but always in connection with households and the provision of ICT infrastructure (Tranos and Gillespie, 2009).…”
Section: Introductionmentioning
confidence: 99%
“…In both countries, trait exploration was more strongly related to new lifestyle options in regions with higher divorce rates, signifying a more individualized social ecology with more permissive social norms regarding individual lifestyle choices (Kraaykamp, ; Lester, ; Talhelm et al, ). Additionally, in Germany (but not Poland), exploration was more strongly related to new learning opportunities in regions with higher Internet domain registration rates, reflecting a culture of learning and innovation (Sternberg & Krymalowski, ; see also Billon et al, ). Importantly, these Personality × Context interactions occurred only with the corresponding socioecological indicator, but not with the other, noncorresponding one.…”
Section: Discussionmentioning
confidence: 99%
“…To index the strength of the societal trend toward lifelong learning, and hence the socioecological boundaries for exploring new learning opportunities, we used the Internet domain registration rate , or more specifically, the number of newly registered top‐level domains (Germany: .de; Poland: .pl) per 1,000 inhabitants in a given time period. As a measure of the amount of Internet content production in a region, domain registrations strongly mirror the innovativeness of the region, as well as its potential to create new knowledge (Sternberg & Krymalowski, ; see also Billon, Ezcurra, & Lera‐López, ). Internet domain registrations per capita were related to many aspects of the “knowledge economy,” such as a region's share of employees in the information and communication sector ( r = .52), the share of research and development employees ( r = .58), the share of students ( r = .25), and the number of patent applications per capita ( r = .49) in a study in Germany (Sternberg & Krymalowski, ).…”
Section: Methodsmentioning
confidence: 99%
“…5 This measurement part is almost identical every year; the only difference is that one of the indicators (sinceInt) is only present in year 2008. 6 In EQS, we use the least squares (LS) estimation option with robust standard errors. For the technical details of this method, see Satorra & Bentler (1990, 1994.…”
Section: A Confirmatory Factor Model For Longitudinal Datamentioning
confidence: 99%