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Perez Amaral, Teodosio [Verfasser:in] ; Valarezo, Angel [Sonstige Person, Familie und Körperschaft]; Lopez, Rafael [Sonstige Person, Familie und Körperschaft]; Garín Muñoz, Teresa [Sonstige Person, Familie und Körperschaft]; Herguera García, Iñigo [Sonstige Person, Familie und Körperschaft]

E-Commerce and Digital Divide in Spain Using Individual Panel Data 2008-2016

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  • Medientyp: E-Book
  • Titel: E-Commerce and Digital Divide in Spain Using Individual Panel Data 2008-2016
  • Beteiligte: Perez Amaral, Teodosio [Verfasser:in]; Valarezo, Angel [Sonstige Person, Familie und Körperschaft]; Lopez, Rafael [Sonstige Person, Familie und Körperschaft]; Garín Muñoz, Teresa [Sonstige Person, Familie und Körperschaft]; Herguera García, Iñigo [Sonstige Person, Familie und Körperschaft]
  • Erschienen: [S.l.]: SSRN, [2020]
  • Umfang: 1 Online-Ressource (30 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.3376544
  • Identifikator:
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments April 23, 2019 erstellt
  • Beschreibung: Digital technologies sometimes create digital divides. One of the remedies for certain divides in Europe is the creation of the Digital Single Market, of which e-commerce is one of the main elements. The focus of this work is e-commerce in Spain. The current study improves substantially on existing international literature by using a large and representative panel data set on individuals, with 133,420 observations for the period 2008-2016. Moreover, it uses economic models that incorporate previously omitted variables, and employs a variety of panel techniques. This paper starts by measuring digital divides and their evolution along time. Next, a model that incorporates previously neglected explanatory variables, such as income and digital skills, is formulated. Individual demand models are estimated using panel logistic regression techniques. This allows quantifying the impact of each of the socioeconomic and geographic characteristics on the adoption of the service. The resulting models have high explanatory power. Newly incorporated variables like income and digital skills are highly significant. Age, education, gender and geographical variables are also significant. The results also allow novel regional comparisons. Policy recommendations are derived, suggesting effective and affordable measures targeted at specific socio-demographic groups
  • Zugangsstatus: Freier Zugang