JOURNAL ARTICLE

Smart innovations for sustainable cities: Insights from a public‐private innovation ecosystem.

  • Published In: Corporate Social Responsibility & Environmental Management, 2024, v. 31, n. 3. P. 1654 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Cambra‐Fierro, Jesús J.; López‐Pérez, Mª. Eugenia; Melero‐Polo, Iguacel; Pérez, Lourdes; Tejada‐Tejada, Macarena 3 of 3

Abstract

Over‐urbanization poses important challenges—both for citizen well‐being and quality of life, and for the sustainability of our planet. Traffic, accidents and pollution are just a few of the problems facing people living in cities. The need arises, then, to foster sustainable urban planning and management using, among other elements, smart solutions. In such a context, we would do well to reflect on effective economic, social, and environmental policies aimed at achieving sustainable cities and high quality of life for urban inhabitants. This article presents the most relevant aspects of the #eCity‐Sevilla project, a successful case of a sustainable public‐private innovation ecosystem. To this end, we take the Quintuple Helix Model as our reference, with a view to identify project stakeholders and better understand their relationships and objectives. Our data derives from secondary sources as well as from a set of in‐depth interviews with key informants. In the final section, the main theoretical and practical implications of our study are discussed. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Corporate Social Responsibility & Environmental Management. 2024/05, Vol. 31, Issue 3, p1654
  • Document Type:Article
  • Subject Area:Environmental Sciences
  • Publication Date:2024
  • ISSN:1535-3958
  • DOI:10.1002/csr.2660
  • Accession Number:176988685
  • Copyright Statement:Copyright of Corporate Social Responsibility & Environmental Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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