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Cited by 171

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Smart City Research: Contextual Conditions, Governance Models, and Public Value Assessment

Open access
Meijer, Albert J., Gil-Garcia, J. Ramon, Bolívar, Manuel Pedro Rodríguez·2016·Social Science Computer Review

Abstract

There are three issues that are crucial to advancing our academic understanding of smart cities: (1) contextual conditions, (2) governance models, and (3) the assessment of public value. A brief review of recent literature and the analysis of the included papers provide support for the assumption that cities cannot simply copy good practices but must develop approaches that fit their own situation ( contingency) and concord with their own organization in terms of broader strategies, human resource policies, information policies, and so on ( configuration). A variety of insights into the mechanisms and building blocks of smart city practices are presented, and issues for further research are identified.

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Crossref · 10.1177/0894439315618890

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Metadata

Authors
Meijer, A. J., Gil-Garcia, J. R., & Bolívar, M. P. R.
Venue
Social Science Computer Review
Published
2016-08-03
Volume
34
Issue
6
Pages
647-656
ISSN
  • 0894-4393 (ISSN-L)
  • 1552-8286
OpenAlex
W2335816333
Cited by
171
References
6
FWCI
10.17
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Smart City Research: Contextual Conditions, Governance Models, and Public Value Assessment. https://app.cochat.ai/papers/10.1177/0894439315618890
The paper
Meijer, A. J., Gil-Garcia, J. R., & Bolívar, M. P. R. (2016). Smart City Research: Contextual Conditions, Governance Models, and Public Value Assessment. Social Science Computer Review. https://doi.org/10.1177/0894439315618890

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.