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Towards a theory of SocioCitizenry: Quality anticipation, trust configuration, and approved adaptation of governmental social media

Research output: Contribution to journalArticlepeer-review

116 Scopus citations

Abstract

The past few years have witnessed growing governmental interest in engaging citizens through social media. With this interest comes a genuine need to understand the process and outcomes of government–citizen interactions. Therefore, this article seeks to address this important issue by proposing and validating a SocioCitizenry theory that depicts government–citizen interaction through social media. The present study uses data gathered through two field surveys and analyses the relationships among three main SocioCitizenry constructs: quality anticipation, trust configuration, and approved adaptation. The following factors are examined with respect to the aforementioned three constructs: differential influences of familiarity with social media and government services; perceived importance of interactions with government services; social media quality reputation; and family members’ and friends’ perceptions of social media quality. Overall, results show that anticipated governmental social media quality influences configured trust, which in turn influences the extent of approved adaptation. The implications of these results in research and practice are discussed.

Original languageEnglish
Pages (from-to)261-272
Number of pages12
JournalInternational Journal of Information Management
Volume43
DOIs
StatePublished - Dec 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Ltd

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 16 - Peace, Justice and Strong Institutions
    SDG 16 Peace, Justice and Strong Institutions

Keywords

  • Governmental social media
  • Quality
  • SocioCitizenry

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Marketing
  • Library and Information Sciences
  • Artificial Intelligence

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