International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

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 Volume 13, Issue 4 (April 2026), Pages: 108-121

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 Original Research Paper

The impact of perceived government public service quality on social network development and trust formation: Evidence from ten villages in Guangdong Province

 Author(s): 

Zhang Lina 1, 2, *, Doris Padmini Selvaratnam 1

 Affiliation(s):

1Faculty of Economics and Management, Universiti Kebangsaan Malaysia, Bangi, Malaysia
2School of Management, Guangzhou College of Technology and Business, Guangzhou, China

 Full text

    Full Text - PDF

 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0009-0007-1889-5040

 Digital Object Identifier (DOI)

  https://doi.org/10.21833/ijaas.2026.04.011

 Abstract

This study investigates how residents’ perceptions of government public service quality affect social capital formation in ten villages in Guangdong Province, China. Using data from 388 respondents collected in 2025, structural equation modelling was applied to examine the effects of perceived infrastructure quality and perceived social service quality on social networks and trust. A conceptual model was tested that included both direct effects and indirect effects through interaction opportunities. The results show that both types of perceived service quality significantly promote social capital, with perceived infrastructure quality (β = 0.235) having a slightly stronger effect than perceived social service quality (β = 0.210). Interaction opportunities played a significant mediating role (β = 0.216), indicating that public spaces and community activities encourage social interaction and relationship building. The measurement model showed strong reliability and validity across all constructs (Cronbach’s α = 0.843–0.855; AVE = 0.760–0.774). These findings enhance understanding of rural development in China by demonstrating that positive perceptions of government service quality strengthen social ties during periods of rapid economic change. The study supports complementarity theory rather than substitution views in the state–society relationship and highlights the importance of aligning material development with efforts to build social cohesion. It also suggests that policy evaluation should combine quantitative investment indicators with residents’ qualitative assessments of service quality.

 © 2026 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

Public service quality, Social capital formation, Rural community development, Citizen perceptions, China

 Article history

Received 2 September 2025, Received in revised form 1 February 2026, Accepted 5 April 2026

 Acknowledgment

This article arises from an academic activity funded by EP-2018-001, Faculty of Economics and Management, Universiti Kebangsaan Malaysia. I am very grateful to Dr. Doris for her guidance and help in the paper-writing process. This paper is also part of the research results of the 2025 Foshan Social Science Planning Support Project "Research on Factors Influencing the Residence Intention and Countermeasures of High-tech Talents in Foshan under the Background of High-quality Development" (Project No.: 2025-GJ106). Therefore, I am also very grateful to the Foshan Social Science Planning Center and Guangzhou Technology and Business University for their support and help for this project. 

 Compliance with ethical standards

 Ethical considerations:

Informed consent was obtained from all participants prior to data collection. Respondents were assured of anonymity and their right to withdraw at any time. 

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

Lina Z and Selvaratnam DP (2026). The impact of perceived government public service quality on social network development and trust formation: Evidence from ten villages in Guangdong Province. International Journal of Advanced and Applied Sciences, 13(4): 108-121

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