A dataset on public participation intention in smart city development among Vietnamese citizens.

IF 1.9 Q3 MULTIDISCIPLINARY SCIENCES
Data in Brief Pub Date : 2026-08-30 eCollection Date: 2026-08-01 DOI:10.1016/j.dib.2026.113211
Thi Thanh Hoa Phan, Ho Diem Chau Nguyen, Le Trung Duong, Thi Yen Nhi Pham, Minh Tam Bui, Viet Hoang Le, Van Trung Tran
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引用次数: 0

Abstract

Our research presents a survey dataset on Vietnamese citizen's public participation intention in smart city development. The data was collected from residents living in three major urban areas in Viet Nam, namely Ha Noi, Da Nang, and Ho Chi Minh, which represent different contexts of smart city development. The survey was designed based on the smart city perception framework encompassing six dimensions such as Smart Economy, Smart People, Smart Governance, Smart Mobility, Smart Environment, and Smart Living combined with the Technology Acceptance Model (TAM), including its main components of perceived usefulness, perceived ease of use, and public participation intention in a smart city. In addition, trust in the new local government was implemented as a unique feature in the research model. Besides the theoretical constructs, the survey also collected respondents' demographic information, such as gender, age, educational level, workplace, and area of residence to support control analyses and comparisons across population groups. A total of 846 valid responses were retained for analysis. The dataset provides valuable empirical evidence for research on smart cities, technology acceptance behavior, and is available for comparative analyses across population groups and urban contexts in Viet Nam.

越南公民在智慧城市发展中的公众参与意愿数据集。
我们的研究提供了越南公民在智慧城市发展中的公众参与意愿的调查数据集。数据来自越南三个主要城市地区的居民,即河内、岘港和胡志明,这三个城市代表了智慧城市发展的不同背景。该调查是基于智慧城市感知框架设计的,该框架包含智慧经济、智慧人、智慧治理、智慧出行、智慧环境和智慧生活等六个维度,并结合技术接受模型(TAM),包括智慧城市的感知有用性、感知易用性和公众参与意愿的主要组成部分。此外,在研究模型中,对新地方政府的信任是一个独特的特征。除了理论建构之外,调查还收集了受访者的人口统计信息,如性别、年龄、教育程度、工作场所和居住地区,以支持跨人群的控制分析和比较。共保留846份有效回复进行分析。该数据集为智慧城市、技术接受行为的研究提供了宝贵的经验证据,并可用于越南不同人口群体和城市背景的比较分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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