Paths to open government data reuse: A three-dimensional framework of information need, data and government preparation

Wang, Fang; Zhang, Zhaoqi; Ma, Xin; Zhang, Yichen; Li, Xuguang; Zhang, Xiaofei

doi:10.1016/j.im.2023.103879

Cited by 6 publications

(2 citation statements)

References 100 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Meaning that instructional rules transfer their effects to SRI partly through perceived data usefulness. It suggests that data instructions can make researchers think the data is useful because they provide clear guidance on how to use and interpret the data effectively; when researchers perceive the data is useful or of high quality, they will be satisfied with the data and generate greater reuse intention (Wang et al, 2023).…”

Section: Testing the Direct And Indirect Effects Of Individual Instit...mentioning

confidence: 99%

How do institutional dimensions of open government data affect innovation? Evidence from research institutes in China

Mu,

Zhao

2024

AJIM

View full text Add to dashboard Cite

PurposeThis study investigates the individual and binary (i.e. combined) effects of institutional dimensions of open government data (which include instructional, structural and accessible rules) on scientific research innovation, as well as the mediating roles that researchers' perceived data usefulness and data capability play in between.Design/methodology/approachBased on a sample of 1,092 respondents, this study uses partial least squares structural equation modeling (PLS-SEM) and polynomial regression with response surface analysis to evaluate the direct and indirect effects of individual and binary institutional dimensions on scientific research innovation.FindingsThe findings demonstrate that instructional, structural and restricted access data have a positive effect on scientific research innovation in the individual effect. While the binary effect of institutional dimensions produces varying degrees of scientific research innovation. Furthermore, this study discovers that the perceived usefulness and data capability of researchers differ in the mediating effect of institutional dimensions on scientific research innovation.Originality/valueTheoretically, this study contributes new knowledge on the causal links between data publication institutions and innovation. Practically, the research findings offer government data managers timely suggestions on how to build up institutions to foster greater data usage.

show abstract

Section: Testing the Direct And Indirect Effects Of Individual Instit...mentioning

confidence: 99%

How do institutional dimensions of open government data affect innovation? Evidence from research institutes in China

Mu,

Zhao

2024

AJIM

View full text Add to dashboard Cite

show abstract

“…Current research on continuance intention mainly involves fields such as the Learning community ( 10–12 ), tourism business ( 13 , 14 ), and information dissemination ( 15 , 16 ). Not as much research has focused on the field of digital health, so our study aimed to fill that void.…”

Section: Introductionmentioning

confidence: 99%

Continuance intention and digital health resources from the perspective of elaboration likelihood model and DART model: a structural equation modeling analysis

Fei,

Zhou,

et al. 2024

Front. Public Health

View full text Add to dashboard Cite

BackgroundInternet hospitals, online health communities, and other digital health APPs have brought many changes to people’s lives. However, digital health resources are experiencing low continuance intention due to many factors, including information security, service quality, and personal characteristics of users.MethodsWe used cross-sectional surveys and structural equation modeling analysis to explore factors influencing user willingness to continue using digital health resources.ResultsInformation quality (β = 0.31, p < 0.05), service quality (β = 0.19, p < 0.05), platform reputation (β = 0.34, p < 0.05), and emotional support (β = 0.23, p < 0.05) have significant positive effects on user value co-creation behavior. Additionally, user trust and perceived usefulness could mediate the association between user value co-creation behavior and continuance intention, with mediation effects of 0.143 and 0.125, respectively. User involvement can positively moderate the association between user value co-creation behavior and user trust (β = 0.151, t = 2.480, p < 0.001). Also, user involvement can positively moderate the association between value co-creation behavior and perceived usefulness (β = 0.103, t = 3.377, p < 0.001).ConclusionThe keys to solving the problem of low continuance intention are improving the quality and service level of digital health resources, and promoting users’ value co-creation behavior. Meanwhile, enterprises should build a good reputation, create a positive communication atmosphere in the community, and enhance user participation and sense of belonging.

show abstract

Systematic Literature Review of Data Quality in Open Government Data: Trend, Methods, and Applications

Zainuddin,

Akhir

2024

IEEE Access

View full text Add to dashboard Cite

Paths to open government data reuse: A three-dimensional framework of information need, data and government preparation

Cited by 6 publications

References 100 publications

How do institutional dimensions of open government data affect innovation? Evidence from research institutes in China

How do institutional dimensions of open government data affect innovation? Evidence from research institutes in China

Continuance intention and digital health resources from the perspective of elaboration likelihood model and DART model: a structural equation modeling analysis

Systematic Literature Review of Data Quality in Open Government Data: Trend, Methods, and Applications

Contact Info

Product

Resources

About