How Political Interest and Knowledge Shape Political Efficacy in Institutionalized Participation

Wei Cui et al.

International Journal of Electronic Government Research2025https://doi.org/10.4018/ijegr.387830article
ABDC C
Weight
0.37

What the paper says

This study examine the roles of internal and collective political efficacy across different forms of political participation, with a focus on how generative AI, used as a digital engagement tool by governments, influences citizens' political interest, knowledge, efficacy, and participation. The findings reveal that internal political efficacy significantly promotes political participation, especially non-institutionalized participation, while collective political efficacy plays a more limited role. The government's use of generative AI improves access to policy information and political participation opportunities. However, its impact on political efficacy depends on whether online engagement leads to real policy responsiveness. Policy responsiveness plays a key role in enhancing efficacy and sustained participation. This study shows that political efficacy is influenced by both individual cognition and external factors, highlighting the need for digital government strategies to combine innovation with effective policy feedback to better engage citizens.

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https://doi.org/https://doi.org/10.4018/ijegr.387830

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@article{wei2025,
  title        = {{How Political Interest and Knowledge Shape Political Efficacy in Institutionalized Participation}},
  author       = {Wei Cui et al.},
  journal      = {International Journal of Electronic Government Research},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.4018/ijegr.387830},
}

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How Political Interest and Knowledge Shape Political Efficacy in Institutionalized Participation

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.