Artificial Intelligence (AI) methods empowering empirical research in public policy: a review of theoretical foundations and practices
Research Article
Open Access
CC BY

Artificial Intelligence (AI) methods empowering empirical research in public policy: a review of theoretical foundations and practices

Youcheng Gu 1*
1 Business School, Soochow University, Suzho, China
*Corresponding author: youchenggu@outlook.com
Published on 22 September 2025
Journal Cover
JAEPS Vol.18 Issue 9
ISSN (Print): 2977-571X
ISSN (Online): 2977-5701
Download Cover

Abstract

Artificial Intelligence (AI) has become a key theoretical and practical focus in public policy, yet its specific applications and impacts in empirical public policy research still require in-depth exploration. Adopting a systematic literature review approach, this study collects recent literatures on the application of AI methods in empirical public policy research from the Web of Science Core Collection, as well as academic platforms such as CNKI and Wanfang Data. Through sorting and analyzing these literatures, this paper systematically combs the theoretical foundations of AI in the field of public policy and the practical applications of AI in empirical public policy research, aiming to reveal the current status of theoretical foundations and practical applications of AI methods in empirical public policy research.

Keywords:

Artificial Intelligence, public policy, empirical research

View PDF
Gu,Y. (2025). Artificial Intelligence (AI) methods empowering empirical research in public policy: a review of theoretical foundations and practices. Journal of Applied Economics and Policy Studies,18(9),28-32.

References

[1]. Acemoglu, D., & Restrepo, P. (2018). The race between man and machine: Implications of technology for growth, factor shares, and employment.American Economic Review, 108(6), 1488–1542.

[2]. Aghion, P., Bergeaud, A., Lequien, M., et al. (2022). The heterogeneous impact of market size on innovation: Evidence from French firm-level exports.Review of Economics and Statistics, 1–56.

[3]. Guo, K. M. (2019). Artificial intelligence development, industrial structure transformation and upgrading, and changes in labor income share.Management World, 35(7), 60–77+202–203.

[4]. Cai, Y. Z., & Zhang, J. N. (2015). The substitution effect and penetration effect of information and communication technology on China's economic growth.Economic Research Journal, 50(12), 100–114.

[5]. Muscio, A., Nardone, G., & Stasi, A. (2017). How does the search for knowledge drive firms' eco-innovation? Evidence from the wine industry.Industry and Innovation, 24(3), 298–320.

[6]. Magazzino, C., Mele, M., Morelli, G., et al. (2021). The nexus between information technology and environmental pollution: Application of a new machine learning algorithm to OECD countries.Utilities Policy, 72, 101256.

[7]. Wang, X., Feng, Y., Qian, L., et al. (2025). Talent introduction policies, optimal labor allocation, and corporate green innovation.Sustainability, 17(3), 1112.

[8]. Xuan, Y., & Zhang, W. L. (2021). The micro-level impact mechanism of intelligence on enterprise production performance: Taking capacity utilization and profitability as examples.Science of Science and Management of S.& T., 42(11), 96–119.

[9]. Munawar, S., Yousaf, D. H., Ahmed, M., et al. (2022). Effects of green human resource management on green innovation through green human capital, environmental knowledge, and managerial environmental concern.Journal of Hospitality and Tourism Management, 52, 141–150.

[10]. Lasswell, H. D., & Kaplan, A. (1970). Power and society. Yale University Press.

[11]. Zhang, J. M. (1992). Introduction to policy science. China Renmin University Press.

[12]. Chen, Z. M. (2003). Public policy analysis. China Renmin University Press.

[13]. Dunn, W. N. (1981). Public policy analysis: An introduction. Prentice-Hall.

[14]. Dunn, W. N. (2011). Public policy analysis: An introduction (4th ed.). (X. Ming, F. Yan, & Z. X. N., Trans.). China Renmin University Press. (Original work published 1981)

[15]. van Noordt, C., & Misuraca, G. (2019). New wine in old bottles: Chatbots in government. InProceedings of the 11th International Conference on Electronic Participation(pp. 49–59). Springer.

[16]. van Noordt, C., & Misuraca, G. (2022a). Exploratory insights on artificial intelligence for government in Europe.Social Science Computer Review, 40(2), 426–444.

[17]. van Noordt, C., & Misuraca, G. (2022b). Artificial intelligence for the public sector: Results of landscaping the use of AI in government across the European Union.Government Information Quarterly, 39(3), 101714.

[18]. Roberts, H., Cowls, J., Hine, E., et al. (2021). Achieving a 'Good AI Society’: Comparing the aims and progress of the EU and the US.Science and Engineering Ethics,27(6), 68.

[19]. Robinson, S. C. (2020). Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI).Technology in Society, 63, 101421.

[20]. Sampath, P. G. (2021). Governing artificial intelligence in an age of inequality.Global Policy,12(S6), 21–31.

[21]. Saveliev, A., & Zhurenkov, D. (2021). Artificial intelligence and social responsibility: The case of the artificial intelligence strategies in the United States, Russia, and China.Kybernetes, 50(3), 656–675.

[22]. Calboli, S., & Engelen, B. (2025). AI-enhanced nudging in public policy: Why to worry and how to respond. Mind & Society [Advance online publication].

[23]. Rooy, V. D. (2025). A cognitive science framework could prevent harmful public policy decisions involving AI.Behavioral Science & Policy, 11(1), 33–43.

[24]. Hakimi, M., Amiri, A. G., & Shamsi, E. S. (2024). Artificial intelligence and public health: Addressing pharmacy practice challenges and policy issues.British Journal of Pharmacy and Pharmaceutical Sciences, 1(1), 9–21.

[25]. Cory, S. R. (2020). Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI).Technology in Society,63, 101421.

[26]. Vassilakopoulou, P., Haug, A., Salvesen, L. M., et al. (2023). Developing human/AI interactions for chat-based customer services: Lessons learned from the Norwegian government.European Journal of Information Systems,32(1), 10–22.

[27]. Waldman, A., & Martin, K. (2022). Governing algorithmic decisions: The role of decision importance and governance on perceived legitimacy of algorithmic decisions.Big Data & Society,9(1).

[28]. Levin, L., & Budak, L. (2024). Implementation of public health policies and integration of artificial intelligence and social media in dental traumatology—cornerstones for effective dental trauma management.Dental Traumatology, 40(6), 607–611.

[29]. Li, J., & Yuan, Y. T. (2025). How generative artificial intelligence reshapes public communication: Logical mechanism, potential risks, and response paths.China Publishing Journal,(10), 29–33.

[30]. Wei, Y. M., Jia, K., Zeng, R. X., et al. (2025). Artificial intelligence innovation development and governance transformation under the breakthrough effect of DeepSeek.E-Government,(3), 2–39.

References

[1]. Acemoglu, D., & Restrepo, P. (2018). The race between man and machine: Implications of technology for growth, factor shares, and employment.American Economic Review, 108(6), 1488–1542.

[2]. Aghion, P., Bergeaud, A., Lequien, M., et al. (2022). The heterogeneous impact of market size on innovation: Evidence from French firm-level exports.Review of Economics and Statistics, 1–56.

[3]. Guo, K. M. (2019). Artificial intelligence development, industrial structure transformation and upgrading, and changes in labor income share.Management World, 35(7), 60–77+202–203.

[4]. Cai, Y. Z., & Zhang, J. N. (2015). The substitution effect and penetration effect of information and communication technology on China's economic growth.Economic Research Journal, 50(12), 100–114.

[5]. Muscio, A., Nardone, G., & Stasi, A. (2017). How does the search for knowledge drive firms' eco-innovation? Evidence from the wine industry.Industry and Innovation, 24(3), 298–320.

[6]. Magazzino, C., Mele, M., Morelli, G., et al. (2021). The nexus between information technology and environmental pollution: Application of a new machine learning algorithm to OECD countries.Utilities Policy, 72, 101256.

[7]. Wang, X., Feng, Y., Qian, L., et al. (2025). Talent introduction policies, optimal labor allocation, and corporate green innovation.Sustainability, 17(3), 1112.

[8]. Xuan, Y., & Zhang, W. L. (2021). The micro-level impact mechanism of intelligence on enterprise production performance: Taking capacity utilization and profitability as examples.Science of Science and Management of S.& T., 42(11), 96–119.

[9]. Munawar, S., Yousaf, D. H., Ahmed, M., et al. (2022). Effects of green human resource management on green innovation through green human capital, environmental knowledge, and managerial environmental concern.Journal of Hospitality and Tourism Management, 52, 141–150.

[10]. Lasswell, H. D., & Kaplan, A. (1970). Power and society. Yale University Press.

[11]. Zhang, J. M. (1992). Introduction to policy science. China Renmin University Press.

[12]. Chen, Z. M. (2003). Public policy analysis. China Renmin University Press.

[13]. Dunn, W. N. (1981). Public policy analysis: An introduction. Prentice-Hall.

[14]. Dunn, W. N. (2011). Public policy analysis: An introduction (4th ed.). (X. Ming, F. Yan, & Z. X. N., Trans.). China Renmin University Press. (Original work published 1981)

[15]. van Noordt, C., & Misuraca, G. (2019). New wine in old bottles: Chatbots in government. InProceedings of the 11th International Conference on Electronic Participation(pp. 49–59). Springer.

[16]. van Noordt, C., & Misuraca, G. (2022a). Exploratory insights on artificial intelligence for government in Europe.Social Science Computer Review, 40(2), 426–444.

[17]. van Noordt, C., & Misuraca, G. (2022b). Artificial intelligence for the public sector: Results of landscaping the use of AI in government across the European Union.Government Information Quarterly, 39(3), 101714.

[18]. Roberts, H., Cowls, J., Hine, E., et al. (2021). Achieving a 'Good AI Society’: Comparing the aims and progress of the EU and the US.Science and Engineering Ethics,27(6), 68.

[19]. Robinson, S. C. (2020). Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI).Technology in Society, 63, 101421.

[20]. Sampath, P. G. (2021). Governing artificial intelligence in an age of inequality.Global Policy,12(S6), 21–31.

[21]. Saveliev, A., & Zhurenkov, D. (2021). Artificial intelligence and social responsibility: The case of the artificial intelligence strategies in the United States, Russia, and China.Kybernetes, 50(3), 656–675.

[22]. Calboli, S., & Engelen, B. (2025). AI-enhanced nudging in public policy: Why to worry and how to respond. Mind & Society [Advance online publication].

[23]. Rooy, V. D. (2025). A cognitive science framework could prevent harmful public policy decisions involving AI.Behavioral Science & Policy, 11(1), 33–43.

[24]. Hakimi, M., Amiri, A. G., & Shamsi, E. S. (2024). Artificial intelligence and public health: Addressing pharmacy practice challenges and policy issues.British Journal of Pharmacy and Pharmaceutical Sciences, 1(1), 9–21.

[25]. Cory, S. R. (2020). Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI).Technology in Society,63, 101421.

[26]. Vassilakopoulou, P., Haug, A., Salvesen, L. M., et al. (2023). Developing human/AI interactions for chat-based customer services: Lessons learned from the Norwegian government.European Journal of Information Systems,32(1), 10–22.

[27]. Waldman, A., & Martin, K. (2022). Governing algorithmic decisions: The role of decision importance and governance on perceived legitimacy of algorithmic decisions.Big Data & Society,9(1).

[28]. Levin, L., & Budak, L. (2024). Implementation of public health policies and integration of artificial intelligence and social media in dental traumatology—cornerstones for effective dental trauma management.Dental Traumatology, 40(6), 607–611.

[29]. Li, J., & Yuan, Y. T. (2025). How generative artificial intelligence reshapes public communication: Logical mechanism, potential risks, and response paths.China Publishing Journal,(10), 29–33.

[30]. Wei, Y. M., Jia, K., Zeng, R. X., et al. (2025). Artificial intelligence innovation development and governance transformation under the breakthrough effect of DeepSeek.E-Government,(3), 2–39.

Cite this article

Gu,Y. (2025). Artificial Intelligence (AI) methods empowering empirical research in public policy: a review of theoretical foundations and practices. Journal of Applied Economics and Policy Studies,18(9),28-32.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Journal: Journal of Applied Economics and Policy Studies

Volume number: Vol.18
Issue number: Issue 9
ISSN: 2977-5701(Print) / 2977-571X(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).

For authors
For editors
For reviewers

Cookies are used by this site.
Copyright © 2024 EWA Publishing, its licensors, and contributors. All rights reserved, including text and data mining, AI training, and similar technologies.