Algorithms for a New Season? Mapping a Decade of Research on the Artificial Intelligence-Driven Digital Transformation of Public Administration

Yanto Chandra; Naikang Feng

doi:10.1080/14719037.2025.2450680

Algorithms for a New Season? Mapping a Decade of Research on the Artificial Intelligence-Driven Digital Transformation of Public Administration

Yanto Chandra, Naikang Feng^*

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

3 Citations (Scopus)

Abstract

This article reviews a decade (2013–2023) of scholarly discourse to deepen our understanding of the AI-driven digital transformation of public administration (PA). Structural topic modelling and manual coding of 169 articles that focused on contextual conditions, mechanisms, outcomes, and policies revealed various topics. Findings show a focus on policies and, to a lesser extent, mechanisms, with algorithmic decision-making as a key theme. Issues like algorithmic trustworthiness, bias, and accountability in algorithmic bureaucracies are highlighted. Research gaps include insufficient exploration of contextual conditions and policy implementation, with a narrow focus on organizational and ethical outcomes. A research agenda is suggested. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

Original language	English
Journal	Public Management Review
Online published	18 Jan 2025
DOIs	https://doi.org/10.1080/14719037.2025.2450680
Publication status	Online published - 18 Jan 2025

Funding

The work described in this paper was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CityU 15513723).

Research Keywords

AI
Artificial intelligence
digital transformation
review
topic modelling

Publisher's Copyright Statement

COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: This is an Accepted Manuscript of an article published by Taylor & Francis in PUBLIC MANAGEMENT REVIEW on 18 Jan 2025, available online: https://doi.org/10.1080/14719037.2025.2450680.

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title = "Algorithms for a New Season? Mapping a Decade of Research on the Artificial Intelligence-Driven Digital Transformation of Public Administration",

abstract = "This article reviews a decade (2013–2023) of scholarly discourse to deepen our understanding of the AI-driven digital transformation of public administration (PA). Structural topic modelling and manual coding of 169 articles that focused on contextual conditions, mechanisms, outcomes, and policies revealed various topics. Findings show a focus on policies and, to a lesser extent, mechanisms, with algorithmic decision-making as a key theme. Issues like algorithmic trustworthiness, bias, and accountability in algorithmic bureaucracies are highlighted. Research gaps include insufficient exploration of contextual conditions and policy implementation, with a narrow focus on organizational and ethical outcomes. A research agenda is suggested. {\textcopyright} 2025 Informa UK Limited, trading as Taylor & Francis Group.",

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author = "Yanto Chandra and Naikang Feng",

year = "2025",

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language = "English",

journal = "Public Management Review",

issn = "1471-9037",

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T1 - Algorithms for a New Season? Mapping a Decade of Research on the Artificial Intelligence-Driven Digital Transformation of Public Administration

AU - Chandra, Yanto

AU - Feng, Naikang

PY - 2025/1/18

Y1 - 2025/1/18

N2 - This article reviews a decade (2013–2023) of scholarly discourse to deepen our understanding of the AI-driven digital transformation of public administration (PA). Structural topic modelling and manual coding of 169 articles that focused on contextual conditions, mechanisms, outcomes, and policies revealed various topics. Findings show a focus on policies and, to a lesser extent, mechanisms, with algorithmic decision-making as a key theme. Issues like algorithmic trustworthiness, bias, and accountability in algorithmic bureaucracies are highlighted. Research gaps include insufficient exploration of contextual conditions and policy implementation, with a narrow focus on organizational and ethical outcomes. A research agenda is suggested. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

AB - This article reviews a decade (2013–2023) of scholarly discourse to deepen our understanding of the AI-driven digital transformation of public administration (PA). Structural topic modelling and manual coding of 169 articles that focused on contextual conditions, mechanisms, outcomes, and policies revealed various topics. Findings show a focus on policies and, to a lesser extent, mechanisms, with algorithmic decision-making as a key theme. Issues like algorithmic trustworthiness, bias, and accountability in algorithmic bureaucracies are highlighted. Research gaps include insufficient exploration of contextual conditions and policy implementation, with a narrow focus on organizational and ethical outcomes. A research agenda is suggested. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

KW - AI

KW - Artificial intelligence

KW - digital transformation

KW - review

KW - topic modelling

UR - http://www.scopus.com/inward/record.url?scp=85215264256&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85215264256&origin=recordpage

U2 - 10.1080/14719037.2025.2450680

DO - 10.1080/14719037.2025.2450680

M3 - RGC 21 - Publication in refereed journal

SN - 1471-9037

JO - Public Management Review

JF - Public Management Review

ER -

Algorithms for a New Season? Mapping a Decade of Research on the Artificial Intelligence-Driven Digital Transformation of Public Administration

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Algorithms for a New Season? Mapping a Decade of Research on the Artificial Intelligence-Driven Digital Transformation of Public Administration

Abstract

Funding

Research Keywords

Publisher's Copyright Statement

Access Output

Other Access Options

Permanent Link

Other Files and Links

Embargoed Document

Fingerprint

Projects

GRF: Understanding the Governance of Decentralized Autonomous Organizations as a Novel Organizational Form in the Blockchain Economy

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