The Local Government and Artificial Intelligence Nexus: A Five-Decade Scientometric Analysis on Evolution, State-of-The-Art, and Emerging Trends

39 Pages Posted: 27 Feb 2024

See all articles by Tan Yigitcanlar

Tan Yigitcanlar

Queensland University of Technology

Sajani Senadheera

Queensland University of Technology

Raveena Marasinghe

Queensland University of Technology

Simon Elias Bibri

affiliation not provided to SSRN

Thomas W. Sanchez

Texas A&M University

Federico Cugurullo

University of Melbourne - Trinity College

Renee Sieber

McGill University

Abstract

Artificial intelligence (AI) technologies, in recent years, have surged across various sectors, extending its influence on public governance, particularly in local governments. Despite this, there exists a limited grasp of the overarching narrative surrounding the adoption of AI in local governments and its future trajectory. This study, hence, aims to provide a comprehensive overview of the historical evolution, current state-of-the-art, and emerging trends in the adoption of AI in the local government context. A comprehensive scientometric analysis was conducted on the relevant literature records (n=7,112) published in the Scopus database during the last five decades (1973-2023). The study findings revealed the following key insights: (a) Exponential technological advancements in the last decades brought the Blooming Era of AI adoption for local governments; (b) The main AI adoption purposes in local governments include decision support, automation, prediction, and service delivery; (c) The main AI adoption areas in local governments include planning, analytics, security, surveillance, energy, and modelling; (d) Under-researched but critical research areas include responsibility and ethics of AI adoption in local governments. This study informs research, policy and practice by offering a comprehensive understanding of the literature on AI applications in local governments.

Keywords: artificial intelligence (AI), local government, municipality, technology adoption, smart city, GeoAI

Suggested Citation

Yigitcanlar, Tan and Senadheera, Sajani and Marasinghe, Raveena and Bibri, Simon Elias and Sanchez, Thomas W. and Cugurullo, Federico and Sieber, Renee, The Local Government and Artificial Intelligence Nexus: A Five-Decade Scientometric Analysis on Evolution, State-of-The-Art, and Emerging Trends. Available at SSRN: https://ssrn.com/abstract=4739812 or http://dx.doi.org/10.2139/ssrn.4739812

Tan Yigitcanlar (Contact Author)

Queensland University of Technology ( email )

2 George Street
Brisbane, Queensland 4000
Australia

Sajani Senadheera

Queensland University of Technology ( email )

2 George Street
Brisbane, 4000
Australia

Raveena Marasinghe

Queensland University of Technology ( email )

2 George Street
Brisbane, 4000
Australia

Simon Elias Bibri

affiliation not provided to SSRN ( email )

No Address Available

Thomas W. Sanchez

Texas A&M University ( email )

College Station, TX
United States

HOME PAGE: http://tomwsanchez.com/

Federico Cugurullo

University of Melbourne - Trinity College ( email )

Royal Parade
Parkville, VIC 3052
Australia

Renee Sieber

McGill University ( email )

1001 Sherbrooke St. W
Montreal, Quebec H3A 1G5
Canada

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