The role of artificial intelligence and bureaucracy in frugal innovation for social and environmental performance: A structuration theory approach

Dubey, R ORCID: 0000-0002-3913-030X (2025) The role of artificial intelligence and bureaucracy in frugal innovation for social and environmental performance: A structuration theory approach. Journal of Environmental Management, 387. p. 125860. ISSN 0301-4797

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Abstract

Artificial Intelligence (AI) has played a crucial role in decision-making within public departments. The impact of AI on the discretion exercised by public officials and bureaucrats has attracted significant scholarly attention. Despite the growing body of literature, there remains a need to explore how digital discretion and social structures shape innovation, particularly in disadvantaged communities facing resource constraints, limited accessibility, and complex societal issues. In such contexts, AI-assisted decision-making by public officials can promote frugal innovation, contributing to social and environmental performance. To investigate this, I based my research hypotheses on social structuration theory. I conducted a survey using a pre-tested instrument and collected 179 usable responses. The hypotheses were then analysed using PLS-SEM software, specifically WarpPLS 8.0. The results provided valuable insights into structuration theory and its application in complex rural settings, highlighting its potential to foster frugal innovation aimed at addressing social and environmental sustainability. This study makes a significant contribution to the theoretical understanding of AI-assisted discretion among public officials. It explores the interplay between agents and social structures and addresses the social complexities involved in frugal innovation for sustainability. Finally, I acknowledge the limitations of the study and propose directions for future research.

Item Type:	Article
Uncontrolled Keywords:	Humans; Decision Making; Conservation of Natural Resources; Artificial Intelligence; Artificial intelligence; Digital discretion; Environmental sustainability; Frugal innovation; Social sustainability; Structuration theory; Artificial Intelligence; Humans; Decision Making; Conservation of Natural Resources; 4407 Policy and Administration; 44 Human Society; Machine Learning and Artificial Intelligence; Artificial Intelligence; Humans; Decision Making; Conservation of Natural Resources; Environmental Sciences
Subjects:	H Social Sciences > HF Commerce > HF5001 Business Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General)
Divisions:	Liverpool Business School
Publisher:	Elsevier BV
Date of acceptance:	16 May 2025
Date Deposited:	15 Jan 2026 09:27
Last Modified:	15 Jan 2026 09:27
DOI or ID number:	10.1016/j.jenvman.2025.125860
URI:	https://researchonline.ljmu.ac.uk/id/eprint/27925

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