Moderation and mediation effect of green management on AI and OP of a medium-size criminal investigation department
Abstract
The current widespread use of artificial intelligence (AI) in law enforcement represents a paradigm shift towards intelligence-led, predictive and data-driven criminal management, resulting in unprecedented advances in operational efficiency and strategic decision making globally. While these developments characterise AI policing in some world nations, their use in resource-constrained, post-conflict situations such as the Sierra Leone Police (SLP) is unclear. Using the medium-sized criminal investigation department (CID) of the SLP, the study on which this paper is based examined the effect of AI on the operational performance of the SLP, considering the mediating and moderating effect of green management (GM). A survey research design was employed, following a quantitative and deductive approach. A total of 181 out of 196 staff members at the CID headquarters were sampled. Primary data was collected using a structured and validated questionnaire and analysed using inferential statistics, with Smart PLS-SEM as the analytical tool. The findings revealed a statistically significant positive effect of AI on the operational performance (OP) (β = 0.356, t = 4.054, p < 0.001) of the SLP CID while the moderating interacting effect (AI*GM) on OP is negative and statistically significant (β = –0.221, t = 2.517, p = 0.012). On the other hand, the indirect effect (mediating role) of AI on OP through GM is positive but insignificant (β = 0.067, t = 1.906, p = 0.057). The study concluded that deliberate investment in AI and conscious consideration of GM will be a strategic tool for boosting policing and small and medium-sized establishments. Therefore, this paper recommends deliberate investment, proper implementation and constant monitoring of the usage of AI tools alongside GM, which will boost the general OP of police establishments and specifically bring them up to speed in meeting the demand for global practices. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
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Author's Biography
Oluwajuwon Gabriel Ariyo PhD is an Adjunct Lecturer in the Business Administration and Marketing Department at Redeemer’s University, Nigeria. He has over a decade and a half of industry experience and has published in local and international journals. Ariyo’s research interests include workplace gender distribution, generational diversity and inclusion, and learning organisation.
Edafe Bawa Dogo PhD is an academic who is passionate about research and mentorship. Her scholarly interests span digitalisation, operational resilience, lean manufacturing, entrepreneurial development and production optimisation. Edafe lectures in both undergraduate and postgraduate programmes at Babcock University, Nigeria. Her work focuses on enhancing performance and productivity by equipping managers with data-driven decision-making tools and applying analytical approaches to solve operational and strategic business challenges.
Temitayo A. Joshua MSc is a Lead Research Consultant with Wonder Tower Consulting Ltd. He has a robust industry background spanning nearly five years in industry research. Temitayo’s research interests converge at the nexus of artificial intelligence (AI), organisational behaviour and human capital development. His scholarly work, featured in esteemed local and international journals, underscores his commitment to advancing knowledge in employee performance, motivation and AI-driven solutions. Temitayo is an accomplished author with three published books and forthcoming titles. Through his research, Temitayo aims to inform policy, practice and innovation in these critical domains.
