Ukwuoma, Ogochukwu (2025) An Investigation into the role artificial intelligence (AI) in management decision-making within retail businesses. Masters thesis, York St John University.

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Abstract

This study explores how Artificial Intelligence (AI) impacts decision-making in retail organisations, focusing on perceived benefits, limitations, ethical concerns, and managerial roles. The study also investigates how managers interact with AI systems and how ethics shape trust and acceptance. A quantitative research design was adopted. Data were collected using a structured questionnaire administered to 160 participants across various roles in retail organisations. After data cleansing, 129 valid responses were retained for analysis. The analysis used descriptive statistics, correlation tests, chi-square, and multiple regression to examine relationships between AI use, organisational strategy, and ethical considerations. Findings show that most organisations are already using AI in key areas like inventory control, pricing, customer service, and demand forecasting. Respondents agreed that AI improves efficiency, reduces costs, and speeds up decision-making. However, they also noted key limitations, including lack of contextual understanding, data quality issues, and high costs. Managers felt that AI supports rather than replaces them. Most agreed that AI increases pressure to adapt but also frees them for strategic thinking. Ethical concerns were widespread. Data privacy and algorithmic fairness were viewed as major risks, while trust in AI decisions remained moderate. These concerns were shared across job levels and experience groups. Regression results show that ethical awareness is the strongest predictor of effective AI strategy adoption. The study adds to the literature by highlighting the balance between human judgment and AI capabilities. It also provides practical guidance for retail firms, especially in developing economies, on how to implement AI responsibly. Limitations include the use of self-reported data, a single data collection method and a moderate sample size. Future research should adopt mixed methods and examine how AI use evolves over time.

Item Type:	Thesis (Masters)
Status:	Unpublished
School/Department:	London Campus
URI:	https://ray.yorksj.ac.uk/id/eprint/13723

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