The Impact of Artificial Intelligence on Inventory Management Efficiency: A Study of Retail Stores in Plateau State
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- NGN 5000
Background of the Study
Inventory management is critical to the success of retail businesses, as it directly affects operational efficiency, cost control, and customer satisfaction. Artificial intelligence (AI) technologies, such as machine learning and predictive analytics, are revolutionizing inventory management by enabling accurate demand forecasting, real-time inventory tracking, and automated reordering (World Bank, 2023). AI enhances efficiency by minimizing stockouts, overstocking, and wastage, ultimately improving profitability.
Retail stores in Plateau State face unique inventory management challenges, including fluctuating demand patterns, supply chain disruptions, and limited access to advanced technologies. The integration of AI into inventory systems presents an opportunity to overcome these issues, but adoption remains limited due to factors such as high costs and lack of technical expertise (Bello & Musa, 2024). This study investigates how AI impacts inventory management efficiency in retail stores in Plateau State.
Statement of the Problem
Inventory mismanagement is a persistent challenge for retail stores in Plateau State, resulting in lost sales, high holding costs, and dissatisfied customers. Traditional inventory management systems are often inadequate in addressing the complexities of modern retail operations. While AI has been shown to enhance inventory management efficiency globally, its implementation in Plateau State is limited (Yusuf et al., 2024). This study examines the role of AI in improving inventory management efficiency and identifies barriers to its adoption in retail stores.
Objectives of the Study
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To assess the level of adoption of AI technologies in inventory management among retail stores in Plateau State.
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To examine the impact of AI on inventory management efficiency.
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To identify challenges faced by retail stores in implementing AI-based inventory systems.
Research Questions
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What is the level of adoption of AI technologies in inventory management among retail stores in Plateau State?
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How does AI influence inventory management efficiency?
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What challenges do retail stores face in implementing AI-based inventory systems?
Research Hypotheses
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There is no significant relationship between AI adoption and inventory management efficiency.
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AI does not significantly improve demand forecasting and inventory tracking.
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The challenges of implementing AI in inventory management are not significant in retail stores in Plateau State.
Scope and Limitations of the Study
The study focuses on retail stores in Plateau State, examining their use of AI in inventory management, including demand forecasting and inventory optimization. Limitations include access to detailed operational data and variations in AI adoption across stores.
Definitions of Terms
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Artificial Intelligence (AI): The simulation of human intelligence processes by machines, particularly computer systems.
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Inventory Management Efficiency: The ability to maintain optimal stock levels while minimizing costs and maximizing customer satisfaction.
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Retail Stores: Businesses that sell goods directly to consumers.
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