The Effect of Real-Time Analytics on Logistics Optimization: A Case Study of Transport Companies in Jigawa State
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- NGN 5000
Background of the Study
Real-time analytics has emerged as a critical tool for optimizing logistics operations, providing businesses with actionable insights to enhance efficiency and reduce costs. By analyzing live data from sources such as GPS systems, Internet of Things (IoT) devices, and customer feedback, real-time analytics enables transport companies to make informed decisions quickly (McKinsey, 2024).
Transport companies in Jigawa State face challenges such as inefficient route planning, delayed deliveries, and high operational costs. Real-time analytics presents an opportunity to address these challenges by improving decision-making, streamlining operations, and enhancing customer satisfaction. Despite its potential, the adoption of real-time analytics remains limited in Jigawa State due to technical and financial constraints (Bashir & Suleiman, 2023). This study evaluates the impact of real-time analytics on logistics optimization in transport companies in Jigawa State.
Statement of the Problem
Logistics inefficiencies remain a significant issue for transport companies in Jigawa State, leading to increased costs and reduced competitiveness. Traditional logistics systems often lack the capability to analyze and respond to dynamic changes in real-time. While real-time analytics has demonstrated significant benefits in other regions, its practical impact on logistics operations in Jigawa State is not well-documented (Ali et al., 2024). This study addresses this gap by assessing how real-time analytics influences logistics optimization in the local transport sector.
Objectives of the Study
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To assess the adoption level of real-time analytics in transport companies in Jigawa State.
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To examine the impact of real-time analytics on logistics optimization.
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To identify challenges faced by transport companies in implementing real-time analytics.
Research Questions
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What is the adoption level of real-time analytics in transport companies in Jigawa State?
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How does real-time analytics affect logistics optimization?
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What challenges do transport companies face in implementing real-time analytics?
Research Hypotheses
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There is no significant relationship between real-time analytics adoption and logistics optimization.
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Real-time analytics does not significantly improve route planning and delivery efficiency.
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Challenges in implementing real-time analytics are not significant in transport companies in Jigawa State.
Scope and Limitations of the Study
The study focuses on transport companies in Jigawa State, analyzing their use of real-time analytics tools for logistics optimization. Limitations include access to proprietary analytics data and variations in technology adoption across companies.
Definitions of Terms
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Real-Time Analytics: The process of analyzing data as it is generated to enable immediate decision-making.
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Logistics Optimization: The process of improving logistics operations to minimize costs and enhance efficiency.
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Transport Companies: Firms involved in the movement of goods or passengers from one location to another.
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