An Examination of IoT Data Analytics in Smart Logistics: A Study of Transport Companies in Gombe State
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Background of the Study
The integration of Internet of Things (IoT) technology into logistics has transformed the industry, enabling real-time monitoring, predictive maintenance, and enhanced operational efficiency. IoT data analytics, which involves analyzing data generated by IoT devices, provides actionable insights that improve decision-making in smart logistics (Okonkwo & Bello, 2023).
Transport companies in Gombe State face challenges such as inefficient fleet management, high operational costs, and limited visibility into supply chain operations. By leveraging IoT data analytics, these companies can address these challenges and enhance service delivery (Ibrahim & Musa, 2024).
This study examines the application of IoT data analytics in smart logistics, focusing on its adoption, benefits, and challenges among transport companies in Gombe State.
Statement of the Problem
The logistics sector in Gombe State is plagued by inefficiencies, including poor fleet utilization, delays, and high maintenance costs. Despite the potential of IoT data analytics to address these issues, its adoption among transport companies remains limited due to high implementation costs, inadequate technical expertise, and infrastructure challenges (Ahmed & Bello, 2023).
While global studies highlight the benefits of IoT data analytics in logistics, there is limited research on its application in the Nigerian context, particularly in Gombe State. This study seeks to fill this gap by exploring the use of IoT data analytics in smart logistics and its impact on transport operations.
Objectives of the Study
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To assess the adoption of IoT data analytics in smart logistics by transport companies in Gombe State.
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To evaluate the impact of IoT data analytics on operational efficiency and decision-making in logistics.
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To identify challenges and propose solutions for enhancing the adoption of IoT data analytics in smart logistics.
Research Questions
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How widely is IoT data analytics adopted in smart logistics by transport companies in Gombe State?
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What impact does IoT data analytics have on operational efficiency and decision-making in logistics?
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What challenges hinder the adoption of IoT data analytics, and what solutions can address these challenges?
Research Hypotheses
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IoT data analytics has no significant impact on operational efficiency in logistics.
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The adoption of IoT data analytics does not significantly improve decision-making in transport companies.
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Solutions for enhancing the adoption of IoT data analytics have no significant effect on logistics performance.
Scope and Limitations of the Study
The study focuses on transport companies in Gombe State, assessing the adoption and impact of IoT data analytics in smart logistics. Limitations include variability in technology adoption, access to proprietary data, and biases in survey responses.
Definitions of Terms
IoT Data Analytics: The process of analyzing data generated by Internet of Things devices to derive insights.
Smart Logistics: The use of advanced technologies, including IoT, to optimize logistics operations.
Transport Companies: Firms that provide transportation services for goods and passengers.
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