This research investigates the current status and impact of Internet of Things (IoT) technology on supply chain efficiency within the logistics industry. It analyzes the essential elements affecting the implementation of IoT in firms, aiming to propose a set of critical components necessary for effective system development. The study employs a positivistic research philosophy, utilizing literature reviews, surveys, and the AHP-TOPSIS method for data analysis. Findings indicate significant benefits and challenges associated with IoT adoption, providing insights for logistics and supply chain managers.

Purpose of the Research

The primary aim of this research is to explore the impact of IoT and RFID technologies on logistics services and supply chain frameworks. By examining how these systems are employed in the industry, this study seeks to uncover the benefits and challenges associated with their use. The research addresses several key questions:

• How are instructions to process information received and acted upon?
• How is the flow of information monitored in a digital environment?
• How is the status of information forwarded within the supply chain?

Given the rapid technological advancements in logistics services and the supply chain industry, this research intends to investigate the latest developments in IoT and RFID technologies. The study will focus on their influence on logistics services and supply chain frameworks, analyzing both the advantages and drawbacks. The objectives include:

• Introducing existing IoT developments to firms
• Describing conceptual models of IoT in supply chain frameworks
• Discussing the benefits and disadvantages of IoT advancements
• Evaluating the application of IoT and RFID systems in supply chain networks
• Ranking the importance of drivers and barriers for firms investing in IoT

Background of IoT in Logistics

The Internet of Things (IoT) is transforming various industries, including logistics and supply chain management. IoT refers to the network of physical devices embedded with sensors, software, and other technologies to connect and exchange data with other devices and systems over the internet. This chapter delves into the current state of IoT technology, its applications in the logistics industry, and the critical factors influencing its adoption.

Conceptual Models and Theoretical Frameworks

This section explores various conceptual models and theoretical frameworks related to IoT in supply chain management. These models provide a foundation for understanding how IoT technologies are integrated into logistics operations and their potential impact on efficiency and performance.

Drivers and Barriers of IoT Adoption

A comprehensive review of the drivers and barriers to IoT adoption in the logistics industry is presented. Factors such as cost, technological readiness, data security, and organizational culture are analyzed to understand their influence on the implementation of IoT solutions.

Research Philosophy and Approach

The research philosophy behind this study is positivistic, relying on empirical evidence and statistical analysis to answer the research questions. A thorough literature review sets the stage for developing research questions, which are then tested and analyzed using a sample.

Data Collection and Survey Design

Due to limitations in public web-based tools, a customized survey questionnaire was designed using PHP, HTML/5, CSS/3, and jQuery. The survey aimed to gather data on the awareness, involvement, benefits, and disadvantages of IoT technology among participants from various industries.

Analytical Methods

The AHP-TOPSIS method was used to analyze the survey data. This chapter describes how this method was utilized to develop a pairwise comparison matrix, facilitating the ranking of drivers and barriers to IoT adoption.

Quantitative Data Analysis

This section presents the analysis of quantitative data collected from the survey. The responses to various questions are quantified to determine the level of awareness, involvement, and perceived benefits and risks of IoT technology among participants.

Application of AHP-TOPSIS Method

The results of the AHP-TOPSIS analysis are detailed, highlighting the ranked importance of different drivers and barriers. This analysis helps in understanding the factors that influence firms’ decisions to invest in IoT technology.

Findings

The research confirms that IoT technology significantly impacts the logistics industry, improving efficiency and performance. The study identifies key drivers and barriers to IoT adoption, providing insights for organizations considering the implementation of IoT solutions.

Validity and Reliability

The validity and reliability of the research are discussed, ensuring that the methods used to collect and analyze data are robust and accurate. The AHP-TOPSIS method is validated as an effective tool for ranking criteria in this context.

Limitations

The study acknowledges several limitations, including the short data collection period and the relatively small sample size. These limitations are discussed in detail, along with their potential impact on the research findings.

Future Work

Suggestions for future research are provided, emphasizing the need for extended data collection, qualitative interviews, and more complex analytical methods. Future studies could explore additional drivers and barriers, as well as the impact of specific IoT software on supply chain performance.