The Impact of Data-driven Dispatching and Load Recommendation Systems on Logistics Platform Continuance Intention: A PLS-SEM Analysis
This study employs PLS-SEM analysis of freight operators in Jeollanam-do to demonstrate that continuance intention toward digital logistics platforms is significantly driven by platform reliability and compatibility, which enhance strategic orientation and, crucially, the efficiency of delivery and pickup systems that mediate the relationship between strategy and user retention.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
In the vast, moving world of global trade, the movement of goods relies on a delicate balance between supply and demand. For decades, this balance was struck through phone calls, paper lists, and local knowledge, a system that often left trucks running half-empty or drivers waiting idly for hours. As the digital age advanced, new platforms emerged to act as digital matchmakers, connecting shippers who need to move cargo with carriers who have space on their trucks. These systems promise to reduce waste and save money by using data to find the best routes and loads. However, simply building a new app does not guarantee that people will keep using it. The real question for the industry is not just whether a technology works, but whether the people who rely on it every day—truck drivers and small business owners—decide to stick with it after the initial excitement fades. This decision depends on whether the technology actually makes their daily work easier and more profitable, turning a digital tool into a trusted partner in their business.
A team of researchers set out to understand exactly how this decision happens in the real world, focusing on the logistics industry in Jeollanam-do, a province in South Korea. This region is a perfect place to study the problem because it is filled with small, independent trucking companies that often struggle with the inefficiencies of the old system, yet they have been slow to adopt new digital tools. The researchers wanted to see if the advanced features of modern logistics platforms, such as artificial intelligence that suggests the best loads or predicts traffic, could convince these drivers to continue using the service long-term. They did not just ask if the drivers liked the technology; they investigated a chain of events. They looked at how the reliability of the platform changed the drivers' mindset, how that new mindset influenced their view of the delivery process, and finally, how that perception of efficiency led to a decision to keep using the system.
To find the answers, the researchers surveyed 180 freight transport operators in the region, including both company drivers and owners who drive their own trucks. They asked these workers about their experiences with a specific digital platform known as KTA Freight Line, which has recently upgraded its services to include smart matching and recommendation features. The survey asked detailed questions about whether the information provided by the app was accurate and up-to-date, whether the app fit smoothly into their existing work routines, and whether it felt like it understood their specific needs. The researchers then analyzed the responses to see how these factors connected to one another, tracing the path from the quality of the technology to the final decision to keep using it.
The study revealed a clear and logical path that explains why drivers stay with a platform. First, the researchers found that the drivers' trust in the system began with two things: reliability and compatibility. When the platform provided accurate, timely information that matched the reality of the road, and when the app was easy to use without disrupting their daily habits, the drivers began to view the technology as a strategic asset rather than just a nuisance. This shift in mindset was crucial. It meant that the drivers started to see the platform not as a simple tool for finding a single load, but as a vital part of their business strategy that could help them compete and grow.
This change in attitude then had a direct impact on how the drivers experienced their actual work. The study showed that when drivers felt the platform was a strategic asset, they perceived a significant improvement in their pickup and delivery systems. They felt that their trucks were moving faster, their response times to new jobs were quicker, and their overall delivery performance was more stable. In other words, the digital tool successfully translated into a tangible improvement in the physical movement of goods. The researchers found that this perceived improvement in efficiency was the most powerful factor of all. It was the bridge that connected the drivers' trust in the technology to their decision to keep using it.
The data confirmed that the decision to continue using the platform was not driven by a love of technology for its own sake. Instead, it was driven by the results the technology produced. When the platform helped drivers get more work, reduce empty miles, and deliver goods more reliably, they were far more likely to say they would use it again. The study also found that the platform's ability to offer personalized recommendations, such as suggesting loads that fit a specific truck's size or route, played a role in shaping the drivers' strategic outlook, though it was the overall reliability of the information that mattered most.
In the end, the research suggests that for digital logistics platforms to succeed in regions dominated by small carriers, they must do more than just offer a new way to find work. They must prove that they can fundamentally improve the efficiency of the pickup and delivery process. The study indicates that when a platform successfully integrates into a driver's workflow and delivers measurable improvements in speed and reliability, it transforms from a novelty into an essential part of the business. This finding offers a clear guide for the future of the industry: the key to keeping users engaged is not just in the sophistication of the algorithm, but in the visible, daily benefits it brings to the people who drive the trucks.
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