Development and Evaluation of an Intelligent Mobile Application for Tourism Route Planning Using Route Optimization and Real-time Location-Based Service
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Abstract
Phra Nakhon Si Ayutthaya Province has a large number of tourist attractions. Tourists often experience circuitous and disordered travel routes, resulting in unnecessary loss of time and resources. Therefore, the development of an intelligent route planning system on mobile devices is an important approach to addressing this problem. This research aimed to: 1) develop a mobile application for intelligent tourism route planning in Phra Nakhon Si Ayutthaya Province using the Nearest Neighbor Algorithm combined with real-time location-based services; 2) evaluate the efficiency of the automatic route planning system in reducing travel distance, travel time, and the number of route crossings; and 3) study users’ satisfaction and technology acceptance based on the Technology Acceptance Model (TAM). The application was developed using the Flutter framework and consisted of core features for trip planning, place exploration, and map display. It worked with Google Places API and Distance Matrix API to support automatic route sequencing on mobile devices.
The research findings revealed that an experiment with 100 Thai tourists who used smartphones, selected through purposive sampling, and planned trips to five locations showed that the automatic route planning system could reduce travel distance by 28.5% (t = 14.82, p < .001), travel time by 31.2% (t = 16.37, p < .001), and the number of route crossings by 82.9%
(t = 21.54, p < .001) compared with manual planning, as analyzed using a paired t-test. The differences were statistically significant in all indicators. In addition, the evaluation of satisfaction and technology acceptance showed that users’ overall satisfaction ( = 4.54, S.D. = 0.51) and overall technology acceptance (
= 4.54, S.D. = 0.51) were at the highest level, particularly in perceived usefulness (PU:
= 4.63) and behavioral intention to use (BI:
= 4.57). These results indicate that the application can significantly enhance the efficiency and experience of tourism route planning.
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References
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