Using Multivariate Statistical Methods to Analyze High-Quality Bicycle Path Service Systems: A Case Study of Popular Bicycle Paths in Taiwan

Abstract

Taiwan has promoted bicycle tourism for nearly 20 years, and the bicycle paths it has constructed throughout the island are diverse in design. In the present study, an evaluation scale for bicycle path sightseeing potential was devised with a focus on the overall service quality of the paths; 30 popular bicycle paths were analyzed using a field survey, with expert consultation on quantitative indicators, and a qualitative analysis entailing interviews with people regarding the bicycle paths. A multivariate statistical analysis was performed on the quality of the service systems for these paths. The results revealed that the quality of these service systems is influenced by four principal components, namely, landscape attractiveness, image management, bicycle-specific paths, and accessibility, for a total explanatory power of 76.21%; the individual explanatory power of these components was 25.89%, 21.49%, 16.81%, and 12.03%, respectively. Bicycle path conditions, service maintenance, and cleanliness and bicycle specificity are required for future high-quality bicycle paths; diverse bicycle rental services and bicycle types, entrance visibility, and ecological introduction boards along paths are value-added factors to bicycle path quality.