The China–Pakistan Economic Corridor (CPEC) represents a transformative transport infrastructure initiative with the potential to reshape tourism in South Asia. However, the behavioral mechanisms through which corridor development translate into travel willingness remain insufficiently understood, particularly between domestic and cross-border tourism. This study investigated the determinants of domestic tourism willingness within Pakistan and cross-border tourism willingness toward China using a stated preference survey of 441 Pakistani respondents collected through an online questionnaire. To balance behavioral interpretation and predictive performance, this study integrated ordinal logistic regression (OLR) with multiple machine learning classifiers. The results revealed clear behavioral asymmetries between domestic and cross-border tourism decisions. Domestic tourism willingness was primarily driven by attitudinal evaluations, particularly perceived desirability, pleasantness, and comfort of travel along the CPEC. In contrast, cross-border tourism willingness was more strongly constrained by knowledge-related and institutional factors, including awareness of visa procedures, accommodation arrangements, and destination information. Comparative performance analysis indicated that machine learning models outperformed ordinal logistic regression, improving predictive accuracy by approximately 12.6 percentage points for domestic tourism (93.6% vs. 81.0%) and 1.7 percentage points for cross-border tourism (81.1% vs. 79.4%). These findings demonstrate that corridor-induced tourism demand is governed by distinct behavioral mechanisms across domestic and international contexts, highlighting the need for differentiated tourism development strategies. From a policy perspective, the results suggest that domestic tourism development along the CPEC should prioritize experiential quality and travel comfort, whereas cross-border tourism promotion should focus on reducing informational and procedural barriers such as visa knowledge, accommodation awareness, and travel facilitation.
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Yousaf Ali
Fahd bin Sultan University
Jialei Shi
Hammersmith Hospital
Muhammad Hussain
The University of Western Australia
Future Transportation
Tsinghua University
The University of Western Australia
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Ali et al. (Sun,) studied this question.
synapsesocial.com/papers/69ccb7c216edfba7beb89e2c — DOI: https://doi.org/10.3390/futuretransp6020073