Improving highway accessibility to tourist attractions is critical for promoting social sustainability and reducing regional disparities in tourism development. However, existing accessibility optimization often ignores the resource scarcity of tourist attractions and lacks fairness considerations, leading to biased investment allocation and perpetuating such disparities. Here, this study introduces a TF-IDF-based scarcity measure of tourist attractions and formulates a fairness-oriented optimization model to reduce these spatial disparities. The results of the case study in Shanxi Province show that after applying the scarcity measure, 77 northern and western counties experience increased travel cost, while 40 southern counties see decreases, revealing a pronounced scarcity penalty. The fairness-oriented optimization allocates over 80% of the budget to counties with high-scarcity attractions and reduces the variance of accessibility by 55.8%. At the county level, the investment–accessibility improvement correlation reaches an R2 of 0.85, confirming that fairness-driven investment reliably translates into measurable accessibility improvements. In contrast, the weaker OD-pair level correlation (R2 = 0.50) confirms that aggregated county-level indicators are more appropriate for assessing the effectiveness of fairness-driven investment. This study quantifies tourism resource scarcity and demonstrates that fairness-driven optimization effectively reduces spatial disparities, laying a foundation for transport infrastructure planning and investment that enhances accessibility and promotes equity in tourist attractions.
Wu et al. (2026) studied this question.