To explain and predict active school travel (AST), most studies have not investigated to what extent considering taste heterogeneity is an important influence on AST share. The main aim of the present study was to evaluate whether considering unobserved taste heterogeneity through mixed logit models – including random coefficient and random coefficient analysis (RCA) – materially improves/influences the AST prediction compared to a simpler model – the multinomial logit (MNL) model. The database comprises 735 valid observations. The results show that, with a 10% increase in perceived walking time to school, the MNL model predicts that the AST share would decrease by 7.8% (from 18.9% to 17.4%) while the RCA model predicts that it would decrease by 8.5% (from 18.9% to 17.3%). Thus, the expected share of AST is overestimated by MNL by one-tenth of a percentage point. Although there might be random taste variations around perceived distance to school, it seems the other important policy-sensitive variables, such as safety perception, homogeneously impacts on the AST share across households with different socioeconomic and built environment characteristics. Our empirical assessment suggests that considering taste heterogeneity does not necessarily improve the accuracy of analysis for the aggregate share of the AST concerning policy-sensitive variables.

为了解释和预测活跃的学校旅行（AST），大多数研究都没有调查考虑异味对AST份额的重要影响的程度。本研究的主要目的是评估是否通过混合logit模型（包括随机系数和随机系数分析（RCA））考虑未观察到的味道异质性，与较简单的模型多项式logit（MNL）相比，从实质上改善/影响了AST预测模型。该数据库包含735个有效观察值。结果表明，随着上学步行时间的增加10％，MNL模型预测AST份额将下降7.8％（从18.9％下降到17.4％），而RCA模型预测它将下降8.5％。 （从18.9％到17.3％）。从而，MNL将AST的预期份额高估了十分之一个百分点。尽管在上学距离附近可能会有随机的口味变化，但似乎其他重要的政策敏感变量（例如安全感）对具有不同社会经济和建筑环境特征的家庭的AST份额具有同等影响。我们的经验评估表明，考虑口味异质性并不一定会提高有关政策敏感变量的AST总份额的分析准确性。社会经济和建筑环境特征各异的家庭对AST份额的均等影响。我们的经验评估表明，考虑口味异质性并不一定会提高有关政策敏感变量的AST总份额的分析准确性。社会经济和建筑环境特征各异的家庭对AST份额的均等影响。我们的经验评估表明，考虑口味异质性并不一定会提高有关政策敏感变量的AST总份额的分析准确性。