Congestion management in protected areas: accounting for respondents’ inattention and preference heterogeneity in stated choice data
研究通过联合处理属性忽视和偏好异质性的模型，分析游客对意大利阿尔卑斯山保护区可持续管理的偏好，发现新模型比传统方法更优，为公园管理提供参考。
Abstract Congestion levels in protected areas can be predicted by destination choice models estimated from choice data. There is growing evidence of subjects’ inattention to attributes in choice experiments. We estimate an attribute non-attendance latent class–random parameters model (LC–RPL) that jointly handles inattention and preference heterogeneity. We use data from a choice experiment designed to elicit visitors’ preferences towards sustainable management of a protected area in the Italian Alps. Results show that the LC–RPL model produces improvements in model fit and reductions in the implied rate of inattention, as compared to traditional approaches. Implications of results for park management authorities are discussed.