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Railway shippers’ heterogeneous preferences with random parameters latent class model

机译:带有随机参数潜在类模型的铁路托运人的异质偏好

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Railway shippers’ preferences heterogeneity is caused by their attitudes and perception towards attributes of various rail freight services, and is differentiated amongst shippers. Random Parameter Latent Class (RPLC) model is applied to elicit Chinese railway shippers’ preferences heterogeneity in both continuous and discrete way. With a Discrete Choice Experiment (DCE) conducted in southwest area of China, 83 respondents are counted to calculate their utilities towards five rail service attributes: cost, time, frequency, reliability and safety. Results by RPLC model are compared with MNL, ML and LC model, and shows that quality attributes are more preferred by railway shippers than price attributes. Further market segmentation with RPLC clarifies that heterogeneous valuation of railway freight service quality dimension does exist among shippers, and segmentation according to shippers latent variables can be more suitable than the traditional exogenous market segmentation way. For railway companies in China, multidimensional freight services could be provided by the combination of different attributes and levels, to attract more and more shippers making railway as their first choice.
机译:铁路托运人的偏好异质性是由于他们对各种铁路货运服务属性的态度和看法所致,并且在托运人之间存在差异。应用随机参数潜在类(RPLC)模型以连续和离散方式得出中国铁路托运人的偏好异质性。通过在中国西南地区进行的离散选择实验(DCE),统计了83位受访者的效用,以评估其对铁路服务的五个属性:成本,时间,频率,可靠性和安全性。将RPLC模型的结果与MNL,ML和LC模型进行比较,结果表明,铁路运输者更喜欢质量属性,而不是价格属性。使用RPLC进行的进一步市场细分表明,托运人之间确实存在铁路货运服务质量维度的异构评估,并且与传统外生市场细分方式相比,根据托运人潜在变量进行细分可能更为合适。对于中国的铁路公司而言,可以通过组合不同的属性和级别来提供多维货运服务,以吸引越来越多的选择铁路的托运人。

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