Empirical analysis and comparisons about time-allocation patterns across segments based on mode-specific preferences
Empirical analysis and comparisons about time-allocation patterns across segments based on mode-specific preferences
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DOI：
10.1007/s11116-014-9561-2
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发表时间：
2016
期刊：
影响因子：
4.3
通讯作者：
Xue-mei Fu;Z. Juan
中科院分区：
文献类型：
--
作者：
Xue-mei Fu;Z. Juan
采用因子-集群-多群体结构方程模型（SEM）这一三阶段方法，探讨了不同人群中社会人口特征与时间使用模式之间关系的共性和多样性。通过因子聚类分析，从态度陈述中提取有意义的因素，然后将样本人群分为三个部分，每个部分都有公共交通、私家车和摩托车的独特偏好组合。通过多群体SEM，发现社会人口统计学与活动和旅行时间之间的关系在不同细分市场之间存在显著差异。本研究强调了潜在心理因素在分割中的重要性。就政策含义而言，必须以具有独特心理特征的特定人群为目标，以便高效和有效地设计和实施运输措施。
A three-stage approach, i.e., factor-cluster-multi-group Structural Equation Modeling (SEM), is designed to explore the commonalities and diversities with respect to relationships between socio-demographic characteristics and time-use patterns across different segments. Factor-cluster analysis is conducted to extract meaningful factors from attitudinal statements, and then group the sample population into three segments, each with a unique combination of mode preferences for public transit, private car, and motorcycle. By virtue of multi-group SEM, the relationships between socio-demographics and time allocated to activities and travel are found to be significantly different across segments. This study highlights the importance of latent psychological factors in segmentation. For policy implication, specific population with unique psychological features must be targeted in order to efficiently and effectively design and implement transport measures.