华南理工大学学报(自然科学版) ›› 2026, Vol. 54 ›› Issue (3): 114-126.doi: 10.12141/j.issn.1000-565X.250067

• 智慧交通系统 • 上一篇    下一篇

考虑同群效应的大学生出行方式选择行为研究

张锐1,2, 葛郁晗1   

  1. 1.长安大学 运输工程学院,陕西 西安 710064
    2.北京交通大学 综合交通运输大数据应用技术交通运输行业重点实验室,北京 100044
  • 收稿日期:2025-03-13 出版日期:2026-03-25 发布日期:2025-08-22
  • 作者简介:张锐(1991—),女,博士,讲师,主要从事多方式条件下出行者出行行为分析、交通规划等研究。E-mail: zhangrui@chd.edu.cn
  • 基金资助:
    国家自然科学基金项目(72371035);综合交通运输大数据应用技术交通运输行业重点实验室(北京交通大学)开放基金项目(ZHJTDSJ202203)

Research on College Students' Travel Mode Choice Behavior Considering Peer Effect

ZHANG Rui1,2, GE Yuhan1   

  1. 1.School of Transportation Engineering,Chang’an University,Xi’an 710064,Shaanxi,China
    2.Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Beijing Jiaotong University,Beijing 100044,China
  • Received:2025-03-13 Online:2026-03-25 Published:2025-08-22
  • About author:张锐(1991—),女,博士,讲师,主要从事多方式条件下出行者出行行为分析、交通规划等研究。E-mail: zhangrui@chd.edu.cn
  • Supported by:
    the National Natural Science Foundation of China(72371035)

摘要:

研究在校大学生的校外出行方式选择行为,对于改善高校学生的校外出行环境、提高社会参与度、促进其身心健康发展具有重要意义。已有研究忽视了同伴群体对个体出行方式选择的影响。该文针对缺乏统一标准确定大学生有效群组的不足,通过室友关系质量量表界定有效群组,基于问卷调查获得不同出行场景下在校大学生的校外出行偏好数据;为补充同群效应在出行行为决策中的作用机制研究,从关系质量与心理特性出发,引入关系强度调节的同伴矩阵并构建多个同群效应的网络经济学线性模型,结合固定效应和两阶段最小二乘法解决潜在的内生性问题,通过模型评估确定识别和测度同群效应的最佳模型;基于模型标定结果分析宿舍群体对在校大学生个体校外出行方式选择的影响和潜在作用机制。结果表明:相较于广义计量模型和局部聚集模型,考虑关系强度的局部平均模型在识别和测度同群效应时具有更好的稳健性;随着出行距离的增加以及出行时间约束的放松,在校大学生个体出行方式选择行为受同伴相关行为的影响程度(即内生同群效应)降低;同伴的月生活费、家庭成员人数、有无驾照、开放性及环保意识等因素对在校大学生个体出行方式选择具有显著的外生同群效应;外向型个体相较于内向型个体具有更为显著的从众性同群效应,休闲娱乐场景下开放型个体比保守型个体的从众性同群效应更显著。该研究拓展了相关理论边界,可为高校低碳出行的精细化引导与分群体干预提供实证依据。

关键词: 城市交通, 出行方式选择行为, 局部平均模型, 在校大学生, 同群效应

Abstract:

Investigating the behavior of college students in choosing off-campus travel mode is of great significance for enhancing the off-campus travel environment, increasing their social engagement, and further promoting their physical and mental health development. However, previous studies neglected the influence of peer groups on individual travel mode choices. To address the lack of uniform standard for defining effective peer groups among college students, this study employs a roommate relationship quality scale to identify effective peer groups. Data on off-campus travel preferences across different travel scenarios are collected via questionnaire surveys. To further explore the role of peer effects in travel behavior decision-making, we introduce a peer matrix adjusted by relationship strength based on relational quality and psychological traits, and construct multiple network econometric linear models to capture peer effects. Potential endogeneity issues were addressed though combining fixed effects and two-stage least squares, and the optimal model for identifying and measuring peer effects is determined through model evaluation. Finally, based on the model calibration results, the influence and potential mechanisms of dormitory groups on individual college students’ off-campus travel mode choice are analyzed. The results show that, compared to gene-ralized econometric models and local aggregation models, the local average model incorporating relationship strength demonstrates greater robustness in identifying and measuring peer effects. As travel distance increases and time constraints relax, the influence of peer-related behaviors on college students’ individual travel mode choices-that is, the endogenous peer effect-decreases. Factors such as peers’ monthly living expenses, number of family members, possession of a driver’s license, openness and environmental awareness have significant exogenous peer effects on individual travel mode choices. Furthermore, extroverted individuals exhibit more pronounced conformity-based peer effects compared to introverted ones, and in entertainment contexts, open-minded individuals show stronger than conservative individuals. The research extends the boundaries of relevant theories and provides empirical evidence for the targeted guidance and group-specific interventions aimed at promoting low-carbon travel among college students.

Key words: urban transportation, travel mode choice behavior, local average model, college student, peer effect

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