基于深度访谈对人们出行方式选择行为的研究
Research on People’s Travel Mode Choice Behavior Based on In-Depth Interview
DOI: 10.12677/orf.2025.152071, PDF,    科研立项经费支持
作者: 何妤婕, 干宏程:上海理工大学管理学院,上海
关键词: 深度访谈出行方式影响因素作用程度In-Depth Interviews Travel Modes Influencing Factors Degree of Influence
摘要: 深入地理解人们出行方式的选择行为,是加快推进国家未来的交通规划和低碳战略的必然要求,本文探究人们出行方式选择的影响因素,并比较各影响因素的作用程度。通过质性研究中的深度访谈法面对面直接了解人们出行方式选择行为,运用开放式编码法对原始访谈语句进行范畴化,剖析人们选择出行方式的原因。结果表明,影响出行方式选择的因素主要有经济、出行紧迫性、出行耗时、出行距离、出行目的、天气情况、便利情况、交通情况、舒适程度、个人偏好、低碳意愿,其中影响最大的是出行距离和便利程度,个人偏好的影响最小,人们在选择出行方式时往往将多个因素综合起来考虑。大部分受访者对低碳出行有所了解,但低碳出行的意愿尚且欠缺,需要政府部门采取措施加以引导。
Abstract: Understanding the factors that influence people’s travel mode choices is a necessary step for accelerating the implementation of national transportation planning and low-carbon strategies in the future. This paper explores the factors affecting travel mode choices and compares their relative importance. Through qualitative research using in-depth interviews, we directly gather insights into people’s travel mode choice behavior. The open coding method is employed to categorize the raw interview statements and analyze the reasons behind their travel mode choices. The results show that the main factors influencing travel mode choices include economic considerations, urgency of travel, travel time, travel distance, purpose of travel, weather conditions, convenience, traffic conditions, comfort, personal preferences, and low-carbon awareness. The most significant factors are travel distance and convenience, while personal preference has the least influence. People often take multiple factors into account when making their travel mode choices. Although most respondents are aware of low-carbon travel, their willingness to adopt it remains insufficient, indicating the need for government measures to provide guidance.
文章引用:何妤婕, 干宏程. 基于深度访谈对人们出行方式选择行为的研究[J]. 运筹与模糊学, 2025, 15(2): 146-153. https://doi.org/10.12677/orf.2025.152071

参考文献

[1] Jiao, Q., Wang, J., Cheng, L., Chen, X. and Yu, Q. (2025) Carbon Emission Reduction Effects of Heterogeneous Car Travelers under Green Travel Incentive Strategies. Applied Energy, 379, Article 124826. [Google Scholar] [CrossRef
[2] 袁韵, 徐戈, 陈晓红, 等. 城市交通拥堵与空气污染的交互影响机制研究——基于滴滴出行的大数据分析[J]. 管理科学学报, 2020, 23(2): 54-73.
[3] 陈月霞, 陈龙, 查奇芬, 等. 基于低碳心理潜变量Logit模型的出行方式预测模型[J]. 公路交通科技, 2017, 34(9): 100-108, 137.
[4] Yu, L., Xu, Y. and Shi, H. (2023) How Low-Carbon Travel Improves Travel Well-Being: Evidence from China. Sustainable Production and Consumption, 42, 247-258. [Google Scholar] [CrossRef
[5] 刘宇峰, 安韬, 钱一之, 等. 不同规模城市居民出行方式影响因素分析[J]. 中国公路学报, 2022, 35(4): 286-297.
[6] 李杨. 基于扎根理论的城市居民绿色出行影响因素分析[J]. 社会科学战线, 2017(6): 265-268.
[7] 杨冉冉, 龙如银. 基于扎根理论的城市居民绿色出行行为影响因素理论模型探讨[J]. 武汉大学学报(哲学社会科学版), 2014, 67(5): 13-19.
[8] 孙晓娥. 深度访谈研究方法的实证论析[J]. 西安交通大学学报(社会科学版), 2012, 32(3): 101-106.
[9] 王华丽, 宁静. 发达国家低碳交通建设经验[J]. 生态经济, 2022, 38(12): 1-4.
[10] 宗芳, 隽志才, 张慧永, 等. 出行时间价值计算及应用研究[J]. 交通运输系统工程与信息, 2009, 9(3): 114-119.
[11] Jing, Q., Liu, H., Yu, W. and He, X. (2022) The Impact of Public Transportation on Carbon Emissions—From the Perspective of Energy Consumption. Sustainability, 14, Article 6248. [Google Scholar] [CrossRef
[12] Lin, B. and Wang, X. (2021) Does Low-Carbon Travel Intention Really Lead to Actual Low-Carbon Travel? Evidence from Urban Residents in China. Economic Analysis and Policy, 72, 743-756. [Google Scholar] [CrossRef
[13] 田丽君, 吕成锐, 黄文彬. 基于累积前景理论的合乘行为建模与研究[J]. 系统工程理论与实践, 2016, 36(6): 1576-1584.
[14] 宗刚, 曾庆华, 魏素豪. 基于时间价值的交通出行方式选择行为研究[J]. 管理工程学报, 2020, 34(3): 142-150.
[15] 周城溪, 肖玲玲. 考虑家庭成员的早高峰出行行为分析[J]. 系统工程理论与实践, 2020, 40(12): 3220-3229.
[16] Shen, Q., Chen, P. and Pan, H. (2016) Factors Affecting Car Ownership and Mode Choice in Rail Transit-Supported Suburbs of a Large Chinese City. Transportation Research Part A: Policy and Practice, 94, 31-44. [Google Scholar] [CrossRef