社交网络信息对出行行为的影响研究综述

doi:10.16097/j.cnki.1009-6744.2023.02.001

摘要/Abstract

摘要： 为定量梳理社交网络信息对出行行为影响的研究成果，本文基于Web of Science核心数据库与CNKI知网数据库，检索并筛选2010—2022年间133篇英文文献和32篇中文文献。采用知识图谱分析和传统定性文献分析相结合的方法，量化统计文献的年度发文量、研究热点国家、关键词图谱这3类指标，并从方法模型、社交网络信息行为、社交网络信息对出行决策的影响、社交网络信息对出行活动的影响这4个方面总结现有研究成果。结果表明：数据来源上，现有研究的基础数据尚未实现特征维与决策维融合，需要进一步融合多源数据提升研究结论的鲁棒性；研究方法上，现有研究缺乏分析方法之间的相互支撑，可整合多种研究手段跨学科分析社交网络信息对出行行为的影响；研究内容上，现有研究成果无法全面反映未来出行的发展趋势，且对出行者异质性关注不足，需结合无人驾驶、共享出行等新场景，考虑出行者异质性解析社交网络信息与出行行为之间的联系模式。

关键词: 城市交通, 社交网络, 出行行为, 影响, 知识图谱

Abstract: To quantitatively review the research results of the influence of social network information on travel behavior, this paper retrieved and screened 133 English and 32 Chinese literatures from 2010 to 2022 based on the database of Web of Science and China National Knowledge Infrastructure. Through the combination of knowledge graph and qualitative literature analysis, the paper quantified and counted three indexes of annual publication volume, research hotspot countries, and keyword graph. The research results were presented in four aspects, including research methodology, social network information behavior, the influence of social network information on travel decisionmaking, and the influence of social network information on travel activities. The results show that: (1) in terms of data sources, the basic data of existing research haven't achieved the integration of feature dimension and decision dimension, and it is necessary to further integrate multi-source data to improve the robustness of research conclusions. (2) In terms of research methods, the existing research lack mutual support among analysis methods, and a variety of research methods can be integrated to analyze the influence of social network information on travel behavior across disciplines. (3) In terms of research content, the existing research results cannot fully reflect the development trend of future travel, and the heterogeneity of travelers can be given more attention. It is necessary to analyze the connection mode between social network information and travel behavior considering traveler heterogeneity in combination with new scenarios such as autonomous driving and shared travel.

Key words: urban traffic, social network, travel behavior, influence, knowledge graph

中图分类号:

U121

陈坚, 张弛, 傅志妍, 刘柯良. 社交网络信息对出行行为的影响研究综述[J]. 交通运输系统工程与信息, 2023, 23(2): 1-10.

CHEN Jian, ZHANG Chi, FU Zhi-yan, LIU Ke-liang. Research Review of Influence of Social Network Information on Travel Behavior[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(2): 1-10.

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链接本文: http://www.tseit.org.cn/CN/10.16097/j.cnki.1009-6744.2023.02.001

http://www.tseit.org.cn/CN/Y2023/V23/I2/1

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