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Modelling contact mode and frequency of interactions with social network members using the multiple discrete-continuous extreme value model

机译:使用多重离散连续极值模型对社交网络成员的联系方式和互动频率进行建模

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摘要

Communication patterns are an integral component of activity patterns and the travel induced by these activities. The present study aims to understand the determinants of the communication patterns (by the modes face-to-face, phone, e-mail and SMS) between people and their social network members. The aim is for this to eventually provide further insights into travel behaviour for social and leisure purposes. A social network perspective brings value to the study and modelling of activity patterns since leisure activities are influenced not only by traditional trip measures such as time and cost but also motivated extensively by the people involved in the activity. By using a multiple discrete-continuous extreme value model (Bhat, 2005), we can investigate the means of communication chosen to interact with a given social network member (multiple discrete choices) and the frequency of interaction by each mode (treated as continuous) at the same time. The model also allows us to investigate satiation effects for different mode's of communication. Our findings show that in spite of people having increasingly geographically widespread networks and more diverse communication technologies, a strong underlying preference for face-to-face contact remains. In contrast with some of the existing work, we show that travel-related variables at the ego level are less important than specific social determinants which can be considered while making use of social network data. (C) 2017 Elsevier Ltd. All rights reserved.
机译:交流模式是活动模式以及由这些活动引起的旅行的组成部分。本研究旨在了解人与社交网络成员之间的沟通方式(通过面对面,电话,电子邮件和短信的方式)的决定因素。目的是最终为社交和休闲目的提供进一步的旅行行为见解。社交网络的观点为活动模式的研究和建模带来了价值,因为休闲活动不仅受时间和费用等传统旅行方式的影响,而且还受到活动人员的广泛推动。通过使用多个离散的连续的极值模型(Bhat,2005年),我们可以调查与特定社交网络成员进行交互的通信方式(多个离散选择)以及每种模式的交互频率(视为连续)与此同时。该模型还允许我们研究不同通信模式下的饱食感。我们的发现表明,尽管人们在地理上分布越来越广泛,通信技术也越来越多样化,但面对面接触的强烈内在偏好仍然存在。与一些现有的工作相反,我们表明,在自我层面上与旅行相关的变量没有在使用社交网络数据时可以考虑的特定社会决定因素重要。 (C)2017 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Transportation research》 |2017年第3期|16-34|共19页
  • 作者单位

    Univ Leeds, Inst Transport Studies, Leeds LS2 9JT, W Yorkshire, England|Univ Leeds, Choice Modelling Ctr, Leeds LS2 9JT, W Yorkshire, England;

    Univ Leeds, Inst Transport Studies, Leeds LS2 9JT, W Yorkshire, England|Univ Leeds, Choice Modelling Ctr, Leeds LS2 9JT, W Yorkshire, England;

    Univ Leeds, Inst Transport Studies, Leeds LS2 9JT, W Yorkshire, England|Univ Leeds, Choice Modelling Ctr, Leeds LS2 9JT, W Yorkshire, England;

    Oak Ridge Natl Lab, Ctr Transportat Anal, Oak Ridge, TN USA;

    RheinMain Univ Appl Sci, Wiesbaden, Germany;

    Swiss Fed Inst Technol, Zurich, Switzerland;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Social network analysis; Multiple discrete continuous; Snowball sample;

    机译:社交网络分析;多个离散连续;雪球样本;

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