2016年7月16-18号，由南京大学和IACP主办的“信息技术、活动、时间利用和出行国际学术研讨会”在南京大学成功召开！本次研讨旨在促进国际学者之间、国际学者与中国学者之间的学术交流。研讨会邀请了来自美国、加拿大、德国、英国、荷兰、以色列、智利、澳大利亚、香港等18位国际学者以及来自北京大学、中山大学、上海交通大学、华东师范大学、东南大学等20多为国内高校学者，就ICT、activity space-time and mobility发展前沿展开主题报告和圆桌论坛。专家学者们一致认为研讨会的讨论紧扣当前信息技术的快速发展，对当前研究在理论与方法上都具有重要贡献。会后，Transportation (SSCI/SCI) 杂志特组织专栏，邀请参会学者及其他学者投稿。最终，专栏共收录来自南京大学、麻省理工学院、香港大学、伦敦帝国学院、乌特勒支大学、马里兰大学、悉尼大学、东南大学学者的9篇文章，以及由Patricia L Mokhtarian, Glen Lyons, Eran Ben-Elia三位顶尖学者在圆桌论坛发起的关于（1）信息通信技术与行为、（2）旅行时间利用、（3）大数据、活动与城市空间的讨论记录。
（参会嘉宾合影）
经历了近30年的快速发展，信息通信技术已经深刻得改变了人们的活动行为及时空间利用，吸引了国外城市、交通、地理学者的广泛关注与探讨。与国外不同的是，中国正同时经历着快速的城市化与信息化，智慧城市、大数据、智慧社会等都已经上升到国家发展战略，为学者在理论与方法创新，以及规划实践与政策提供了丰富的研究案例。近年来，南京大学“ICT与城市研究团队”在甄峰教授的带领下，在ICT影响下的城市空间与居民行为活动、大数据应用与城市规划、智慧城市理论与顶层设计、文化与消费空间、流动空间、智慧旅游等领域展开了一系列的学术研究与规划实践工作。近年来，团队结合已有的研究和实践积累基础，致力于与国外学术界对话，一方面积极吸纳国外的相关研究理论与方法，并邀请国际知名学者交流指导；另一方面，将中国的研究案例介绍给国外，吸引更多的国际学者关注中国的发展，在国际学术平台中发出中国的声音！
基于此，本次专栏正是这一努力方向的体现。当然，本次专栏只是发起了本研究的一个起点。当前，信息通信技术发展的广度与深度都在快速推进，并正在或已经对我们的社会和日常生活产生了深远的影响，并且这一影响在未来的发展中仍将持续重要的作用。在中国，这一作用与城市化的影响并驾齐驱，并交织作用在一起，重构了区域/城市空间组织。因此，仍然有许多未知的问题需要回答和更为深入的研究，有待于世界范围的学者共同的努力与贡献！
最后，特别感谢Transportation杂志主编Kay Axhausen教授及编辑团队对本次专栏的支持与工作，感谢曹新宇教授发起本次专栏计划和IACP的大力支持，以及所有的匿名审稿人！
本次专栏收录文章及摘要如下：
1. Tang J., Zhen F*., Cao J., Mokhtarian. How do passengers use travel time? A case study of Shanghai-Nanjing high speed rail
Abstract: Traditional travel behavior theory regards travel time as a waste. Recent studies suggest that it carries a positive utility, among other reasons for the benefit of the activities conducted while traveling. However, most studies of travel time use have focused on conventional trains in developed countries. Few have systematically examined the permeation of information and communication technology (ICT) into travel time use and the correlates of activity participation in developing countries, particularly on high speed rail (HSR). Using a survey conducted on the Shanghai–Nanjing corridor (N = 901), this study examines how HSR passengers use their travel time and explores the correlates of the different types of activities of business and non-business travelers, respectively, through multivariate probit models. We found that 96% of the respondents use ICT during their HSR journey and that most passengers spend some of their travel time on work-related activities. Moreover, items carried and advance planning as well as work-related travel attributes contribute significantly to activity participation. However, the factors affecting time use of business and non-business travelers differ. HSR service design should facilitate passenger engagement in various activities and improvement of their travel experience. A stable internet connection, adequate power sockets, and a noise-free environment will promote both work and leisure activities on the HSR.
2. Mulley C., Ma L. How the longer term success of a social marketing program is influenced by socio-demographics and the built environment
Abstract: Urban sprawl is pervasive in Australian cities arising from the low density development of dwellings with the consequence that private vehicle use dominates daily travel in Australia. This paper examines a community based social marketing program, TravelSmart, which targeted reducing vehicle kilometres travelled as part of a transport demand management strategy. This paper uses 3-year panel data collected by GPS tracking and a conventional survey methodology in northern Adelaide, South Australia, to examine whether TravelSmart had a sustained impact and whether this was impacted by socio-economic and built-environment factors. A latent growth model is employed and demonstrates TravelSmart led to a declining trend in private car driving over the 3 years at both individual and household levels with effects being sustained beyond 1 year and up to 2 years. There is some evidence of compensatory behaviour between household members. Socio-demographic factors are significant with males decreasing their driving times faster than females. Built environment impacts were also significant with different levels of walkability showing different trajectories in the reduction of car trips after the implementation of TravelSmart, suggesting social marketing interventions work better when supported by hard policies such as a supportive built environment.
3.Ettema D. Apps, activities and travel: an conceptual exploration based on activity theory
Abstract: With the continuous advancement of (mobile) ICT devices and applications, their impact on travel, activities and time use becomes more diverse. This holds in particular for apps developed for mobile devices (smartphones). In this paper, we argue that the effect of ICT on travel and activities should be analysed at the level of a single specific device or application, rather than for broad classes of ICT devices. We propose activity theory as a framework to analyse the impact of smartphone apps on travel and activities. Activity theory describes how subjects apply tools (such as apps) to work on an object and achieve an outcome that is in line with the subject’s motive. The application of the tool is embedded in an activity system which includes a community, formal and informal rules and in which a division of labour exists. We apply activity theory to analyse the effects of Whatsapp and travel feedback apps, based on existing literature about these apps. The analyses suggest that the activity systems of each app differ greatly in terms of object, motive, outcomes, community and rules, with implications for their use and impact. Both apps have an impact on travel, but differ with respect to whether this effect is intentional. For both apps contradictions in the activity system can be identified, which may give rise to further development of the activity system. These seem, however, to be largest for travel feedback apps. Based on our exploration, we argue that quantitative research on the impact of apps should be complemented by qualitative research based on activity theory. In particular, activity theory may help to gain a better understanding of underlying mechanism by which apps influence travel, to strengthen the theoretical underpinning and interpretation of the results of quantitative research and to explore changes in the development and use of apps and their impact on travel behaviour.
4.Loo BPY., Wang B*. Factors associated with home-based e-working and e-shopping in Nanjing, China
Abstract: The widespread adoption of information and communication technology has facilitated frequent e-activities in people’s daily life. From the perspective of individual’s time use on e-working and e-shopping at home, this paper aims to enhance our understanding of the function of home beyond a living space for family life. Using a household survey of 608 full-time paid employees who conducted e-activities at home in Nanjing, China, we investigated the characteristics and patterns of home-based e-working and e-shopping. Only 7.9% of the respondents neither e-shopped nor e-worked at home. We find that the socio-demographic context, Internet use habits, attitudes towards e-working/e-shopping, and geographical accessibility have influenced the patterns of home-based e-working and e-shopping. The results indicate that the rich e-activities taking place at home have changed the time use at home and reinforced the function of home as a multifunctional hub.
5.Zegras C., Li M., Kilic T., Lozano-Gracia N., Ghorpade A., Tiberti M., Aguilera A., Zhao F. Assessing the representativeness of a smartphone-based household travel survry in Dar es Salaam, Tanzania
Abstract: The household travel survey (HTS) finds itself in the midst of rapid technological change. Traditional methods are increasingly being sidelined by digital devices and computational power—for tracking movements, automatically detecting modes and activities, facilitating data collection, etc.. Smartphones have recently emerged as the latest technological enhancement. FMS is a smartphone-based prompted-recall HTS platform, consisting of an app for sensor data collection, a backend for data processing and inference, and a user interface for verification of inferences (e.g., modes, activities, times, etc.). FMS, has been deployed in several cities of the global north, including Singapore. This paper assesses the first use of FMS in a city of the global south, Dar es Salaam. FMS in Dar was implemented over a 1-month period, among 581 adults chosen from 300 randomly selected households. Individuals were provided phones with data plans and the FMS app preloaded. Verification of the collected data occurred every 3 days, via a phone interview. The experiment reveals various social and technical challenges. Models of individual likelihood to participate suggest little bias. Several socioeconomic and demographic characteristics apparently do influence, however, the number of days fully verified per individual. Similar apparent biases emerge when predicting the likelihood of a given day being verified. Some risk of non-random, non-response is, thus, evident.
6.Song Y., Fan Y., Li X., Ji Y*. Multidimensional visualization of transit smartcard data using space-time plots and data cubes
Abstract: Given the wide application of automatic fare collection systems in transit systems across the globe, smartcard data with on- and/or off-boarding information has become a new source of data to understand passenger flow patterns. This paper uses Nanjing, China as a case study and examines the possibility of using the data cube technique in data mining to understand space–time travel patterns of Nanjing rail transit users. One month of smartcard data in October, 2013 was obtained from Nanjing rail transit system, with a total of over 22 million transaction records. We define the original data cube for the smartcard data based on four dimensions—Space, Date, Time, and User, design a hierarchy for each dimension, and use the total number of transactions as the quantitative measure. We develop modules using the programming language Python and share them as open-source on GitHub to enable peer production and advancement in the field. The visualizations of two-dimensional slices of the data cube show some interesting patterns such as different travel behaviors across user groups (e.g. students vs. elders), and irregular peak hours during National Holiday (October 1st–7th) compared to regular morning and afternoon peak hours during regular working weeks. Spatially, multidimensional visualizations show concentrations of various activity opportunities near metro rail stations and the changing popularities of rail stations through time accordingly. These findings support the feasibility and efficiency of the data cube technique as a mean of visual exploratory analysis for massive smart-card data, and can contribute to the evaluation and planning of public transit systems.
7.Dong H., Cirillo C*., Diana M. Activity involvement and time spent on computers for leisure: an econometric analysis on the American Time Use Survey dataset
Abstract: Internet is capturing more and more of our time each day, and the increasing levels of engagement are mainly due to the use of social media. Time spent on social media is observed in the American Time Use Survey and recorded as leisure time on Personal Computer (PC). In this paper, we extend the traditional analysis of leisure activity participation by including leisure activities that require the use of a PC. We study the substitution effects with both in-home and out-of-home leisure activities and the time budget allocated to each of them. The modeling framework that includes both discrete alternatives and continuous decision variables allow for full correlation across the utility of the alternatives that are all of leisure type and the regressions that model the time allocated to each activity. Results show that there is little substitution effect between leisure with PC and the relative time spent on it, with in-home and out-of-home leisure episodes. Households with more children and full-time workers are more likely to engage in in-home and PC related leisure activities (especially during weekends). Increments in the travel time of social trips result in significant reductions in leisure time during weekdays.
8.Zhu P., Wang L., Jiang Y., Zhou J. Metropolitan size and the impacts of telecommuting on personal travel
Abstract: Telecommuting has been proposed by policy makers as a strategy to reduce travel and emissions. In studying the metropolitan size impact of telecommuting on personal travel, this paper addresses two questions: (1) whether telecommuting is consistently a substitute or complement to travel across different MSA sizes; and (2) whether the impact of telecommuting is higher in larger MSAs where telecommuting programs and policies have been more widely adopted. Data from the 2001 and 2009 National Household Travel Surveys are used. Through a series of tests that address two possible empirical biases, we find that telecommuting consistently had a complementary effect on one-way commute trips, daily total work trips and daily total non-work trips across different MSA sizes in both 2001 and 2009. The findings suggest that policies that promote telecommuting may indeed increase, rather than decrease, people’s travel demand, regardless of the size of the MSA. This seems to contradict what telecommuting policies are designed for. In addition, model results show that the complementary impact of telecommuting on daily travel is lower in larger MSAs, in terms of both daily total work trips and daily total non-work trips.
9.Suel E., Daina N., Polak J. A hazard-based approach to modelling the effects of online shopping on intershopping duration
Abstract: Despite growing prevalence of online shopping, its impacts on mobility are poorly understood. This partially results from the lack of sufficiently detailed data. In this paper we address this gap using consumer panel data, a new dataset for this context. We analyse one year long longitudinal grocery shopping purchase data from London shoppers to investigate the effects of online shopping on overall shopping activity patterns and personal trips. We characterise the temporal structure of shopping demand by means of the duration between shopping episodes using hazard-based duration models. These models have been used to study inter-shopping spells for traditional shopping in the literature, however effects of online shopping were not considered. Here, we differentiate between shopping events and shopping trips. The former refers to all types of shopping activity including both online and in-store, while the latter is restricted to physical shopping trips. Separate models were estimated for each and results suggest potential substitution effects between online and in-store in the context of grocery shopping. We find that having shopped online since the last shopping trip significantly reduces the likelihood of a physical shopping trip. We do not observe the same effect for inter-event durations. Hence, shopping online does not have a significant effect on overall shopping activity frequency, yet affects shopping trip rates. This is a key finding and suggests potential substitution between online shopping and physical trips to the store. Additional insights on which factors, including basket size and demographics, affect inter-shopping durations are also drawn.
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