Studying the relationship between activity participation,social networks,expenditures and travel behavior on leisure activities

Transportation - In the context of an increasing interest in understanding travel for non-mandatory activities, such as recreation and socializing, this work focuses on studying the relationships...     

Commuting trip satisfaction in Beijing: Exploring the influence of multimodal behavior and modal flexibility

In the past decade, many studies have explored the relationship between travelers’ travel mode and their trip satisfaction. Various characteristics of the chosen travel modes have been found to influence trip experiences; however, apart from the chosen modes, travelers’ variability in mode use and their ability to vary have not been investigated in the trip satisfaction literature. This current paper presents an analysis of commuting trip satisfaction in Beijing with a particular focus on the influence of commuters’ multimodal behavior on multiple workdays and their modal flexibility for each commuting trip. Consistent with previous studies, we find that commuting trips by active modes are the most satisfying, followed by trips by car and public transport. In Beijing, public transport dominates. Urban residents increasingly acquire automobiles, but a strict vehicle policy has been implemented to restrict the use of private cars on workdays. In this comparatively constrained context for transport mode choice, we find a significant portion of commuters showing multimodal behavior. We also find that multimodal commuters tend to feel less satisfied with trips by alternative modes compared with monomodal commuters, which is probably related to their undesirable deviation from habitual transport modes. Furthermore, the relationship between modal flexibility and trip satisfaction is not linear, but U-shaped. Commuters with high flexibility are generally most satisfied because there is a higher possibility for them to choose their mode of transport out of preference. Very inflexible commuters can also reach a relatively high satisfaction level, however, which is probably caused by their lower expectations beforehand and the fact that they did not have an alternative to regret in trip satisfaction assessments.     

Traveler delay costs and value of time with trip chains, flexible activity scheduling and information

The delay costs of traffic disruptions and congestion and the value of travel time reliability are typically evaluated using single trip scheduling models, which treat the trip in isolation of previous and subsequent trips and activities. In practice, however, when activity scheduling to some extent is flexible, the impact of delay on one trip will depend on the actual and predicted travel time on itself as well as other trips, which is important to consider for long-lasting disturbances and when assessing the value of travel information. In this paper we extend the single trip approach into a two trips chain and activity scheduling model. Preferences are represented as marginal activity utility functions that take scheduling flexibility into account. We analytically derive trip timing optimality conditions, the value of travel time and schedule adjustments in response to travel time increases. We show how the single trip models are special cases of the present model and can be generalized to a setting with trip chains and flexible scheduling. We investigate numerically how the delay cost depends on the delay duration and its distribution on different trips during the day, the accuracy of delay prediction and travel information, and the scheduling flexibility of work hours. The extension of the model framework to more complex schedules is discussed.     

An empirical investigation on the dynamic processes of activity scheduling and trip chaining

Investigation of the dynamic processes of activity scheduling and trip chaining has been an interest of transportation researchers over the past decade because of its relevance to the effectiveness of congestion management and intelligent transportation systems. To empirically examine the processes, a computerized survey instrument is developed to collect household activity scheduling data. The instrument is unique in that it records the evolution of activity schedules from intentions to final outcomes for a weekly period. This paper summarizes the investigation on the dynamic processes of activity scheduling and trip chaining based on data collected from a pilot study of the instrument. With the data, ordered logit models are applied to identify factors that are pertinent to the scheduling horizon of activities. Results of the empirical analysis show that a daily schedule often starts with certain activities occupying a portion of the schedule and other activities are then arranged around these pre-occupants. Activities of shorter duration are more likely to be opportunistically inserted in a schedule already anchored by their longer duration counterparts. Persons with children often expect more constraining activities than those with no children. The analysis also shows that female respondents tend to be more structured in terms of how the week is planned. Additionally, analysis of travel patterns reveals that many trip-chains are formed opportunistically. Travel time required to reach an activity is positively related to the scheduling horizon for the activity, with more distant stops being planned earlier than closer locations.     

The effect of round-off error on computed solutions of trip distribution problems

Round-off error analyses of two versions of the Kruithof method are given. It is shown than an alternative implementation is numerically superior to the usual implementation. Since it also has the advantage of requiring less writing in secondary memory, and requires the same number of arithmetic operations, the case for always using the alternative implementation seems indisputable.     

On the effect of operational service attributes on transit satisfaction

Public transport (PT) providers aim to offer services that meet users’ satisfaction, and for this, they can control some operational service attributes such as frequency, speed, crowdedness and reliability. Understanding how these objective attributes affect user satisfaction is essential to improve it cost-effectively, but these associations have not been examined enough in the PT literature. This study aims to unveil how key transit operational variables actually experienced by users affect their satisfaction. We analysed data derived from a multiannual consumer satisfaction survey for the Santiago de Chile Metro system; between January 2013 and June 2016 (n?=?41,993), where approximately 1000 questionnaires were completed each month. We also gained access to a set of operational variables managed by Metro for the same period, including more than 1.4 million records. With this unique dataset, we first developed a structural equation model (SEM) with users’ perceived attributes, finding that safety, ease of boarding, response to critical incidents (CI), the number and type of CI endured, and information, were the variables that mostly affected satisfaction. We also examined heterogeneity in transit satisfaction with SEM-MIMIC models, by characterising the user population through their trip and socioeconomic characteristics, finding a striking result: that as users age they are more satisfied with the system. Next, we assessed whether including operational service attributes, such as crowding levels, frequency, commercial speed and CI, added predictive power to the proposed model. We found that the number of CI, speed, frequency and crowdedness, plus their variability (measured through the coefficient of variation), affected transit satisfaction at significant levels. Including these objective service attributes provided more explanatory power to the SEM-MIMIC transit satisfaction models. Policy recommendations for improving satisfaction, derived from our results, are: to implement an automatic control system for the number of passengers on Metro platforms (as safety and ease of boarding are critical issues for passengers); and to deploy a comprehensive tactical plan to address CI: determine which happen more often, take actions to minimise them and provide better responsive actions.

     

Examining the effects of out-of-home and in-home constraints on leisure activity participation in different seasons of the year

Using multi-day, multi-period travel diaries data of 56 days (four waves of two-week diaries) for 67 individuals in Stockholm, this study aims to examine the effects of out-of-home and in-home constraints (e.g. teleworking, studying at home, doing the laundry, cleaning and taking care of other household member[s]) on individuals’ day-to-day leisure activity participation decisions in four different seasons. This study also aims to explore the effects of various types of working schedules (fixed, shift, partial- and full-flexible) on individuals’ decisions to participate in day-to-day leisure activities. A pooled model (56 days) and wave-specific models (14 days in each wave) are estimated by using dynamic ordered Probit models. The effects of various types of working schedules are estimated by using 28 days of two waves’ data. The results show that an individual’s leisure activity participation decision is significantly influenced by out-of-home work durations but not influenced by in-home constraints, regardless of any seasons. Individuals with shift working hours engage less in day-to-day leisure activities than other workers’ types in both spring and summer seasons. The thermal indicator significantly affects individuals’ leisure activity participation decisions during the autumn season. Individuals exhibit routine behaviour characterized by repeated decisions in participating in day-to-day leisure activities that can last up to 14 days, regardless of any seasons.     

Analysis of social networks,social interactions,and out-of-home leisure activity generation: Evidence from Japan

Transportation - This article analyses the connection between social networks, social interactions and out-of-home leisure activity generation in the context of Japanese society. A multilevel...     

A conceptual and methodological framework of leisure activity loyalty accommodating the travel context

As leisure travel continues to grow, it has become a critical subject for planners and decision-makers since it significantly impacts regional economic and social development as well as contributes to emission levels and congestion. Despite being a significant percentage of our travel, however, leisure travel behavior is still not very well understood. The goal of this article is to contribute to our understanding of leisure activity participation by considering leisure activity loyalty within the travel context. In particular, this study focuses on one specific dimension of travel context: travel extent (i.e., whether an individual participates in a leisure activity on a daily versus a long-distance basis). As such, this article first introduces a unified conceptual framework for measuring leisure activity loyalties within a travel context, based on two distinct dynamics of leisure loyalty behavior—destination attachment and activity involvement. Additionally, this article uses a unique 2001 NHTS dataset comprised of households’ daily and long-distance leisure activities to undertake a unique empirical analysis of five distinct leisure activities using the conceptual framework and a copula-based model methodology. The findings confirmed that households demonstrate significant loyalties to travel contexts across all leisure activities, especially resting and sightseeing.     

Inferring origin–destination trip matrices from aggregate volumes on groups of links: a case study using volumes inferred from mobile phone data

The origin–destination matrix is an important source of information describing transport demand in a region. Most commonly used methods for matrix estimation use link volumes collected on a subset of links in order to update an existing matrix. Traditional volume data collection methods have significant shortcomings because of the high costs involved and the fact that detectors only provide status information at specified locations in the network. Better matrix estimates can be obtained when information is available about the overall distribution of traffic through time and space. Other existing technologies are not used in matrix estimation methods because they collect volume data aggregated on groups of links, rather than on single links. That is the case of mobile systems. Mobile phones sometimes cannot provide location accuracy for estimating flows on single links but do so on groups of links; in contrast, data can be acquired over a wider coverage without additional costs. This paper presents a methodology adapted to the concept of volume aggregated on groups of links in order to use any available volume data source in traditional matrix estimation methodologies. To calculate volume data, we have used a model that has had promising results in transforming phone call data into traffic movement data. The proposed methodology using vehicle volumes obtained by such a model is applied over a large real network as a case study. The experimental results reveal the efficiency and consistency of the solution proposed, making the alternative attractive for practical applications. Copyright © 2011 John Wiley & Sons, Ltd.