Tomás Ruiz

Empirical Analysis of Factors Affecting the Resolution of Activity-Scheduling Conflicts

This paper describes an analysis undertaken to characterize how individuals resolve conflicts in activity scheduling. The focus is on the case in which a single new activity episode is inserted between two existing consecutively planned activities. The data used in the analysis were collected from students and staff members at a university, with the use of a web-based survey instrument. A range of characteristics, including demographic and socioeconomic variables of the individual, attributes of the observed activity-travel schedule, and attributes of the implied activities can be linked with resolution of the conflict. The results suggest that people tend to resolve schedule conflicts by simultaneously changing the starting time and the duration of the posterior planned activity. Several endogenous relationships have been found among the amount of modifications of these variables.

Analysis of Planning Decisions During the Activity-Scheduling Process

This paper focuses on studying the incidence of different types of activity-scheduling decisions, using data from a computerized activity-scheduling survey (CHASE) conducted in Toronto, Canada. Several decisions are studied: with whom the activity takes place, location of the activity, the time planning horizon, and modification or deletion of activities during the scheduling process. The results from a multivariate probit model show that several characteristics of the planned schedule and planned activities are most important in explaining the decisions made during the scheduling process. Individual and household characteristics also play an important role. Significant correlations among the planning decisions suggest that the process of activity scheduling occurs with a high degree of endogeneity.

Assessing planning decisions by activity type during the scheduling process

Existing activity-based models still make assumptions about scheduling decision processes that are not well-informed by empirical evidence. In this article, a step forward is taken to better understand the activity-scheduling process and to improve activity-based models. In particular, different planning decision mechanisms depending on several activity type classifications are explored. First, models describing the planning of several aggregate activity types are considered. For these activities, three planning decisions are studied: location, planning time horizon and rescheduling. The ‘with whom’ planning decision is also studied when subtypes of recreational/entertainment activities are investigated in depth. Significant differences are found in modelling results for each activity type and subtype and each planning decision. These results confirm the existence of different mechanisms underlying the activity-travel decision process when activity types and subtypes are considered. Important conclusions related to the improvement of microsimulation models are highlighted.

Characterizing Global Activity Schedule Adjustment Behavior by Using a Sequence Alignment Method

Considerable interest has developed recently in the decision-making processes underlying activity schedule adjustment. This paper suggests a method, based on sequence alignment techniques, to measure schedule adjustment behavior and applies the method to develop a model of the factors influencing schedule adjustment, with the use of data from a recent Internet-administered survey. The results indicate that the amount of schedule modification that occurs is largely determined by characteristics of the planned schedule instead of background socioeconomic or activity-related variables. The implications of this finding for future research in this area are considered.

Measuring the impact of travel behavior change programs on the activity scheduling process

Abstract This paper describes data collection techniques that were used in a pilot research with the aim of studying how individual activity scheduling processes are modified after participating in Travel behavior change programs (TBCP). Measuring instrument consisted of a weekly activity–travel scheduling process panel survey. Two survey waves were implemented before and after the application of TBCP to about 60 per cent of panelists. The other 40 per cent joined a control group (CG). A descriptive analysis of differences found on the activity scheduling process is presented. Average number of decisions related to adding or modifying the pre-planned activity–travel agenda during the scheduling process did not vary appreciably between first and second survey wave. In contrast, significant differences in planned and executed activity–travel attributes between TBCP and CG participants, and between first and second survey waves, are found. After participating in TBCP, respondents planned and executed less use of private vehicle (PV) than previously. Other changes on activity–travel attributes during the scheduling process are observed as well. Survey fatigue and conditioning effects are minor. But the combination of both effects causes a reduction of number of activities reported per person-day by the end of the research week in second survey wave.

Simultaneous Analysis of Global Decisions in Activity Travel Scheduling Process

This paper presents a global characterization of activity travel scheduling decisions that uses a new data set recently collected in Valencia, Spain. As an innovative approach, bivariate probit sample selection models are used to take into account potential self-selectivity bias in the decision process. Model 1 studies decisions to realize or not realize activity travel episodes by considering whether they have been included in the planned agenda. Model 2 analyzes decisions to perform activity travel episodes as they were planned or to modify one or more of their attributes before execution by considering whether their realization had been previously decided. Random parameters are used in both models to accommodate heterogeneity effects. Location, timing, and duration of activity travel episodes are important explanatory variables in the two scheduling processes studied. Few demographic and socioeconomic variables affect the decision processes. Significant correlations between decisions included in both models are found. Policy implications of the analysis results are highlighted.

Effect of travel behaviour change programmes on time allocated to driving

Since part of car dependency is stemmed from personal choices of car over other modes of transportation, technological solutions are not the only way to reduce car use. Travel Behaviour Change Programmes (TBCP) are significantly cheaper transportation policy measures, which have evolved in order to shift people voluntarily out of their cars and into public transportation or non-polluting modes of travel, such as walking or cycling. Recently, a two-wave activity scheduling process panel survey was conducted over a period of two years in the city of Valencia (Spain). Part of the respondents received a set of TBCP between both survey waves. We have used doubled censored Tobit models to assess the effect of the TBCP on time allocation to driving a car or a motorbike. Results show that participation in the TBCP is significantly positive to reduce car or motorbike use, and its effectiveness is affected by different socio-economic factors.

Assessment of the Degree of Willingness to Change from Motorized Travel Modes to Walking or Cycling

This paper presents an analysis of the degree of willingness to change from motorized travel modes to walking or cycling. The aim of the analysis is to reduce uncertainty between stated willingness to change and real shifts from car or transit to nonmotorized transportation modes. Data were collected in the city of Valencia, Spain, through a novel data collection effort based on multiple survey methods. Respondents traveling by car or transit were asked about their willingness to change to walking or cycling under the implementation of improvement measures to be selected. Then a hypothetical scenario was presented to respondents who stated a willingness to change; in the scenario, the previously selected measures were implemented and respondents were supposed to be cycling or walking. In addition, the costs of their usual travel mode were gradually reduced until they gave up cycling or walking. Those who decided to keep on walking or cycling were assumed to have a strong willingness to change. A statistical analysis performed with Heckmans sample selection model permitted identification of demographic, socioeconomic, and travel-related factors influencing the degree of willingness to change. Results revealed that car users presented a stronger willingness to switch to walking or cycling than transit users. In addition, older respondents showed a stronger willingness to change to both walking and cycling. Work- and school-related journeys were less associated with walking than noncommuting journeys, but they were more related to cycling. Policy implications of the results are highlighted.

Determinants of elimination decisions in the activity scheduling process

Abstract This paper presents an analysis on the determinants related to a particular rescheduling decision in the activity-travel scheduling process: elimination decisions, which consist in the non-execution of pre-planned activity-travel episodes. Data used come from an in-depth computer-assisted telephone interview (CATI) follow up survey carried out during the implementation of the first wave of an activity scheduling process panel survey. Open-ended answers related to the reasons associated to changes between pre-planned and executed agenda are studied. First, an interpretative qualitative method based on analytic induction (AI) is used to cope with the complex nature of the rescheduling decision under study and the characteristics of the available data. Then, econometric models are used to analyze factors influencing those decisions and complement the qualitative analysis. The detailed qualitative and quantitative study of those decisions has resulted in the identification of several reasons associated to the elimination of activity-travel episodes from the activity agenda. Factors influencing those reasons have been explored.

Factors Influencing the Travel Scheduling of Driving Trips of Habitual Car Users

The paper presents an analysis of scheduling and rescheduling decisions that are associated with driving trips of habitual car users and that employs a new data set for processing of activity travel schedules collected in Valencia, Spain, in 2010. A bivariate probit model with sample selection is used to accommodate the influence of planning on the decision to execute a trip as planned or not. The explicative variables included in the model are socioeconomic characteristics of respondents, travel characteristics, and facets of the activity at origin and the activity executed at destination, including the scheduling process decisions associated with them. The results demonstrate that a significant correlation exists between the choice of planning and rescheduling a driving trip. Other findings suggest that characteristics of the activity at destination, including the scheduling process decisions, have a greater influence on the choice of planning or executing spontaneously than the characteristics of the activity at origin. In contrast, characteristics and scheduling of the activity at origin have significantly more influence on the decision of rescheduling or not rescheduling a planned driving trip than attributes of the activity at destination.