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Departure Time Choice: Modelling Individual Preferences, Intention and Constraints. Mikkel Thorhauge Supervisors : Jeppe Rich and Elisabetta Cherchi. Papers.
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Departure Time Choice: Modelling Individual Preferences, Intention and Constraints Mikkel Thorhauge Supervisors: Jeppe Rich and Elisabetta Cherchi
Papers • Thorhauge, M., Cherchi, E., Rich, J., 2014. Building Efficient Stated Choice Design for Departure Time Choices using the Scheduling Model: Theoretical Considerations and Practical Implementations. Selected Proceedings from the Annual Transport Conference at Aalborg University, ISSN 1903-1092. • Thorhauge, M., Cherchi, E., Rich, J, 2015. How Flexible is Flexible? Accounting for the Effect of Rescheduling Possibilities in Choice of Departure Time for Work Trips. Transportation Research Part A: Practice and Policy, 86, 177-193. • Thorhauge, M., Haustein, S., Cherchi, E, 2015. Social Psychology Meets Microeconometrics: Accounting for the Theory of Planned Behaviour in Departure Time Choice. Transportation Research Part F: Traffic Psychology and Behaviour, 38, 94-105. • Thorhauge, M., Cherchi, E., Rich, J, 2014. The Effect Of Perceived Mobility Necessity in the Choice of Departure Time. 93rd Transportation Research Board (TRB), Washington, USA. • Thorhauge, M., Cherchi, E., Walker, J., Rich, J, 2016. Joining Random Utility Models with the Theory of Planned Behaviour in a Framework of Departure Time Choice Modelling. 95th Transportation Research Board (TRB), Washington, USA, 2016. • Walker, J, L., Wang, Y., Thorhauge, M., Ben-Akiva, M., 2015. D-Efficient or Deficient? A Robustness Analysis of SP Experimental Designs in a VOT Estimation Context. 94th Transportation Research Board (TRB), Washington, USA. • Thorhauge, M., Kaplan, S., Vuk, G., 2012. A Survey of Joint Activities and Travel of Household Members in the Greater Copenhagen Metropolitan Region. Selected Proceedings from the Annual Transport Conference at Aalborg University, ISSN 1903-1092. External papers
Content • Background and motivation • Role of constraints • Role of psychological effects • Definition of a unified conceptual framework • Data collection • Methodology and modelling results: • Constraints at work • Daily activities • Integration of psychological effects into the scheduling model • Conclusion
Content • Background and motivation • Role of constraints • Role of psychological effects • Definition of a unified conceptual framework • Data collection • Methodology and modelling results: • Constraints at work • Daily activities • Integration of psychological effects into the scheduling model • Conclusion
Background & Motivation WHY Departure Time Choice? Urban congestion is “One of the most relevant preoccupations of transport specialists both in the developed and developing world.” (Ortúzar et al., 2014, pp. 691) • The daily economical loss in relation to congestion in the Greater Copenhagen Area has been estimated to a total of 6 billion DKK (approx. 800 million euros). • Congestion is expected to increase further due to urbanisation. • Studies have shown that people are more likely to change their departure time to address the problem of congestion rather than changing mode.
Background & Motivation Departure time studies The problem has mainlybeenstudied from a microeconomic perspective (the basic concept: the Scheduling Model by Small, 1982). The basic concept of the Scheduling Model is that it assumes that individuals make a rational choice based on the tradeoff between travel time, departure time (and thus the early or late delay with respect to their preferred arrival time at destination). Commonly studies also account for travel cost, travel time variability, and a discrete lateness penalty (e.g. Hendrickson & Planke, 1984; Small, 1987; Small et al, 1995; Börjesson, 2009; Arellanaet al., 2012).
Background & Motivation The Scheduling Model ) Where:
Background & Motivation Role of constraints Crucial in the departure time is whether individuals are flexible or not in their choice. Flexibility can be: • Direct: i.e. at work (or more generally on the activity we are studying the departure time for) • Indirect: i.e. due to other activities realised before/after work or more generally during the day.
Background & Motivation Constraints at work Two approaches have mainly been used to measure flexibility at work: • Fixed/flexible work hours. • Constraints/no constraints at work. They have been used for the same purpose However: • Having fixed working hours does not necessarily imply that people are not allowed a certain degree of flexibility in how early or late they can arrive at work and vice versa. • The information about fixed/flexible working hours measures general working conditions, while the information on constraints can vary from day to day and it is more related to the specific trip. It has not been discussed if the two approaches in fact captures the same type of flexibility, and if not, to which extend they differ.
Background & Motivation Constraints due to other daily activities Daily activities have been studied only in terms of: • Joint decision between the outward and return legs of the same tour (de Jong et al., 2003; Hess et al., 2007; Arellanaet al., 2012). • Number of intermediate stop on the way to work (Lizanaet al., 2013). However: • The choice of when to realize a given trip is (often) related to the full daily activity schedule. • Time/space constraints in one activity can also form restrictions in the flexibility of other activities, since these affect the preference for the related departure time. No studies provide evidence of the effect that daily activities and their constraints have on the choice of departure time to work.
Background & Motivation Psychological effects The psychological literature has produced many evidences that individual behaviour clearly departs from the “perfect rationality”. Most psychological literature within transport focusses on the Theory of Planned Behaviour (TPB, Ajzen, 1991) because it: • is a widely accepted psychological methodology. • can be regarded “as a social psychological variant of the general rational choice approach” (Bamberg, 2012, p. 222). In TPB Intention is the main determinant of behaviour, and is influenced by Attitude, Subjective Norms, and Perceived Behavioural Control.
Background & Motivation Psychological effects Several studies have tried to capture psychological effects and have used the Hybrid Choice Model framework (Ben-Akiva et al., 2002; 2012) to estimate the joint effect of the latent variables in the discrete choice. However: • The majority of the studies focus only on few latent constructs, and often consider only attitudes (Daly et al., 2012; Jensen et al., 2013; Kamargianni and Polydoropoulou, 2013; Glerum et al. 2014). • Only few studies consider a hierachical structure among some, but not all, psychological items (Paulsen et al., 2013; Kamargianni et al., 2014). • Arellana (2012) is the only study to measure attitudinal effects in a departure time context. No studies in transport have explored the full psychological effects as implied in the Theory of Planned Behaviour in a micro-economic framework.
Background & Motivation Objective Define a methodological framework for the departure time problem that link together the following effects: • Objective constraints,daily activity schedule. • Full psychological effects, also beyond the TPB. Explore in detail the role of constraints: • The effect of the typical ways of measuring flexibility for work trips • The effect of other activities realised during the day. Explore the broader spectrum of psychological effects: • Derive psychological factors based on the TPB • Estimate their effect in a HCM framework Discuss the impact of these effects in prediction Along the line, I also explored the use of efficient designs for departure time
Content • Background and motivation • Role of constraints • Role of psychological effects • Definition of a unified conceptual framework • Data collection • Methodology and modelling results: • Constraints at work • Daily activities • Integration of psychological effects into the scheduling model • Conclusion
Unified conceptual framework Utility Dep. time activity j Scheduling Model Objective Constraints Level of Service • State of the art: • Flexibility at work • Trips/activities in the main working tour only Socio-economic characteristics Dep. time activity j-1 Dep. time activity j+1
Unified conceptual framework Behaviour: Departure time choices Utility Dep. time activity j SchedulingModel Dep. time activity 1 Dep. time activity j-1 Objective Constraints Level of Service Dep. time activity j+1 • Extension: • Account for the full daily activity schedule • These activities can be constrained Socio-economic characteristics Dep. time activity N
Unified conceptual framework Behaviour: Departure time choices Utility Dep. time activity j Attitude Perception Norms Psychological effects Dep. time activity 1 Dep. time activity j-1 State of the art (not in dep. time problems) Objective Constraints Elements of the TPB Level of Service Dep. time activity j+1 Socio-economic characteristics Dep. time activity N
Unified conceptual framework Perceived Mobility Necessities Extended TPB Perceived Behavioural Control Behaviour: Departure time choices Utility Dep. time activity j Intention Attitude Personal Norms Social Norms Psychological effects Dep. time activity 1 Dep. time activity j-1 Extention Objective Constraints Level of Service Dep. time activity j+1 Socio-economic characteristics Dep. time activity N
Unified conceptual framework Perceived Mobility Necessities Extended TPB Perceived Behavioural Control Family, friends, colleagues Behaviour: Departure time choices Societal influence Utility Values Dep. time activity j Intention Attitude Personal Norms Social Norms Frequency of past behaviour Further extension: overall effects Habit Dep. time activity 1 Emotions Social Role Dep. time activity j-1 Objective Constraints Level of Service Dep. time activity j+1 Socio-economic characteristics Dep. time activity N
Unified conceptual framework Family, friends, colleagues Behaviour: Departure time choices Societal influence Values Frequency of past behaviour Further extension: overall effects Habit Dep. time activity 1 Emotions Social Role Dep. time activity j-1 Objective Constraints Extended TPB Dep. time activity j+1 Attitude Dep. time activity N Social Norms Utility Dep. time activity j Intention Personal Norms Perceived Behavioural Control Perceived Mobility Necessities Level of Service Socio-economic characteristics
Content • Background and motivation • Role of constraints • Role of psychological effects • Definition of a unified conceptual framework • Data collection • Methodology and modelling results: • Constraints at work • Daily activities • Integration of psychological effects into the scheduling model • Conclusion
Data collection Structure of the questionnaire: • Introduction • Full trip diary of a 24-hour period • Specific questions about activity/trip reschedule flexibility • Stated Preference experiment • Statements for Psychometrics items • Socio-demographic information about the respondent
Data collection Information about Activity flexibility • Activity compulsory/essential : • Could you have omitted this trip/activity? (yes/no) • Activity constrained in space: • Could you have carried out this activity at another location? (yes/no). • Activity constrained in time: • Could you have done this activity another day? (yes/no) • Could you have done this activity at another time of the day? (yes/no). • Were there any restrictions to how early you could have departed? (yes/no) If “yes” what is the earliest possible departure time? • Were there any restrictions to how late you could have arrived? (yes/no) If “yes” what is the latest possible arrival time? • Activityconstrained due to the interrelation with other people (social constraints): • Could another person have done this activity for you? (yes/no) • Did you decide yourself when to depart? (yes/partly/no)
Data collection Stated Choice experiment • Efficient design with: • 3 alternatives: early, the same, later • 4 attributes (Dep. Time, TT, TC, TTV) • 3 levels for each attribute, except TC which have 4 levels
Data collection Stated Choice experiment Prior parameters are nessesary in order to build effecient designs: A meta analysis reported in Börjesson (2009) was used, in order to maintain the same ratio between the parameters for TT and SDE/SDL. With these priors we simulated appr. 18000 choices assuming people choose according to the scheduling model plus an EV1 error term. The prior parameters could be recuperated during the design phase when estimating simulated choices.
Data collection TPB statements
Data collection Target sample • Criterias to select the sample of interest: • People between 18-65, commuting to the city center. • Has a car and use it to work. • Experiencing congestion or traffic jam and arrived between 6:00 to 10:00 at the workplace yesterday. • TT to work (by car) should be between 10-60 minutes. • Data were collected directly at companies, organisations and universities • After cleaning the data, the final sample consists of 286 individuals and 2515 observations in total.
Methodology and modelling results Content • Background and motivation • Role of constraints • Role of psychological effects • Definition of a unified conceptual framework • Data collection • Methodology and modelling results: • Constraints at work • Daily activities • Integration of psychological effects into the scheduling model • Conclusion
Methodology and modelling results Constraints at work We note that: • 65% of our sample is formed by individuals with flexible working hours (35% with fixed working hours), while 51% declared that they have no constraints in their arrival time to work. • 30% of the workers with flexible working hours declared that they do have constraints in arriving later; while 16% of the workers with fixed working hours declared they had no constraints in arriving later. Numbers in brackets shows the column percentage
Methodology and modelling results Constraints at work To study this further Mixed Logit models were estimated based on the Scheduling Model These two models does not allow us to estimate the same difference among preferences. To see how this affected peoples elasticy, we test the models in a forecast scenario.
Methodology and modelling results Constraints at work Assumptions: • People do not change mode • Travel time does not change Forecast scenario: We introduce a toll ring around Copenhagen Tollcost: • 7:30-8:30: 20 DKK (appr. 2.50€) • 7:00-7:30 and 8:30-9:00: 10 DKK (appr. 1.25€) • Before 7:00 and after 9:00: notollcost
Methodology and modelling results Constraints at work Assumptions: • People do not change mode • Travel time does not change Tollcost: • 7:30-8:30: 20 DKK (appr. 2.50€) • 7:00-7:30 and 8:30-9:00: 10 DKK (appr. 1.25€) • Before 7:00 and after 9:00: notollcost
Methodology and modelling results Content • Background and motivation • Role of constraints • Role of psychological effects • Definition of a unified conceptual framework • Data collection • Methodology and modelling results: • Constraints at work • Daily activities • Integration of psychological effects into the scheduling model • Conclusion
Methodology and modelling results Effect of daily activities
Methodology and modelling results Effect of daily activities We adopted the following operational definition of flexibility in daily activities: • trip complexity:refers to the number of stops involved in a trip chain • activity pattern complexity:involve not only the number of activities performed, it also involves the relative amount of time devoted to each activity. In particular we used: • Shannon’s entropy measure: where p is the percentage of stops realized in each trip chain t. means that all stops (i.e. other activities) are concentrated only in a trip chain, means that activities are spread across different trip chains during the main tour around work.
Methodology and modelling results Effect of daily activities
Methodology and modelling results Effect of daily activities Marginal Utility of ESDE No Constraints at work:
Methodology and modelling results Effect of daily activities 22% 10% 28% 194% 23% 51% Neglecting other daily activities overestimate the elasticity.
Methodology and modelling results Content • Background and motivation • Role of constraints • Role of psychological effects • Definition of a unified conceptual framework • Data collection • Methodology and modelling results: • Constraints at work • Daily activities • Integration of psychological effects into the scheduling model • Conclusion
Methodology and modelling results Integrated TPB and SM The extended TPB specifically applied to the departure time choice requires some more consideration. We suggest departure time choice to be determined by three behavioural intentions: • intention to arrive on time. • intention to have short travel times. • intention to have low travel costs. It was not possible to study all items.
Methodology and modelling results Integrated TPB and SM Hybrid Choice Model
Methodology and modelling results Integrated TPB and SM The mathematical model of the Hybrid Choice Framework is formed by: Structural equations: Choice of dep. time: Psychological constructs: Measurement equations: Choice of dep. time: Psychological constructs:
Methodology and modelling results Model estimation: Discretechoice model
Methodology and modelling results Model estimation: latent variables
Methodology and modelling results Integrated TPB and SM
Methodology and modelling results Integrated TPB and SM
Content • Background and motivation • Role of constraints • Role of psychological effects • Definition of a unified conceptual framework • Data collection • Methodology and modelling results: • Flexibility constraints • Daily activities • Integration of psychological effects into the scheduling model • Conclusion
Methodology and modelling results Conclusions In this thesis I have tried to define a unified framework to study departure time choice, highlighting the role of the daily activities schedules, constraints, and psychological elements and how all these affect each other. Inside this theoretical framework, this thesis in particular: • Has explored the role of constraints (at work and due to the full activity schedule) in the departure time choice and its effect in demand prediction. • Has explored the psychological items relevant for departure time choices and showed the importance of accounting for all the TPB effects and in particular the mediating role of intention. • Provides evidence of a fully D-efficient stated choice design for a departure time context, which performed very well.