GEO4-3907 (5 EC)
Written Exam (65%)
Policy brief (35%)
Introduction (Dick Ettema, 11 nov)
Policies don't seem to have a huge impact on the use of mobility, car use very stable
Transport poverty: not having enough public transportation leading to … exclusion
Lecture 1: Mobility Behaviour and Sustainability Mobility (Dick Ettema, 11 nov)
If we want to make changes to the mobility system, we usually want to change system level outcomes
(congestion, air pollution, number of people injured in traffic)
Examples of challenges
- Plans to ban fossil fuel cars in 2025 → convince households to buy an electric car (and make this
choice/behaviour)
- Klimaat akkoord: stimulate EV Ownership, use zero/low emission modes and use shared mobility
options
- Air pollution → stimulate zero emission travel modes
- Battling regional congestion in Utrecht region
→ depends on individual citizens’ choices, changing behaviour. Much of the policies target people’s
behaviour
Homo economicus: utility maximalization
Act in an economic rational way (to predict people's behaviour)
● Traveller makes discrete choices out of a choice set
○ Go shopping or not (trip generation)
○ Go to hypermarket or corner store (destination choice)
○ Car, bus, bike (mode choice)
○ Buy an EV or a PHEV (or e-bike)
Underlying assumptions:
● Individuals have free choice (you will not be experiencing constraints)
● Individuals have complete information
● Individuals are rational decision makers
Random Utility Theory
- Individuals expect to derive utility from choosing an alternative (EU = expected utility)
- The utility EU depends on characteristics (attributes) of the alternative and of the individual
- Individuals choose the alternative with the highest expected utility
, ● Utility U (is a linear function of attributes of the alternatives (time it takes by bus, costs of bus)
and individuals (age)
● Attributes Xi of alternative
● Attributes Yi of individual
e.g.
● Choice probability
● Alternative with the highest utility is most likely chosen (Logit model)
● Coefficients derived from observed choices
Example of Random Utility Theory (Ben-Elia & Ettema, 2011)
- Issue: how to make people travel out of the peak?
- Focus on economic incentive
- Losses (tolls, taxes, fuel prices, early/late arrival) vs gains (monetary incentives)
→ als mensen vaak er rijden krijgen ze een brief om buiten de spits te rijden, waarvoor ze een bijdrage
kregen. Stop people giving incentives → back to old behaviour
Implication 1
● Random Utility Maximization Discrete Choice Models are the basis of travel forecasting models
● Combination of engineering and economics!
● Effects of population growth
● Effects of job locations
● Effects of new roads, public transport services
● Based on invariant preferences!
● Predict (road capacity, demography etc) and provide
You make a forecast from other sources
, Recent example: verbreding A27, want veel file verwacht.
Implication 2
● Monetization!
● U= a*time + b*cost
● Value of travel time savings (VTTS) = a/b (€/hour)
● Idea: People would be willing to reduce their commute time.
Homo psychologicus
Traveller as homo psychologicus
● Doubts about ‘homo economicus’ → see behavioural economics (Thaler, Kahneman)
● Psychological theories about how humans make decisions:
○ Theory of Planned Behavior (Ajzen, 1991)
If your intention to do something is stronger, than people are more likely to change their
behaviour
○ Norm Activation Theory (Schwartz, 1977)
● Personal norms drive pro-social behavior
● Personal norms are feelings of moral obligation
● Personal norms lead to action in case of awareness and responsibility
● Underlying value orientation
● E.g.:
○ ‘With my travel mode choice for university routes I am also responsible
for the degree of traffic pollution in the environment.’
○ If I use the car for university routes next time, I would have a “moral
stomach-ache”
● “Flying guilt” - IATA
○ Habit formation theories (Verplanken et al., 1997)
■ Habit is a repeated choice
■ Scripts stored in long-term memory
■ Prevent overload of information processing
■ Adaptive, leading to goal attainment
■ Behaviour change requires a break of habit
■ The stronger the habit, the less likely a behaviour change
→ Many travel that we do we don’t think about it, we just do it
Written Exam (65%)
Policy brief (35%)
Introduction (Dick Ettema, 11 nov)
Policies don't seem to have a huge impact on the use of mobility, car use very stable
Transport poverty: not having enough public transportation leading to … exclusion
Lecture 1: Mobility Behaviour and Sustainability Mobility (Dick Ettema, 11 nov)
If we want to make changes to the mobility system, we usually want to change system level outcomes
(congestion, air pollution, number of people injured in traffic)
Examples of challenges
- Plans to ban fossil fuel cars in 2025 → convince households to buy an electric car (and make this
choice/behaviour)
- Klimaat akkoord: stimulate EV Ownership, use zero/low emission modes and use shared mobility
options
- Air pollution → stimulate zero emission travel modes
- Battling regional congestion in Utrecht region
→ depends on individual citizens’ choices, changing behaviour. Much of the policies target people’s
behaviour
Homo economicus: utility maximalization
Act in an economic rational way (to predict people's behaviour)
● Traveller makes discrete choices out of a choice set
○ Go shopping or not (trip generation)
○ Go to hypermarket or corner store (destination choice)
○ Car, bus, bike (mode choice)
○ Buy an EV or a PHEV (or e-bike)
Underlying assumptions:
● Individuals have free choice (you will not be experiencing constraints)
● Individuals have complete information
● Individuals are rational decision makers
Random Utility Theory
- Individuals expect to derive utility from choosing an alternative (EU = expected utility)
- The utility EU depends on characteristics (attributes) of the alternative and of the individual
- Individuals choose the alternative with the highest expected utility
, ● Utility U (is a linear function of attributes of the alternatives (time it takes by bus, costs of bus)
and individuals (age)
● Attributes Xi of alternative
● Attributes Yi of individual
e.g.
● Choice probability
● Alternative with the highest utility is most likely chosen (Logit model)
● Coefficients derived from observed choices
Example of Random Utility Theory (Ben-Elia & Ettema, 2011)
- Issue: how to make people travel out of the peak?
- Focus on economic incentive
- Losses (tolls, taxes, fuel prices, early/late arrival) vs gains (monetary incentives)
→ als mensen vaak er rijden krijgen ze een brief om buiten de spits te rijden, waarvoor ze een bijdrage
kregen. Stop people giving incentives → back to old behaviour
Implication 1
● Random Utility Maximization Discrete Choice Models are the basis of travel forecasting models
● Combination of engineering and economics!
● Effects of population growth
● Effects of job locations
● Effects of new roads, public transport services
● Based on invariant preferences!
● Predict (road capacity, demography etc) and provide
You make a forecast from other sources
, Recent example: verbreding A27, want veel file verwacht.
Implication 2
● Monetization!
● U= a*time + b*cost
● Value of travel time savings (VTTS) = a/b (€/hour)
● Idea: People would be willing to reduce their commute time.
Homo psychologicus
Traveller as homo psychologicus
● Doubts about ‘homo economicus’ → see behavioural economics (Thaler, Kahneman)
● Psychological theories about how humans make decisions:
○ Theory of Planned Behavior (Ajzen, 1991)
If your intention to do something is stronger, than people are more likely to change their
behaviour
○ Norm Activation Theory (Schwartz, 1977)
● Personal norms drive pro-social behavior
● Personal norms are feelings of moral obligation
● Personal norms lead to action in case of awareness and responsibility
● Underlying value orientation
● E.g.:
○ ‘With my travel mode choice for university routes I am also responsible
for the degree of traffic pollution in the environment.’
○ If I use the car for university routes next time, I would have a “moral
stomach-ache”
● “Flying guilt” - IATA
○ Habit formation theories (Verplanken et al., 1997)
■ Habit is a repeated choice
■ Scripts stored in long-term memory
■ Prevent overload of information processing
■ Adaptive, leading to goal attainment
■ Behaviour change requires a break of habit
■ The stronger the habit, the less likely a behaviour change
→ Many travel that we do we don’t think about it, we just do it
