Table 1 Running example of an agent’s decision-making for a 18km-journey from Sion to Sierre/Siders. Note that the expected utility is a cost function, i.e. agent prefer lower valueFootnote
Data collected from (Google Map; Rome2rio website; Mobility and Transport Microcensus 2017; Swiss Household Energy Demand Survey (SHEDS) 2017)
Level | Determinant | w | EU |
|---|---|---|---|
1st | Evaluation (Price - Swiss franc), Belief = 100% | 2 | EU(car) = 4 EU(train) = 3 EU(bike) = 0 |
Evaluation (Duration - hours), Belief = 100% | 4 | EU(car)≈ 0.3 EU(train)≈ 0.2 EU(bike)≈ 1 | |
Norm (similarity with others) | 3 | EU(train) = 1 EU(car) = 2 EU(bike) = 3 | |
Role (environmental friendliness) | 2 | EU(car) = 3 EU(train) = 2 EU(bike) = 1 | |
Self-concept (personal preference) | 3 | EU(car) = 1 EU(train) = 2 EU(bike) = 3 | |
Emotion (enjoyment) | 1 | EU(car) = 1 EU(train) = 2 EU(bike) = 3 | |
Frequency (past similar trips - note that lower value means more usage) | 3 | EU(car) = 0 EU(train) = 0 EU(bike) = 1 | |
2st | Consequence (Evaluation + Belief) | 4 | EU(car) = 4/7*2 + 0.3/1.5*4 ≈ 1.94 EU(train) = 3/7*2 + 0.2/1.5*4 ≈ 1.39 EU(bike) = 0/7*2 + 1/1.5*4 ≈ 2.67 |
Social factors (Norm + Role + Self-concept) | 2 | EU(car) = 1/6*3 + 3/6*2 + 1/6*3 = 2 EU(train) = 2/6*3 + 2/6*2 + 2/6*3 ≈ 2.67 EU(bike) = 3/6*3 + 1/6*2 + 3/6*3 = ≈ 3.33 | |
Affects (Emotion) | 2 | EU(car) = 1/6*1 ≈ 0.17 EU(train) = 2/6*1 ≈ 0.33 EU(bike) = 3/6*1 = 0.5 | |
3rd | Intention (Consequence + Social factors + Affect) | 4 | EU(car) = 1.94/6*4 + 2/8*2 + 0.17/1*2 ≈ 2.13 EU(train) = 1.39/6*4 + 2.67/8*2 + 0.33/1*2 ≈ 2.26 EU(bike) = 2.67/6*4 + 3.33/8*2 + 3/1*2 ≈ 3.28 |
Habit (Frequency) | 3 | EU(car) = 0/1*3 = 0 EU(train) = 0/1*3 = 0 EU(bike) = 1/1*3 = 3 | |
Facilitating conditions (lower mean easier to access) | 2 | EU(car) = 0 EU(train) = 1 (agent is far from train station) EU(bike) = 0 | |
Behaviour output | EU(car) = 2.13/7.67*4 + 0/2*3 + 0/2*2 ≈ 1.11 EU(train) = 2.26/7.67*4 + 0/2*3 + 1/2*2 ≈ 2.18 EU(bike) = 3.28/7.67*4 + 1.5/2*3 + 3/2*2 ≈ 6.96 |