• Problem and Context• Survey Tool• What the Future May Bring: Model Estimation

Empirically Approaching Destination Choice Set Formation A. Horni, IVT, ETH Zürich

Destination choice in MATSim Utility maximizing approach

Robustness of Estimated Parameters

Thesis Schuessler (2010):Route choice

Pellegrini et al. (1997): Shopping destination choice

Problem for operational model

The Deterministic Approach

robserved

rt

csreal(t) if any!threshold rt = f(rt)

cs formation criteria (exogenous)

To date: specification of exogenous factors for destination choice set formation rather ad hoc and more like a proof of concept.

The Probabilistic Approach

cs formation criteria

Speed-ups e.g. → convergence to deterministic approch

endogenous!

But: combinatorial complexity

Conclusion in the words of Pagliara and Timmermans (2010):

„Even though the inclusion of latent stochastic thresholds and the simultaneous estimation of thresholds and utility functions represents an important step forward in discrete choice analysis, forecasting results still depend on the researchers’ specification of the choice set.“

Decision Horizon: e.g., Grocery Shopping

meat for dinner

vegetables for dinner

dinner for cat

→ relevant choice between

and

… and not in cs immediately prior to choice!

choice set immediately prior to choice

context!

Decision Horizon – Generation of PS

Habitual „decisions“/ Routine response behavior

preferred set of stores → relevant for transport planning

extensive decisions

impulsivedecisions

non-compensatory decision behavior→ rule-based

learning process

e.g. grocery shopping

Decision Horizon: Sets Involved in the Decision Process (a First Step)

Unawareness set

Awareness set= cs(t –t)

Inept set (-)(Inert set (0))

cs(t)

Narayana and Markin 1975

Evoked set (+) (Inert set (0))

Purely Statistical Approach vs. Behavior-Based Approach

Homo oeconomicus → universal choice set

Thresholds where parameters stabilize

Lacking research

Computationally infeasibleNot explicative

inconsistentproductive?

Behavior-based criteria for cs formation

Lacking research

Allora, …

EmpiricalMethodologial

• Decison horizon• Statistical vs. behavioral model

• Preferred set- characteristics- frequencies

• Sets involved in decision process• Core area within STP• Reasons for NOT visiting a store• Trip chaining

Model estimation

MATSim model

Providing a research (survey) tool

Survey „Tool“

• Web-based • Google street view

• Grocery shopping• 300 stores, partly manually collected• future: attributes of stores

Web-based Survey Overview

Web-Survey – Google Maps & Street View

•Street View

Model Estimation

Observed choice

Awareness set?

Preferred set

Choice set

Requirements:1. Easy to survey and generate in op. models

2. Actually plays a well defined role in decision process

„New“ model

Concluding Remarks

Empirical basisTTB for time-geography

Input to discussion on decision horizon and extent of behavioral basis of discrete choice models (vs. purely statistical)

Survey tool

Pretest

- Game-like traits appreciated → less fatigue

- Dominance of closest Coop or Migros (not deliberated)