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Abstract
The PhD thesis consists of four selfcontained chapters in the area of Transport Economics.
The main aim of the thesis is not to produce a single message which is supported by all
four chapters. Rather, each chapter is written to make a contribution of its own. The
thesis covers a wide range of issues such as modelling behavioural reactions to travel
time variability, the measurement of the cost of travel time variability, the labour market
implication of changes in commute costs, and the application of discrete choice models to
investigate variations in willingness to pay for travel information systems across individuals
and the implication of model assumptions on the estimated distribution.
Chapter 1 is titled: “Testing the slope model of scheduling preferences with stated
preference data”, and is a joint work with Katrine Hjorth and Jeppe Rich. This study
used a stated preference data to challenge the theoretical equivalence of two methods for
measuring the value of travel time variability: the slope model of the scheduling approach
(Fosgerau & Engelson, 2011) against its reduced form model. The analysis is based on data
from two choice experiments that are identical except one has a fixed departure time while
the other allows respondents to choose their optimal departure time. According to the
scheduling model, the two experiments yield the same result if travellers can freely choose
departure time to maximise utility, and if the distribution of travel times is independent of
departure times. It turns out that the empirical results in this paper do not support the
theoretical equivalence of the two models as the implied value of travel time variability
under the reduced form model is an order of magnitude larger. This finding is robust and
is in line with a recent Swedish study by Börjesson et al. (2012). Because of data better
suited for the analysis, we ruled out some potential explanations lined up by past research
for the observed discrepancy between the two models. Although the similarity of results
across studies could suggest the presence of a more fundamental problem in estimating
the valuation of travel time variability based on data from hypothetical experiments, it
is recommended to test the equivalence of the models based on real life data before we
can rule out hypothetical bias as a potential explanation for the discrepancy. (A paper
based on this chapter was presented at the 3rd Symposium for the European Association
for Research in Transportation, Leeds, UK, 1012 September, 2014.)
Chapter 2 is titled “Valuation of travel time variability with endogenous scheduling
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of a meeting time”, and is a joint work with Mogens Fosgerau. The chapter involves a
theoretical model to examine the choice of an optimal meeting time in a situation where
individuals can freely choose meeting times. It extends the model of Fosgerau et al. (2014)
by introducing a notion of a designated meeting time and a penalty that may be imposed
when one arrives later than the meeting time. Such a meeting time can be obtained as
an agreement outcome in a bargaining process over potential meeting times. The model
considers two individuals who choose departure and meeting times in the presence of
uncertain travel times for a trip towards a joint meeting. An important feature of the
model is the physical property that a meeting starts only when both individuals arrive
at the destination. The study shows the existence of a unique optimal meeting time and
a unique Nash equilibrium in departure times. It finds that an increase in the variance
of the difference between individual travel times is costly for both individuals. It also
find that an increase in travel time variance of one person is costly for both. Compared
to Fosgerau et al. (2014), the introduction of a lateness penalty allows an additional
mechanism through which a change in travel time variance of one individual affects the
payoff of both individuals. (Previous versions of this paper were presented at the 2nd
Symposium of the European Association for Research in Transportation, Stockholm, 46
Sept, 2013; and at the ITEA’s Annual Conference and Summer School on Transportation
Economics, Toulouse, 2–6 June, 2014.)
This paper is related the scheduling model in chapter 1: both models consider scheduling
choices in the presence of travel time variability. They differ in two important respects:
First, whereas the model in this chapter allows individuals to choose a meeting time, the
slope model assumes a fixed arrival time. Moreover, while the slope model takes scheduling
choices merely as a personal matter, the model in this chapter allows strategic interaction
in scheduling choice. As a result, the slope model does not capture the effect of improved
variability of travel times for one person on another.
Chapter 3 is titled:“Advanced methods make a difference: A case of the distribution
of willingness to pay for advanced traveller information systems”. This study is concerned
with the use of discrete choice models to estimate the distribution of willingness to pay for
advanced traveller information systems and the implication of certain model assumptions
on the estimated distribution of willingness to pay. The study uses a flexible estimation
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method based on data from a stated choice experiment designed to measure the willingness
to pay for several types of information that an advanced traveller information system
can provide. Different models were estimates that vary in terms of restrictions embodied.
While simpler and relatively more advanced models yield nicely dispersed distribution
for willingness to pay, this distribution ceased to exist when some restrictions are set
free. The less restrictive model fitted the data better, and in this model, which combines
the latent class and mixed logit models, it turns out that the data do not reveal any
dispersion in the willingness to pay for advanced traveller information systems. Results
indicate that a significant share of individuals is unwilling to pay for advanced traveller
information systems and that willingness to pay is tightly distributed among those who are
willing to pay a positive amount. Findings in this study illustrate the importance of model
specification testing, and that results regarding the estimated distribution of willingness to
pay can be highly dependent on restrictions built into the model. (A paper based on this
chapter is under review at Transportation Research Part C: Emerging Technologies, and
was presented at the 94th Annual Meeting of the Transportation Research Board (TRB),
Washington, D.C., 1114 January 2015.)
Chapter 4 is titled “The effect of a firm’s relocation distance on worker turnover”,
and is a joint work with Ismir Mulalic, Jos van Ommeren and Ninette Pilegaard. Using a
matched workerfirm data from Denmark for the years 20002007, this study examines
whether and how much a firm’s relocation distance is related to worker turnover. Firm
relocation alters the pattern of commutes to workers: some workers benefit from shortened
commutes while other face lengthened commutes. The costs of residential mobility and
long distance commuting could induce those whose face lengthened commutes to move
jobs. Those who faced longer commutes incur higher commuting costs; and they can
minimise these costs by moving residence to shorten commutes or by moving to a nearby
job. When the costs of residential mobility and long distance commuting are higher, job
mobility becomes a more attractive proposition.
The analysis finds a positive and significant but moderate effect of relocation distance
on worker turnover. This effect is robust to the inclusion of firm level characteristics and
year and municipality fixed effects. Results in this chapter establish that, on average, a
10 km increase in relocation distance leads to a 2–4 percent increase in the annual rate
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of worker turnover at the firm level over a period of three years, including the year of
relocation. The estimated effect is stronger in the first year after relocation and pales
away after the third year as workers more or less fully adjust to the relocation. It is
not surprising that we obtained a smaller effect since, first most firms relocated locally.
Second, the high rate of job mobility in Denmark means that workers expect to be mobile
in the labour market; hence, it may matter less when their firm relocates. Moreover, it is
possible that workers knew about the relocation decision and left the firm in the years and
months before the relocation. The study also examines whether the distance of relocation
captures the effect of changes at the firm because of the relocation. Results indicate that,
after controlling for relocation distance, firm relocation has no significant effect on worker
turnover.
Original language  English 

Publisher  DTU Transport 

Number of pages  120 
Publication status  Published  2015 
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 1 Finished

Measurement of scheduling preferendes and the value of travel time variability
Fentie Abegaz, D., Cherchi, E., Rouwendal, J., Fosgerau, M., Hjorth, K. & Börjesson, M.
Technical University of Denmark
15/12/2011 → 30/11/2015
Project: PhD