CPB

Time Use and Values ofTime and Reliability in
the Netherlands

Discussion Paper

176
Gerard de Jong
Marco Kouwenhoven
SignificanceRoundtable

Corporate Partnership
Board

176

Discussion Paper

Gerard de Jong
Marco Kouwenhoven
SignificanceRoundtable

Time Use and Values ofTime and Reliability in
the Netherlands

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Cite this work as: de Jong, G. and M. Kouwenhoven (2019), “Time Use and Values of Time and Reliability
in the Netherlands”, International Transport Forum Discussion Papers, No. 2019/11, OECD Publishing,Paris.

TIME USE AND VALUES OF TIME AND RELIABILITY IN THE NETHERLANDS | DISCUSSION PAPER NO. 2019/11 | ITF ROUNDTABLE 176

Table of contents
National studies of the values of travel time in the Netherlands ......................................................... 5
Results from the third national value of travel time study in the Netherlands ..................................... 6
Determining values of travel time for business, work and other trips ............................................ 6
Impact of distance on the value of travel time................................................................................ 9
Estimating the value of travel time reliability ................................................................................ 11
Calculating values of travel time for business travel with the Hensher equation ............................... 12
Calculating the employer part on the value of travel time for business........................................ 13
The impact of productive use of travel time on valuing travel time savings ....................................... 16
Changes in value of travel time over the years .................................................................................. 17
Summary and discussion ................................................................................................................... 19
Notes................................................................................................................................................. 21
References ........................................................................................................................................ 22
Annex A. Impact of base time and distance on value of travel time: Results from the2011 Dutch study .............................................................................................................................. 24

FiguresFigure 1. A stated preference experiment choice screen with a reliability factor for car users ............ 7
Figure 2. Value of travel time by trip purpose as a function of travel time in the observed
reference situation .............................................................................................................................. 9
Figure 3. Value of travel time for commuting by mode as a function of travel time in theobserved reference situation............................................................................................................. 10
Figure 4. Value of travel time by trip purpose as a function of travel cost in the observed
reference situation ............................................................................................................................ 10
Figure 5. Differences in the value of travel time between the stated preference experiments,
by trip purpose .................................................................................................................................. 11© OECD/ITF 20193

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TablesTable 1. Number of completed surveys in 2011................................................................................... 8
Table 2. Values of time for passenger transport .................................................................................. 8
Table 3. Reliability ratios for passenger transport .............................................................................. 12
Table 4. Fraction of journey time spent working by mode for business trips ..................................... 14
Table 5. Relative productivity of work during travel by mode for business trips ................................ 14
Table 6. Fraction of saved time that would be spent working by mode for business trips ................. 15
Table 7. Productive value of a unit of work time by mode for business trips ..................................... 15
Table 8. Mean employer’s value for travel time for business trips in 2010 EUR per hour .................. 16
Table A1. Value of travel time by trip purpose as a function of travel time in the observed
reference situation ............................................................................................................................ 24
Table A2. Value of travel time for commuting by mode as a function of travel time in theobserved reference situation............................................................................................................. 24
Table A3. Value of travel time for by trip purpose as a function of travel cost in the observed
reference situation ............................................................................................................................ 25

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National studies of the values of travel time in
the Netherlands
Value of travel time (VTT) is used in the Netherlands primarily for converting travel time changes intomonetary benefits as part of cost-benefit analysis (CBA) of investment projects and policies in transport.1
Official standard tables with VTTs by travel purpose and mode (at some stage also by income group)
have been available since 1990. VTTs need to be regularly updated as they may change over time, andthese changes may not be properly captured by annual growth factors in VTT based on income
elasticities. The first national VTT study in the Netherlands was carried out in between 1988-1990 (Hague
Consulting Group, 1990). Follow-up studies were conducted between 1997-1998 (Hague Consulting
Group, 1998) and 2009-2013 (Significance et al., 2013; KiM, 2013; Kouwenhoven et al., 2014a).2
All three national surveys shared the following study characteristics:


Reliance on willingness-to-pay for travel time by travellers – determined using within-mode
stated preference experiments (including two-attribute experiments) and discrete choicemodels – that takes into account observed heterogeneity through personal and householdinteraction terms for all modes and travel purposesCombination of stated preference results for travellers with productivity measurements fromthe same survey for the employer, combined in the framework of the Hensher equation, for thebusiness VTTExpansion of the survey results to national average values using the national travel surveys.

There were, however, some changes in the methodology that took into account methodologicaldevelopments that had taken place over time and to meet new objectives:

Shift from paper-based interviews to internet interviews in the third survey, but with the same
method of recruiting the travellers en-route (at stations, bus stops, petrol stations and parkings)

Inclusion of the value of travel time reliability (VTTR) as a second study objective besides VTT(also in the third survey)

Use of nonlinear transport time and cost functions and dependence on the offered changes intime and cost (both added to the third survey).

Use of discrete choice methods (notably panel latent class models) that take account ofunobserved heterogeneity (and heteroskedasticity) in the VTT distribution (in the third survey).

Comparisons have been made between the outcomes of the first and the second surveys (Gunn, 2001)
as well as between those of the second and third surveys (Kouwenhoven et al., 2014b, 2017) to see whatmight be learned about changes in the VTT over time. Finally, the impact of worthwhile use of travel timeitself on the VTT has been analysed in Kouwenhoven and de Jong (2018) using data from the third
national survey.
This paper will discuss work carried out in the Netherlands on the VTT itself as well as on some related
topics that have received more attention in recent years extending the scope of VTT research. The next
section will present the main methodological characteristics and the key outcomes for both VTT and
VTTR from the latest national study. It will also present some new results on the relation between VTT© OECD/ITF 20195

TIME USE AND VALUES OF TIME AND RELIABILITY IN THE NETHERLANDS | DISCUSSION PAPER NO. 2019/11 | ITF ROUNDTABLE 176

and travel time and cost for all purposes. A discussion of the use of the Hensher equation for businesstravel will follow. The paper will then look specifically at the issue of spending travel time in a useful way,
generating utility which reduces the travel time disutility used in CBA. The comparisons between thethree valuation studies to see how the VTT changes over time will be presented next. The final section
will summarise the results and discuss what can be expected to happen to the VTT and its use in projectappraisals in the future.

Results from the third national value of travel time
study in the Netherlands
The first and the second national VTT studies in the Netherlands did not include the value of travel time
reliability. During early 2000s, decision-makers on projects in the Netherlands began to realise thepotential importance of including benefits from travel time variability improvements in CBAs since thebenefits from transport investment might be otherwise underestimated. This change in perspective also
resulted from a shift in transport policy from reducing travel time to reducing the uncertainty in travel
time. Projects with a focus on the latter could not be properly evaluated. As a result, the third national
study was not only undertaken to update the official values of time in both passenger and freighttransport in the Netherlands, but also to deliver values of reliability based on empirical foundation.

Determining values of travel time for business, work and other trips
In the third national VTT study in the Netherlands, the method used for the employee part of thebusiness VTT is the same as for the full VTT for work and other trips. The Hensher equation (see page 12)
was used to get the full business VTT including an employer and an employee component.
For determining a VTT and VTTR of travellers, stated preference (SP) experiments were designed where
respondents were asked to choose between two hypothetical alternatives for a trip they actually made.
In all these experiments, respondents should trade between improvements and deteriorations of travel
time and travel cost, and in some experiments also between changes in reliability and arrival time.
The questionnaire used in the 2009 and 2011 surveys included three SP experiments:A simple travel time and costs trade-off experiment (experiment 1)



Two experiments that add reliability of travel time, but also include departure and arrival time(experiments 2a and 2b).

In earlier projects, it had already been decided that the variability of transport time should be measured
by the standard deviation of the travel time distribution (RAND Europe, 2004; Hamer, de Jong and Kroes,
2005; HEATCO, 2006). The main reason behind this choice was the assessment that including travel time
variability in transport forecasting models would be quite difficult, and that using the standard deviation
would be the easiest option. Any formulation that would go beyond the standard deviation of travel time6

© OECD/ITF 2019

TIME USE AND VALUES OF TIME AND RELIABILITY IN THE NETHERLANDS | DISCUSSION PAPER NO. 2019/11 | ITF ROUNDTABLE 176(or its variance) would be asking too much from the national and regional models that are regularly usedin CBA in the Netherlands.3
Even when one uses the standard deviation in the later modelling, it does not have to be used as such in
the SP experiments. Many survey respondents will not understand the concept of standard deviation.
Therefore, in the SP experiments 2a and 2b reliability of travel time is presented by a series of fivepossible (equi-probable) travel times. Exploratory in-depth face-to-face interviews had been carried out
earlier to determine the best concept and format for the presentation of the concept of reliability torespondents. The verbal presentation of five possible travel times turned out to work best in many
respects (Significance et al., 2007; Tseng et al., 2009). Figure 1 gives an example of a choice situation for
the SP experiments that include reliability.
The difference between experiments 2a and 2b is that in experiment 2b the most likely arrival times(corresponding with the second and third travel times) for both alternatives are the same. In experiment
2a these are different, so that this experiment has more scope for rescheduling.
Figure 1. A stated preference experiment choice screen with a reliability factor for car users

Note: The text has been translated to English from the original Dutch.
Source: Significance et al. (2007).

In the third national VTT study, the respondents were initially recruited from a commercial internet panel(the 2009 data). This resulted in VTTs which were implausibly low, probably because the internet panel© OECD/ITF 20197

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consists by its nature of people with a relatively low VTT (selectivity). A second round of data collection
took place in 2011 with recruitment of travellers in railway stations, at bus stops and at petrol stations
and parking garages, ports and airports, and with subsequent interviews using an internet link. Theinternet questionnaires contained both SP experiments as well as questions to obtain data to populate
the Hensher equation (the latter is discussed on page 12).
Table 1. Number of completed surveys in 2011
Mode of transport

Reason for travel

Total

CommuteBusiness

Other

Car

184

306

125

615

Public transport

256

69

194

519

Train

131

52

103

286

BTM*

125

17

91

233

Air

9

29

163

201

Recr. navigation

0

0

95

95

Total

449

404

577

1 430

*BTM stands for bus, tram, metro

The 2011 data on 1 430 respondents have been used for the estimation of the final models. The internet
panel responses (5 760 respondents) are only used for the estimation of the interaction effects withperson and households attributes.
For the travellers, advanced discrete choice models were estimated on the data from the three SP
experiments. These models allow the values of time to depend on the actual travel time and travel cost,on the size of the time and cost changes offered in the SP experiments and on other attributes of the
respondents (e.g. education, income, age, household composition). Panel Latent Class models were used
to account for unobserved value of time differences in the population and for the fact that theestimation sample is a panel, i.e. that each respondent provided multiple observations.
Table 2. Values of time for passenger transport (Euro per hour, price level 2010)
Car

Train

Trip purpose
CommuteBus, tram,
metro

All surface
modes

9.25

11.50

7.75

9.75

Business

26.25

19.75

19.00

24.00

85.75

Business employee

12.75

15.50

10.50

13.50

85.75

Business employer

13.50

4.25

8.50

10.50

-

Other

7.50

7.00

6.00

7.00

47.00

8.25

All purposes combined

9.00

9.25

6.75

8.75

51.75

8.25

Mode

Air

Recr.
navigation

Note: All values are rounded off to the nearest multiple of EUR 0.25 and include VAT.

The recommended values of time were calculated by weighting the sampled respondents to represent
the distribution of time travelled in the trips recorded in the 2010 Dutch national travel survey
8© OECD/ITF 2019

TIME USE AND VALUES OF TIME AND RELIABILITY IN THE NETHERLANDS | DISCUSSION PAPER NO. 2019/11 | ITF ROUNDTABLE 176“Onderzoek Verplaatsingen in Nederland” (Dutch for “study on trips in the Netherlands”), or OViN (CBS,2011). The resulting values of time are displayed in Table 2.

Impact of distance on the value of travel time
Distance was not explicitly included in the discrete choice models estimated on the 2011 (and 2009)
survey data. However, the models do include the (non-linear) influence of travel time and travel cost on
the VTT. This refers to the direct dependence of the VTT on the travel time and costs of the reference
trip (base time and base cost). However, there are also indirect effects (i.e. through income). Up to now,
the overall influence of base time and cost on the VTT has not been quantified. The new evidence
presented below is based on a sample enumeration on the 2011 respondents, with expansion factors
based on the OViN national travel survey 2010 (CBS, 2011). Figure 2 shows the outcomes for the threetrip purposes for the dependence on time. Annex A provides the actual numbers.
Figure 2. Value of travel time by trip purpose as a function of travel time in theobserved reference situation

For commuting, Figure 2 shows a clear increase of the VTT (from EUR 6 to 18 per hour) with increasing
travel time. For other trips, there also is an increase with time, but not as strong (from EUR 4 to 9 perhour). For business trips there is no clear trend.
Enough commuters responded to further segment by mode. See Figure 3.
The increasing pattern for commuting holds for all three modes, but the VTT increases fastest with travel
time for car, then for train and, finally, for bus. Note that the functions for car and train seem to overlap,
suggesting that respondents travelling by car or train have similar values of travel time for a givenreference travel time. Table 2 showed a clear VTT difference between car and train users. This suggeststhat the average distance of a car trip is shorter than of a train trip.

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Figure 3. Value of travel time for commuting by mode as a function of travel time in theobserved reference situation

The dependence of the VTT on travel cost is depicted in Figure 4.
Figure 4. Value of travel time by trip purpose as a function of travel cost in theobserved reference situation

Figure 4 is quite similar to Figure 2: the patterns of time and cost dependence of the VTT by trip purpose
are similar. For commuting, the increase with increasing cost is very clear (from EUR 6 to 14 per hour).

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For other trips there is a noticeable, but less substantial increase (from EUR 4 to 8 per hour). Finally, forbusiness, we do not see a clear pattern in the VTT with increasing travel cost.
For appraisal, the Netherlands did not adopt a distance-, time- or cost-based VTT. Instead, a mean value
is used based on a weighting using travel time from the OViN national travel time survey (CBS, 2011).
This is to a large degree due to a desire to use the same VTTs per hour irrespective of distance, time ofcost levels of the base situation and of the size of the time and cost benefits (common appraisal value forall projects that are financed from the same budget). The official values based on the 1988 and1997 surveys did not differentiate between distance classes either, but only between trip purpose andmode (and initially there was a distinction also by income class, but this was not used in practicalappraisals due to lack of inputs on income classes).

Estimating the value of travel time reliability
One of the research questions for this study was whether the VTT might be higher in SP experiments
without a reliability attribute because it might include some aspects of reliability. For the three surface
mode segments for commute, business and other, a VTT has been estimated for experiments 1, 2a and2b separately using a simple Multi-Nominal Logit that also allowed for a reliability ratio. For eachpurpose, these VTTs were averaged (using the inverse variance of the estimated VTT as weight factor).
Figure 5 shows the difference between the VTT of each experiment and the average VTT over the threeexperiments. Error bars indicate one standard deviation.
Figure 5. Differences in the value of travel time between the stated preference experiments,
by trip purpose

From this figure it is clear that there is no significant difference between the three experiments (within
two standard errors). It has been hypothesised that the VTT of experiment 1 would be larger than that ofexperiments 2a and 2b since the value of reliability is estimated explicitly in the latter two and may be© OECD/ITF 201911

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part of the VTT in the former. However, as can be seen from Figure 5, there is no indication whatsoeverthat this hypothesis is true. There is no evidence that the VTT from experiment 1 (without a reliability
attribute) contains any value of reliability.4
The recommended VTTR was calculated from the same models as the VTT. In the table below we present
the results for the VTTR (measured as the standard deviation of travel time) in the form of a reliability
ratio RR (RR=VTTR/VTT). This RR was also how reliability entered the choice models.
Table 3. Reliability ratios for passenger transport
Car

Train

Bus, tram,
metro

All surface
modes

Commute

0.4

0.4

0.4

0.4

Business

1.1

1.1

1.1

1.1

0.7

Other

0.6

0.6

0.6

0.6

0.7

Mode
Trip purpose

Recr.
navigationAir

0

Note: All values are rounded off to the nearest multiple of 0.1

In business travel the RRs come from the individual travellers (the employees), but there is also a VTT for
business trips that includes an employer and an employee component (though both were derived frominterviewing the traveller). There is no information for calculating a separate employer component in thebusiness VTTR. It is best to assume that the business RR applies to the sum of the employer andemployee component, i.e. to the total business VTT.

Calculating values of travel time for business travelwith the Hensher equation
Since the first national VTT study (Hague Consulting Group, 1990), the Netherlands has used theso-called Hensher equation (see Hensher, 1977; Fowkes, Marks and Nash, 1986; Wardman et al., 2015),
which decomposes the VTT into an employee and an employer component for the VTT for travelling on
employer’s business (”business travel”). The main reason for making this choice in the original study andfor staying with it in later studies is that the most important competing approach internationally forbusiness travel, the cost savings approach, misses a number of potentially important aspects. The costsavings approach values business travel time at the marginal productivity of labour (in practice, the wage
cost for employers per unit of time).
The Hensher formula (Gunn, 2007) tries to take account of several phenomena that the cost savings
approach ignores:

12The VTT for business travel is determined by the employer and the employee who both receivea benefit.

Only the employer component depends on the marginal productivity of work time.

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

The employee component also depends of the value of leisure time.

Some share of the travel time is spent working (which in the formula is part of the employer
benefit; useful travel time for the employee himself/herself is not specifically included in thisframework), though the productivity of this time is not quite as high as that of working at theworkplace.
VTTBUSI = PVWT * (W - TW * PTW) + L[1]

where:VTTBUSI: the business VTT for use in appraisal
PVWT:

productive value of a unit of work time to the employer

W:

proportion of time savings returned to work in the work place; the remainder (1-W) is spent
as leisure timeTW:

proportion of travel time spent working

PTW:

relative productivity of work undertaken while travellingL:the value of business travel time savings to the employee

The first component on the right-hand side is that for the employer, the second component is that for
the employee. The idea that the travel time might be spent working, thereby reducing the overall travel
disutility, is perfectly in line with the underlying theory (see page 16 for a short exposition of the relevant
theory). The formula above actually is a reduced Hensher equation. The original formulation also takes
account of the impact of reduced travel fatigue when travel time decreases and the value of work timeat the workplace versus leisure time to the employee. Wardman et al. (2015) discuss the full equation
and results on this from various countries.

Calculating the employer part on the value of travel time forbusiness
The employer’s part of the business VTT is calculated on the basis of information from the 2011 VTT
surveys of travellers, as was done for the first and the second national VTT projects (where the datacollection took place in 1988 and 1997 respectively).
Sample enumeration with expansion to national totals from the 2010 OViN was used to calculate therecommended VTTs for both the employee and the employer components. For this reason, the means
provided below are indicative only. They are based on responses from the 404 business travellers
interviewed. Some further observations are lost due to item non-response. Table 4 compares the new
outcomes from the 2011 survey with those of the 1988 and 1997 surveys (Hague Consulting Group,
1990, 1998).
In 2011, almost the same part of journey time of business travellers using car or train is spent working as
in 1997. For BTM this fraction has increased a lot, but it remains much smaller than for train. In planes it
is higher than in cars and slightly lower than in trains.

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Table 4. Fraction of journey time spent working by mode for business trips
1988

Study

1997

2011

Mode

mean

stdev.

obs

mean

stdev.

obs

mean

stdev.

obs

Car

0.01680.0882390

0.03510.1057866

0.03590.1332246

Train0.11030.1518590.16130.2243226

0.15690.233841

BTM

0.0286

0.094720

0.02590.103569

0.05970.1121110.13560.270426

0.06000.1703324

Airplane
All modes
combined

0.02910.1032469

0.05910.1458

1 161

The productivity of time spent working during travel by train has increased over time and now
approaches the productivity of working at the workplace. The figures show equivalence between the
productivity at work and travelling by plane, but there are very few observations from 2011. This is after
truncating the mean to be not higher than 1.
Table 5. Relative productivity of work during travel by mode for business trips
1988

Study

1997

2011

Mode

mean

stdev.

obs

mean

stdev.

obs

mean

stdev.

obs

Car

0.89740.245326

0.93110.21281450.90530.193022

Train

0.88670.169126

0.90250.177496

0.94050.154814BTM

0.93330.115530.88890.1721

60.83330.28873

1.0000-6

0.91490.173945

Airplane
All modes
combined

0.89430.204255

0.91890.1987247

In 1988, 1997 and 2011, the share of time that would be used for all activities for the employer was usedin the calculation of the employer VTT. This had dropped somewhat for all three modes between 1988
and 1997, and remained fairly constant between 1997 and 2011. For plane it is much lower than for theother modes.

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Table 6. Fraction of saved time that would be spent working by mode for business trips
1988

Study

1997

2011

Mode

factorobs

factorobs

factorobs

Car

0.6654390

0.5445866

0.5589246

Train0.466159

0.3695226

0.378041

BTM

0.5250200.340669

0.545411

0.211526

0.5077324

Airplane
All modes combined

0.6343469

0.49831161

Table 7 shows that the productive value of an hour worked in 2011, calculated on the basis of theincome and number of workers per household information, is slightly lower than the 1997 outcome(after conversion to EUR using a factor 0.454 and inflation correction for 1997-2011 using a factor
1.375). For train and BTM, the 2011 values are clearly higher than in 1997 and more in line with those forcar. The productive value for air travellers is the highest of all modes.
Table 7. Productive value of a unit of work time by mode for business trips
1997

Study

2011

mean

stdev.

obs

mean

stdev.

obs

Car

34.84

23.22

866

31.17

15.49

22

Train

27.26

22.23

226

37.78

13.46

14

BTM

21.12

17.73

69

33.14

5.97

3

39.12

16.66

6

34.42

14.60

45

Mode

Airplane
All modes combined

32.55

22.70

1161

Note: All values are in 2010 EUR.

Table 8 summarises the estimated mean employer’s VTT for 2011, compared with the 1997 estimates.
This shows a small decline in values for car travel in 2011. Values for train increase, which is mainly due
to a higher productive value per hour. The BTM value is much higher than in 1997, as a result of thehigher share that would be spent working and the higher productive value of an hour. The employer’s
VTT for plane travel is quite low, mainly because only one fifth of the time savings would be allocated towork time.

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Table 8. Mean employer’s value for travel time for business trips in 2010 EUR per hour
PVWT
(in EUR 2010)

W

TW

PTW

Mean VTT2011(in EUR 2010)

Mean VTT1997(in EUR 2010)

Car

31.17

0.55890.03590.9053

16.41

18.31

Train

37.78

0.37800.15690.9405

8.71

5.14

BTM

33.14

0.54540.05970.8333

16.43

8.16

Airplane

39.12

0.21150.13561.0000

2.97

Total

34.42

0.50770.06

0.9149

15.59

15.14

Note: These means were not used in the recommended VTTs. A mean employers’ VTT based on sample
enumeration and expansion to OViN was applied instead.

The impact of productive use of travel time on
valuing travel time savings
The VTT used in appraisal and determined in the previous sections can be written as the difference
between two monetary5 factors (De Serpa, 1971; Evans, 1972; McFadden, 1981; Jara-Diaz, 2007):

VTT =  /  – ( U / Ttravel ) / [2]

where:
U= utility= change in the variable

Ttravel= travel time

= Lagrangian multiplier of the time constraint= Lagrangian multiplier of the money budget constraint (marginal utility of income).

In words, the VTT is the difference between:16

the opportunity value of time – the utility that could be attained if the travel time was used forsome other activity at the origin or destination (e.g. for working). This value is sometimes calledthe ”resource value” or ”opportunity costs” of travel. Tseng and Verhoef (2008) explain how
this might change during the day.



the value of the utility that is created during the travel time (compared to some reference
activity), e.g. by relaxing, reading a book or a newspaper, typing messages on a smartphone or
laptop, or watching a movie on a tablet.

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The VTT will change over time or space if any of these factors do. When activity time becomes moreproductive, the first component changes (this component also depends on changes in the productivity oflabour). The marginal utility of income is likely to decline with income. Therefore, an increase in income
over time will raise the VTT, because the first component of equation [2] increases, and the second
component decreases, whereby the former effect is likely to dominate. When the direct utility of travel
time increases, for instance as a result of increased presence of Wi-Fi connections or electric sockets intrains, the VTT becomes lower. On the other hand, an increase in the level of crowding would increase
the VTT.
The 2011 Dutch VTT survey has been re-analysed (Kouwenhoven and de Jong, 2018) to shed light onthese issues. In this survey some specific questions were asked on the use of the travel time (ie. Could
the the traveller perform a useful activity during the trip? What is the use of devices during the trip?).
Respondents that indicate that a shorter travel time is useful to them have, on average, a VTT that is22.1%  3.7% higher than the other respondents. This is in line with the theory presented above and isrepresented by the first component of equation [2].
The survey data also show that train or local public transport (bus, tram, metro) users who are able tospend their travel time usefully have, on average, respectively a 20.0%  5.5% and a 20.9%  5.6% lower
VTT than others. This is the second component of equation [2]. No significant effect was found on the
VTT for the ability of car users to spend their travel time in a useful way.
Finally, survey results indicated that train and local public transport users who had a computer, laptop,
BlackBerry, or other device available during their trip had an above average ability to spend their travel
time usefully. Assuming that this correlation is actually a causal relation, VTT for train passengers would
have been 0.8% higher if nobody had had an electronic device available during the trip. For local public
transport users this is 0.9%. The current VTT would decrease by 3.0% (train users) and 4.9% (local public
transport users) if everybody had access to an electronic device during the trip (Kouwenhoven andde Jong, 2018).
An important implication of the above findings is that investments in the comfort of a trip that increase
the possibility to work, read, watch movies and communicate with others during this trip may lead to a
reduction of the VTT. These findings also underline the importance of including questions concerning theway travel time is used in VTT surveys. These surveys should not only include questions on whether
travellers were able to spend their travel time in a useful way, but also on different aspects of comfort
during the journey, such as the level of crowding, whether the traveller was sitting or standing, which
devices were available, which services (e.g. electricity sockets and Wi-Fi) were offered, and what thetraveller would have done if these devices or services had been unavailable. This will allow further
specification of the impact of comfort on the VTT (Kouwenhoven and de Jong, 2018).

Changes in value of travel time over the years
This section looks at changes in the VTT in the same country over many years and possibly decades. CBAof transport investment projects needs to be done for a distant horizon (e.g. 30 years ahead), and part of
the CBA analysis should then predict how the VTT (in real terms: after correction for inflation) will change© OECD/ITF 201917

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in the next decades until the end of the forecasting horizon. Usually simple escalation factors reflecting
the expected increase in GDP as well as an income elasticity of the VTT are used for this. This income
elasticity or another way of predicting the future VTT in the long run can be based on outcomes from ameta-analysis that cover VTT studies over many decades (e.g. Abrantes and Wardman, 2011; Wardman
et al., 2015). It can also be based on comparing VTT from several studies in the same country, whereby
one carefully tries to avoid or control for any methodological differences in the survey and modelling
techniques (repeat studies) to obtain a fair comparison. This section focuses on such repeat studies, very
few of which exist (e.g. Gunn, 2001; Tapley et al., 2007; Börjesson, Fosgerau and Algers, 2012).
Accent and Hague Consulting Group (1999) found that in the United Kingdom, at the same income levels,the 1994/1995 values of travel time savings were even lower than in 1985. However, this was believed tobe largely due to the longer distances studied in 1985 (they also found that VTT increases with distance).
It has been suggested (Gunn, 2001) that another cause for this less than proportional growth of the VTTwith income over time may be the change that has occurred in the disutility of travel time and the
productivity of travel time. The principle influence on this has been the introduction of new technologythat can be used whilst travelling (mobile phones, laptop computers, audio and video equipment) andother comfort improvements.
Gunn (2001) also reports the outcomes from a repeat study carried out in the Netherlands. This
comparison is based on the national VTT survey data collected in 1988 and 1997. These two surveys usedessentially the same questionnaire and survey methods. Gunn (2001) found that between 1988 and1997 the VTT grows with income over time, but clearly less than proportionally. As for theUnited Kingdom, he recommended distinguishing between the disutility of travel time and the
productivity of travel time, where income growth leads to increases in the former and the introductionof new technology that can be used whilst travelling (mobile phones, laptop computers, audio and video
equipment) and other comfort improvements increase the latter. This, again, is in line with the theory
described in the previous section. The net result can be a positive or a negative change. In this particularcomparison, income growth itself might have led to a proportional increase in the VTT, but thedifference from 1 is explained by the technological innovations that can be used while travelling.
Gunn suggested using an income elasticity of the VTT (all purposes, car and public transport) of about
0.5. This has since been used in the Netherlands for the VTT escalation factor over time for CBA. A sourceof uncertainty, however, is that this relationship not only depends on income effects but also on the
introduction of new technology. Technological developments are by nature rather erratic, not a smoothline over the years, and have their own life cycle. Therefore, a single two-period comparison is notconclusive enough to determine whether these findings constitute a once-and-for-all downward shift of
the VTT or a structural trend that will continue in the future.
More recently, a comparison of the second and third Dutch national VTT studies was carried out (datacollection in 1997 and 2009/2011 respectively) and reported at conferences (Kouwenhoven et al.,2014b, 2017). It was found that in the period 1997-2009/2011 for most combinations of trip purposeand mode the average VTT went up by an amount that was smaller than the price change plus the full
real income change (so the income elasticity would be less than 1). For some modes and purpose
combinations, the VTT in real terms had even gone down over time (which would imply a negative
income elasticity of the VTT). Differences between purposes (and modes) were also found that could be
related to information and communication technology (ICT) developments and their use to make the trip
more productive or pleasant.

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Summary and discussion
This paper has presented the main methodology aspects and key outcomes of the third national VTT
study in the Netherlands. It focussed on the use of the Hensher equation for business trips, which has
been used since the first study that was reported in 1990. It also discussed some issues that have cometo the fore in recent years, such as the dependence of the VVT on trip distance, the additional
importance of travel time reliability (measured here as the standard deviation of travel time), the impactof the productive of pleasant use of travel time which reduces the VTT used for CBA, and evidence fromrepeat studies on changes in the VTT over the years.
Many of these issues are relevant when it comes to forecasting the future VTT. ICT has already made it
possible to work during the trip, to some degree in the car (hands-free mobile phone kit), but more so inthe bus and especially in the train, adding to possibilities that already existed long ago (such as readingfrom paper). New technological developments such as automated vehicles would increase thepossibilities of working during a trip at a productivity level that is the same as is now in the train, or evenhigher (because it may be quieter in the car).
The Hensher equation for business takes working during the trip into account. The 2011 survey in
the Netherlands shows that working on the train nowadays is almost as productive as in the workplace(factor of 0.94). If (at the margin) as much of the travel time would be spent working as at the workplace,and at the same productivity, the business VTT for appraisal would be reduced to zero. However, thefraction of the travel time that was spent working within business trips in the 2011 survey was only 16%
for train users (and 4% for car users). It is likely that these fractions will increase in the future when newtechnology will make working during the trip easier, but to reduce the VTT for appraisal to zero, verylarge changes in the choice of activity during travel will be needed.
It is unrealistic to think that this fraction can become 1 or even close to 1 for all business travellers. Some
types of travellers can never do any work during business trips (e.g. blue collar workers such as plumbers
and painters travelling to the next client). Furthermore, some travel time cannot be used for work
anyway (such as time to find a seat in the train, or time in crowded conditions). Finally, even businesstravellers who currently work effectively during their travel time still value shorter travel times. They lackflexibility during travel: they do not have at hand everything available to them in their office and not all
types of working activities can be done during travelling. They need to schedule their activities in order
to be able to be fully productive during the trip.
Nevertheless, data from the Netherlands between 1988 and 1997 and again between 1997 and 2010
show that the VTT did not increase as much as could be expected from income change alone. This lessthan proportional relation with income is likely due to improvements in ICT technology, which make thetime travelled more productive and pleasant. This explanation is fully consistent with the underlying
theory and has been corroborated by empirical research in the Netherlands on additional data collectedin the third national VTT survey. Users of train and bus, tram and metro that could spend their travel
time usefully were found to have a 20-21% lower VTT than other travellers. The possibilities to spend
travel time in a useful way depend on many factors. For instance, having a laptop available during thetrip has an impact of not more than 5% on the VTT.
Furthermore, it is difficult to predict technological developments, and especially the speed of their largescale adoption. There might be further innovations that make travel time in public transport moreproductive or pleasant than it is now. Automated vehicle technology could result in private or shared© OECD/ITF 201919

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cars where the driver needs not pay attention to driving, resulting in a sort of mobile office. However, azero or very low VTT will only result if considerably more travellers than today would decide to spend thetravel time performing an activity that has the same utility as at the origin and destination.
Taking all the above into account, the VTT will most likely not decrease all the way to zero. The VTT will
most likely not increase as much as income and may even decline in real terms. A practical implication isthat time escalation factors of (close to) 1, which are now used in several countries to determine the VTT
for future years, should be reconsidered.
As a more methodological recommendation, future studies on the value of travel time should focus moreon how precisely travel time was spent and why. They should also ask explicitly whether the type of jobof the respondent is such that work can be done during a business or commute trip (or even during a trip
for another purpose).

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Notes

1 The transport model that is mostly used for national and regional analyses, the National Model System (in Dutch: Landelijk Model Systeem or
LMS) and its regional equivalents (NRMs), contain sub-models for mode-destination-time of day choice in which both time and cost coefficientswere estimated. The VTTs that were determined for use in CBA are not used here.
2 Three similar national surveys have been carried out for freight transport. These are not further discussed in this paper.
3 Nevertheless, other specifications than the one where unreliability is measured as the standard deviation of transport time, such as thescheduling model, have been tried as well in the third national VTT study, to see which specification performs best on the data obtained. The
scheduling model did not perform better in explaining the data than the models with the standard deviation of transport time.
4 Of course, this analysis is based on relatively simple models. An analysis on the differences in the VTT between the three experiments using
some of the more sophisticated models also used in the study is recommended as further work.
5 This implies that both factors are actually ratios of a numerator for changes in the number of minutes or hours travelled and a denominator
which is the marginal utility of income (the latter for the translation into money units).

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Annex A. Impact of base time and distance onvalue of travel time: Results from the2011 Dutch study
Table A1. Value of travel time by trip purpose as a function of travel time in theobserved reference situation
TRIPLENGTH Class

CommuteBusiness

CommuteAll modes

All modes

All modes

0 - 19 minutes

1 6.41

21.22

4.41

20 - 29 minutes

2 7.84

28.81

5.98

30 - 39 minutes

3 6.94

22.41

5.88

40 - 49 minutes

4 8.20

27.17

7.07

50 - 59 minutes

5 9.98

27.33

7.48

60 - 69 minutes

6 9.40

30.09

7.73

70 - 79 minutes

7 11.54

24.32

7.84

80 - 89 minutes

8 12.44

25.80

8.91

90 - 99 minutes

9 12.35

23.71

6.89

100 - 119 minutes

10 12.73

19.62

8.84

120 - 149 minutes

11 16.25

13.73

11.08

150+ minutes

12 18.25

21.92

9.01

Table A2. Value of travel time for commuting by mode as a function of travel time in theobserved reference situation
TRIPLENGTH Class

CommuteCommuteCommute

Car

Train

BTM

0 - 39 minutes

1

7.44

8.17

6.04

40 - 49 minutes

2

9.03

6.53

6.02

50 - 59 minutes

3

10.67

10.85

8.32

60 - 69 minutes

4

10.60

9.14

7.04

70 - 79 minutes

5

12.53

11.18

7.66

80 - 89 minutes

6

9.16

17.07

9.60

90+ minutes

7

15.38

13.21

10.25

24

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Table A3. Value of travel time for by trip purpose as a function of travel cost in theobserved reference situation
TRIP COST Class

CommuteBusiness

Other

All modes

All modes

All modes

0 - 1 EUR

1

5.92

17.49

4.00

1 - 2 EUR

2

6.65

17.45

5.32

2 - 3 EUR

3

7.92

38.84

6.51

3 - 4 EUR

4

9.45

22.97

8.06

4 - 5 EUR

5

10.32

33.53

6.89

5 - 6 EUR

6

11.02

27.40

8.79

6 - 10 EUR

7

12.03

23.81

10.06

10+ EUR

8

14.99

22.97

7.74

© OECD/ITF 201925

Time Use and Values of Time andReliability in the Netherlands
This paper compares the survey results of three value of travel time(VTT) surveys conducted in the Netherlands since the late 1980s. It
discusses the method used in the Dutch studies for estimating VTT
for business travel; the importance of travel time reliability; and theimpacts of distance and productive or pleasant use of travel timeon VTT. By comparing how VTT has evolved over time, this paper
discusses potential impacts of technological changes on VTT and theuse of VTT in project appraisals in the future.

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Published: 11/2019 | Photo credit: Shutterstock/metamorworks

All resources from the Roundtable on Zero Value of Time are available
at: www.itf-oecd.org/zero-value-time-roundtable.