Selfishness and altruism in the distribution of travel time and income

19 Pages·2013·0.46 MB·English

Transportation(2013)40:1043–1061
DOI10.1007/s11116-013-9456-7
Selfishness and altruism in the distribution of travel time
and income
Nebiyou Tilahun • David Levinson
Received:30October2011/Accepted:12January2013/Publishedonline:6March2013
(cid:2)SpringerScience+BusinessMediaNewYork2013
Abstract Mosteconomicmodelsassumethatindividualsactouttheirpreferencesbased
on self-interest alone. However, there have also been other paradigms in economics that
aim to capture aspects of behavior that include fairness, reciprocity, and altruism. In this
studyweempiricallyexaminepreferencesoftraveltimeandincomedistributionswithand
without the respondent knowing their own position in each distribution. The data comes
from a Stated Preference experiment where subjects were presented paired alternative
distributions of travel time and income. The alternatives require a tradeoff between dis-
tributional concerns and the respondent’s own position. Choices also do not penalize or
reward any particular choice. Overall, choices show individuals are willing forgo alter-
nativeswheretheywouldbeindividuallywelloffintheinterestofdistributionalconcerns
inboththetraveltimeandincomecases.Exclusivelyself-interestedchoicesareseenmore
intheincomequestions,wherenearly25 %ofrespondentsexpresssuchpreferences,than
inthetraveltimecase,whereonly5 %ofrespondentsmakesuchchoices.Theresultsalso
suggest that respondents prioritize their own position differently relative to regional dis-
tributionsoftraveltimeandincome.Estimatedchoicemodelsshowthatwhenitcomesto
traveltime,individualsaremoreconcernedwithsocietalaveragetraveltimefollowedby
thestandarddeviationintheregionandfinallytheirowntraveltime,whileinthecaseof
income they are more concerned with their own income, followed by a desire for more
variability, and finally increasing the minimum income in their region. When individuals
donotknowtheirfateafterapolicychangethataffectsregionaltraveltime,theirchoices
appear to be mainly motivated by risk averse behavior and aim to reduce variability in
outcomes. On the other hand, in the income context, the expected value appears to drive
choices. In all cases, population-wide tastes are also estimated and reported.
N.Tilahun(&)
DepartmentofUrbanPlanningandPolicy,UniversityofIllinoisatChicago,
412S.PeoriaSt.Suite254,Chicago,IL60607,USA
e-mail:[email protected]
D.Levinson
DepartmentofCivilEngineering,UniversityofMinnesota,500PillsburyDriveSE,Minneapolis,
MN55455,USA
e-mail:[email protected]
URL:http://nexus.umn.edu
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Keywords Selfishness (cid:2) Altruism (cid:2) Travel time distribution (cid:2) Income distribution (cid:2)
Preferences (cid:2) Inequality (cid:2) Choice experiment
Introduction
Bothtimeandmoneyarescarceresources.Wescheduleourdailyactivitiesandprioritize
among them in the 24 h available. We are willing to use some of that time to travel to
activitiesoftenbalancingbetweenthetimetravelled,timespentatthedestination,andtime
leftforotheractivities.Wetreatmoneyinthesamefashion.Mostofushavetolivewithin
a budget and prioritize how it is spent or saved for other purposes. There are of course
differencesbetweenthetwo.Thevalueoftimeiscontingentontheactivitiesitistiedto.
Time during a leisurely drive has a different value from that spent over the morning
commutewhichisagaindifferentfromwhatitwouldbeduringanemergency.Moneyon
theotherhanddoesn’tusuallysufferfromsuchfluctuationsintheshortrun,whileoverthe
long run its value can change dramatically.
Distributionalconcernsoverincomehavelongbeenapartofpoliticalandeconomicdis-
course.Theimpactofhowincomeisdistributedinasocietyshowsupindisparitiesinliving
conditions,education,skills,andhealthoutcomes.Manygovernmentsputinplaceredistrib-
utivepoliciesthroughtaxationandspendingtoaddressthesedisparities.Comparatively,the
distributionoftraveltimeattractsmuchlessattentioneventhoughmanytransportationpolicies
alsoaltertraveltimedistributionseitherimplicitlyorexplicitly.Butdebatesareseldomframed
in terms of travel time distribution. These views prevail because travel time outcomes are
mostlyseenasarisingfromhouseholdchoicesofresidenceanddestinations.
Transportationsystemchanges,includingtrafficsignalsandrampmeters,advancedtravel
guidancesystems,androuteexpansions,altertraveltimedistributionsandcreatewinnersand
losers.Individualreactionstotheseoutcomesmaydependonhowmuchthelosersfromthese
policiesloseaswellaswhethertheyunderstandtheoverallsocietalgainstobehadfromthe
change.Properlyunderstandingthethresholdsthatpeopleacceptcanhelpengineers,plan-
ners, and policy makers adjust their prescriptions by balancing efficiency with what is
behaviorallyacceptable.Preferencesaboutpolicieswherepeoplearefullyinformedabout
whattheymaygiveuppersonallyandwhatisbroadlygainedbytheregionorcommunitymay
bedifferentfromsituationswheresuchinformationismissingorincorrect.
Thispaperreportsonanexperimentwhereindividualsareaskedtotradeofftheirown
travel time and income for overall changes in travel time distributions and income dis-
tributions, respectively. The travel time questions in the experiments are framed in the
context of a transportation improvement. The end distribution of the improvements and
whereitleavesthetravellerareexplicitlyshown.Intheincomecontext,preferencesreflect
achoicebetweenalternatelocationswherethepersonwishestolive.Inthiscasenopolicy
is presented which alters the individuals own income to avoid the intricacies of political
debatesaroundtaxationandtheroleofgovernmentinredistributingincome.Respondents
choosearegiontoliveingiventwosimilarjobsinplaceswheretheincomedistributions
andofferedsalariesaredifferent.Bothsetsofquestionsarealsoaskedinacontextwhere
respondents do not know their own position. This allows us to discuss how preferences
change when uncertainty about one’s own fate is introduced.
Thenextsectionprovidesabriefbackgroundoneconomicmodelsthatconsiderfairness
anddistributionaspartofdecisionmaking.Thatisfollowedbyadiscussionofthesurvey
and a section on the data. The choice patterns under conditions where respondents know
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their position in the travel time and income distributions are then discussed. That is
followed by a section where a choice model is estimated using the data. Finally, ‘‘Model
estimates’’ section provides summary and conclusions.
Background
Thetraditionaleconomicparadigmisthatpeopleareself-interestedactorswhosechoices
derive from a goal of maximizing their individual utility. The rational utility maximizing
actor is concerned about getting the highest utility given his budget by allocating it to
consumption at prevailing prices. Increases in income lead to higher utilities and maxi-
mization of individual utility drives consumption decisions. Allocation of time for the
utilitymaximizingindividualalsoproceedssimilarlythoughthereexistsahardconstraint
where increases in time are not possible. Given this constraint the individual chooses an
allocation of time between different activities that leads to the highest utility. Some
activitiessuchasworkarelinkedtogeneratingtheincomethatgoestoconsumption;other
timeisallocatedtoleisureandstillotherisallocatedtoactivitiessuchastravelwherethere
are minimum time requirements (DeSerpa 1971; Evans 1972). This formulation leads to
the derivation of different values of time and also provides the basis for a valueof travel
timesavingsforactivitiessuchastravelwhereapersonspendstheminimumrequiredtime
(DeSerpa 1971; Mackie et al. 2001).
Wedonotdisputethatchoicesareinlargepartself-interested.Peoplechoosewhereto
live so that the location best suits their needs subject to a budget. They choose particular
routestogotoworkbecausetheyexpectitwillbringthemtotheirdestinationfaster.We
have no evidence that any traveler makes systematic route or destination choices so that
others are able to have shorter travel times (though individuals often yield to others at
intersections, merges, or lane changes, which is a small version of this phenomenon,
accruing delay to avoid delay for another). This is however not to argue that individuals
would not want reduced travel time for others even while being self-interested. Such
behavior may be observed because individuals see benefits from redistribution even if it
leavesthempersonallyworseoffinonedimension.Forinstancehighertraveltimemaybe
acceptable if individuals see that the change that increases their travel time also reduces
overall pollution, the benefits of which they will share directly. Alternatively, altruistic
preferences,wherepeopleaccepthighertraveltimesforsomeotherglobalgainmayalso
be present. Personal position may be sacrificed if people believe some level of overall
efficiency is realized, or if they perceive that being fair to others, a group that includes
friendsandrelatives,isagoodthingorisconsistentwiththeirmoralvalues.Thesekindsof
choices are presented to people often through policy initiatives that have the effect of
altering their own experiences as well as that of those around them. In the transportation
context, the willingness for such tradeoffs can inform implementation of ramp metering,
signals, advanced traveler information systems, and other Intelligent Transportation Sys-
tems technologies, which by their very nature adjust time distributions while fulfilling
differentsocietal/globalobjectives[e.g.see(ZhangandLevinson2005)].Theimplication
herewouldbethatindividualsmayhaveawillingnesstopay(oratleasthaveawillingness
togiveup)someoftheirowntraveltime,iftheyknewthatpolicymeasurescouldleavea
majority of others well off.
Awillingnesstoforegoone’sownincomeforadistributionthatavoidsextremepoverty
is also possible. One can be motivated by a variety of concerns none of which are nec-
essarily looking at fairness itself as an end (Scanlon 1997). If one perceives that more
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equalitywillleadtoabetterqualityoflife,betterhealthcare,lesscrime,orbetterschools,
these may in fact be within the individuals self-interest since these benefits apply to the
individual as well as their kin. The self-interested paradigm need not change to accom-
modatetheseconcerns.Butpreferencescanalsobedrivenbythedesiretoseeotherswell
off, though the motivations behind such willingness could be difficult to discern (Elster
2006).
Several experiments from ultimatum games summarized in Thaler (1988) provide
evidencefortheexistenceoffairnessconsiderationindecisionmaking.Insuchgamesone
person would offer another a share s of a total amount x. In the event of acceptance, the
proposer gets x - s and the acceptor s. If the acceptor rejects the offer, then both get
nothing. While the game theoretic solution (for a non-repeated game) to this problem is
thatthepersonproposingshouldofferaverysmallamountandthepersongettingtheoffer
should accept any positive gain, experimental findings do not reflect this outcome. For
instance,intheexperimentsofGuthet al.(1982),mostoftheoffersmadeweregenerous
andwereaccepted,whileintheexperimentsofKahnemanet al.(1986),respondentswere
willing to reject what were unfair offers even when it meant the payoffs to themselves
would have been positive. More recently, Marchetti et al. (2011) have shown acceptance
ratesalsodependonthecharacteristicsofthosemakingtheoffer.Therejectionsshowthe
existence of a willingness to pay to attain fairness from others (Kahneman et al. 1986).
While those who offered generous amounts may have been motivated by a need for
fairness, fear of rejection might also induce a similar behavior.
Attemptstoincorporatefairnessintotraditionaleconomicmodelshavebeenmade.For
instanceRabin(1993)proposesamodelwherepeoplearenicetothosewhoarenicetothem,
andmeantothosewhoaremeantothem.FehrandSchmidt(1999)offersatheoryoffairness
basedonthehypothesisthatindividualswantequitableoutcomes.Autilityformisproposed
that penalizes an unfair allocation. In this framework, both an advantageous (where the
individualisearningmorethanothers)aswellasadisadvantageousinequality(wherethey
areearningless)arepenalized.BoltonandOckenfels(2000)alsofindsupportforinequality
aversionusingtheirtheoryofEquity,ReciprocityandCompetition.Theyproposetoaccount
fortheanomaliesintheexperimentswithamodelwhereplayerstrytomaximizea‘‘moti-
vationfunction’’whichdependsontheirpayoff(inabsoluteterms)andtheirrelativeshareof
the payoff. Engelmann and Strobel (2004), on the other hand, argue that efficiency and
maximinstrategiesexplaintheobservedbehaviorratherthantheinequalityaversionmodels
offeredinFehrandSchmidt(1999)andBoltonandOckenfels(2000).
Adoptingadifferentstrategyfromthegametheoreticapproach,Carlssonet al.(2005)try
tounderstandwhetherindividualsareinequalityaverseorjustriskaverse.Intheirstudythey
ask respondents to choose a society for their grandchild to live in using uniform income
distributions.Inonesetofcases,thepositionofthegrandchildisgivenandinanotherthe
position is not known. They propose utility forms from which both risk aversion and
inequality aversion coefficients can be extracted. When the position for the grandchild is
known,thereisnorisktothegrandchildandchoicesreflectpreferencesoninequality.When
thegrandchild’spositionisunknown,bothriskandinequalityaversioncanplayaroleinthe
decision.Theyfindthatmanypeopleareinequalityaverseaswellasriskaverse.Inaddition
theyreportasizablecorrelationbetweenindividualriskandinequalityaversion.
ThesurveyforourstudyissimilartotheoneusedbyCarlssonet al.(2005)butwitha
few notable differences including the types of distributions used and the method of
analysis.Ouraimistotestwhetherdistributionalconsiderationsaffectchoicesaboutown
traveltimeandincomedistributions,howthesepreferenceschangeonceuncertaintyabout
own position is introduced, and whether these preferences are informed by different
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aspectsofthedistributionsfortraveltimeandincome.Thefollowingsectionsdiscussthe
surveyusedtogatherdataforthisstudyandtheparticipantsfollowedbytheanalysisand
interpretations of what respondents choices imply.
Survey
The data for this analysis comes from a computer-based Stated Preference survey
administeredattheUniversityofMinnesotainMarchof2006.Thestatedpreference(SP)
approachwaschosenbecauseitallowstheexplorationoftradeoffsthatarehardtoobserve
in real life. In this setting we are able to test preferences over a range of individual and
societaltraveltimeandincomedistributions thatinreality wouldnotbeobservedforthe
same individual. A revealed preference approach would be difficult to undertake because
therearemanyfactorsoutsideoftheresearcher’sandtherespondent’scontrolthatdictate
whereonelives.TheSPapproachgivesusmorecontroloverthevariablesofinterest.Even
with some of its limitations, a stated preference approach seems to be the most straight
forward way to empirically evaluate the tradeoffs we are interested in this paper.
The survey consistsof two parts. One part deals with the distribution of travel time in
the community where people live and their own position in that distribution. These
questions are posed in the context of a project which is about to alter travel time distri-
butionsintherespondentsarea.Asecondpartdealswiththedistributionofincomeandthe
personspositioninthatdistribution.Sincepolicyscenariosthatredistributeincomemaybe
politicized,thesequestionsareposedwithinthecontextofarelocationdecisiontooneof
two locations because of a job change where different income distributions are observed.
Survey design
Thetraveltimequestionsareposedasbeforeandafterscenariosresultingfromachangein
policy.Respondentsaretoldthatastudyisunderwaytoputinplaceanewrampmetering
strategy.Theyareinformedthatwhenputinplace,thisstrategywillleadtoaredistribution
oftraveltimeforpeopleintheTwinCitiesarea.Histogramsareusedtodepictthetravel
time distributions in the before and after scenarios. The respondent’s personal position in
either case is also identified. An example of the question is given in Fig. 1a. The
respondent is then asked to choose between the before and after conditions.
Inthesecondcase,weconsiderincome.Inthiscase,respondentsaretoldthatajobofferis
onthetableforthemwhichrequiresthemtorelocatetoanewarea.Therearetwojoboffers
locatedintwodifferentcities.Therespondentistoldthatthepositionsarevirtuallyidentical
andthatthecostoflivingisequalineithercity.Theincomedistributioninthetwolocationsis
howeverdifferent.Ineithercasethedistributionofincomeforresidentsofeachcityisgiven
usingahistogramandtheofferedsalaryfortherespondentisalsogiven.Figure 1bshowsone
ofthequestions.Therespondentisthenaskedtochoosebetweenthetwooffers.
The design of both the travel time and income questionnaires were based on the dif-
ferencesinpersonalposition,differencesinsocialaverage,anddifferencesinthestandard
deviation of the distributions in question. For travel time, the before after differences
betweenowntimewassetupsothatthedifferencecouldbeaatleastasgoodasbeforethe
change or loss, the societal average difference was setup to be either negative (societal
averageincreasing)orpositive(decreasinginafterperiod).Thesewereinadditionpaired
with large and small differences in the standard deviation of the population distribution.
This roughly 2 9 2 9 2 design has 8 potential combinations for the three factors. Next
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(a) Exampletraveltimequestion
(b) Exampleincomedistributionquestion
Fig.1 Statedpreferencequestions
alternative distributions whose differences would satisfy these requirements were gener-
ated. Since we are using continuous variables, these alternatives were generated with the
goalofalsolimitingthecorrelationbetweenthedesignvariables.Thefinalcoverageofthe
traveltimequestionsofdifferencesinowntime,societalaveragetraveltimeandstandard
deviation is as shown in Fig. 2a. The figure shows just differences in the variables of
interestinthepairedpresentations.The‘Base’isarelativeoriginforeachpresentationand
doesn’t refer to the same before distribution.
A similar approach is used in developing the paired differences for the income ques-
tions.ThecoveragefortheincomequestionsisalsogiveninFig.2b.Again,thepresented
diagramreflectsthedifferencesinthepairedchoices.Inthefigure,sinceplace1and2are
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Fig.2 Differencesintraveltime Changes in variance
8
andincomeconditionsamong er) mlarogdeerate
alternatives aft
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Changes in personal position (before−after)
positive values are time savings
(a) Travel time differences
ce2) 0000 Changemlasro gidnee vraatreiance
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Changes in personal position (Place1−Place2)
(b) Income differences
interchangable as opposed to the travel time case where there is a clear ’before’ case,
switching them for a subset of the presentations would occupy the two remaining quad-
rants. Correlations between own position, societal average and standard deviation were
within ±0.1 for the travel time case and within ±0.3 for the income case.
Threeofthetraveltimequestionsandfouroftheincomepresentationswereaskedina
different format of each respondent. Respondents were asked to choose a distribution,
under the same conditionsas before, butwithout knowingwhat theirpersonal position in
thedistributionswere(i.e.frombehindaveilofignorance).Thesequestionswillallowus
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to test whether distributional concerns are different when people do not know their own
position. In the other scenarios, the respondent must decide if they are willing to trade
some of their own income or travel time to live in a region that has a more equal distri-
bution. In total, respondents were given a eighteen questions relating to time preferences
and seventeen questions relating to income preferences.
Survey administration
Prior to starting the survey individuals are given a quick tutorial on interpreting distri-
butionsthatarepresentedbyusinghistograms.Thetutorialtakesthemthroughmeanand
variance identification, comparing mean and variance of different distributions, reading
frequency of an event occurrence based on given distributions and identifying their own
positions within a distribution when explicitly indicated. The survey then presents the
respondents with a series of binary alternatives where they make choices based on their
own personalposition as well as the position of thosearoundthem inthe travel timeand
income contexts discussed above. There were a total of three randomizations that were
used to preorder the survey questions. In addition the information was presented in two
ways.Inonecasethedistributionsforthealternativeswereplacedoneovertheotherand
in the other they were placed side by side. One of these was installed per computer. As
respondents came in, they were each randomly assigned to a computer.
Participants
Subjects for the survey were recruited via email from the University of Minnesota’s
employeedatabase.Invitationsweresentoutto2,500randomlyselectednon-faculty,non-
student employees who had not participated in previous transportation studies conducted
bytheauthors.Therecruitmentemailindicatedthatindividualswereinvitedtoparticipate
in a computer based commute study and offered $15 for participation. Participants were
asked to come to a central testing station, where the survey was administered. Based on
previous experience of similar recruitments, a target of 200 participants was set (split
evenlybetweenmaleandfemale).Atotalof187respondentsagreedandparticipatedinthe
study. Descriptive statistics for the subjects are given in Table 1.
In addition to the income and travel time questions, a separate set of questions about
route preferences was also administered along with the survey (Tilahun and Levinson
2010). Two questions in that set were control questions that were used to gauge whether
respondents understood the distributions that they were making choices over. Briefly, the
questionsaskediftherespondentwouldpayahighertolltousearoutethathadonaverage
alongertraveltimeandlargevarianceoftraveltimebetweenthesameorigin-destination
pair. Only eight of the 187 respondents made what appeared to be an irrational choice,
illustrating respondents largely understood the questions.
Analysis and results
Self-interested choices
Inamajorityofthetraveltimeandincomechoicesthatarespondentfaces,onealternative
leaveshimpersonallybetteroffthantheother(eitherwithalowertraveltimeorahigher
personalincome,respectively).Thiswastruein12ofthe15traveltimequestionsand11
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Table1 Demographiccharacteristicsofrespondents(total=187)
Variable Description Count Proportion
Sex Male 99 52.9%
Female 88 47.1%
Age Mean(range) 40.6(2265)
Education Collegelevel 151 80.7%
Lessthancollegelevel 35 18.7%
Unknown 1 0.5%
Personalincome \$30,000 34 18.2%
$30,000–$45,000 84 44.9%
$45,000–$60,000 45 24.1%
$60,000–$75,000 17 9.1%
$75,000–$100,000 6 3.2%
[$100,000 0 0%
Unknown 1 0.5%
Householdsize 1 47 25.1%
2 69 36.9%
3 34 18.2%
4? 32 17.1%
Unknown(5) 5 2.7%
Usualmode(yearround) Car 138 73.8%
Transit 32 17.1%
Bike 10 5.3%
Walk 5 2.7%
Unknown 2 1.1%
Commutetime \15min 22 11.8%
15–29min 98 52.4%
30–44min 47 25.1%
45–59min 10 5.3%
C60min 9 4.8%
Unknown 1 0.5%
of the 13 income questions. The remaining questions leave the respondent at the same
position in either scenario while altering the distribution of travel time and income. If
respondents were solely interested in their own well-being, they would simply pick the
alternative that would leave them better off in the questions where their positions were
unequal. However, purely self-interested choices were observed only for a subset of the
respondents.Inthetraveltimequestions,only10ofthe187respondents(5.3 %)chosethe
lower travel time alternative for themselves in all 12 questions. The proportion that con-
sistentlychosethehigherpersonalincomealternativewasrelativelylargerfortheincome
questions. Here, 47 of the 187 respondents (25.1 %) chose in a solely self-interested
manneronall11questions.Thisstillleaves75 %oftherespondentswhowerewillingto
foregopersonalincomeforotherdistributionalconcerns.Table 2presentsthecumulative
proportion of respondents who chose in a manner consistent with self-interest.
Whilenoonealwayschosethehighertraveltimeorlowerincomealternative,abouta
third of the respondents for income (33.2 %) and nearly a quarter for travel time (23 %)
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Table2 Cumulativefrequency
Percentofquestionsanswered Percentofrespondents
ofself-interestedchoicesinthe
inself-interest(%)
incomeandtraveltimequestions
Traveltime(%) Income(%)
100 5.3 25.1
C75 29.4 44.4
C50 77.0 66.8
\50 23.0 33.2
100%ofquestions=11for 0 0 0
incomeand12fortraveltime
chose alternatives that were not to their personal advantage in over half the questions.
Lookingatper-subjectchoices,themedianproportionofquestionsasubjectansweredina
self-interested manner is 72 % for income (out of 11 questions) while it was 58 % for
travel time (out of 13 questions). Unlike results in ultimatum games which involve pen-
alties,subjectsinthissurveyhadnodirectincentivethatcouldinfluencetheirdecisionto
befairtoothers(asidefromsomepsychicrewardofbeingperceivedasafairpersoneither
to themselves or to the research team). Yet, the choices show altruistic motivations for a
large portion of the subjects.
Choices where own position is uncertain
Asdiscussedearlier,alimitednumberofquestionsposedtraveltimeandincomequestions
where the respondent did not know their own position. Because there is an element of
uncertainty,choicesinthisinstancemaybequitedifferentfromchoiceswhererespondents
knowtheirposition(wherethereisnouncertainty).Sevenquestionsfromthepreviousset
(3 for travel time, 4 for income) were takes and the respondent’s income removed from
thesequestions.ThesewouldbetheoriginalpositioninRawls(1999)formulation,where
the respondent would choose a fair distribution lest they find themselves in either the
highest travel time or lowest income group, respectively.
Here again, there is a great deal of variation in how respondents evaluate these alter-
natives. Relatively simple choices mechanisms are possible in each case that can neatly
explain one motivation or another. For example in the income case, respondents may be
motivated by the risk of falling into the lowest income category and may seek to avoid
those situations. Or, they may seek the distribution with the highest expected income
(average) for the distribution - regarding this as their most likely outcome. In the travel
time case, the risk of ending up with the highest travel time may lead them to select the
distributionwithalessextremeoutcome,ortheloweraveragemaybethemostattractive.
Alternatively,highlyrisk-seekingbehaviormaydominatewhererespondentsalignchoices
with the most optimistic outcomes.
InTables 3and4wesummarizethefrequencywithwhichsimilarconsistentbehavior
wasobserved.Ascanbeseen,theproportionwhoconsistentlyselectedalternativesbased
on simple rules is not very large especially in the income case. The most consistent
behaviorinthetraveltimecase,istooptforasmallerstandarddeviationwhenowntravel
time is not known, where 42 % of respondents consistently chose this alternative. In the
income case, the largest percentage is for the highest average income where 35.8 % of
respondentschosethehigheraverageincomealternativeeverytime.Thehighestminimum
incomealternative,whichwaschosenalwaysinby65.2 %ofrespondents,isnotincluded
in this table because only two of the four veiled income choices had unequal minimums.
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