Lost in transit? Unfamiliar public transport travelexplored using a journey planner web survey

Lorelei Schmitt • Graham Currie • Alexa Delbosc

� Springer Science+Business Media New York 2014

Abstract Attracting and retaining public transport users is fundamental to a number of land

use and transport policy objectives which seek to reduce single-occupant vehicle travel.

Understanding the psychological processes underlying unfamiliar public transport use may

assist in achieving this aim. This paper explores unfamiliar transit travel using a survey

conducted through an online travel planning website in Melbourne, Australia. The survey

obtained ‘before and after’ travel data and explored the circumstances of unfamiliar travel,

travel experiences, and the impact of these experiences on attitudes and behavior. A total of

3,537 ‘before’ responses and 658 eligible ‘after’ surveys were obtained including 152

unfamiliar transit journeys. Compared with familiar travel, unfamiliar travel was more

commonly associated with: life events, less time living in Melbourne, travel companionship,

visiting new locations, and non-work-related trip purposes. Unfamiliar travel experiences

were rated more negatively for ‘navigation’ and ‘emotional state (level of anxiety)’ and more

positively for ‘expected versus actual travel time’ and ‘level of comfort’. Analysis of travel

attribute ratings and intention to re-patronize services indicated that there was a significant

relationship between positive trip experiences and intention to re-patronize services for all

users, and particularly for unfamiliar travelers. These results suggest that unfamiliar public

travel experiences are quite different to familiar travel and are important to optimize to

encourage re-patronization and help grow public transport markets.

Keywords Unfamiliar public transport travel � First trips � Life events � Transit

passenger information website � Travel planning websites � Primacy effect

Introduction

Growing public transport markets is often recognized as fundamental to reducing auto-

mobile dependence. Although most travel is undertaken habitually (e.g. Thøgersen 2009;

L. Schmitt (&) � G. Currie � A. DelboscDepartment of Civil Engineering, Institute of Transport Studies, Monash University, Melbourne,VIC 3800, Australiae-mail: lorelei.schmitt@monash.edu

123

TransportationDOI 10.1007/s11116-014-9529-2

Verplanken and Aarts 1999), an important component of growing the public transport

market is to encourage people to undertake new and unfamiliar travel, including attracting

new users, retaining existing users, and for occasional users, increasing the frequency of

use and widening the spectrum of journey purposes for which transit is used. In this

context, gaining a better understanding of the characteristics, experience, and impact of

unfamiliar public transport travel is important. Indeed, it has been argued that transport

policy measures that account for users’ capabilities and perceptions will be more suc-

cessful than those that do not (Gehlert et al. 2013).

Previous research by the authors found that compared to familiar public transport travel

made to a University campus, unfamiliar travel was associated with more negative

experiences including increased anxiety and trouble with wayfinding, transferring and

ticketing (Schmitt et al. 2013). Impressions of unfamiliar travel (or ‘first trips’) were also

found to influence overall attitudes about services particularly for non-captive users (those

with the option to drive). These findings are consistent with the findings of numerous

studies from psychology which indicate that first impressions are often remembered more

vividly than other impressions (except the most recent) and thus may have a dispropor-

tionate influence on attitudes (e.g. Forgas 2011).

However this previous research had limitations; only travel made to a university campus

was explored, it was reliant on respondents’ recalling first trips over a very long period

(many of which occurred several years earlier) and only a limited range of issues regarding

unfamiliar trips were explored. The present paper concerns subsequent research about

unfamiliar travel and includes a new survey of a larger and more diverse sample of transit

users, adopting an innovative approach which permits the recall of first trip experiences

more immediately after they have occurred. Three research questions are explored

including:

• How prevalent is unfamiliar travel and under what circumstances does unfamiliar

travel occur?

• What experiences are associated with unfamiliar travel: in contrast to familiar travel,

how do unfamiliar travel experiences vary with circumstances?

• Do unfamiliar travel experiences impact attitudes and behavior related to mode choice?

In the context of this research, a new public transport trip, or ‘unfamiliar travel’, refers

to use of a transit service that the respondent has not used before, for example, a train line

that has not previously been used by the subject.

The paper begins by summarizing previous relevant research. This is followed by a

description of the research methodology. Results are then presented, followed by a dis-

cussion of the findings and their implications for policy and future research.

Research context

There is limited research literature focusing specifically on unfamiliar transit travel; most

papers only touch on these issues indirectly. Therefore this literature review incorporates

studies from the broader fields of transport and psychology to explore the existing infor-

mation related to the three research questions explored in this paper. It begins with a

review of circumstances surrounding unfamiliar transit travel and then discusses the

experiential characteristics of unfamiliar travel. Finally, research related to the potential

impacts of unfamiliar travel on attitudes and subsequent transit usage is explored.

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Circumstances surrounding unfamiliar travel

Given that travel is often habitual (Chorus et al. 2007), it is likely that unfamiliar travel is

not commonly undertaken. Very little is published about what prompts unfamiliar travel

and how unfamiliar travel differs from familiar travel. However a number of studies

suggest that travel behavior change may be more likely to occur during an important life

events, or ‘turning points’, such as moving homes or cities, starting university, starting a

new job or workplace relocations, obtaining a driver’s license, switching schools, changed

physical mobility and having children (Davidov 2007; Sharples 2009; Van Exel and Ri-

etveld 2009; Beige and Axhausen 2012). Although they do not happen often, life events

can serve as a prompt for people to reconsider their travel patterns, often due to a change in

origin, destination or available travel options (Goodwin et al. 2004; Davidov 2007; Ver-

planken et al. 2008). Due to evidence suggesting that life events may prompt new travel

behaviors, the present study has incorporated questions around life events into the survey

and the associated analysis. A further set of questions explores other circumstances of

unfamiliar travel which may differ from familiar travel, such as time of travel and journey

purpose.

The experience of unfamiliar travel

Many studies explore various aspects of the travel experience, however little research

focuses specifically on the experience of unfamiliar public transport travel, which may

differ from the experience of familiar journeys. Research about habitual travel offers some

insights about unfamiliar travel experiences; in particular, compared to habitual travel,

unfamiliar travel may be associated with increased cognitive effort for pre-trip planning.

For example, Davidov (2007, p. 319) describes how ‘‘the price of using the bus, for

example, is not only the price of purchasing the ticket but also includes the cost of looking

for information’’ including the timetable, the location of bus stops and which route to take.

Similarly, new behaviors may require a process of information searching and decision-

making thereby necessitating increased cognitive effort (Aarts et al. 1997; Klockner and

Friedrichsmeier 2011; Klockner and Matthies 2004; Van Exel and Rietveld 2001; Chorus

et al. 2007).

Other research looks at unfamiliar public transport travel experiences more directly.

Travelling in an unknown environment by public transport is discussed by Dziekan and

Dicke-Ogenia (2010) as being challenging and stressful due to a perceived lack of control,

a lack of information and a process of updating one’s ‘cognitive map’. Stradling (2002,

pp. 26–27) describes the potential for embarrassment, frustration and regret, ‘‘waiting in

the wrong place at an interchange makes you vulnerable to ridicule as well as to the

possibility of missing the right bus or catching the wrong one’’. Wayfinding is an important

cognitive process associated with travel in a novel environment but is not as well-

researched for public transport as other modes. Wayfinding on public transport systems is

associated with an intensified need for good, easily accessible, legible, information

(Hutchinson 2009). Woyciechowicz and Shliselberg (2005) describe how illegible public

transport signs may increase the amount of time passengers spend finding a route and may

result in non-optimal route selection which may take more time and have an adverse

impact on perceptions of public transport travel times. Zhang (2002) argues that transit

centers can be difficult to find one’s way around due to multitudes of services coming

together in one location with sometimes complex passages and stairs to venture around.

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Some research about variability of trip experiences between different passenger and trip

types may offer insights about the variability of unfamiliar public transport travel expe-

riences. Within the general research about public transport travel experience, some studies

touch upon the role of familiarity in affecting experience. For example Lyons et al. (2007)

looked at activities undertaken during travel and found that more people gazed out of

windows for leisure trips than for business trips and that perceived value of travel time

varied by passenger types. Bissell (2010, p. 271) looked at transit experience in terms of

the interpersonal experience between passengers and noted the ‘‘sense of familiarity that

might develop between passengers who commute by the same bus, tube or train on a daily

basis’’. Earlier work by Bissell (2009) noted that repetition of public transport journeys

might aide development of skills and techniques for moving with large objects through

railway stations and that ‘‘inexperienced travelers who have not had the chance to develop

such strategies…might experience relatively greater degrees of encumbrance’’ (Bissell

2009, p. 191). Rochefort (1981) found differences between regular users, non-users and

occasional users in perceptions about the quality of service offered by local bus system.

Mackett and Edwards (1998) argue that for unfamiliar travel associated with the intro-

duction new services, many of the new users will have undertaken the same journey

previously on another service or by another mode, so will be somewhat familiar with the

surrounding area. Wayfinding abilities vary greatly between individuals (Zhang 2002;

Woyciechowicz and Shliselberg 2005) which could impact unfamiliar travel experiences.

Those who are prolific at wayfinding would require less cognitive, and potentially affec-

tive, effort to use public transport. Meanwhile, those who are less skilled in wayfinding

may find first trips to be extremely taxing both cognitively and affectively. Navigational

ability may also vary between tourists and long-time residents, partly because they per-

ceive the city layout differently, using different bearings (Woyciechowicz and Shliselberg

2005).

Although behavior change campaigns and transit marketing tend to assume that use of

public transport will result in more favorable attitudes about the mode (Thøgersen 2009),

the actual experiences of unfamiliar travel, and its importance in shaping attitudes in

subsequent travel behaviors has attracted relatively little research attention. For this reason,

the present research investigates how travel experiences differ for familiar versus unfa-

miliar travel.

The importance of unfamiliar travel in shaping attitudes and travel behavior

There are several research areas that suggest that unfamiliar travel may have an impact on

attitudes and subsequent travel behavior.

One of the most widely-supported and accepted frameworks used to understand the

psychology of travel behavior is the Theory of Planned Behavior (TPB) posed by Ajzen

(e.g. 1991). It states that intention, which precedes behavior, is determined by people’s

attitudes (or evaluations of) performing that behavior, perceived social pressure, and

perceived behavioral control (Mann and Abraham 2006). This suggests that if unfamiliar

travel has a significant impact on attitudes toward public transport, these attitudes may in

turn impact on future intent to use public transport.

Furthermore, in the discipline of psychology, it has repeatedly been observed that the

first event occurring in a sequence (e.g. a trip in sequence of trips) has a well-known

tendency to affect evaluations of the subsequent events in the sequence and to be

remembered better than subsequent events (the primacy effect), except for the most recent

events (the recency effect) (Engel et al. 2014; Kusev et al. 2011; Forgas 2011; Asch 1946;

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Dennis and Ahn 2001). In fact, first impressions have been shown to be one of the most

robust and reliable factors which distort judgments, with neurobiological studies even

indicating that first presentations of stimulus are processed differently in the brain than

subsequent exposures (DiGirolamo and Hintzman 1997; Tulving et al. 1994; Miller et al.

2004).

In conclusion, there is only limited research specifically about unfamiliar travel, and

much of the research only offers indirect insights. However, the existing research suggests

that the topic is worthy of further consideration. The authors’ past research offered

important insights but did have some contextual and methodological limitations. Thus the

present paper is intended to explore unfamiliar public transport travel in greater detail and

using a different research method.

Methods

A self-response web survey was administered in two steps: an initial poll before a journey

and a follow-up survey after the journey.

The poll and follow-up survey were administered through a popular travel planning

website, or ‘Transit Passenger Information Website’ (TPIWS) in Melbourne, Australia.

Melbourne’s TPIWS is managed by Public Transport Victoria (PTV) and offers timetables

and route maps for transit services across the state of Victoria, a journey-planning tool, and

other transit-related information. During the recruitment period, October and November

2012, the PTV website had approximately 4.8 million visits (Nielsen NetRatings 2013),

including 2.2 million visits to the journey planner section of the website and 3.7 million

journeys planned (Nielsen NetRatings 2013; PTV Journey Planner 2013).

The journey planner is used by inputting an origin, destination and, desired time of

travel. Public transit services in Melbourne include trains, trams, buses, and special late

night bus services (‘NightRider’). Outside of the metropolitan area, there are regional

trains (‘v/Line’), regional coaches (also called ‘v/Line’), and regional bus services.

Participants and procedure

The data was collected over a period of 6 weeks during October 2012–January 2013 using

a journey planner website PTV administers for the poll and PTV’s own surveying software

for the follow-up survey. An overview of the research process, from the participant’s

perspective, is depicted in Fig. 1.

Journey planner poll (the ‘before survey’)

A two-question poll was first presented to a random sample of journey planner users when

their search results were provided.1 The first question was a ‘‘yes’’ or ‘‘no’’ question asking

whether it would be the person’s first time taking the trip on public transport. The second

question was an attitudinal question: ‘‘to what extent does your experience of public

transport, on average, meet your expectations of Melbourne’s public transport?’’

Respondents could respond with one of the following six options:

1 During the study period, every fourth journey planner searcher was offered the poll, and if completed, aJavaScript cookie was sent to the associated computer so that the person would not be offered the poll again.

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1. My expectations are often greatly exceeded

2. My expectations are sometimes exceeded

3. My expectations are typically met

4. My experience sometimes falls short of my expectations.

5. My experience often falls well short of my expectations

6. No basis for judgment/have never used public transport in Melbourne before

If a person opted to fill in the poll their response, along with their journey planner data

were saved. A new browser window invited the respondent to provide their email address

to complete a post-travel follow-up survey in exchange for the chance to win a prize.2 One

day after their journey would have occurred; those who provided their email address were

Search for journey byorigin, destination

and time

Travel option resultsappear with the pollquestions on the left

Person answers poll,questions, and submits

‘Thank you’ screen pops up,inviting the respondent to

provide email address to fill infollow up survey for chance to

win prizes

Participant goes to link,completes survey, and isentered into prize draw

After trip searched would haveoccurred, email including survey

link is sent to participant

Fig. 1 Research process fromthe perspective of a participant

2 It is surmised that in many instances this window would have been blocked by ‘pop-up blockers’. Hencein order for the new browser to appear for many participants, they would have had to notice the blocked pop-up, and manually instruct their browser to allow the new window.

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sent a link to the follow-up survey. The initial poll could be filled in by anyone but in order

to fill in the follow-up survey one had to be 18 years of age or older (for ethics reasons).

Follow-up questionnaire (the ‘after’ survey)

The follow-up survey was prefaced with an explanatory statement before respondents were

asked questions about demographics, usual travel habits, the participants’ recent travel

experience, and whether the participants would use public transport for that journey again.

The attitudinal poll question about travel expectations was also asked again. Characteristics

of the travel experience were explored through rating scales (1–5 scale) to explore a

number of travel attributes, depicted in Table 1.

Results

Sample size

The initial poll attracted 3,537 responses. 658 participants completed enough of the follow-

up survey questions to have their responses retained for analysis. The large difference in

number of people completing the poll versus the follow-up survey may be partly due to the

mechanism of recruitment for the follow-up survey: pop-up blockers may have stopped the

second ‘thank you’ window from displaying to invite people to complete the follow-up

survey.3 Due to participants’ occasional inability to recall aspects of their travel

Table 1 Public transport experience attributes measured

Attribute Rating scale

Ease of navigation (wayfinding on publictransit)

1. Extremely difficult tounderstand

5. Very easy to understand

Ease of ticketing (purchasing) 1. Extremely difficult tounderstand

5. Very easy to understand

Emotional state during the trip 1. Very anxious 5. Very relaxed

Expected versus actual travel time 1. Much longer than expected 5. Much quicker than expected

Concern about being late 1. Very concerned aboutbeing late

5. Not worried about being lateat all

Comfort 1. Very uncomfortable 5. Very comfortable

Ease of transfer (e.g. finding nextservice)

1. Very confusing 5. Not at all confusing

Appearance of stations/stops 1. Very unattractive 5. Very attractive

Sense of security while travelling 1. Very unsafe 5. Very safe

Sense of security while waiting 1. Very unsafe 5. Very safe

Overall convenience 1. Very inconvenient 5. Very convenient

Overall satisfaction 1. Very unsatisfied 5. Very satisfied

All attribute ratings included a ‘don’t recall’ option and for ‘ease of transfer’ a ‘did not have to transfer’option could also be selected

3 The new browser window was intended to minimize disruption to people using the journey planner byretaining their journeys.

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experiences, sample sizes for individual analyses varied, but were generally in the vicinity

of 600 participants.

As indicated in Table 2 the sample included a particularly young demographic (61 %

were under 30 years of age), had slightly more females (53 %) and likely reflecting the

young age group, quite a large proportion of the sample either lived at home with parents

(25 %) or with friends or flatmates (24 %). Most of the respondents were working either

full time (43 %), part time (17 %) or studying full time (29 %). It may be that the

research method, which involved a somewhat ‘advanced’ internet technique (allowing

internet pop-ups), somewhat biased the sample toward a younger demographic. This

matter is considered further in the discussion section. More detailed analysis of the

research method and the demographics of the sample are available in Schmitt et al.

(2014). Unfamiliarity with services (as defined in the next section) was not found to be

significantly related to any of these respondent characteristics as tested by Pearson Chi

Square tests.

Definition of unfamiliar travel

In terms of the prevalence of unfamiliar travel, both the poll and follow-up survey asked

participants whether or not their journey was unfamiliar to them.4 In the poll, 23 % of the

3,537 respondents reported taking trips for the first time, suggesting that among users of

internet-based trip planning sites, approximately 1/5 are undertaking a journey where some

or all of the trip is unfamiliar. However, for the remainder of this paper, unfamiliar travel is

defined by the responses to the follow-up survey which asked about familiarity in a more

specific way.5 This asked, ‘‘Were any parts of your journey on an unfamiliar route?’’ with

three possible responses:

• ‘‘yes all of the routes were unfamiliar to me (e.g. I had never used that bus route or train

line before)’’

• ‘‘I had already used some of the routes, but not all of them (e.g. I had used the train

service before but not the bus)’’

• ‘‘No, none of the routes were new to me.’’

Responses to this question were comprised of:

• 75 % (n = 447) of journeys taken included no new routes

• 20 % (n = 119) of journeys included a familiar leg as well as one ‘new’ leg

• 5 % (n = 33) of journeys only included ‘new’ legs.

For the remainder of the paper, unless stated otherwise, unfamiliar travel is defined as

this 25 % who in the follow-up survey reported being unfamiliar with some, or all, of their

journey.

4 Refer to Methodology section for poll wording.5 The more simplistic wording was preferred for the poll whereas space permitted more detail andexplanation in the follow-up survey. The former allowed for some open interpretation. There were someinconsistencies between these two responses for some participants. The follow-up question offered morespecificity but asked about ‘route familiarity’ rather than ‘first time taking trip’. This slight change mayexplain some of the inconsistency in responses. The discrepancy illustrates a key challenge associated withthis topic: familiarity can be somewhat subjective.

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Circumstances of unfamiliar travel

Participants were asked if any major life events had occurred within the last 6 weeks and if

their travel was related to these life events (Table 3). For unfamiliar travelers, 18 % stated

that their travel was related to a life event which was a much higher percentage than for

familiar travelers (9 %). Chi square tests confirmed that this difference was significant,

x2(1, N = 594) = 10.3, p \ 0.01. The most commonly identified life event associated with

unfamiliar travel was beginning or switching jobs. These results suggest that there is a

tendency for life events to prompt unfamiliar public transport travel, though the majority of

unfamiliar travel was not related to a life event.

It was also expected that unfamiliar travel would be more common among those who

had more recently moved to Melbourne. While the majority of all travelers had lived in

Melbourne for more than 10 years, unfamiliar travelers were observed to be newer to

Melbourne than familiar travelers (Fig. 2). Chi square tests confirmed that this relationship

was significant: x2(5, N = 599) = 37.1, p \ 0.01.

Table 4 shows other characteristics surrounding unfamiliar travel. The proportion of

‘peak’ and ‘off-peak’ travel was approximately equal between the unfamiliar and familiar

Table 2 Respondent characteristics (socio-demographic)

Respondent characteristic Proportion (%)(n = 658)

Gender Proportion of sample (%)

Male 46

Female 53

No response 1

Age

\30 61

31–60 36

61? 3

Employment

Working full time 43

Studying full time 29

Working part time 17

Unemployed/seeking work 6

Retired 3

Studying part time 2

Income

$1–$399 per week ($1–$20,799 per year) 27

$1,000–$1,399 per week ($52,000–$72,799 per year) 15

$400–$699 per week ($20,800–$36,399 per year) 12

$700–$999 per week ($36,400–$51,999 per year) 12

$1,400–$1,999 per week ($72,800–$103,999 per year) 10

Nil or negative income 5

$2,000 or more per week($104,000 or more per year) 5

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groups.6 Significant differences were observed for companionship, trip purpose, and

whether or not participants had been to the destination before. Unfamiliar travelers were

more likely to have a travelling companion (16 % compared to 8 %). Unfamiliar travel

Table 3 Recent life events related to travel

Life event** All Related to travel undertaken

%Total %Total(n = 599)

%Familiar(n = 447)

%Unfamiliar(n = 152)

Moved home recently 9 2 3 1

Began/switched jobs recently 13 5 4 8

Began education/switched program 4 1 0 3

Required healthcare (or someone significant requiredhealthcare)

5 1 1 3

Changed family status (e.g. moved in with partner,had child, etc.)

1 0 0 0

Other 2 1 1 3

% of population selecting any of the life events 10 (n = 68) 9 (n = 40) 18 (n = 28)

None 64 NotApplicable

Respondents could select more than one life event

** p \ 0.01, * p \ 0.05

0%3%

11%17%

13%

56%

8% 9% 9% 12% 13%

49%

0%

10%

20%

30%

40%

50%

60%

% o

f sa

mp

le

Time living in Melbourne

Familiar Unfamiliar

Fig. 2 Percentage of respondents selecting each length of time for having lived in Melbourne

6 The peak and off-peak grouping was somewhat simplistic in that it has not taken into account direction oftravel; so counter-peak travel during peak time would still be categorised as peak.

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was associated with a larger proportion of travel related to ‘Leisure/Errands/Shopping/

Fitness-Related’ (35 %) and a lower proportion for employment (27 %) than for familiar

travelers (20 and 38 %, respectively). Unfamiliar travelers were much less likely to report

having been to a destination many times previously (27 %) compared with familiar trav-

elers (84 %).

As also indicated in Table 4, while familiar travelers were rarely visiting locations for

the first time (5 %), 37 % of unfamiliar travelers had never been to the destination before,

36 % had been a few times, and 27 % had been many times before. Thus, a fairly large

proportion of unfamiliar travelers were at least somewhat familiar with the destination

which may have positively impacted wayfinding, making it easier to find one’s way at the

end of the public transit trip.

Experience of unfamiliar travel

Participants were asked to rate their trip in terms of several travel attributes (Fig. 3).

The results of an independent samples t test examining these attributes between the

familiar and unfamiliar groups is presented in Table 5. The results indicate that unfamiliar

users rated ‘navigation (wayfinding on public transport)’ significantly lower than familiar

users did, t(595) = 2.78, p \ 0.01 and ‘emotional state during the trip’ (relaxed vs. anx-

ious) significantly lower than familiar users, t(590) = 2.03, p \ 0.05. Conversely, unfa-

miliar users more highly rated ‘expected versus actual travel time’, t(584) = -2.28,

p \ 0.05; and ‘level of comfort’, t(594) = -2.11, p \ 0.05.

Table 4 Travel characteristics (by percentage of respondents)

Characteristic %Total %Familiar %Unfamiliar

Time of day

Peak (Monday–Friday either 7:30–9:30 or 3:30–6:30) 42 41 43

Off-peak 58 59 57

Travel companionship*

I was travelling by myself 90 92 84

I was travelling with someone 10 8 16

Travel purpose**

Employment 35 38 27

Leisure/errands/shopping/fitness-related 24 20 35

Education 19 20 15

Visiting friends and relatives 12 12 11

Other 6 7 5

Healthcare (for self or other) 4 4 3

On holiday/visiting Melbourne 1 0 3

Previously been to location by other travel means**

Never (my first time travelling to this destination was this trip onpublic transport)

13 5 37

A few times (1–3 times) 18 12 36

Many times (4 or more times) 69 84 27

** p \ 0.01, * p \ 0.05

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In order to investigate whether other factors, beyond ‘familiarity’ impact travel expe-

riences, regression modelling was undertaken to control for factors previously identified as

differing between unfamiliar and familiar travel. In addition, whether or not travel included

a transfer, and respondents’ average weekly frequency of public transport use were con-

sidered in the models as it was predicted that these two factors would potentially affect

travel experiences. One model was run for each of the twelve travel attributes.

The results from the multiple regression models (Table 6) indicate variation in which

factors seemed to affect different attribute ratings. When multiple influences were consid-

ered, travel familiarity was only a significant influence on emotional state: being unfamiliar

was associated with being less relaxed and more anxious. This suggests that for many aspects

of the travel experience, familiarity was less important than other characteristics such as

travel purpose. However unfamiliarity was still shown to have an important, additional

impact on passenger emotions (consistent with past research). In addition to ‘emotional state’,

unfamiliarity was important to (p \ 0.10) but not significant at the p \ 0.05 level to: ‘nav-

igation (wayfinding)’, ‘sense of security’, and ‘expected versus actual travel time’; the latter

being a positive influence and the former two attributes being a negative influence. Also,

variables closely related to familiarity (including ‘time living in Melbourne’ and having

‘previously been to a destination’) were also significant for a number of attribute ratings. It

should also be noted that although the regression models were statistically significant, the R2

values were extremely low (.009 .047), suggesting other factors, which are not modelled (or

perhaps measured), may also have been significant.7

4.2

3.53.8

2.92.6

3.2

3.7

2.9

3.7 3.7 3.6 3.6

3.93.7 3.6

3.12.8

3.4 3.5

3.1

3.6 3.5 3.6 3.7

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5M

ean

Rat

ing

Attribute

MeanUnfamiliar

Neg

ativ

eP

ositi

veMeanFamiliar

Fig. 3 Mean attribute ratings by travel familiarity, including error bars

7 Interaction effects between the significant predictor variables from the regression were also examined withsubsequent ANOVA’s to potentially improve model fits however interaction effects were not observed tostatistically significant.

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How do unfamiliar travel experiences vary with circumstances?

It was predicted that unfamiliar travel would be different for frequent public transport users

compared to those who use public transport for very little of their travel. As shown in the

previous section, background public transport use was only significant in the regression

analysis for two outcome variables.8 In order to investigate the background use of transit as a

factor affecting unfamiliar travel experiences more directly, Multivariate Analysis of

Covariance (MANCOVA) was undertaken with each of the attribute ratings as dependent

variables, the unfamiliarity grouping as the fixed factor variable, and each respondent’s

reported percentage of travel in a typical week being by public transport as a covariate scale

variable. This analysis, with the trip experiences for the dependent variables, was only

significant for unfamiliarity (p \ 0.01) and not significant for background use of transit

(overall, for any of the individual attribute ratings, nor for groups of attribute ratings clustered

via factor analysis), though it is worth noting that the MANCOVA did eliminate a large

number of cases due to missing values. Thus, although it was hypothesized that background

use of transit would impact unfamiliar trip experiences (e.g. that regular public transport users

would rate trip experiences differently to frequent transit users) this was not observed.

Effect of unfamiliar travel on attitudes and behavior

In order to measure whether travel experiences impacted on attitudes, an attitudinal

question was asked prior to undertaking travel (in the poll) and then again in exactly the

Table 5 Public transport experience by travel familiarity

Attribute Familiar Unfamiliar Result

Mean SD Mean SD

Navigation (wayfinding on public transport) 4.2 0.82 3.9 0.91 t(595) = 2.78**

Ease of ticketing (purchasing) 3.5 1.23 3.7 1.23 t(530) = -1.35

Emotional state during the trip 3.8 1.11 3.6 1.03 t(590) = 2.03*

Expected versus actual travel time 2.9 0.77 3.1 0.80 t(584) = -2.28*

Concern about being late 2.6 1.31 2.8 1.42 t(594) = -1.55

Level of comfort 3.2 0.94 3.4 1.02 t(594) = -2.11*

Ease of transfer (e.g. finding next service) 3.7 1.16 3.5 1.15 t(371) = 1.16

Appearance of stations/stops 2.9 0.92 3.1 0.88 t(591) = -1.82

Sense of security while travelling 3.7 0.98 3.6 1.09 t(234) = 0.60

Sense of security while waiting 3.7 1.04 3.5 1.12 t(592) = 1.53

Overall convenience of the travel 3.6 1.01 3.6 1.08 t(595) = -0.72

Overall satisfaction with the journey 3.6 0.99 3.7 0.97 t(595) = -1.25

All ‘don’t recall’ options and ‘did not have to transfer’ responses have been excluded. For the attribute‘‘sense of security while travelling’’ The relatively small sample size associated with ‘sense of security whiletravelling’ is because Levene’s Test for Equality of Variances was significant, so statistics for ‘‘equalvariances not assumed’’ is presented

** p \ 0.01, * p \ 0.05

8 Though in this analysis, background transit used was grouped somewhat arbitrarily with those who usetransit for 40 % or more of their weekly travel classed as ‘frequent’ users and those who with a lowermodeshare of transit classed ‘infrequent’ users.

Transportation

123

Tab

le6

Pu

bli

ctr

ansp

ort

exp

erie

nce

,b

yv

aria

ble

san

dfa

mil

iari

ty

Dep

enden

t

var

iable

s?

Eas

eof

nav

igat

ion

(N=

586)

Eas

eof

tick

etin

g

(purc

has

ing)

(N=

521)

Em

oti

onal

stat

e

(N=

579)

Expec

ted

ver

sus

actu

al

trav

elti

me

(N=

575)

Conce

rn

about

bei

ng

late

(N=

583)

Lev

elof

com

fort

(N=

585)

Eas

eof

tran

sfer

(N=

366)

Appea

rance

of

stat

ions/

stops

(N=

584)

Sen

seof

secu

rity

(tra

vel

ling)

(N=

588)

Sen

seof

secu

rity

(wai

ting)

(N=

582)

Over

all

conven

ience

(N=

585)

Over

all

sati

sfac

tion

(N=

585)

Indep

enden

t

Var

iable

s;

Sta

ndar

diz

edB

etas

Unfa

mil

iar

trav

el-

0.0

8�

x-

0.1

2**

0.0

8�

xx

xx

x-

0.0

8�

xx

Liv

edin

Mel

bourn

e

more

than

6m

onth

s

x-

0.0

9�

-0.0

9*

-0.0

9*

-0.1

2**

-0.0

7�

x-

0.1

0*

-0.1

1**

-0.1

0*

-0.0

8�

-0.0

7�

Tra

vel

rela

ted

to

life

even

ts

-0.1

0*

xx

xx

xx

xx

xx

x

Pre

vio

usl

ybee

n

todes

tinat

ion

xx

xx

x-

0.0

8�

xx

x-

0.0

8�

-0.0

9*

-0.1

1**

Had

trav

el

com

pan

ion

xx

xx

0.0

8*

xx

xx

xx

Tra

vel

purp

ose

(hea

lthca

re)

x-

0.1

0*

-0.1

1*

xx

xx

xx

xx

x

Tra

vel

purp

ose

(educa

tion)

xx

-0.1

3**

xx

xx

xx

xx

x

Tra

vel

purp

ose

(em

plo

ym

ent)

x-

0.0

8�

-0.0

8�

xx

xx

xx

x-

0.0

7�

-0.1

4**

Tra

vel

purp

ose

(lei

sure

/

shoppin

g…

)

xx

xx

0.2

4**

0.0

8�

xx

xx

xx

Tra

vel

purp

ose

(vis

itin

g

frie

nds…

)

xx

xx

0.1

3**

x0.1

3*

xx

xx

x

Journ

eyin

cluded

tran

sfer

-0.0

9*

xx

x-

0.1

3**

xx

xx

-0.1

5**

-0.2

0**

-0.1

4**

Transportation

123

Tab

le6

con

tin

ued

Dep

enden

t

var

iable

s

?

Eas

eof

nav

igat

ion

(N=

586)

Eas

eof

tick

etin

g

(purc

has

ing)

(N=

521)

Em

oti

onal

stat

e

(N=

579)

Expec

ted

ver

sus

actu

altr

avel

tim

e

(N=

575)

Conce

rn

about

bei

ng

late

(N=

583)

Lev

elof

com

fort

(N=

585)

Eas

eof

tran

sfer

(N=

366)

Appea

rance

of

stat

ions/

stops

(N=

584)

Sen

seof

secu

rity

(tra

vel

ling)

(N=

588)

Sen

seof

secu

rity

(wai

ting)

(N=

582)

Over

all

conven

ience

(N=

585)

Over

all

sati

sfac

tion

(N=

585)

Fre

quen

t

PT

use

r

x0.0

9*

x-

0.1

0*

xx

xx

xx

xx

Adju

sted

R2

0.0

23

0.0

21

0.0

28

0.0

22

0.0

96

0.0

17

0.0

14

0.0

09

0.0

11

0.0

35

0.0

49

0.0

47

F5.5

3**

3.7

6**

4.3

4**

5.2

7**

13.5

6**

4.3

0**

6.2

8*

6.0

7*

7.2

9**

6.3

4**

8.6

2**

8.2

0**

Sta

ndar

dis

edB

eta

val

ues

only

pro

vid

edfo

rvar

iable

sre

tain

edin

final

model

s.F

or

the

sake

of

sim

pli

city

,in

term

sof

trip

purp

ose

,‘‘

oth

er’’

and

‘‘on

holi

day

/vis

itin

gM

elbourn

e’’

wer

enot

incl

uded

in

the

model

asonly

4par

tici

pan

tsse

lect

edth

isfo

rth

eir

trip

purp

ose

**

p\

0.0

1,

*p\

0.0

5,�

p\

0.1

0

Transportation

123

same way after travel (in the follow-up survey): ‘‘to what extent does your experience of

public transport, on average, meet your expectations of Melbourne’s public transport?’’

Responses were recoded as ordinal variables and the difference between before and after

responses calculated. A paired samples t test suggested that there was a small but statis-

tically significant shift toward a more positive attitude following travel in the sample

overall (M = -0.08, SD = 0.73, p \ .01). When disaggregated by familiarity, the results

of this analysis (Fig. 4) show that familiar travelers were less likely to have their attitudes

shift in either direction than unfamiliar travelers, who seemed to be split in terms of

whether their attitudes shifted positively or negatively. However, Chi square tests indicated

that this trend was not statistically significant, x2(1, N = 594) = 1.98, p = 0.16.

Next, analysis was then undertaken to determine whether or not familiarity, on its own,

impacted behavior related to modal choice. As indicated in Table 7, when asked, ‘‘do you

think that you will use public transport to travel to this destination again?’’ most travelers

(97 % of familiar travelers and 75 % of unfamiliar travelers) said that they would use

public transport for this travel again, but the proportion of a travelers stating that they

‘would not’ or ‘did not know’ if they would use a service again was larger in the unfamiliar

group (even after controlling for people who were unlikely to use a service because they

were unlikely to visit a destination again). A Pearson’s Chi square indicated that familiarity

was significantly related to intention to use transit services again, x2(2) = 40.23, p \ 0.01.

In order to better understand how the actual travel experiences impacted intention to use

services again, independent samples t tests were undertaken to determine whether people

who had more positive travel experiences were more likely to say they would use public

transport again (Table 8). In general, higher attribute ratings were associated with intention

to use services again, especially for unfamiliar travelers. For unfamiliar travelers, ratings of

‘emotional state during the trip’, ‘comfort’, ‘ease of ticketing (purchasing)’ and ‘overall

satisfaction’ were all significantly more positive for those who said they would use the

service again. In contrast, for familiar travelers only ‘overall satisfaction’ ratings differed

0% 2%

9%

70%

17%

2% 0% 0%1% 1%

14%

64%

18%

3% 1% 0%0%

10%

20%

30%

40%

50%

60%

70%

80%

-3.00 -2.00 -1.00 .00 1.00 2.00 3.00 4.00

% o

f g

rou

p

Shift in attitude following travel

Familiar % Unfamiliar %

Improved attitude following travelWorse attitude following travel

Fig. 4 Shift in attitude following travel

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123

between those who would use the service again and those who would not. This suggests

that trip experience has a greater impact on future behavior for unfamiliar travelers than for

familiar travelers.

Another interesting finding was that ‘soft’ variables such as ‘comfort’ and ‘emotional

state’ were more influential than ‘harder’ and more conventional factors such as ‘expected

travel time’ and ‘concern about being late’. However for this analysis, there were very few

travelers who reported that they would be unlikely to use services again so the results

should be interpreted with some caution.

Discussion and conclusions

This research explores unfamiliar travel in terms of circumstances, experiences, and the

significance of travel impressions on travel and attitudes and behavior, using an online

Table 7 Intention to use service again, by familiarity

Will use service again? Familiar (%) Unfamiliar (%)

Yes 97 75

No 1 7

Don’t know 2 17

Participants who said that they would not be using transit again for that journey because they were unlikelyto be travelling to that destination again were excluded from this analysis. Also those who responded ‘‘donot know’’ to their likelihood of re-using a service are presented in this table, but were excluded from theChi square analysis

Table 8 Mean trip attribute ratings based on intention to use service again, by familiarity

Travel familiarity Familiar Unfamiliar

Intend to use service again Yes(n = 429)

No(n = 3)

Yes(n = 113)

No(n = 9)

Ease of navigation (wayfinding on publictransit)

4.2 3.3 4.0 3.8

Ease of ticketing (purchasing) 3.5 2.5 3.8* 2.8*

Emotional state during the trip 3.8 4.3 3.7** 2.8**

Expected versus actual travel time 2.9 3.0 3.1 2.7

Concern about being late 2.6 3.0 2.8 2.8

Comfort 3.2 3.3 3.5** 2.6**

Ease of transfer (e.g. finding next service) 3.7 3.0 3.5 3.2

Appearance of stations/stops 2.9 2.7 3.1 2.8

Sense of security while travelling 3.7 4.3 3.6 3.1

Sense of security while waiting 3.7 4.0 3.5* 2.7*

Overall convenience 3.6 2.7 3.7 3.0

Overall satisfaction 3.6* 2.3* 3.8* 2.8*

Participants who said that they would not be using transit again for that journey because they were unlikelyto be travelling to that destination again were excluded from this analysis. Also those who responded ‘‘donot know’’ to their likelihood of re-using a service have been excluded

** p B 0.01 and * p \ 0.05

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123

survey of a travel planning website in Melbourne, Australia. Three key research questions

were explored, offering interesting and potentially important insights about unfamiliar

travel.

Research question 1 How prevalent is unfamiliar travel and under what circumstances

does unfamiliar travel occur?

Approximately one-fifth of the participants surveyed were undertaking unfamiliar tra-

vel, which is high given the amount of literature suggesting that most travel is habitual

(Thøgersen 2009; Verplanken and Aarts 1999), but this could be partly attributed to the

recruitment mechanism (engagement through a journey planner website). Also, a large

number (n = 119) of the unfamiliar travel included a familiar trip-leg in addition to the

familiar trip-leg.

Reflecting literature about life events obtaining a driver’s license, switching schools,

changed physical mobility and having children (Davidov 2007; Sharples 2009; Van Exel

and Rietveld 2009; Beige and Axhausen 2012), this study found that unfamiliar travel was

more commonly associated with life events than familiar travel. The research also revealed

a number of other circumstances surrounding unfamiliar travel:

• Having lived in Melbourne for less time

• Travelling with another person

• Travelling for leisure/errands/shopping/fitness rather than employment

• Not having previously been to a destination.

Understanding these circumstantial trends also provides the context of unfamiliar travel

experiences. The finding that unfamiliar travel was more often associated with leisure

travel may partly explain why Lyons (Lyons et al. 2007) found that people were more

likely to gaze out the window during leisure travel than travel for work, because it is more

likely to be un-ordinary.

Research question 2 What experiences are associated with unfamiliar travel?

One great challenge for transport professionals and infrastructure providers is to

understand the unfamiliar traveler’s mindset. In terms of unfamiliar travel experiences,

travel attributes that were rated significantly more negative for unfamiliar travelers than

familiar travelers were ‘navigation (wayfinding on public transport)’ and ‘emotional state

during the trip’ (level of anxiety). Conversely, travel ratings for ‘expected versus actual

travel time’ and ‘level of comfort’ were higher than for familiar travelers. The finding that

unfamiliar travel can be challenging in terms of navigation and associated with a negative

emotional state (anxiety) is consistent with the authors’ previous research and the other

(though somewhat limited) existing research about unfamiliar travel (e.g. Dziekan and

Dicke-Ogenia 2010). However unfamiliar travelers rating some travel attributes as sig-

nificantly more positive than familiar travelers differed from the authors’ previous

research. Further research is clearly needed to see if this is a result of the research method

used, or whether other characteristics of the travel/traveler are influencing these experi-

ences. For example, travel to work (more common for familiar travelers) may be less

comfortable due to crowding and workers may be more sensitive to travel time than travel

related to leisure/shopping (more common for unfamiliar travelers). Also the research

method utilized a travel planning website, thus the journeys had pre-trip planning which

may have influenced some aspects of the travel experiences.

Meanwhile the regression analysis indicated that when multiple influences are con-

sidered, except for ‘emotional state’, unfamiliarity is less important to attribute ratings than

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123

other factors for most attributes of travel experience measured. The finding that ‘emotional

state’ was significantly more negative for unfamiliar travelers, even with other factors

considered, is again consistent with past research by Dziekan and Dicke-Ogenia (2010)

who found that travelling through unfamiliar environments is particularly challenging and

stressful due to a perceived lack of control, a lack of information and a process of updating

one’s ‘cognitive map’. The regression analysis also showed that variables closely related to

familiarity, including ‘time living in Melbourne’ and having ‘previously been to a desti-

nation’ were significant predictors for a number of attribute ratings, a finding also con-

sistent with the study by Dziekan and Dicke-Ogenia (2010).

Past research offers some insights about particular aspects of unfamiliar transit expe-

riences that may be influencing the attribute ratings observed in this study. Woyciechowicz

and Shliselberg (2005, p. 35) discuss challenges of wayfinding, ‘‘constraints imposed by

the road network and local geography often create patterns that, however obvious to the

professional transportation planner, are not at all obvious to the average user examining a

map’’. Wayfinding may also be affected by the presence or absence of landmarks (Coxon

et al. 2008). For example, transferring at a landmark is much simpler for a passenger than

at sites that are utterly unfamiliar (Woyciechowicz and Shliselberg 2005). These authors

maintain that arterial roads are typically more familiar to individuals, even those who do

not know an area well and can, in a way, mimic landmarks. Thus our research further

confirms the recommendation by Hutchinson (2009); that wayfinding on public transport

systems is associated with an intensified need for good, easily accessible, legible,

information.

As discussed in the review of literature, existing research offers some guidance about

how different circumstances may impact unfamiliar trip experiences, notably, trip purpose

may impact activities undertaken while travelling (Lyons et al. 2007). Likewise, the inter-

passenger familiarity associated with habitual commute trips described by Bissell (2010)

would not exist for unfamiliar travel; and unfamiliar travelers may be more encumbered in

moving objects through railway stations (Bissell 2009). Pedersen et al. (2011) found that

car users underestimate future satisfaction of transit services. On the basis of these studies,

it was hypothesized that unfamiliar travelers who were frequent transit users would have

more positive unfamiliar experiences than less frequent transit users. However the analyses

did not find frequency of use to be a significant predictor of experiences.

Research question 3 Do unfamiliar travel experiences impact attitudes and behavior

related to mode choice?

Among the entire survey population, on average, attitudes toward public transport

became slightly more positive after undertaking a trip. Although unfamiliar travelers were

more likely to change their attitude (50 %) than familiar travelers (30 %), the relationship

was not found to be statistically significant. Thus, it may be that unfamiliarity is associated

with more pliable travel attitudes in relation to recent experiences, but this requires further

investigation. The observed (but not statistically significant) pliability of unfamiliar trav-

elers’ attitudes, reflects, in a micro-example way, research about life events, indicating that

life events can disrupt habitual behavior prompting re-evaluations of travel habits and

sometimes new travel behaviors (refer to studies by Goodwin et al. 2004; Davidov 2007;

Verplanken et al. 2008). It is worth noting that in the present study only one attitudinal

question related to expectations was asked both before and after the trip. Further research

may benefit from examining more components of attitudes and customer satisfaction both

before and after unfamiliar travel.

Transportation

123

In relation to modal behavior, the finding that attribute ratings were higher for travelers

who stated that they intended to use services again than for those who did not, suggests that

positive trip experiences impact intention to re-use services, particularly in the case of

unfamiliar transit travel. The key attributes where this is most evident included ‘emotional

state during the trip’, ‘comfort’, ‘ease of ticketing (purchasing)’, and ‘overall satisfaction’.

This provides support for the hypothesis that unfamiliar travel experiences can have an

impact on intention to use a service again, highlighting the importance of improving the travel

experience of unfamiliar travelers. This finding is consistent with Lai and Chen (2011, p. 318)

who explain that, ‘‘travelers who perceive good quality of public transit service are…more

likely to have a higher level of perceived value and satisfaction, and so continue to use this

service’’. Thus, these authors argue that positive experiences are thought to contribute to other

customer loyalty practices such as word-of-mouth interactions, purchase intentions, and price

insensitivity, improving the financial performance of public transport systems. Overall, the

findings of the present study provide useful insights to help grow public transport markets by

attracting and retaining new users, keeping existing users, and preserving and enticing

increased use of public transport by occasional users.

Limitations and future directions

Despite the important findings of the research, there are also research limitations worthy of

consideration. This study relied on a TPIWS for participant recruitment. As such, both

familiar and unfamiliar travelers would have obtained information to plan their trip which

may have reduced anxiety and cognitive costs. Thus the findings in this study should be

interpreted with this in mind. It would be beneficial for future research about unfamiliar

travel to more comprehensively examine the role of information tools. Another point worth

considering is that although the number of survey responses was quite high, the sample was

self-selected and included a very high representation of young participants. Moreover,

while the research was designed to evaluate a great variety of travel types and geographies

across Victoria, this also meant that there are a large number of variables that could be

impacting experiences in addition to travel familiarity.

Despite these limitations, the research offers important information that could con-

tribute to the success of travel behavior change campaigns and the design of transit sys-

tems. It highlights the importance of adequate information for unfamiliar users (even

unfamiliar users who frequently use other public transport services on the network). It

shows that life event events, such as changing jobs, provide a unique opportunity to engage

with unfamiliar public transport users. It highlights that some aspects of travel are more

negative for unfamiliar travelers and that negative experiences can discourage them from

using public transport services again. Notably the findings suggest that ‘soft’ factors such

as comfort, understanding the ticketing system and being relaxed while travelling may be

more important to unfamiliar users than traditional metrics such as expected travel time

and concern about being late.

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Lorelei Schmitt is a doctoral student at Monash University and works for the university’s facilities divisionas a sustainable transport officer. Her research interests include transport and land use planning, transportpsychology, and travel demand management. She also has prior industry and academic experience in thesefields.

Graham Currie is a Professor of Public Transport and Director of the Public Transport Research Group atthe Institute of Transport Studies (ITS), Monash University. He directs the World Transit ResearchClearinghouse (www.worldtransitresearch.info) and has published over 200 research papers in leadingresearch journals and conferences.

Alexa Delbosc is a research fellow in the Public Transport Research Group of the Institute of TransportStudies in the Monash University Department of Civil Engineering. Her research focuses on the changingtravel habits of young people, transport psychology, human factors in public transport and the use ofpowered-two-wheel transport.

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