Transportation (2014) 41:75–89
DOI 10.1007/s11116-013-9472-7

Persuasive communication aimed at public
transportation-oriented residential choice
and the promotion of public transport
Ayako Taniguchi • Satoshi Fujii • Tomohide Azami • Haruo Ishida

Published online: 23 April 2013
Ó Springer Science+Business Media New York 2013

Abstract In this study, we developed a persuasive communication program to induce
public-transport-oriented residential (PTOR) choice. We implemented an experiment thattargeted students from the University of Tsukuba, Japan, who were in the process ofchanging their residential location. These students were randomly assigned to four groups:
the first group was a control group; the second group received an information brochure
about apartment flats typically used by students in Tsukuba city; the third group received abrochure identical to the one given to the second group, except that it also included
information about the level of bus service for every flat; and the fourth group was provided
with a leaflet that provided motivation for PTOR choice, in addition to the brochure used
for the third group. The residential locations were investigated 5 months after the intervention. There was a significant difference between the control group and the third andfourth groups. The ratio of PTOR choice in the group with the information was twice ashigh as that for the control group. Furthermore, the persuasive message also increased
PTOR choice. Additionally, the target groups’ frequency of bus use from home or theuniversity was significantly high compared with the control group.
Keywords Residential choice  Public-transport-oriented residential (PTOR) choice 
Mobility management  Persuasive communication  Contingent focus model

An earlier version of this paper was presented at 40th European Transport Conference.
A. Taniguchi (&)
Department of Risk Engineering, University of Tsukuba, 1-1-1 Ten-noudai, Tsukuba 305-8573, Japane-mail: taniguchi@risk.tsukuba.ac.jp
S. Fujii
Kyoto University, Kyoto, JapanT. Azami
East Japan Railway Company, Tokyo, Japan
H. Ishida
University of Tsukuba, Tsukuba, Japan

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Introduction
Recently, the concept of a ‘‘compact city’’ that offers public transportation options forresidents living close to the city centre has been proposed as a potential solution to thevarious traffic and environmental problems in urban areas (e.g., CEC 1990; Jenks et al.
1996). The realization of a compact city would require land-use regulations and infrastructure development, in addition to measures to induce people to live or work in areas
close to public transportation. However, measures to regulate residence choice may bedifficult to introduce because they may be viewed as reducing people’s free choice
regarding their living arrangements. Thus, soft measures to voluntarily induce behaviourchange regarding residential choice, combined with regulatory measures and infrastructuredevelopment, may provide the needed results.
In Japan, the number of public transportation users in rural areas is decreasing. The
promotion of public transportation has become an important issue for local governments inJapan to secure travel options for people who are unable to drive themselves. To promote
public transportation, it is essential to not only offer a high level of service (e.g., highfrequency service and low fares) but also to locate people’s homes or workplaces close to
public transportation.
A compact city with an integrated transportation system would be feasible if people
lived close to the city centre or near railway stations or bus stops, lessening their relianceon car use. Persuasive communication to induce people to choose to live in such locations
could aid in developing a compact city and solving various types of urban transportation
problems. The objective of this study was to develop a persuasive communication program
to induce public-transport-oriented residential choice (PTOR choice).

Theoretical background
Literature
Numerous studies have examined residential choice, with many focusing the developmentof models to quantitatively determine the factors influence residential choices or preferences. Lerman (1976), Louviere (1979), McFadden (1978), White (1988), and Young(1984) formulated discrete residential location choice approaches, and Timmermans et al.
(1992), Sermons and Koppelman (2001), and Zhang and Fujiwara (2009) further developed such work. As a state-of-the-art on this topic, Pagliara et al. (2010) represented arange of approaches used to model residential locations within the context of developing
land-use and transport models. However, these studies did not use a proactive approach toinfluencing choice of living arrangements.
As a measure to actually induce PTOR choice, in the city of Toyama, Japan, the local
government gave apartment owners a subsidy if their apartment complex was located close to
public transportation (see website: http://www.city.toyama.toyama.jp/english/English.html).
If the apartment was located close to a railway station, a maximum one-time subsidy of
1,200,000 yen (*12,000 Euros) was allotted per apartment. For apartment buildings with fouror more units located close to the central zone, a maximum of 1 million yen (*10,000 Euros)
per apartment was given to the owner (Takami and Hatoyama 2008). Moreover, Toyama
citizens received a subsidy of as much as 500,000 yen (*5000 Euros) per household forpurchasing a residence in the central zone. These measures may aid in developing a ‘‘compact

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city,’’ but it would still take a long time to realize a compact city. Soft measures of persuasion,in addition to subsidies, are required to induce changes in behaviour regarding PTOR choice.
Some psychological studies have examined the use of soft measures to induce voluntary
behavioural change (VBC) to a more sustainable lifestyle (e.g., Stern et al. 1986, 1993;
Fransson and Gärling 1999; Gärling and Fujii 2002). The major characteristic of VBC is toinduce voluntary behaviour change by providing information and motivation rather thanmonetary incentives or restrictions. These communications to motivate people are typicallycalled ‘‘persuasive communications’’ in academic psychological research (cf. Ajzen 1992).
Mobility management may be a practical measure for inducing voluntary travel behaviourchange, as shown by various studies (Jones 2003; Cairns et al. 2004; Brög 1998; Ampt andRooney 1999; Rose and Ampt 2001; James 2002; Fujii and Taniguchi 2005; Taniguchi
et al. 2007; Enoch 2012). The EU has supported several such projects, as listed on theEuropean Platform on Mobility Management website (http://www.epomm.eu/index.php).
We referred to these projects when developing and implementing our experiment.
Overview of the contingent focus model
We also referred to the contingent focus model when developing our persuasive communication program for PTOR (Takemura 1994; Fujii and Takemura 2001, 2003). Here,
we briefly describe this model.
Identical decision problems in form may yield different outcomes. The outcome
depends on the subjective decision framing as a function of how the situation is described.
This is called the framing effect (Tversky and Kahneman 1981). Tversky and Kahneman(1981) conducted experiments on the framing effect and found that different phrasing
affected participants’ responses to a question about disease prevention strategy. In theirstudy involving 600 participants, they offered two alternative solutions to the participants
afflicted with a hypothetical deadly disease. One solution was offered in a positive framethat emphasized ‘‘lives gained’’; the second was presented in a negative frame thatemphasized ‘‘lives lost’’. The choice of the participants was more likely to be based on thediscrepancy between ‘‘gained’’ and ‘‘lost’’. This demonstrates the essence of the framing
effect: the two groups favoured different options because the options were expressed
employing different language. In the first problem, a positive frame emphasized lives
gained; in the second, a negative frame emphasized lives lost. A slight alteration in thelanguage underlies the differences in the preferences.
The contingent focus model (Takemura 1994) can theoretically explain why the framing
effect emerges. This model hypothesizes that risk attitude depends on how one focuses on
the possible outcome (focusing hypothesis). The ability to focus on the outcome is, in turn,
contingent on the decision-making situation (contingent focus hypothesis).
According to contingent focus model, the decision-making frame would be affected bydifferences in the message and communication approach. As a result, behaviour would also
be expected to be different. For example, for the case of residential choice, if people
receive information that emphasizes the level of bus service, then they would be expected
to choose based on the bus service level. If this is true, then we could induce PTOR choice.
Two methods can be used to emphasize a particular attribute: cognitive and motivational. ‘‘Cognitive’’ emphasis means that the attribute displays more merit after one obtains
and processes information on the attribute in an organized, rational manner, carefully
weighing the choices before making a final decision. For example, specific text is displayedlarger or more distinct colour than the others. It was indicated by past cognitive decisionmaking research that this method was effective to change people’s decision making.

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Transportation (2014) 41:75–89‘‘Motivational’’ emphasis refers to the ability to induce a decision by explaining theimportance of the attribute, using various data and examples. This approach is often used in
actual persuasive communication. For example, a salesman emphasizes the merits andimportance of the goods which he wants to sell.
In this study, on the basis of the theoretical discussion above, we conducted a persuasive
communication program to induce PTOR choice using both cognitive and motivational
emphasis methods.

Overview of the target
In this project, the target population was students from the University of Tsukuba, Japan.
The University of Tsukuba is located in northern Tokyo and has approximately 12,000
students and 6,000 faculty. It takes approximately 1 h to get to the university from thecentre of Tokyo by train. In August 2005, a new bus system was introduced for the students
and faculty, in addition to a new railway line, the ‘‘Tsukuba Express’’ which runs from
Akihabara (at the centre of Tokyo) to Tsukuba. The price of an annual commuter pass forthe new bus service is only 4,200 yen (about 42 Euros) per year for students and 8,400 yen
for faculty. This annual commuter pass is sold to students at a 97 % discount. During rush
hours, the bus frequency is one bus every 5 min. In non-rush hours, buses arrive every
6–10 min.
Although the new bus system offers a high level of service, as mentioned above, only
3,000 passes (2,300 for the student population) were sold during the first year. In thesecond year of service (2006), we implemented a promotion that provided easy but detailed
information on transportation pass purchases and transportation system use to students andfaculty. This promotion was successful, resulting in 5,700 passes sold (4,800 to students).
However, university officials felt that there was more potential demand for the new bus
system. To investigate this further, we interviewed several students to learn why they did
not use the new bus system or purchase the pass. The interview results indicated that somestudents did not use the new bus system because they lived too far from a bus stop. People
living far from a bus stop or rail station were less likely to use public transportation. Our
results also suggest that if people do not consider public transportation accessibility whenchoosing their residence, sprawl will continue, leading to an inefficient, underutilized city.
Considering these issues, we examined the use of persuasive communication for encouraging residency closer to public transportation.
We implemented our study with freshmen students at the University of Tsukuba, manyof whom live on the campus in dormitories. Freshmen are given priority regarding dormitory residency. However, because of limited dormitory space, many sophomores are notawarded dorms and have to move into apartments around the university. We thus focusedon freshmen students who were planning to move from the dormitory to an apartment intheir sophomore year.

MethodExperimental groups and materials distributed
As mentioned above, we targeted students at the University of Tsukuba who were about tochange their residency. These students were randomly assigned into four groups (Fig. 1):

123Transportation (2014) 41:75–89

Common Info. Group

79

Cognitive Info. Group

Motivational Info. Group“Bus Conveniencemarks”
are added to
the flat list

Flat List & Map

Red circles areadded to show locations
within a 200-m radiusof bus stops

Plus
Motivational Leaflet

Fig. 1 Experimental groups and materials distributed

the first group was a control group; the second group (the common information group) was
provided with an information brochure about typical apartments used by students in
Tsukuba City; the third group (the cognitive information group) was provided with abrochure that was identical to the one used for the second group, except that it also
included information about the level of bus service for every apartment; the fourth group(the motivational information group) was provided with a leaflet to motivate PTOR choicein addition to the brochure used for the third group. The information brochure distributed
to the common group, cognitive group, and motivational group consisted of two components: a list of each apartment’s attributes (such as rent, room size, age of the building) andlocation maps of the apartments.
For the cognitive group, we attached ‘‘bus convenience marks’’ (in red) to the apartments listed in the brochure, if the apartment was located less than 200 m from the bus stop(within a 3-min walk). Moreover, to increase the appeal of apartments conveniently locatedfor bus use, we attached location maps with red circles around the apartments locatedwithin a 200-m radius of a bus stop. The cognitive group did not receive any motivational
information.
For the motivational group, a motivational leaflet was added to the brochure used by the
cognitive group discussed above. The motivational leaflet consisted of three parts:
advantages to living close to the bus stop (such as health, all-weather mode of transportation, environmentally friendly), an overview of the new bus system at the University ofTsukuba, and how to look for an apartment around bus stops (Fig. 2).
Experimental procedure
In November and December of 2007, we distributed the materials randomly at two places:
freshmen lecture halls and the venue for the ‘‘dormitory lottery’’ event revealing which

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Fig. 2 Example of the motivational leaflet

non-freshmen have been awarded dormitory rooms for the upcoming year. The participants
were asked to read the materials carefully and to fill out a form using their name andstudent ID number.
In April 2008, 5 months after the intervention (material distribution and dormitory
lottery), we conducted a questionnaire survey to measure the effects of the interventions,targeting all of the sophomores who had completed their freshmen year at the university(Fig. 3). (Note that in Japan, the new academic/fiscal year begins in April.) For the survey,
we requested that the participants fill in their name, student ID number, and home address,
in addition to other pertinent information. We then verified the name and student ID
number and identified the participants who had received the intervention materials. For thecontrol group, we selected 77 students from the 2,714 participants that received the firstquestionnaire survey in April 2008. Of these, 47 completed the first questionnaire in April
2008, among which 37 were identified as having moved to apartments in Tsukuba. These
37 students comprised the control group.

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81

November – December 2007 (before moving)
Control Group

Common Info.

Cognitive Info.

Motivational Info.

Group

Group

Group

Only provided
residential informationon commonly used

Provided residential
information focusing on
bus stop distance

Provided residential information
focusing on bus stop distanceand a motivational leaflet

April 2008: 1st Questionnaire survey (after moving)

November 2008: 2nd Questionnaire survey
Fig. 3 Flow of the experiment

In November 2008, approximately 11–12 months after the intervention, we conducted asecond survey. With the cooperation of the university’s administrative office, we compiled
a list of students who were given intervention materials in 2007. This list, displayed on abulletin board at the university, asked the students to contact the university so that they
could receive the second questionnaire for our study.
Table 1 indicates the number of materials distributed and the number of materials andquestionnaires collected.
Measures and indexes
To analyse the effects of the experiment, we asked the participants several questions,using two separate questionnaires, and calculated the measures and indices, as shown in
Table 2.

Table 1 Number of materials distributed and questionnaire respondents

Nov.–Dec.
2007
April 2008

November
2008# Receiving the distributed materials

Controlgroup

Commoninfo. group

Cognitive
info. group

Motivational
info. group

(77)

72

78

53

1st questionnaire respondents

47

30

48

35

# Of respondents who had moved toan apartment in Tsukuba City

37

18

34

20

# Of students participating in theanalysis

37

18

34

20

2nd questionnaire respondents

35

26

31

16

# Of respondents who had moved toan apartment in Tsukuba City

16

22

22

9

# Of students participating in theanalysis

16

22

22

9

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Table 2 Questionnaire responses and indices
1stquestionnaire

Index

Questions used in survey
calculation

Scale

X

(1) Cognition of level ofbus service

Q. Do you think your apartment isconvenient for bus use?

No/yes(sevenpoint
scalea)X(2) Intention to movecloser to bustransportation for the
next residence

Q. The next time you move, will
you likely choose an apartment
convenient to bustransportation?

No/yes(sevenpoint
scale)X(3) Self-assessment oftime/distance fromhome to the nearest bus
stop

Q. How many minutes does it takeyou to get from your home to thenearest bus stop?

Minute(s)

X(4) Calculated time/
distance from home to
the nearest bus stop

Q. Please list your address andblock number
Calculate time distances from theapartment to the nearest bus stopusing a GIS system, in which theaverage walking speed is defined
as 80 m/s

X(5) Living within 3 minfrom bus stop

Participants who live within 3 minfrom the bus stop by
walking = 1, otherwise = 0(6) Ownership of annual
bus commuter pass

Q. Do you have an annual bus
commuter pass for this year?

Yes/no(7) Frequency of bus use(for April)

Q. How many times did you
recently use the campus bus in
1 week?

Times/weekX(8) Frequency of bus use
from home (forNovember)Q. How many times did you
recently use the campus bus
from your home in 1 month?

Times/monthX(9) Frequency of bus use
from university (forNovember)Q. How many times did you
recently use the campus bus
from the university in 1 month?

Times/
month

X

2nd
questionnaire

X

X

a

The 7-point scale rankings: ‘‘0’’ means that respondent do not think it at all, and ‘‘7’’ means that
respondent think it strongly

Results
We analysed the data of the two questionnaire surveys from three viewpoints: (1) cognition, intention, and self-assessment of the participant’s residential choice, (2) residential
choice, (3) ownership of the annual commuter pass and (4) frequency of bus use.
Cognition, intention, and self-assessment
Table 3 shows the mean and standard deviation for each of the experimental groups
regarding their cognition and intention towards residential choice, self-assessment, andcalculated time distance. Table 4 shows the results of a one-tailed t test of paired comparisons for the groups.

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83

Table 3 Mean and standard deviation of each experimental group
ControlCommon info

Cognitive info.

Motivational
info.

N

M

SD

N

M

SD

N

M

SD

N

M

SD

(1) Cognition of level of bus
service

37

2.27

1.84

18

3.17

1.42

33

2.94

2.28

20

4.05

2.09

(2) Intention to move to alocation convenient to bus
service next time

37

2.62

2.03

17

2.59

1.80

33

3.30

2.05

20

3.35

2.13

(3) Self-assessed time/distancefrom home to the nearest bus
stop

36

6.00

3.56

18

4.72

2.40

34

4.88

3.61

19

4.16

3.20

(4) Calculated time/distancefrom home to the nearest bus
stop

37

6.93

4.51

18

5.80

3.84

34

5.84

4.85

20

4.63

3.68

N sample size, M mean, SD standard deviation
Table 4 Results of one-tailed t test of paired comparisons of each group
Commoninfo. vs.
motivational
info.
t

Cognitive
info. vs.
motivational
info.
t

0.384

-1.505*-1.774**-1.213-1.160-0.0801.886**-0.169

0.604

0.729

1.954**-0.035

0.957

0.965

Controlvs.
commoninfo.
tControlvs.
cognitiveinfo.
tControl vs.
motivational
info.

(1) Cognition oflevel of bus service-1.819**-1.360*-3.328***(2) Intention to moveto a location
convenient to bus
service for the next
move

0.058

-1.393*-1.269(3) Self-assessedtime/distance fromhome to the nearest
bus stop

1.372

1.304*(4) Calculated time/
distance fromhome to the nearest
bus stop

0.915

0.977

Results of one-tailedt testtCommoninfo. vs.
cognitiveinfo.
t

t: t value* 0.05 \ p \ 0.1; ** p \ 0.05; *** p \ 0.01

Table 4 shows that the control group tended to have low cognition of the level of bus
service compared with the other groups. The motivational group exhibited a particularlyhigh cognition of the bus service available, compared with the common and cognitive
groups.
The intention to move to a location convenient to bus service for the next move tended
to be high for the cognitive group, compared with the control group; there was no significant difference between the other groups. However, the p value between the

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motivational and control groups was 0.1048, close to a 90 % significance level. The
average for the motivational group, shown in Table 4, was high compared with othergroups.
The self-assessed time/distance from home to the nearest bus stop tended to be smaller
for the cognitive group than for the control group and was even smaller in motivationalgroup.
These results suggest that the cognitive group, who were focused on the level of bus
service, tended to see their residential location as convenient to bus service, and that they
intended to live close to a bus stop for their next move, compared with the other groups.
The motivational group, which had a motivational leaflet added to their cognitively
focused materials, was also more likely to consider that their residential location convenient for bus use.
Residential choice
The last lines of Tables 3 and 4 show the mean, standard deviation, and the results of thet tests of calculated time/distance from home to the nearest bus stop for each group. The
calculated time/distance for the motivational group was significantly small compared withthat for the control group.
Table 5 shows the frequency of living in an area within/outside 3 min from a bus stopfor each group, and the results of v2 tests. Figure 4 shows the percentage of students living
within a 3-min walk from the bus stop. The cognitive group (32.4 %) was twice as likely as
the control group (13.5 %) to live within a 3-min walk to a bus stop, a significant difference, and the motivational group (45.0 %) was three times more likely than the control
group. The cognitive group tended to live close to a bus stop, even without the motivational
material.
Ownership of the annual commuter pass
The last two sections of Table 5 show the frequency of ownership of an annual bus
commuter pass (for April and November 2008) and the results of the v2 test divided byliving within a 3-min walk. There was no significant difference of ownership in April 2008;
however in November 2008, ownership in the motivational group (66.7 %) was twice thatin the control group (31.3 %) (Fig. 5).
Frequency of bus use
Table 6 shows the mean and standard deviation of bus use frequency for each of theexperimental groups. Table 7 lists the results of the one-tailed t test of paired comparisonsof the groups. Figure 6 shows the frequency of bus use per week (for April and Novemberof 2008) for each group.
Tables 6 and 7 indicate that there was no significant difference in bus use for April
2008; however, in November 2008, the frequency of bus use from home for the cognitiveand motivational groups was significantly high in comparison to the control group. The
frequency of use for the cognitive group tended to be high compared with that of thecommon group. Furthermore, the frequency of bus use from the university tended to behigh in the motivational group in comparison to the control group. The higher use in the
motivational group can be attributed to the motivational leaflet, which included messages

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85

Table 5 Frequency of living within/outside a 3-min area from a bus stop for each group, owning an annual
bus commuter pass (April and November 2008), and v2 test results
Control
Living within
an area
3 min froma bus stopOut

WithinOwnership ofbus annual
commuterpass (April
2008)

Out

WithinOwnership ofbus annual
commuterpass(November
2008)

Out

WithinCommonCognitive

Motivational

v2

DoF

p

8.34

3

0.040**

2.47

3

0.481

7.16

3

0.067*

Frequency

32

15

23

11

Expected
frequency

27.5

13.4

25.3

14.9

%

86.5 %

83.3 %

67.6 %

55.0 %

Frequency

5

3

11

9

Expected
frequency

9.5

4.6

8.7

5.1

%

13.5 %

16.7 %

32.4 %

45.0 %

Frequency

23

14

20

11

Expected
frequency

23.1

11.2

21.2

12.5

%

62.2 %

77.8 %

58.8 %

55.0 %

Frequency

14

4

14

9

Expected
frequency

13.9

6.8

12.8

7.5

%

37.8 %

22.2 %

41.2 %

45.0 %

Frequency

11

18

13

3

Expected
frequency

10.4

14.3

14.3

5.9

%

68.8 %

81.8 %

59.1 %

33.3 %

Frequency

5

4

9

6

Expected
frequency

5.6

7.7

7.7

3.1

%

31.3 %

18.2 %

40.9 %

66.7 %

0%

20%

40%

DoF degree of freedom, p significance probability* 0.05 \ p \ 0.1; ** p \ 0.05

Fig. 4 Percentage living within
an area 3-min walking distancefrom a bus stop

60%

Control (n=37)

13.5%

86.5%

Common Info.
(n=18)

16.7%

83.3%

Cognitive Info.
(n=34)
Motivational Info.
(n=20)

32.4%

80%

100%

67.6%

45.0%
55.0%

recommending bus use from the university for various objectives such as job hunting orcommuting on a wet day.
These results indicate that the participant’s travel behaviour was not stabilized initiallyafter they moved. Instead, achieving stability in bus use frequency required some time. The
persuasive PTOR communication program conducted in this study appeared to influence
the students’ choices, as indicated by the results from the motivational group.

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Transportation (2014) 41:75–89
0%20%

Control (n=37)
April 2008

40%

60%

37.8%
22.2%

Common Info. (n=18)

80%

100%

62.2%
77.8%

Cognitive Info. (n=34)

41.2%

58.8%

Motivational Info. (n=20)

45.0%

55.0%

November 2008

Owner,
31.3%

Control (n=16)

68.8%

18.2%

Common Info. (n=23)

81.8%

40.9%

Cognitive Info. (n=24)

59.1%

66.7%

Motivational Info. (n=9)

33.3%

Fig. 5 Percentage of ownership of a new annual commuter pass in April and November of 2008
Table 6 Mean and standard deviation of bus use frequency for each experimental group
ControlCommon info

Cognitive info.

Motivational
info.

N

M

SD

N

M

SD

N

M

SD

N

M

SD

Frequency of bus use per week
(April 2008)

37

0.57

1.48

18

0.94

1.51

34

0.74

1.19

20

0.90

1.45

Frequency of bus use fromhome per month (November
2008)

16

0.44

1.09

22

0.91

3.01

22

2.45

3.83

9

2.00

1.94

Frequency of bus use from theuniversity per month(November 2008)

16

0.19

0.54

22

0.27

0.94

22

0.45

1.18

9

0.89

1.76

N sample size, M mean, SD standard deviation
Table 7 Results of one-tailed t-test of paired comparisons for each group
Commonvs.
motivationalt-0.815

0.549

0.092

-0.453-2.042**-2.598**-1.490*-1.0010.337-0.838-1.491*-0.565-1.275-0.802Controlvs.
cognitivettFrequency of bus use per
week (April 2008)-0.879-0.523Frequency of bus use
from home per month(November 2008)-0.597Frequency of bus use
from the university permonth (November
2008)-0.326

t: t value* 0.05 \ p \ 0.1; ** p \ 0.05

123

Cognitive
vs.
motivationaltCommonvs.
cognitivetControl vs.
motivational

Controlvs.
commontTransportation (2014) 41:75–89

87

April 2008

0.00

0.50

1.00

0.94

Common Info. (n=18)
0.74

Cognitive Info. (n=34)
Motivational Info. (n=20)

November 2008 November 2008
from the university
from home

1.50

0.57

Control (n=37)

0.90
0.26

Control (n=16)

0.53

Common Info. (n=22)

1.43

Cognitive Info. (n=22)
Motivational Info. (n=9)

1.17Control (n=16)

0.11

Common Info. (n=22)

0.16

Cognitive Info. (n=22)
Motivational Info. (n=9)

0.27
0.52

Fig. 6 Frequency of bus use per week (for April and November of 2008) for each group

Conclusion
In this study, we conducted a persuasive communication program to induce PTOR choiceusing both cognitive and motivational emphasis methods. We then implemented an experiment that targeted freshmen students at the University of Tsukuba to study their decisions
regarding residency and the availability of bus service close to their residence location.
The results indicate that providing information about the level of bus service for every
apartment complex can induce PTOR choice. The ratio of PTOR choice for the cognitive
group was twice as high as that of the control group. The persuasive message to induce
PTOR choice in the motivational group also contributed to an increase in PTOR choice.
These results imply that simple intervention, like the inclusion of information about thelevel of public transportation availability for each residence, can effectively induce PTOR
choice. Additionally, ownership of an annual commuter pass for the motivational group
was double that of the control group. Furthermore, frequency of bus use from home andfrom the university was significantly higher in the cognitive and motivational groups thanin control group. The cost of these interventions was low, and thus the PTOR choice
approach could be implemented at any university, workplace, or housing agency, leading
to less car use.
The effect of the program developed in this study depends on the balance of supply anddemand for apartments in the target area. From the point of view of free competition, if
PTOR-choice became more generalized for the population as a whole, people may prefer
the convenience of apartment living close to public transportation. This would cause therental prices in areas near transportation to increase. For example, in a metropolitan area
like Tokyo, apartments close to public transportation often command higher rents. In thesecities, it can be said that the supply and demand are balanced.
Nevertheless, if the program we suggest is widely implemented as a practical policy,
people will change their attitudes and behaviours towards PTOR choices. Then, urban
developers in a local region might start developing areas in line with attitudes towards
PTOR choices. For example, public transportation-oriented urban development mightoccur over the long run in the area. Furthermore, public acceptance of regulatory policies

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to promote compact cities might be increased through attitude changes towards PTOR
choices. To realize a compact city, it would be necessary to combine the soft communication measures studied in our research and regulatory policy, such as zoning restrictions.
The PTOR choice approach proposed by this research should be effective for a variety ofdifferent scenarios and areas.

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Author Biographies
Ayako Taniguchi is Associate Professor of Risk Engineering at University of Tsukuba, Japan. Her current
research objective is to apply psychological strategies to manage social dilemmas concerning urban andtransportation policy through inducing people’s attitude and behavior modification. Her research interests
include promotion of public transport, subjective well-being while traveling, and risk communication.
Satoshi Fujii is Professor of Civil Engineering at Kyoto University, Japan. His current research objective is
to apply social psychology to transport policy making, and research interests include travel behavior
analyses, behavioral decision making, personal judgment and decision making in social dilemmas, attitude
toward public policies.
Tomohide Azami is engineer of East Japan Railway Company, Japan. He graduated from University ofTsukuba at 2009, and now he is involved in reestablishment of railway network damaged by the Great East
Japan Earthquake, 2011.
Haruo Ishida is Professor of Social Systems Engineering at University of Tsukuba, Japan. His research
objective is transport planning and urban planning, and research interests include transportation planningunder environmental constraints, and development of transportation performance indicator system.

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