Journal of Natural Disaster Science, Volume 37，Number 2，2016，pp35-47

A Comparison of the Reasons for Evacuation Behavior during Floods–Contrastive Effects of Disaster Consciousness –Yasushi OIKAWA1, Keerati SRIPRAMAI2, Toshitaka KATADA3, and Yusuke ISHII4
1

Associate Professor, Department of Civil and Environmental Engineering,
Faculty of Science and Engineering, Toyo University
2
Lecturer, Environmental Engineering and Disaster Management Program,
School of Interdisciplinary Studies, Mahidol University, Kanchanaburi Campus
3
Professor, Department of Civil and Environmental Engineering,
Graduate School of Science and Technology, Gunma University
4
Graduate Student, Course of Civil and Environmental Engineering,
Graduate School of Science and Engineering, Toyo University(Received: Nov. 15, 2015 Accepted: Sept. 16, 2016 )ABSTRACTThe state of so-called disaster consciousness has generally been seen as one of the typical determinantsof evacuation behavior during floods. However, the preconception that a high level of disaster consciousness ought to lead to a high rate of evacuation, and that a low rate of evacuation is because of a low levelof disaster consciousness, is overly simplistic.
In this paper, a counterexample from Thailand is given in which a high level of disaster consciousness
leads to a low rate of evacuation, and this is then contrasted with a case from Japan in which a high levelof consciousness leads to a high rate of evacuation. Using a questionnaire survey, unified data werecollected. The investigation found that the respondents in Thailand tended to remain in their own homesduring a flood disaster because of their high disaster consciousness. Consequently, in such a region, disasterrisk management education that aims to raise disaster consciousness should be implemented after social
unrest is quelled.
Keywords: evacuation, fear of human damage, fear of material damage, fear of theft

1. INTRODUCTION
The state of so-called disaster consciousness has generally been seen as a major determinant of resident
evacuation behavior when there is some time before the actual disaster event occurs, such as with riverfloods. Japan, one of the study areas in this paper, is no exception. An examination of Japanese reports
found that disaster consciousness was identified as a key determinant of evacuation success (e.g., Kawata
et al., 1999; Miyase et al., 2009; Matsumoto et al., 2010; Saiga et al., 2011; Yoshida et al., 2011; Sugimoto
et al., 2012; Tatsukawa et al., 2012).
While disaster consciousness has been an important consideration in evacuation procedures in bothThailand and Japan, low resident evacuation rates have often been incorrectly and simplistically ascribedto a lower level of disaster consciousness.
The oversimplification of this complex motivation is the primary focus of the research in this paper.

35

Y.OIKAWA, K.SRIPRAMAI, T.KATADA, Y.ISHIIIn other words, the central aim of this paper is to elaborate two cases of disaster consciousness: the firstwhere a high level of disaster consciousness leads to a low evacuation rate (hereafter referred to as the“Negative Correlation Case: NCC”), and the second where a high level of disaster consciousness leads toa high evacuation rate (hereafter referred to as the “Positive Correlation Case: PCC”).
In addition to disaster consciousness, previous research has found other determinant factors forevacuation preparedness. Nakamura (2008) argued that it was useful to hypothesize an “overflow model,”in which residents decide on and carry out evacuation if their “disaster consciousness” and other “social
factors” exceed a specified threshold value. Sorensen (2000) cited “fear of looting” as one of 32 major
determinant factors for evacuation and empirically hypothesized that this contributes to reducing evacuation
rates. However, the reduced evacuation rates observed in these papers were indirect effects that were
externally observed.
This paper takes the view that the choice to “evacuate/not to evacuate” is a result of “actively
choosing/not choosing to stay at home.” Based on this view, in this study, we discuss the differences
between the two contrasting cases (“NCC” and “PCC”) using quantitative unified data.

2. FRAMEWORK OF THIS ANALYSISOur hypothesis regarding the relationships between several key concepts and terms is explained in the following sections. These relationships are also summarized in Fig. 1.
[PCC] or [NCC]

So-called

Disaster Consciousness[HD]
Human Damage(4)

Evacuation
(3)

[MD]
Material Damage(2)

External
Observation
Result(5)

Evacuate or not

Stay at Home

(1)

[FT]
Fear of Theft

Fig. 1 Relationships between several key concepts and terms

2.1. Subject areas
There are many examples that could be used for this discussion of contrasting cases. However, as it is
impossible to cover all cases, with reference to the reports discussed above, in this paper, we take Japan as
an example of a “PCC” in which a high level of disaster consciousness leads to a high evacuation rate.
For an “NCC,” in which a high level of disaster consciousness leads to a low evacuation rate, we referto the reports by Henry et al. (2013; 2015) that found “a public fear of the risk of theft” (hereafter referred
to as “Fear of Theft: FT”) to be one of the background factors for the low evacuation rate during the 2011
Thai flood. “FT” could be seen to be related to a motive related to mitigating material damage (hereafterreferred to as “MD”) as opposed to a motive related to mitigating human damage (hereafter referred to as“HD”) (Fig. 1(1)). This motive to mitigate “MD” could be interpreted as an intention to stay at home (Fig.
1(2)), but also as an obstruction to evacuation (cf. Fig. 1(3)). Therefore, Thailand is considered to be an
example of the “NCC” in this comparative study.

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Journal of Natural Disaster Science, Volume 37，Number 2，2016，pp35-47

2.2. The meaning of “not to evacuate” in the analysis
When facing a flood disaster, being certain that the disaster is going to occur corresponds to being consciousof the possibility of human and/or material damage. This psychological consciousness of the high possibility of human or material damage is often called a “high level of disaster consciousness.” Therefore, fromthe viewpoint of mitigating “HD,” “evacuation” is an effective measure (Fig. 1(4)).[1] On the other hand,from the viewpoint of mitigating “MD,” “staying at home” is an effective measure to protect possessions.
An important point to emphasize here is that “staying at home” inevitably corresponds to “no evacuation”(Fig. 1(3)).
There are three possible reasons for “no evacuation.” First, residents actively choose “not to evacuate,”
although this situation may be rare. Second, residents “withhold a decision”; in other words, they are unable
to choose “evacuation” because they do not have sufficient information to decide whether the disaster isserious enough for evacuation but they are extremely fearful and search for information to alleviate theirfear. The above two possible reasons for “no evacuation” are common to most disaster scenarios, including
the two cases in this study. Third, residents actively choose to “stay at home.” To explain the differences
between the “no evacuation” causes in our two subject areas, we refer to a third possible cause as it ispresumed that a structure in which “FT” reinforces the intention to reduce “MD” is more characteristic ofThailand than of Japan.
Accordingly, it is not enough to only observe “evacuation/no evacuation” externally (Fig. 1(5)). To
fully understand the causes of resident behavior, an analytical framework is essential for focusing onwhether the action “to evacuate/not to evacuate” is a result of “actively choosing to stay at home.”

2.3. Outline of the survey
The same questionnaire was conducted in Japan and Thailand. A summary of the survey is shown in Table
1. Based on a monitor list from an Internet research company (Rakuten Research), it was hoped that the sex
and age distribution of the respondents would closely conform to the actual populations in the respective
regions. However, as there were some shortages in a few age groups, 1,000 respondents from Japan and
400 respondents from the Bangkok region were selected based on the basic attributes shown in Table 2.
Therefore, it is important to remember when interpreting the results for the aggregate analysis that the
distribution of the respondents was based on an Internet survey.[2]Table 1 Summary of the questionnaire survey design
Japan
Date
Sample Numbers
Area
Sampling Method
Answering Method

ThailandDec.18, 2013 - Dec.25, 2013
Jan. 28, 2014 - Feb. 5, 2014
1000
400
All regions
BangkokDistribute the sex and ages of the respondents to conform as closely as possible to the actual populationsin the respective regions based on a monitor list from an Internet research company (Rakuten Research).
The respondents input the answers to each question on the web page to answer the questions.

37

Y.OIKAWA, K.SRIPRAMAI, T.KATADA, Y.ISHII
Table 2 Basic respondent attributes

Japan
Male
Femaleunder 20
20s
Age
30s
40s
over 50
under 200
Japan
under 500
[mill.YEN]
over 500
AnnualIncomeunder 5Thaiunder 15
[mill.THB]
over 15
MarriedMarital status
Unmarried0
1
2
3
4
No. of persons
living with the5
respondent
678
9over 10
Owned
Type of house
RentedElseCompany employee
Public servant
Self-employedOccupation Housewife, househusband
Student
No occupation
Other
Sex

499
501
71
151
190
201
387
330
314
198
------602
398
147
239
237
226
97
39
13
0
1
1
0
705
279
16
371
48
81
186
90
96
128

(49.9%)(50.1%)(7.1%)(15.1%)(19.0%)(20.1%)(38.7%)(39.2%)(37.3%)(23.5%)------(60.2%)(39.8%)(14.7%)(23.9%)(23.7%)(22.6%)(9.7%)(3.9%)(1.3%)(0.0%)(0.1%)(0.1%)(0.0%)(70.5%)(27.9%)(1.6%)(37.1%)(4.8%)(8.1%)(18.6%)(9.0%)(9.6%)(12.8%)

Thailand
199
201
15
120
99
122
44
------117
91
167
191
209
18
18
72
96
91
52
21
17
7
4
4
290
73
37
193
32
67
17
60
4
27

(49.8%)(50.3%)(3.8%)(30.0%)(24.8%)(30.5%)(11.0%)------(31.2%)(24.3%)(44.5%)(47.8%)(52.3%)(4.5%)(4.5%)(18.0%)(24.0%)(22.8%)(13.0%)(5.3%)(4.3%)(1.8%)(1.0%)(1.0%)(72.5%)(18.3%)(9.3%)(48.3%)(8.0%)(16.8%)(4.3%)(15.0%)(1.0%)(6.8%)The remainder of this paper is organized as follows. Section 3 examines the behavior of the respondents during past floods, and Section 4 identifies the factors that motivate people to stay at home during
floods to clarify possible future behavior. Section 5 gives our conclusions and possible future research foci.

3. EVACUATION BEHAVIOR AND AWARENESS DURING PAST DISASTERS
3.1. Inundation damage
To clarify the behavior and awareness of the Thai respondents regarding past disaster experiences, therespondents were asked about their experiences during the 2011 flood. From July to November 2011, heavy
rain fell on the Indochina Peninsula, resulting in disastrous flooding over an extremely wide area centeredon the drainage basin of the Chao Phraya River. In the first 10 days of November, there was significant
inundation damage in the densely populated capital, Bangkok. There were 813 fatalities, about 80% ofwhom drowned, while the remaining 20% died from related causes, such as electrocution (e.g., Komori etal., 2012; CRED, 2015). In the Japanese survey, on the other hand, it was possible to hypothesize about
floods and other types of disasters, so the respondents were asked to describe their most serious disaster
experiences.

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Journal of Natural Disaster Science, Volume 37，Number 2，2016，pp35-47

There were 44 respondents from Japan and 330 from Thailand who could remember their flood evacuation experience. Respondents with vague memories were excluded. As shown in Table 3, only 64 respondents from Japan stated that their most serious disaster experience was a flood. Because the number ofpeople with flood experience in the Japanese survey was smaller than that in the Thai survey, significant
differences in the statistical tests were also recorded for the following aggregation results.
Table 3 Respondents’ past disaster experiences
Disaster experience questions in the survey
Total sample
Type of disaster experience

Evacuation
Evacuated
No evacuation
Don’t remember

Experienced (flooding)Japan

Most serious disaster experiences

19
25
20
199
737
58
272
2
68

Experienced (else)
No experience
ThailandEvacuated
No evacuation
Don’t remember

Experienced

The 2011 flood

No experience

1000

400

3.2. Fear of “HM” and “MD”
Figure 2 shows the responses regarding the occurrence/non-occurrence of inundation damage during flood
experiences from both surveys. Seventy-five percent of the respondents in both surveys stated that someinundation damage occurred.
0%

20%

Japan

29.5

Thai

28.8

40%

60%

80%

40.9

29.5

100%
n=44

p=0.48Inundation damage
during the flood experiences

33.6

37.6

n=330

No inundation
Inundated（living space was not inundated）
Inundated（living space was also inundated）

n: Number of samples
p: p-value for Mann–Whitney U test

Fig. 2 Inundation damage during flood experiences
Figure 3 shows the responses from each survey regarding evacuation behavior during floods. There
was a significant difference between the two surveys, with the Thai respondents showing a stronger tendency to refrain from evacuation.
0%

p=0.00***

20%

Japan
Thai

40%

60%

43.2

80%
56.8

17.6

82.4

Evacuated

100%
n=44
n=330

No evacuation

n: Number of samples
p: p-value for Mann–Whitney U test

Fig. 3 Evacuation behavior during flood experiences

39

Y.OIKAWA, K.SRIPRAMAI, T.KATADA, Y.ISHII

If, as reported, the inundation damage in both countries was about the same and the degree of fear
regarding “HD” (Fig. 4[a]) was also about the same, it is difficult to conclude that the Thai respondents had
extremely low disaster consciousness, even though the evacuation rate was low. Further, there was a wide
gap between the degrees of fear regarding “MD” (Fig. 4[b]) between the two samples. This result indicatedthat it was difficult to directly observe the “evacuation” responses from the Thai respondents who stayedin their homes to reduce the “MD” they strongly feared.
0%

20%

40%

60%

80%

100%

[a] “HD”: Fear of human damage during the disaster experience
Japan

34.1

Thai

33.9

18.2

27.3

11.4

9.1 n=44p=0.35
11.5

25.8

10.0

18.8

n=330

[b] “MD”: Fear of material damage during the disaster experience
p=0.00***

Japan

31.8

Thai 8.8 3.9

13.6
33.0

Nothing at all 

6.8 9.1 n=44

38.6
19.4

34.8

n=330

 Felt strongly

n: Number of samples
p: p-value for Mann–Whitney U test

Fig. 4 Fears during flood experiences

3.3. Reasons for not evacuating
Figures 5 [a] to [j] show the reasons given for not evacuating by respondents who did not evacuate during
the flood. In both surveys, using a five-level answer format, the respondents were asked to define the degree
to which the reason related to their motives. There were similar response distributions in both surveys foralmost every item. However, two items had ratings of only 20% and 30% in Japan compared to 70% in
Thailand: “[e] I wanted to protect my own house and household possessions from material damage” and“[f] I thought that if I left my house vacant for a long period of time, the danger of theft would increase.”
Based on the above results, it can be concluded that the anxiety regarding “MD” and “FT” in the Thai
respondents was stronger than in the Japanese respondents. This result indicates that the Thai respondents
neither ignored evacuation orders nor dismissed the impact of the disaster, but that they deliberately choseto stay at home because their fear of “MD” and “FT” was greater than their fear of human damage.

40

Journal of Natural Disaster Science, Volume 37，Number 2，2016，pp35-47

0%

20%

40%

60%

80%

100%

[a] My house had not been affected by disaster.
p=0.27

Japan

16.0

Thai

9.9

8.8

11.8

16.0

12.0

20.0

31.6

36.0

n=25

37.9

n=272

[b] I had not been advised to evacuate by the administration.
Japan
Thai

8.0

28.0

20.2

19.1

24.0

p=0.2914.7

8.0 n=25

32.0

n=272

25.7

20.2

[c] I thought that I could lead a ordinary life at own house.
p=0.08*Japan 8.0 4.0 16.0
Thai 2.94.8 6.3

n=25

40.0

32.0

n=272

55.1

30.9

[d] I could purchase the necessities of life as usual.

p=0.38Japan 12.0
Thai 8.5

14.7

34.6

10.3

n=25

24.0

36.0

12.0

16.0

n=272

32.0

[e] I wanted to protect my own house and household possessions
from material damage
16.0
44.0
16.0
Japan 12.0
p=0.00***Thai 8.8 6.6 12.1
49.3
23.2

12.0

n=25
n=272

[f] I thought that if I left my house vacant for a long period of time,the danger of theft would increase
12.0 8.0 n=25
24.0
36.0
20.0
Japan
p=0.00***n=272
Thai 9.6 7.7 9.2
52.9
20.6
[g] I thought that remaining at home would be more comfortable and convenient
than evacuation.
n=25
24.0
48.0
Japan 4.0 8.0 16.0
p=0.33n=272
Thai 7.7 5.9 14.0
40.4
32.0
[h] I thought that evacuation would be more dangerous than remaining at home.

p=0.85

Japan 12.0

12.0

Thai 10.7

15.4

16.0

48.0

12.0

n=272

23.9

28.3

21.7

n=25

[i] I lived with a handicapped person who requires assistance in evacuation.
Japan
p=0.26

Thai

16.0

44.0
15.1

35.3

14.3

16.0

16.0
22.4

8.0 n=25
12.9

n=272

[j] Most people who was related to you, acquaintance or in the neighborhood,
did not evacuate.
n=25
16.0
36.0
16.0
20.0
Japan 12.0
p=0.42
Thai
n=272
27.9
29.4
17.6
10.3 14.7
No, not at all  Yes, to a high degree

n: Number of samples
p: p-value for Mann–Whitney U test

Fig. 5 Reasons for not evacuating

4. FACTORS BEHIND STAYING AT HOME DURING A FLOOD DISASTER
4.1. Analytical framework
As stated above, it was assumed that in addition to the fear of “HD” and the fear of “MD” in terms ofresident behavior during a flood, in Thailand in particular, factors related to “FT” were also strong
determinants. To verify this finding, it was not enough to set “evacuated/did not evacuate” as the dependent41

Y.OIKAWA, K.SRIPRAMAI, T.KATADA, Y.ISHII
variable as it was also vital to analyze whether they had a “positive intention to stay at home.”
An analysis of “virtual situations with assumptions concerning flood behavior” (Table 4[2]) was
conducted to clarify the respondents’ behavioral inclinations (the inclination to stay at home). The respondents were asked to indicate their intended behavior in nine situations that had been developed by combining
the three levels in Table 4[2](a) regarding the possibility of “MD” with the three levels in Table 4[2](b)regarding the possibility of “HD.”
Table 4 Dummy variables as independent variables
Dummy variables
Japan
Thailand
Low
Mid
High
High
None
None
Fairly low
Extremely highNone
Fairly low
Extremely highSubject area(a) Annual income[1] Individual attributes(b) “FT”(a) Possibility of “MD”
[2] Virtual situation assumption(b) Possibility of “HD”

-T
L
M
-F
--P1
P2
-H1
H2

The individual attributes of the respondents (Table 4[1]) were studied as independent variables. Of
these, “(a) annual income” conformed to the categorizations shown in Table 2. Responses regarding “FT”
were obtained, as shown in Fig. 6, which indicated that fear of the future, rather than fear during past flood
experiences, was of greater concern. A stronger “FT” was found among the Thai than among the Japanese
respondents.
0%

p=0.00***

20%
31.6

Japan
Thai

13.5

40%
13.9

7.5 8.8

60%
18.1
37.8

80%
19.6

100%
16.8

32.5

n=469
n=400

Fear of theft in the confusion of a disaster during evacuation (“FT”)
No, not at all  Yes, to a high degree

n: Number of samples
p: p-value for Mann–Whitney U test

Fig. 6 Fear of theft during evacuation (“FT”)
Logistic regression analyses were conducted to verify the extent to which the independent variables
shown in Table 4 acted as determinants of a respondent’s “inclination to stay at home” under the ninesituations in Table 4[2].
There were 469 people in the Japanese sample, excluding those who had homes in locations andgeographical conditions unrelated to the flood. As 869 responses were gathered for all nine situations, thelogistic regression analysis data were expected to be 7,821 (869 times 9). However, after rejecting responses
that failed to indicate annual income, 6,894 items of data were used in the analysis.

4.2. Regression analysis results
The independent variables were represented by dummy variables according to the patterns shown in Table
4. In the situational assumptions in Table 4[2], the interacting terms in the nine situational patterns werealso considered. To clearly distinguish between the impact of the independent
variables in42

Journal of Natural Disaster Science, Volume 37，Number 2，2016，pp35-47

Thailand and in Japan, terms that interacted with “T” (the dummy variable representing the Thai sample)
were also studied.
The analytical results are shown as Model-0 in Table 5. However, as many insignificant terms were
included, a stepwise variable selection was conducted, the results of which are shown in Model-1. By plotting the sum of the coefficient values for the independent variables in Model-1, the results were interpreted(Fig. 7.) The presentation conditions and the situational assumptions for “MD” are shown on the horizontal
axis, and the situational assumptions concerning “HD” are shown as differently shaped plots. The higher
the plot on the vertical axis, the stronger the intention to stay at home. As can be seen, there was a significant
difference in the tendencies in the Japanese (Fig. 7[1]) and the Thai samples (Fig. 7[2].)Table 5 Results of the logistic regression analyses
Model-0βConst.
T
L
M
L*T
M*T
F
F*T
P1
P2
H1
H2
X P1*H1
P1*H2
P2*H1
P2*H2
P1*T
P2*T
H1*T
H2*T
P1*H1*TP1*H2*TP2*H1*TP2*H2*T(Sig.)

0.427 (0.002)***-0.821 (0.000)***-0.124 (0.199)-0.027 (0.778)
0.353 (0.006)***
0.296 (0.024)**-0.136 (0.089)*
0.758 (0.000)***-0.104 (0.471)-0.781 (0.000)***-0.599 (0.000)***-1.440 (0.000)***-0.155 (0.451)-0.090 (0.690)
0.116 (0.584)
0.351 (0.130)
0.317 (0.128)
0.411 (0.048)**0.544 (0.009)***0.568 (0.009)***-0.069 (0.816)-0.231 (0.459)-0.268 (0.368)-0.113 (0.720)
Sample size=6894
x2=583.768
p=0.000
Hit ratio=0.648

Model-1
β(Sig.)

0.313 (0.000)***-0.675 (0.000)***--- ----- --0.229 (0.007)***0.269 (0.003)***-0.141 (0.078)*
0.762 (0.000)***--- ---0.706 (0.000)***-0.542 (0.000)***-1.366 (0.000)***-0.217 (0.042)**-0.252 (0.052)*--- --0.296 (0.031)**0.189 (0.074)*
0.265 (0.029)**0.433 (0.000)***0.451 (0.000)***--- ----- ----- ----- --Sample size=6894
x2=579.773
p=0.000
Hit ratio=0.648
Backward stepwise (Wald)[Dependent variable]
1:Intend to stay at home under the presented situational assumption, 0: Else43

Y.OIKAWA, K.SRIPRAMAI, T.KATADA, Y.ISHII*The vertical axis shows the sum of the coefficient values of the independent variables adopted by Model-1[1] Japan[2] Thailand (T=1)(b) Annual income: Mid （M=1）(a) Annual income: High(c) Annual income: Low （L=1）

strong
0.5

0.5

0.0

0.0

Intention tostay at home* -0.5

-0.5

-1.0

-1.0

-1.5

-1.5

weak
None

Fairlylow

Extremelyhigh(P1=1)(P2=1)

None

Situation assumptions forthe possibility of “MD”

Fairlylow

Extremelyhigh(P1=1)(P2=1)

Situation assumptions forthe possibility of “MD”

None

Fairlylow

Extremelyhigh(P1=1)(P2=1)

Situation assumptions forthe possibility of “MD”

None

Fairlylow

Extremelyhigh(P1=1)(P2=1)

Situation assumptions forthe possibility of “MD”

Situation assumptions for the possibility of “HD”

[ Legend ]NoneFairly low (H1=1)

Extremely high (H2=1)

None
“FT”
High (F=1)

Fig. 7 Plotting the coefficients for the independent variables adopted by Model-1a) Discussion of the Japanese survey sample
An examination of the Japanese survey sample results confirmed that as the situational assumptions for“MD” increased in severity, the intention to stay at home tended to gradually weaken. However, the greatest
impact was found in the situational assumptions for “HD.” When the possibility of “HD” was assumed tobe “extremely high” or “fairly low,” regardless of the assumed strength of “MD,” the coefficient value was
not positive (i.e., the probability that “staying at home” was chosen did not exceeds 0.5).
The coefficient value exceeded zero only when the situational assumption for “HD” was “none” andthe situational assumption for “MD” was either “none” or “fairly low.” Therefore, in the Japanese sample,
if there was a possibility of “HD,” it is possible that people would quickly evacuate their homes. Similarly,
if people were cognizant of the possibility of severe “MD,” even though there was no possibility of “HD,”there was a high possibility that they would evacuate. Based on these results, they may be anotherbackground factor for the occasionally low evacuation rates during floods in Japan, as there appeared to be
little knowledge regarding the possibility of “HD” or of “MD.” Inversely, if the possibility of “HD or of“MD” can be correctly identified, prompt evacuation behavior would take place. Therefore, the many
Japanese reports on “disaster consciousness” as a determinant of evacuation behavior appear to be premisedon the judgment of the residents. In summary, in can be concluded that the results correspond to the “PCC”
case.
Of the individual attributes in Table 4[1], “FT” was found to weaken the inclination to stay at home,
but the range of its effects was slight compared to the range of the effects caused by “HD” or “MD.” No
significant gap was found for annual income.

44

Journal of Natural Disaster Science, Volume 37，Number 2，2016，pp35-47b) Discussion of the Thai survey sample
In the Thai survey sample, annual income was significant, as shown in Fig. 7[2], from “(a)” to “(c).”First, the overall plot trend in the Thai sample was higher than in the Japanese sample as shown in Fig.
6[1], indicating that the inclination to stay at home was stronger. This tendency was even more conspicuous
for respondents with low income levels, and in particular “(b)” and “(c).”This tendency—the more severe the “HD” situation, the lower the intention to stay at home—was thesame as in the Japanese sample. However, the effect of the differences in the “MD” situational assumptions
was different from the monotonic tendency observed in the Japanese sample. In other words, it was foundthat when the possibility of “HD” was “none,” the inclination to stay at home was stronger if the possibilityof “MD” was “fairly low” than when the possibility of “MD” was “none.” In situations where the possibilityof “HD” was “fairly low” or “extremely high,” there was a gentler slope than that observed in the Japanesesample; however, the inclination to stay at home weakened as cognizance of the possibility of “MD”
increased. Interestingly, in the Thai sample, the effect of “MD” on whether people decided to evacuate was
not only smaller than it was in the Japanese sample, but also statistically significant under some specificconditions for reinforcement of the inclination to a purposeful decision to “stay at home.”
The effect of “FT” knowledge was the reverse of that in the Japanese sample and the range of impact
was greater. In Thailand, being afraid of theft was the major factor behind people’s inclination to stay athome during a flood. It can be hypothesized, therefore, that when people on average or low annual incomesfear theft and the possibility of “HD” is slight (none or fairly low), the inclination to stay at home isextremely strong, meaning they are unlikely to evacuate.
Based on these results, in can be concluded that, unlike Japan, in Thailand, knowledge of the possibility of “HD” and “MD” is not necessarily directly connected to “evacuation,” and that choosing to “stay athome” because of the possibility of “MD” and “FT” results in “no evacuation.” These results correspondto the “NCC,” as discussed earlier.

5. CONCLUSIONSIn this paper, we demonstrated the existence of an “NCC” case, which was contrasted with a “PCC” case.
A questionnaire was conducted using a Japanese sample as an example of a “PCC” and using a Thai sample
as an example of an “NCC.” These results showed that a high level of disaster consciousness does notnecessarily lead to a high rate of evacuation, and that a low rate of evacuation does not necessarily mean alow level of disaster consciousness. Based on the above discussions, we may conclude that these results
support our hypothesis shown in Section 2.
The behavior was considered reasonable as “FT” was found to reinforce the intention to reduce “MD,”
which in turn led to a purposeful decision to “stay at home.” The most important point is that such behavior
should be interpreted as rational, logical, and practical. As found, depending on individuals’ social
condition, a high disaster consciousness could lead to a purposeful and rational decision to “not evacuate.”
These results suggest that in Thailand in particular, consideration should be given to a reduction insocial unrest, such as “FT,” prior to any implementation of the type of disaster risk management education
being aggressively pursued in Japan to raise disaster consciousness. While a reduction in “FT” over a shortperiod may not be easy, it is advisable that efforts be made to achieve this goal. Future countermeasures inThailand such as implementing police patrols or neighborhood watches in flooded areas would assist in
reducing “FT.”In conclusion, countermeasures for smooth evacuation, such as improving evacuation warning
systems, preparing evacuation sites, providing related education, and so forth, can only be effective after areduction in obstructive factors such as “FT.”45

Y.OIKAWA, K.SRIPRAMAI, T.KATADA, Y.ISHIIACKNOWLEDGMENT
This work was supported by JSPS KAKENHI Grant Numbers 19760350, 16H03139.

NOTES:[1] Resident behavior during a flood can be classified into three types: “Evacuation” refers to leaving thehome in advance to avoid direct human damage by the inundation; “Sheltering” refers to staying at theevacuation destination until the inundation recedes; and “Refuge” refers to staying at a safer placebecause of difficulties/damage after the inundation recedes.
Needless to say, the degree of urgency and the determinants fundamentally differ between these threekinds of behaviors. However, “Sheltering” and “Refuge” are related to ensuring survival. Further, tosurvive, it is necessary to avoid human damage. Therefore, from the perspective of mitigating humandamage, this research focused on evacuation behavior. The purpose of evacuation is to avoid direct
human damage from the inundation.
[2] Of the two surveys, the data in Thailand were limited to residents living in the Bangkok area who also
had Internet access. However, if the survey had included residents from the various social classes inregions outside Bangkok, the differences between the results of the Japanese and the Thai samples may
have been more marked. As can be seen in Fig. 7, residents with low socioeconomic status placed priority
on reducing “MD,” so including outlying regions in Thailand would have given us a wider socioeconomic sample. Such a survey, however, would need to be conducted face to face as it would be unrealistic
to conduct either an Internet survey or a paper questionnaire survey because of issues regarding technological access and literacy levels. We wish to continue this study, and see the design of a more comprehensive survey as a future challenge.

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