Psychological Structuring of citizen’s willingness for seismic reinforcement of houses *By Yuta KAWARASAKI・Eri MORITA・Mayu TAKEZAKI・Yoshinori NAKAGAWA・Seigo NASU

ABSTRACTThe Japanese Islands are said to have entered at the seismic activity term from the time of the Kobe earthquake (1995).
And it is said that the big earthquake from Hokkaido to Kyushu occurs in the probability of 90% within 50 years.
When such a big earthquake occurs, collapse of a structure is one of main causes of bringing about serious damage. The
Building Standard Law was improved in the past earthquake, and the building structure which is less than a BuildingStandard Law act has the very high danger of collapse and it is because many victims by an earthquake are also
generated by building collapse. In the damage situation of the southern Hyogo earthquake which occurred in Heisei 7,
the dead (death from pressure and death in the flames) who consider collapse of a residence as a cause actually formed
about 90 percent of the whole, and the most was the existing disqualified structure.
From this, in order to reduce the damage after an earthquake, it is recognized also from this thing that prior hardmeasures, such as antiseismic reinforcement of the existing disqualified structure, are required, and it becomes importantto perform the antiseismic reinforcement of a residence immediately for that purpose.
Now, according to Headquarter of Earthquake Research Promotion, the Tonankai and Nankai earthquakes will be
expected to happen at 80~90% in 50 years at 40~50% in 30 years from now on.
However, as the present condition of Kochi Prefecture, according to a residence and land investigation estimation, therate of the formation of building earthquake-proof within the prefecture is about 60%, and is a level which is much lessthan 75% of the national average.
Moreover, since the support system to the antiseismic reinforcement which a local-goverment supports etc. is not utilized
enough, it can observe that it is low in civic consciousness about the measure against antiseismic reinforcement.
As such a cause, there are dearth of information about earthquake resistant and the labor burden in procedure andantiseismic reinforcement is a big-ticket burden, even if it uses local government support system. It is thought that thesehave been obstacles.In order to overcome this present situation, examination of the prior measure system which reduces
earthquake damage is important.
Antiseismic reinforcement promotion is prevention of not only mitigation of the death toll immediately after disaster but
a road blockade, mitigation of the cost which disposal takes and a labor burden, the increase in the participant in initialsupport in a stricken area etc, and it leads also to mitigation of the expense concerning a makeshift house or housing
reconstruction.
But, since the source of revenue which can be distributed to various measures is limited, it is necessary to specify the
subject which should be tackled immediately for the time being, and to implement a measure efficiently. In thegoverment, it aims at making the rate of antiseismic reinforcement of a building 90% by the Heisei 27 year as astatement of principles, and the measure planning support for attaining this serves as pressing need. Then, it set up on thetheme of antiseismic reinforcement promotion of the existing disqualified structure for the purpose of "improvement in
the rate of antiseismic reinforcement" of the whole country including Kochi Prefecture. And it aims at building theantiseismic reinforcement consciousness model as a policy evaluation tool for supporting the design of policy for it.
1．Introduction
1.1 Background and Aim
After the Hanshin-Awaji Earthquake (1995), Japan
has entered the period of seismic activities. It is said
that the probability of a big earthquake hitting anywherefrom Hokkaido to Kyushu in the next 50 years is 90%.

Moreover, unknown active faults exist all over Japan,
therefore, an earthquake can occur anywhere andanytime.
One of the main reasons why massive damages
occur during big earthquakes is due to the collapse of

buildings. In the past, the Building Standard Law has
been revised every time an earthquake occurs and thereason for this is because there is an extremely highpossibility that buildings that do not meet the standard
may collapse, and victims of earthquake are often
victims due to the collapse of buildings. According to
the data on due to the earthquake that occurred in thesouthern Hyogo prefecture in 1995, approximately 90 %of the deaths (due to fire or crushed to death) were due tothe collapse of houses that did not meet the standard.
It has become widely recognized that in order todecrease the damages of the earthquake it is necessary tocreate policies prior to the earthquake such as antiseismic reinforcement and that is it important to promoteanti-seismic reinforcement of houses.
At present, according to the earthquake investigationby the research headquarters, it is predicted that thepercentage of a Tonankai or Nankai earthquake to occur
in the next 30 years is 40-50% and 80-90% in the next
50 years.
However, when considering the present situation of
Kochi prefecture, according to the estimate by housing
and land survey, the rate of anti-seismic reinforcement inKochi prefecture is around 60%, which is much lower
than the national average of 75%.
Moreover, people have not made practical use of
subsidy for anti-seismic reinforcement supported by the
local government, which indicates that people’s
consciousness toward measures for reinforcement isquite low. Some of the reasons for this include
insufficient
information
towardanti-seismic
reinforcement, the hassle of various procedures, as wellas the amount of costs for reinforcement, since theaverage amount necessary for reinforcement isapproximately 2.6 million yen and even with the subsidy
from the local government approximately 2 million yen
would need to be paid by the owner of the building. In
order to resolve this situation, it is necessary to examinevarious policies through the paradigm shift that predisaster measures are more significant than post-disastermeasures in order to decrease damages from earthquake.
By promoting anti-seismic reinforcement, not only
will it decrease the number of deaths after disasters, butalso prevent road closures and decrease the costs andburden of labor to clean it up, increase the number ofparticipants for initial support at the site of the earthquake
which may be effective in promoting early activities forrestoration, as well as decrease the costs for temporary

housing and reconstruction of houses.
However, it is necessary to implement policies
effectively by specifying themes that are urgent atpresent since financial resources for various measures arelimited. The basic guideline of the government is toraise the rate of anti-seismic reinforcement of buildings
to 90% by the end of 2015, and the support to propose
such measures to accomplish this goal has become anurgent task. This paper considers the theme ofpromoting anti-seismic reinforcement of buildings thatcurrently do not meet the standard and aim to “improve
the rate of anti-seismic reinforcement” in Japan including
Kochi prefecture. Moreover, another objective is toconstruct an anti-seismic reinforcement consciousness
model as a tool to evaluate policy for the support ofpolicy proposal.

*Keywords: Anti-seismic reinforcement, Logic model,
Quantitative model
1.2 Procedure
This study constructed a logic model of the structureof decision-making for not carrying out anti-seismic
reinforcement, by structuralizing the issue of the low rateof anti-seismic reinforcement based on the “survey
concerning the factors obstructing anti-seismic
reinforcement” conducted by the Building ResearchInstitute in 2006. Upon establishing the priority
strategic goal for the study as improving the rate of antiseismic reinforcement, a survey was conducted targetingthe people of Kochi, in order to extract information on
the elements to be included in the logic model. Next,
the relationship model equation of the factors was
defined based on the logic model, and a multiple
regression analysis was conducted from the results
obtained from the survey concerning independent anddependent variables including related elements,
affiliation and environment and finally obtained afunction for the logic model. Lastly, all the model
equations were combined and a function for “executionof anti-seismic reinforcement” was constructed by thelogistic curve.
As a result, we aim at supporting the design to spread
an anti-seismic reinforcement policy in the future.

First, concerning the elements that make up the“name recognition of the necessity”, after excluding
factors such as affiliation and environment the following
two elements, “name recognition of feeling of fear” and“name recognition of the effects” were established, using
the examples of factors of obstruction from the 2006
materials of the Building Research Institute. Here,“feeling of fear” refers to the fear of an earthquake
regardless of the frequency or size and the presumed lossof life and assets due to the occurrence of the earthquake.
“Effect” refers to the effect of the efficiency of thereinforcement obtained from reinforcing the building
against earthquake by anti-seismic reinforcement andmonetary effect obtained from the decrease in fixing
costs after the earthquake against presumed damages
after the earthquake and the increase in property value
due to anti-seismic reinforcement. Here, “affiliation”
refers to gender, age, income, family members, numberof years the building has existed and the structure of thebuilding. Moreover, “environment” refers to thefrequency of earthquake in different regions and whether
the ground is firm or not.
Name recognitionof necessity

Anti-seismic
reinforcement

Pecuniaryvalue

Performanceofreinforcement

post-sale cost

Asset quality

Further details
about
reinforcement

Performance ofstructure

Cost ofreinforcement

Construction
on the spot
visit

go to thegovernment
officeFill the form

Loss ofproperty

On the spot
visit

Procedure

Disbelief in the
traderDisbelief in theadministration

Sense ofmistrust

Labor hour

Procedural
requirements

Asset quality

post-sale cost

Deficientknowledge

Pecuniaryvalue

Performance ofstructure

Further details
about
reinforcement

Loss ofproperty

Construction
method ofreinforcement

Performanceofreinforcement

Loss of life

Earthquake

Loss of life

Money

PhysicalSpiritEffectFeeling of
fear

Earthquake

Obstacle

Construction
method ofreinforcement

Name recognitionof necessity

EffectFeeling offear

2. Structuralization of the problem and the logic
model
Even if many people recognize the importance ofanti-seismic reinforcement, the reinforcement itself will
not be conducted if there are no policies to implement
such measures. In order to promote the spread of antiseismic reinforcement it is necessary to consider policies
to support measures for the people.
Thus, in order to enforce anti-seismic reinforcement, thestudy extracted and classified the factors of obstaclesfrom 2006 documents and materials from the Building
Research Institute concerning the factors of obstructionthat people felt as burden. Some of the examples offactors of obstruction include “I do not think that a big
earthquake will occur where I live”, “I am not sure of theeffects of anti-seismic reinforcement”, “The cost for
reinforcement is expensive”, “I cannot trust theconstruction workers”, “The application procedure forsubsidy is too much of a hassle”. These various factors
were classified to consider the relationship of each factor.
Among them, we excluded factors that relate toaffiliation (gender, age, income, structure, number ofyears that the building existed, etc), and constructed thelogic model as indicated in Fig. 1. It will become
possible to evaluate a policy appropriately and design
policies rationally by constructing such logic model.

6Fig. 1 Logic model
The following two logic model has been constructed:“name recognition of the necessity for reinforcement” as
the main factor to decide whether people carry out antiseismic reinforcement and “the impact of the obstaclethat obstruct people from going through with antiseismic reinforcement (even if they recognize thenecessity of it” (hereinafter obstacles).

Fig. 2 Logic model (name recognition of thenecessity)
Figure 2 shows the logic model for the part of “namerecognition of necessity”. The execution of antiseismic reinforcement (=A ) is decided by namerecognition of necessity (=N ) and the size of obstacles(=O ) in executing the reinforcement.
“Namerecognition of necessity” is decided by the feeling of fear

(=F ) toward the earthquake and the size of the effect(=E ) by conducting anti-seismic reinforcement. We
shall call the lower factors of feeling of fear as “namerecognition of the fear of earthquake” (a), “namerecognition of the fear of losing life” (b), “namerecognition of the fear of losing one’s asset” (c), and thelower factors of “feeling of effect” as “effect of theefficiency of reinforcement” (d), and “monetary factors”(e).
Next, the elements that make up “obstacles” consistof “spirit or mental”, “physical” and “monetary or
financial” obstacles. Here, “spirit or mental” obstacles
refer to the resistance to antiseimsic reinforcement
technology that which results from the guard against
fraudulent construction workers and lack of knowledge.
“Physical” obstacles refer to the physical burden such as
the application procedure and keeping an eye on theconstruction. Moreover, “monetary” obstacles refer toobstacles concerning the burden of costs needed for antiseismic reinforcement and diagnostic check.

Obstacle

Money

PhysicalSpiritOn the spot
visit

Procedure

Sense ofmistrust

Deficientknowledge

Cost ofreinforcement

Construction
on the spot
visit

go to thegovernment
officeFill the form

Disbelief in theadministration

Disbelief in the
traderLabor hour

Procedural
requirements

Fig. 3 Logic model (obstacles)
Fig. 3 shows the logic model for the part of“obstacles”. “Obstacles” are decided by the spirit (=Sp)
and physical (=Ph) obstacles, and the amount ofmonetary (=Mo) obstacles. The lower factors of spirit
or mental obstacles are “lack of knowledge concerning
construction and procedure” (f), “distrust toward
construction workers and administration” (g), and thelower factors of physical obstacles are “procedure suchas filling out application forms” (h) and “watching overthe construction” (i).

3. Survey
3.1 Objective of the survey
It was necessary to conduct a survey to verify thejustification of the logic model constructed in Fig. 1 as
well as quantify the strength and degree of therelationship among the various factors within the model.
In doing so, we composed a survey to investigate theinfluence of the name recognition of the necessity of“feeling of fear” and “effect” and “spirit or mental”,“physical”, and “monetary obstacles and what methods
would be effective in developing the policies in the
future.
Moreover, the aim of the survey was to consider
what influence affiliation has on the consciousness
toward anti-seismic reinforcement and changes inpeople’s consciousness, by providing information on
predicted damages of the earthquake that may occur inthe future and policies concerning anti-seismic
reinforcement which correspond to name recognition ofnecessity such as feeling of fear and effect and spirit ormental, physical and monetary obstacles, which makes it
is possible to grasp the changes in the response results
before and after providing the information.
3.2 Basic guideline of the survey
The response comprised of the following 5 levelevaluation “extremely”, “very strongly”, “some what”,“no so much”, “not at all” for the question “do you
distrust the administration and construction workers
when going through with anti-seismic reinforcement?”
Moreover, in order to measure the changes inindividual’s consciousness by providing information on
policies concerning anti-seismic reinforcement
Question: Do you think that anti-seismic reinforcement
is required for your house?
Information Service

Anti-seismichouse

It is heard anew.

Not anti-seismichouse

Fig.4 Survey information (examples)

Q: Do you think that anti-seismic reinforcement is required for
Before information

After providing the information, the same question
was asked again in the following question by stating “wewould like to ask you again”.
The following
information was also provided in the survey: “thechances of Nankai earthquake occurring in Kochi
and predicted damages” in order to raise awareness ofthe fear against earthquake; “efficiency that can be
expected by carrying out anti-seismic reinforcement
and exemption for fixed property tax” in order toprovide information on efficiency and monetary effects;“flow chart of what is done for diagnostic check andreinforcement” to provide information to resolve thelack of knowledge; referrals such as “projects
conducted
andanti-seismic
reinforcement
information desk provided by the administration toprevent troubles such as fraudulent construction
workers” to provide information that resolves the
distrust and anxiety; flow chart that illustrates the“procedure for anti-seismic reinforcement and thenecessity to watch over the construction work”; andinformation on monetary support provided by the local
government such as “subsidy and investment policies”.
3.3 Outline of conducting the surveya) Subject of the survey
The subject of this survey was people who live in Kochi
prefecture and own a house.
This survey was conducted in cooperation with people
from the Kochi University of Technology and Citizen’s
Alliance for the Promotion of Community Planning.
b) Response rate
Citizen’s Alliance for the Promotion of Community
Planning: distributed 70, responses 39
Kochi University of Technology: distributed 70,
responses 39
Total: distributed 140, responses 68

After information
4%

16%

12%

24%

28%

9%

24%

extremely
very strongly
somewhat
not so much
not at all

25%

31%

27%

Fig. 5 Response results
As indicated in graph in Fig. 5, there was an improvement from 33% to 59% in people who think a
nti-seismic reinforcement is necessary among those
who responded “extremely” and “very strongly” regarding the name recognition of necessity. We are abl
e to see that the degree of recognition for the necess
ity of reinforcement improved by providing the necessary information. In other words, this implies that i
t is necessary to promote PR and education in order
to raise awareness for the necessity of anti-seismic r
einforcement. As illustrated in Fig. 6 and Fig. 7, w
e can expect the same positive effects in the stage b
elow the awareness of the necessity by providing ne
cessary information.

Feeling of fear (before information)
Feeling of fear (after information)
Loss of assets (before information)
Loss of assets (after information)
Loss of life (before information)
Loss of life (after information)
Earthquake (before information)
Earthquake (after information)

0%

10%

20%

extremely

30%

40%

very strongly

50%

60%

somewhat70%

80%

not so much

90%

100%

not at all

Fig. 6 Feeling of fear-response results
Effect (before information)
Effect (after information)
Efficiency of reinforcement (before information)
Efficiency of reinforcement (after information)

3.4 Survey resultsa）Name recognition of necessity
Figure 5 shows the questions and results concerni
ng name recognition of necessity (Q. 7, Q. 22).

Monetary effects (before information)
Monetary effects (after information)

0%

10%

20%

30%

40%

extremely very strongly

50%

60%

70%

80%

90%

100%

somewhat not so much not at all

Fig. 7 Effects- response resultsb）Obstacles
The response results for obstacles are illustrated in Fig.
8 and Fig. 9.

N = α 1 × F + β1 × E + C
α β ＝parameterPhysical(before)…Eq. 1
C=constantPhysical(after)
extremely
very strongly

Procedure(before)

somewhat
Procedure(after)

not so much
not at all

Watching over(brfore)

Table 1. Name recognition of necessity Regressive
analysis results

Watching over(after)

Before information
0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Regression analysis

100%

Fig. 8 Mental obstacles-response results

Coefficient Standard errortMultiple correlation coefficient R 0.72 Intercept

-0.94

0.60

-1.57

Multiple decision R2

0.51 Feelinng of fear

0.30

0.12

2.47

Correction R2
Standard error
Number of observation

0.49 Effect
0.97
51

0.83

0.13

6.44

Af ter information
Regression analysis

Sprit (before)
Sprit (after)
extremely
very strong

Feeling of distrust(before)

somewhat
not so much

Feeling of distrust(after)

Coefficient Standard errortMultiple correlation coefficient R 0.70 Intercept

1.56

0.52

3.03

Multiple decision R2

0.49 Feelinng of fear

-0.005

0.12

-0.05

Correction R2
Standard error
Number of observation

0.46 Effect
0.72
51

0.59

0.09

6.47

not at all
Money (before)
Money (after)
0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Fig. 9 Physical obstacles-response results

Equations 2 and 3 before and after providing
information are possible when substituting the results ofthe multiple regression analysis by equation 1.
｛before providing information｝

N = 0.30 × F + 0.83 × E − 0.94
4. Construction of a quantitative model
4. 1 Method for quantification
In order to construct a quantitative model, a multiple
regression analysis was conducted based on the results ofthe survey on “name recognition of necessity” and“obstacles”. Next, the model for “consciousness
regarding anti-seismic reinforcement” was constructedby combining the obtained results. Moreover, thenecessity of the affiliation that may have influence was
decided by using the t-value. The value used foraffiliation was once again used after numbering them as
1.2.3. in order of those questions (whether one would
like to go through with anti-seismic reinforcement)
which consciousness had increased after providing
information in the survey. Each of the model equation isdefined as follows.
a) Constructing a model for the name recognition ofnecessity
As provided in Fig. 2, the name recognition ofnecessity is composed by feeling of fear and effect. The
model equation is constructed by using multiple
regression analysis and by substituting the result of thesurvey for equation 1. Table 1 shows the result of themultiple regression analysis.

…Eq. 2｛after providing information｝

N = −0.005 × F + 0.59 × E + 1.56

…Eq. 3

Discussion: The judgment of not considering the term F(=feeling of fear) can be justified in equation 3, because
the coefficient of F (=feeling of fear) is at a low of -0.005
and the t-value at -0.05, and the term does not contributeto N (=need recognition of necessity). The following
Table 2 is the result when only E(=effect) expressing N
after providing information by only E(=effect).
Table 2. Result of the multiple regression analysis(only E)
Before providing information, there was support that ourmodel that “name recognition of necessity” could be
explained possibly by the following two “namerecognition of feeling of fear” and name recognition ofeffect” was right.
Moreover, after providing
information, it was identified that the “name recognitionof necessity” only depended on “name recognition ofeffect”. At this time, one of our future works is to how
to explain this fact.
a-1) Conceptualization of the model of feeling of fearAs illustrated in Fig. 2, feeling of fear is composedby earthquake, loss of life, loss of assets and affiliation.
The model equation is constructed by using multiple
regression analysis and by substituting the results of thesurvey for equation 4. Table 3 shows the result of themultiple regression analysis. (At) of equation 4 is the
explanatory variable of the affiliation of those who
responded to the survey. In the case that a sufficientmodel could not be constructed with only “earthquake”,“loss of life”, “loss of assets”, an affiliation is selected
and added as an explanatory variable.

F = α 2 × a + β 2 × b + γ 2 × c + ( At ) + C…Eq. 4ａ＝earthquake ｂ＝loss of life ｃ＝loss of
asset
At= affiliation α β γ ＝parameter

Table 3. Feeling of fear: Result of the multiple regression
analysis
Before Information
Regression analysis
Multiple correlation coefficient R
Multiple decision R2
Correction R2
Standard error
Number of observation

0.76 Intercept0.59 Earthquake
0.53 Loss of life
0.74 Loss of assets
45 gender
structure

Coefficient Standard error t
1.00
0.97 1.03
0.40
0.13 3.17
0.32
0.19 1.68
0.37
0.19 1.94-0.71
0.23 -3.06-0.57
0.20 -2.83

After Information
Regression analysis
Multiple correlation coefficient R
Multiple decision R2
Correction R2
Standard error
Number of observation

0.73 Intercept
0.53 Earthquake
0.49 Loss of life
0.63 Loss of assets
45 Familly

Coefficient Standard error t-0.23
0.81 -0.28
0.24
0.10 2.34-0.05
0.20 -0.25
0.72
0.19 3.84
0.20
0.17 1.14

Equations 5 and 6 before and after providing
information are possible when substituting the results ofthe multiple regression analysis by equation 4.
｛before providing information｝

F = 0.40 × a + 0.32 × b + 0.37 × c − 0.71
…Eq. 5× ε − 0.57 × ω + 1｛after providing information｝

Thus, the affiliation “gender (male=1, female=2)” and“structure (wood=1, RC=2, iron=3) were added. On
the other hand, in equation 6 a sufficient R2 was
obtained from a, b, and c.
Moreover, regarding the contribution rate of thefollowing 3 explanatory variables a, b, and c, which was
assumed at the stage of Fig. 2, each term of a, b, and cshowed a fixed contribution before providing
information, however, we observed that the contribution
rate of b was extremely low after providing information.
Regarding the affiliation of the participants of thesurvey, it was necessary to add “gender” and “structure”
before providing information, however, we were able toobserve that the model assumed in Fig. 2 initially wasvalid after providing information. One of the reasons
why “gender” and “structure” had a negative effectbefore providing information could be that women had
less feeling of fear than men because they overestimatedtheir house.
a-2) Conceptualization of the model for effect
As illustrated in Fig. 2, effect is composed by theefficiency of the reinforcement and monetary effect, andis analyzed by adding the affiliation which is assumed tohave influence. The model equation is constructed bysubstituting the result of the survey for equation 7 andusing multiple regression analysis. Table 4 shows theresult of the multiple regression analysis. (At) inequation 7 is the explanatory variable concerning theaffiliation of those who responded to the survey. In acase where a sufficient model could not be constructedwith “efficiency of reinforcement” and “monetary
effect”, then an affiliation is selected and added as an
explanatory variable.

E = α 3 × d + β 3 × e × ( At ) + C…Eq. 7ｄ＝efficiency of reinforcement
effect、
α β ＝parameter

ｅ＝monetary

F = 0.25 × a − 0.03 × b + 0.68 × c + 0.08 …Eq. 6
ε=gender ω=structure
Discussion: In equation 5, initially a multiple regressionof F (=feeling of fear) which was only explained by a(=earthquake), b (=loss of life), c (=loss of assets) was
conducted; however a sufficient model could not be
obtained as the coefficient of determination R2 was 0.36.

Table 4 Effect Result of the multiple regression
analysisCoefficient Standard error
1.43
0.60
2.39
0.19
0.13
1.42
0.13
0.13
0.99
0.23
0.05
4.43
-0.36
0.21 -1.78

After Information
Regression analysis
Multiple correlation coefficient R
Multiple decision R2
Correction R2
Standard error
Number of observation

0.78 Intercept
0.60 Efficiency of reinforcement
0.57 monetary effects
0.57 Architecture48

Coefficient Standard error
0.28
0.49
0.53
0.11
0.24
0.12
0.09
0.04

0.58
4.71
1.91
2.44

Equations 8 and 9 are possible before and after
information when substituting the results of the multiple
regression analysis by equation 7.
｛before providing information｝
E = 0.19 × d + 0.13 × e + 0.23 × θ − 0.36 × ω + 1.43 …式８｛after providing information｝
E = 0.53 × d + 0.24 × e + 0.09 × θ + 0.28 …式９ω＝structure
θ＝number of years that the building has existed
Discussion: In equation 8, initially a multiple regressionof E (=effect) which was only explained by d(=efficiency of reinforcement), b (=monetary effect) was
conducted; however a sufficient model could not be
obtained as the coefficient of determination R2 was 0.12.
Thus, the affiliation “structure” and “number of years
that the building existed” were added. On the other
hand, after providing information, “structure” waseliminated and d, e and the number of years the building
existed remained as a result of the finding explanatory
variables that would give a high R2. This reflects thatthe longer the building has existed the effect of antiseismic reinforcement could be acknowledged, which isan extremely rational results. Moreover, the coefficientof determination increased from 0.68 to 0.78 after
providing information, and recognition structure of effectof those who responded to the survey became moreevident.
Conceptualization of the model of obstacle
As illustrated in Fig. 3, obstacle is composed by spirit,
physical and monetary obstacles. The model equationis constructed by using the multiple regression analysis
and by substituting the values of the results of the survey
for equations 10, 11, and 12. Table 5 shows the result of
the multiple regression analysis.

ｈ）＋λ １ ＊monetary （Mo ）＋γ １…Eq. 10
Spirit（Sp）＝α2 ＊lack of information（f）＋β2 ＊distrust(g)+γ2…Eq. 11
Physical （P ｈ）＝ α3 ＊procedure （h ）＋β3 ＊watching over the construction（i）＋γ3※α1～γ1 ,λ1 parameter…Eq. 12
Conceptualization of the model for obstacle (O)Response variable: bstacle(0）Explanatory variables: Spirit (Sp, Physical (Ph),Monetary (Mo)
Model equation: Obstacle (O) ＝α1 Spirit (Sp) ＋β1
Physical (Pｈ)＋γ1 Monetary (Mo)＋C１＜Before providing information＞
Obstacle (O)＝0.151＊(Sp)+0.152＊(Ph）+0.209＊(Mo)－0.425＊ε＋1.923＜After providing information＞
Obstacle (O)＝0.271＊(Sp)＋0.141＊(Ph）＋0.4＊（Mo）＋0.159＊ε＋0.069
Table 5
CoefficientStandard errort

I ntercept

1.923

0.557

3.450

Regression analysis

BeforeInformation

0.69 Intercept
0.48 Efficiency of reinforcement
0.43 monetary effects
0.79 Architecture
48 Structure

Multiple correlation
coefficient R

0.555

Multiple decision R2

0.308

Spirit

0.151

0.105

1.442

Correction R2

0.251

Physical

0.152

0.105

1.450

Standard error

0.757

Money

0.209

0.105

1.997

Number ofobservation

53

Gender

0.219-1.946

Multiple correlation
coefficient R

0.667- 0.425

CoefficientStandard errort

I ntercept

0.069

0.503

0.137

Regression analysis

After
Information

Before Information
Regression analysis
Multiple correlation coefficient R
Multiple decision R2
Correction R2
Standard error
Number of observation

Multiple decision R2

0.445

Spirit

0.271

0.116

2.334

Correction R2

0.398

Physical

0.141

0.098

1.439

Standard error

0.674

Money

0.400

0.113

3.540

Number ofobservation

53

Gender

0.159

0.195

0.818

＜Before providing information＞
Obstacle (O) ＝0.151 ＊(Sp)+0.152 ＊(Ph ） +0.209 ＊（Mo）－0.425＊ε＋1.923＜After providing information＞
Obstacle (O)＝0.271＊(Sp)＋0.141＊(Ph ）＋0.4＊（Mo）＋0.159＊ε＋0.069b)

Obstacle（O）＝α1＊Spirit（Sp）＋β1＊physical （P(Discussion)
A sufficient coefficient of determination could not be
obtained with the model equation that was first defined;
therefore, a multiple regression was conducted byincluding the affiliation “gender”. However, thecoefficient of determination before providing
information was 0.308 and after providing information
was 0.445 which was not sufficient but the best value
obtained. Moreover, the contribution rate of money

Table 6

After
Information

BeforeInformation

Regression analysist

Coefficient Standard error

Multiple correlation
coefficient R

0.770

I ntercept

0.30650.3718Multiple decision R2

0.593

lack ofknowledge

0.07890.0823

0.958

Correction R2

0.580

feeling of
distrust

0.83030.09298.935

Standard error

0.749

Number of observation

65

Regression analysis
Multiple correlation
0.884
coefficient R

0.824

t

Coefficient Standard error
I ntercept

0.099

0.236

0.085

0.0468

1.821

0.814

0.0552

14.76

Multiple decision R2

0.781

lack ofknowledge

Correction R2

0.774

feeling of
distrust

Standard error

0.436

Number of observation

65

0.422

＜Before providing information＞
Spirit (Sp)＝0.0789＊ (f) + 0.8303＊ (g) + 0.3065＜After providing information＞
Spirit (Sp)＝0.0852＊ (f) +0.8146＊ (g) +0.099(Discussion)
The result of the analysis shows that the coefficient ofdetermination of distrust showed a bigger contribution
rate than lack of information. Moreover, the coefficientof determination of regression analysis after providing
information was higher than before providing
information.
b-2) Conceptualization of the model for physicalobstacle (Ph)Response variable: Physical (Ph)Explanatory variables: procedures（ｈ）, watching overconstruction（i）
Definition equation: α ３＊procedures（h） ＋β3 ＊watching over construction（i）＋γ3

Regression analysis

BeforeInformationb-1) Conceptualization of the model for spirit ormental obstacle (Sp)
Response variable: Spirit (Sp)
Explanatory variables: Lack of information (f), Distrust(g)Model equation: α ２＊Lack of information (f)+β ２＊
distrust (g)+γ2＜Before providing information＞
Spirit (Sp)=0.0789＊ (f)+0.8303＊(g)+0.3065＜After providing information＞
Spirit (Sp)＝0.0852＊ (f)+0.8146＊(g)+0.099

Table 7

After
Information

was higher than any other element, and Table 1 showsthat increase after providing information.

Multiple correlation
coefficient R

Coefficient Standard error

t

0.825

Multiple decision R2 0.680

I ntercept

0.443

0.231

1.915

Correction R2

0.670

procedure

0.718

0.090

8.006

Standard error

0.641

watching overconstruction

0.165

0.083

1.992

Number ofobservation

66

Regression analysis
Multiple correlation
0.819
coefficient R
Multiple decision R2 0.671

Coefficient Standard errort

I ntercept

0.528

0.223

2.364

0.661

lack ofknowledge

0.620

0.097

6.392

Standard error

0.630

watching overconstruction

0.207

0.097

2.140

Number ofobservation

66

Correction R2＜Before providing information＞
Physical (Ph)=0.718＊ (h)＋0.165＊(I) + 0.443＜After providing information＞
Physical (Ph)=0.528＊(h)＋0.207＊(I) +0.528(Discussion)
It is clear that the contribution rate of procedures isbigger than watching over construction.
c) [Conceptualization of the model for [execution ofanti-seismic reinforcement]
Lastly, a function to obtain the [execution of antiseismic reinforcement] was constructed based on the
results of the multiple regression model. The model
equation is defined as follows.

A = ( N − O)・・・Eq.

13
N − O(%) = ( F + E ) − ( Sp + Ph + Mo)・・・Eq.

14
20% ≤ N = ( F + E ) × 10 ≤ 100%

・・・Eq.

1520% ≤ O = ( Sp + Ph + Mo) × 100 / 15 ≤ 100%

・・・Eq. 16

Ａ ＝ Antiseismic reinforcement
Ｏ ＝ 0bstacle
F=Feeling of fear
E=Effect
N＝Name recognition of necessity
Ｓｐ＝Spirit Ｐｈ＝Physical Ｍｏ＝Money
Estimated values of the higher goals of obstacle (O)and the name recognition of necessity (N) were
calculated from the model equations, and the [execution
rate of anti-seismic reinforcement] was obtained after
subtracting obstacles (O) from name recognition ofnecessity (N). The model equation of equation 13 wasdefined because anti-seismic reinforcement was not
carried out if there was an obstacle even if people
recognized the necessity of anti-seismic reinforcement.
Moreover, the value of the % here is the conversion of
the 5-level evaluation. Furthermore, in order to set the
maximum as 100%, an appropriate value was multiplied
to each value and equations 15 and 16 were obtained.
Next, the following distribution illustrated in Fig. 10
was obtained by extracting and accumulating the people
who “execute anti-seismic reinforcement” from theresults of the survey and extracting the rate from the total
and the value of A (=rate of anti-seismic reinforcement)(%) of that rate. After, as a result of applying the nonlinear least squares curve to the logistic curve, thefollowing approximation of equation 17 was obtained.
Figure 10 shows the actual measurement value and logic
curve. The value of a (%) is expressed on thehorizontal axis and the rate of people who responded thatthey would carry out the anti-seismic reinforcement (%)
is expressed on the vertical axis.

y=

55.25
1 + 5.65 × exp −0.09 x

・・・Eq. 17

Logistic curve
The number which answered that he wanted tocarry out the anti‐seismic reinforcement in all thequestionnaire respondents60

y=

55.25
1 + 5.65 × exp −0.09 x

(%)
50

40

The rate of the "volition"
which performs anti-seismic
reinforcement

Logistic curve30

20

Actual10

measurement

0
‐30

‐20

‐10

0

10

20

30

40

50

60

N‐O(%)
16

Fig. 10 Logistic curve
5. Conclusion
This study constructed the structuralization of
consciousness and the logic model concerning the namerecognition of necessity as factors that obstruct the

spread of anti-seismic reinforcement. Moreover, thestudy also made it possible to quantitatively measure theeffect of each policy for the promotion of anti-seismic
reinforcement by identifying the degree of which thevariables affiliation and environment should be
introduced to each factors, especially the change instructure after providing information.
For future works, based on the results of this study
and after confirming the universality of the logic model,
we would like to conduct similar survey in all prefectures
around Japan and evaluate policy set for promotion of
the spread of anti-seismic reinforcement and finallyconduct policy proposals, jointly with the Building
Research Institute.

References
1) Building Research Institute: Survey concerning thefactors that obstruct the spread of anti-seismic
reinforcement, 2006.
2) “Laws concerning the promotion of anti-seismic
reinforcement on buildings” based on the
promotion and implementation plan on existingbuildings, Koichi version, Department of public
works of Kochi prefecture