CSIS Discussion Paper No. 123

Community participation in Tokyo and its suburbs:
the importance of savings and interaction effects

Patricia Herbez1, Yasushi Asami2, Sohee Lee3

Center for Spatial Information Science, The University of Tokyo, 5-1-5, Kashiwa-no-ha,
Kashiwa, Chiba, 277-8568, Japan

October 2013

Abstract
In community participation, people are involved in defining the issues of concern to them and try to resolve them.
This study tries to understand what kind of people choose to take part actively in community groups and to what
extent their characteristics may interact between them. People are more likely to participate in community groups
when they live for many years in the community, have more savings, don’t work and live in the suburbs rather thanlive in Tokyo. Women with work and people with a higher education living alone are less involved in the community
life. It seems that interaction effects are more important in the choice of participating than direct effects.
Keywords: community participation, savings, interaction effects, Japan,

1

Ecole Nationale des Travaux Publics de l’Etat, France
E‐mail address : patricia.herbez@entpe.fr
2

Center for Spatial Information Science, The University of Tokyo, JapanE‐mail address : asami@csis.u‐tokyo.ac.jp
3

Korea Advanced Institute of Science and Technology, Korea
E‐mail address : shlee4649@kaist.ac.kr

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1. Introduction
Community participation is one of the forms of volunteering. Volunteering was studied a lot.
Volunteering means any activity in which time is given freely to benefit another person, group ororganization. Volunteering differs from community participation concerning the scale, the goaland people involved. Indeed community participation is a process by which people are enabled
to become actively and genuinely involved in defining the issues of concern to them, in making
decisions about factors that affect their lives, in formulating and implementing policies, inplanning, developing and delivering services and in taking action to achieve change (Breuer,1999). This article focuses on some characteristics of people who participate in community
associations; this paper examines particularly economic and household status.
One of the reasons for residents to participate in community groups is the local community
attachment they may feel. This attachment has two main different origins: the increasing of
population or density of the community and also the length of residence and the friendship,
kinship and associational networks (Kasarda and Janowitz, 1974). Several recent studies confirm
the link between rootedness, living longer in the community, and involvement in community
groups (Wandersman et al., 1987; Taniguchi, 2010), whereas Reingold (1995) considers that the
number of years lived in the neighborhood is not at all significant contrary to the number offamilies known in the neighborhood. Another point to note is that independently the length ofresidence in the community, the living environment itself is inconsequential on the choice ofparticipating whether people live in an urban area or in a rural area (Babchuk and Booth, 1969).
Setting aside the environment and the link to it, other reasons can be taken into account as
demographic or economic characteristics. Indeed if at first sight, living alone or be aged appear
to be incentive to participate in community life, studies prove that they don’t. Persons in couples
and those who live with children are more likely to be embedded in a community group thansingle or more generally people living alone (Babchuk and Booth, 1969; Wandersman et al.,
1987; Taniguchi, 2010). Reingold complete these results in an analysis comparing community
participation according to the housing tenure status proving that owners are more involved incommunity due to the desire to prevent its deterioration.
Concerning the last demographic variables, age and gender seem not to have influence (Olsen,
Perlstadt, Fonseca, et al., 1989), but this affirmation is contradicted in some cases. For example,
in Japan, it appears that older Japanese, and women living alone, not working are more likely toparticipate (Lee et al., 2008). Moreover, part-time employment encourages women’s volunteer
work (Taniguchi, 2006).
Employment is one of the variables contained in the economic status. It is also complex to study
because it contains different aspects related them: income, working status, occupation, education.
Thus the former studies show that education has an influence on the participation in community
groups; high school graduated and above residents are more likely to participate in community2

organizations. (Reingold, 1995; Foskett, 1955; Rochelle and Shardlow, 2012; Wilson and Musick,1997). As a consequence, the same research found that underemployment or unemployed andpeople those with low income are less involved in community affairs. On the contrary, according
to Taniguchi (2010), the level of household incomes plays no significant role in explaining hours
volunteered.
Thus, findings concerning economic status differ between studies and though a lot have beenstudied, the amount of savings has not been taken in consideration against age, or our sample
contains a majority of elderly who work less or not at all, so their income can be less significant
than the amount of their bank account concerning their effective participation in community
groups. However, savings can have an importance because it can explain the need to work and so
the household income. It is both cause and consequence of several others variables studied.
That’s why the role of savings will be studied more closely in the choice of participating incommunity groups.

2. Data
Data used for this study have been taken from a questionnaire submitted within the framework of
the “Urban Reformation Program for Realization of Bright Low Carbon Society”4 by the City
Planning research group.
The questionnaire was sent in February and September 2011 to 4,920 people aged 40-44 andaged 65 or older, who lived in Tokyo’s 23 wards and in two suburbs, Hachiōji and Kashiwa.
The response rate for this survey was 39.6%. Completed questionnaires were obtained from1,946 respondents. Among them, 45.4% (N=884) of whom lived in Tokyo, 27.8% (N=541) in
Hachiōji and 26.7% (N=519) in Kashiwa. Two respondents lived outside our study area. They
were suppressed of the sample for this study. 91 people had not informed the work statusquestion. They were also removed from the analysis sample. Indeed, the relations work/ savings
cannot be neglected for the further analysis. So the following study was realized with 1,853
respondents. Table 1 shows the characteristics of the sample. Women represent 52.7% of thesample. The mean age is 64.1 despite the greater sample of elderly (71.0%) due to the absence of
persons between 45 and 64 years old. 83% of the respondents had completed high school, lessthan half had pursued further studies, but almost a quarter of respondents are undergraduate.
Only 2.9% respondents had been to graduate school. Nevertheless, 42.5% respondents workwhatever age or education. The questions about community participation contained in the survey
were about the participation, its frequency and the reasons of non-participation. Note that 27.5%

4

http://low-carbon.k.u-tokyo.ac.jp/en/outline/index.html

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of the respondents told they participate in the community. Most of them live with one (37.8%) or
two (22.2%) people, only 10.8% live alone.
Table 1. Characteristics of the sample (N=1,853)
Variables
Gender

Percent frequency

Male
FemaleAge (64.1 ± 15.0)
40-44
65-74
75 or older
Currently Employed
Yes
No
Education
Junior High School
High school
Vocational School
Junior School
Undergraduate school
Graduate school
No answer
Location
Tokyo’s 23 wards
Hachiōji
Kashiwa
Community Participation
Yes
No
No answer
Number of people they live with
0
1
2
3
4
5
6 or more
No answer
Number of years living in the community
less than one year
1-2 years
3-4 years
5-9 years
10-19 years
more than 20 years
No answer
Bank accountLess than 1 million yen
1-2 million yen
2-3 million yen
3-4 million yen
4-5 million yen
5-10 million yen
10-20 million yen
20-30 million yen
More than 30 million yen
Don’t know or No answer

47.3%
52.7%
29.0%
44.7%
26.3%
42.5%
57.5%
15.9%
37.7%
10.1%
8.7%
24.0%
2.9%
1.5%
45.3%
27.9%
26.8%
27.5%
68.8%
3.8%
10.8%
37.8%
22.2%
16.4%
6.2%
3.2%
1.9%
1.6%
3.0%
4.4%
7.4%
15.0%
20.7%
49.3%
0.2%
13.2%
7.2%
6.6%
3.7%
5.0%
14.0%
13.4%
8.0%
13.2%
15.7%

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3. Results
In order to understand better the characteristics of people participating in community affairs anddiscover the most significant characteristics, we analyze the questionnaire survey data describedabove. First we use a logistic regression in order to merely compare our results with theliteratures but also to see a relationship between community participation and savings. The mostof studies take place out of Japan or Asia which can present a difference due to culturaldifference, and some studies are quite old. Moreover, according to the review of literatures, theamount of savings has not been considered. It could be interesting to see if this variable has or
hasn’t an influence upon the community participation.
Second, in order to distinguish direct and indirect effects, we analyze the data through astructural equation modeling; this analysis allows to separate real effects to compound effects ofseveral variables on community participation.
Influence of savings and living environment
Logistic regression analysis was conducted using SPSS 12.0 for Windows.
Community participants and non-participants’ characteristics are compared by a logistic
regression analysis with the community participation (reference: positive) as a dependent
variable.
Independent variables are included when they show a significant direct effect with the dependent
variable or if an interaction effect is found when compounded with another variable.
Table 2. Coefficients of logistic regression analysis
Coef.
Work

-.197

Std Error.173

p-value
.255

Tokyo

-.307**

.121

.011

Savings.050**.023.034

Number of years living in thecommunity
Education.232***

.054

.000

-.027

.044

.532

Living alone.823**.414.047

Gender (Woman)

.245

.153

.109

Gender (Woman) * Work-.643**

.255

.012

Live alone * Education-.323**

.147

.028

*p<0.10, **p<0.05, ***p<0.01
Chi-square: 92.114, df=9

As shown in Table 2 above, logistic regression suggests that the main direct effects which inducea participation in community affairs are the city of residence and the number of years living in
the community. Indeed people living in the suburbs and those who live in the community formany years are more likely to participate in community life. The amount of savings or living
alone impact also positively. Not compounded with work, living alone has also a strong effect. It

5appears that gender has no significant effect as Wilson and Musick found in 1997. However
women who work are significantly less likely to be active in the community.
Contrary to literature, education doesn’t appear to be an important element in the choice ofparticipating. Nonetheless people living alone have less chance to participate if they are welleducated.
But most of the direct effect is influenced by others relations that we can see on Figure 1. Someof these indirect effects can result in inaccurate interpretations. To what extent indirect effects
can influence, maybe change the impact of the independent variable on the dependent variable?
To consider a Structural Equation Modeling (SEM) approach permits further analysis to find itout.
Figure 1. Results of logistic regression analysis

Limited direct effects in participating choice
The data are now analyzed using Structural Equation Modeling (SEM). SEM is a set of statisticaltechniques to test causal relations between one or more independent variables and one or more
dependent variables. These variables can be either continuous or discrete. It allows confirmatory
and exploratory modeling. Confirmatory modeling usually starts out with a hypothesis that gets
represented in a causal model. With an initial theory SEM can be used by specifying acorresponding model and using data to estimate the values of free parameters.

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We use here the model defined previously. The results of SEM analysis permit to show only
direct effects between two variables removing indirect effects and allow understanding better thereasons why people participate in community groups. In literature, most of studies use only
logistic regression and don’t separate direct and indirect effects, which might change or influenceinterpretations and conclusions. We obtain thus an estimation of the free parameters.
Table 3. Coefficients of structural equation modeling analysis
Work

Coef.
-.100***

Std Error.021

p-value
.000

Tokyo

-.055***

.021

.008

Savings.010***

.004

.006

Number of years living in
the community
Education.035***

.008

.000

-.010

.007

.157

Live alone

.019

.033

.560

Gender (Woman)

.003

.021

.871

*p<0.10, **p<0.05, ***p<0.01
Chi-square: 799.3095 , df=25

For this purpose, this analysis is realized using the statistics software R including the SEM
package. The resulting coefficients of the SEM analysis are collected in Table 3 and represented
in Figure 2 shown below.

Figure 2. Results of structural equation modeling analysis

Comparing the signs of the different parameters used in this analysis, no major influence appears
in the sign of the coefficients compared with the first table of coefficients in the logistic

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regression, which means that the direct effects have more impact than indirect effects. Note thatno interaction effects could be entered in this model. So there is a large difference in somecoefficients but not an inversion of the effects. The second model is consistent with the first one.
However some differences exist when comparing the results of the SEM analysis with the resultsof logistic regression analysis concerning the significant variables. In the two analyses, the living
location, the amount of the savings and the numbers of years living in the community are
significant. But work appears now to be a significant variable whereas living alone isn’t
significant any more. But this second analysis confirms that education and gender have nosignificant direct effect.
Thus people are more likely to participate in community groups when they live for many years in
the community, have more savings in the bank, don’t work and live in the suburbs rather thanlive in Tokyo. The variable concerning work is the most significant. But the coefficients leading
to community participation are quite low, which means that direct effects are not so importantand are emphasized by indirect effects.

4. Discussion
At first sight, almost all independent variables seem to cause a participation in community except
for those living in Tokyo and those well-educated contrary what literature says. Different reasonscan explain these differences. Babchuk and Booth (1969) find no difference between people
living in rural or urban areas, but this study took place in Nebraska where is a Midwestern stateof the United States sparsely populated (9 inhabitants per square kilometer) and cannot becompared to Japanese cities. Because, the two suburbs cannot be treated as rural areas.
Concerning education, if the coefficients are negative in this study, further analysis shows thattill undergraduate studies, the more people are educated, the more they participate. Only thegraduate participate less than the other groups, which can be explain by the little size of thisgroup, or by the lack of time due to higher responsibilities in their work.
It appears that people who have lived in the community longer participate more in a significant
way as found by previous studies (Taniguchi, 2010; Lee et al., 2008), contradicting the results ofReingold (1995). However, he finds that the number of knowledge in the community isimportant, so he differentiates these two variables. This last variable is not present in thequestionnaire survey data that we used, it is possible that the number of knowledge is here alatent variable induced by the length of residence in the community and which influences
positively the involvement in the community life.
Then the analysis demonstrates that gender has no influence confirming the findings of Olsen etal. (1989). However, this study does not study the correlation between part-time employment of
the women and community participation. But, women with a job are less likely to take part in thecommunity affairs which is consistent with the results of Lee et al. (2008).

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The analysis of the household status reveals that people living alone potentially participate moreto the community life. This result contradicts research findings about people married who would
participate more (Babchuk and Booth, 1969; Wandersman et al., 1987). Findings here can be theresults of interaction effect which influence direct effect coefficients and which are not used in
the other studies. However, when crossed with educational level, the trend is reversed. An
explanation can be that people with a high level of education have a job with greater
responsibilities than the others as said before; moreover if they live alone, they must assume theirwork and the housework which don’t let them much time to participate. Another possible
explanation is that with their responsibilities, they can within their work take part in a way or
another to the welfare of community so they don’t feel an obligation to have another form ofparticipation.
Have money influence on participation? That is what we can ask. It appears that the amount ofsavings impacts positively participation in community, both in logistic regression and SEM
analysis which implies that it is really money possessed and not the fact of working and earnmoney which helps the choice of participation. There are several possible explanations. In thissample, the majority of people are elderly, so most of them don’t work or work less depending of
the amount of their savings. They are not busy, they have time and no problems with their job. It
would be interesting to look their housing tenure to support this assumption. Another explanation
can be that people having more savings may feel more liable to their community, they mightwant to protect and help their community and therefore themselves as a part of this community.

5. Conclusions
Findings show that people are more likely to participate in community groups when they live formany years in the community, have more savings, don’t work and live in the suburbs rather thanlive in Tokyo. But women with work and people with a higher education living alone are lessinvolved in the community life.
These findings are globally consistent with the previous studies, and it appears that interaction
effects are more important in the choice to participate than direct effects considered separately.
The amount of savings has a positive but small effect in this choice. This study shows theimportance of considering the interaction effects to really understand the phenomena ofcommunity participation.
Nonetheless these findings must be taken in the context of the survey. Only people aged 40-44
and 65 or older were studied, so some characteristics like work or savings cannot be expanded toevery category of age. Moreover, only logistic regression takes care of interaction effect in thisstudy, further studies should try to enlarge SEM analysis in order to have comparable data.

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Acknowledgments
This work is partly supported by Social System Reformation Program for Adaptation to Climate
Change, Strategic Funds for the Promotion of Science and Technology, MEXT, Japan.

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