Open Journal of Social Sciences,2014, 2, 179-185
Published Online September 2014 in SciRes. http://www.scirp.org/journal/jss
http://dx.doi.org/10.4236/jss.2014.29031
How to cite this paper: Inayati, T., Arai, T. and Pu tro, U.S. (2014) Career Path and Political Stability: Factors for Leaving In-
donesia?. Open Journal of Social Sciences, 2, 179-185. http://dx.doi.org/10.4236/jss.2014.29031
Career Path and Political Stability: Factors
for Leaving Indonesia?
Tutik Inayati1,2, Takeshi Arai1, Utomo Sarjono Putro2
1Department of Industrial Administration, Tokyo University of Science, Noda, Japan
2School of Business and Management, Institut Teknologi Bandung, Bandung, Indonesia
Received July 2014
Abstract
This study focuses on the relationship between factors career path and political stability on the
decision making whether to live in Indonesia or to live abroad as their future plans; if they do,
what the odds ratio is in each factor to their decisions. This study uses descriptive statistics and
binary logistic regression model as the analysis tools for achieving this study’s objectives on fifty
respondents. The result shows that most of the respondents are Indonesian male students, while
pursuing undergraduate degree abroad with their intention mostly to return home as their future
plans. The correlation between career path and political stability is low and negative. The model is
not fit, but still at an acceptable level since the significance level is high; it shows that career path
will increase the odds ratio people to move abroad or stay abroad almost 3 times likely, while po-
litical stability will increase the odds of people to stay abroad by 50%.
Keywords
Career Path, Political Stability, Staying Intention, Binary Logistic Regression Model
1. Introduction
The mobility of scientists and engineers are inevitable; and most of the mobilizations are centralized in several
developed countries. Although nowadays new countries have emerged as destination countries for students and
professionals in science and engineering area, top destinations have deliberately stood up among others. The
movement is caused mainly by the large demand of scientists and engineers in a country. Also, policies by the
government in a country concerning immigration policies, especially for highly skilled people, also become a
factor of the movement.
This study questions whether two distinctive factors, career path and political stability, influence the decision
of people to live in their home countries or to move abroad. Political stability is one fundamental external factor
that influences the whole condition of a country, including the economic and social factor, as concluded by Fa-
tah et al. (2012) [1] that political freedom, among several other variables, is a significant determinant of eco-
nomic growth. Meanwhile, career path is the internal factor of a person to develop himself or herself further and
to gain more welfare (social and economic). The implication of this study will also explain the how significant

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these factors influence people’s decision. There are more factors that should be inserted, but for now we will
focus on these two variables.
In this paper we conducted a questionnaire on 50 Indonesian respondents (students and professionals), with
tertiary degree particularly in science and technology fields and abroad. Why are students included in this study?
The attraction and the network opening of international labour market begin at the stage of educational pursuit,
particularly tertiary degree. Although the number of respondents is not large, it still represents the population of
students and professionals with the similar characteristics.
2. Literature Reviews
2.1. High-Skilled Workers
High skilled workers are defined of those who achieved university degree or extensive experience in a given
field [2]. The categories include skilled specialists, independent executives and senior managers, specialized
technicians or tradespeople, investors, physicians, business people, “keywork ers” and subcontract workers
(OECD SOPEMI, 1997:21) [3]. The movement of high skilled workers lead us to the migration itself and poli-
cies on immigration from various destination countries. The division between high skilled labour and non-
skilled labour is very difficult, especially if we are talking about the data. So, even the concept is very clear be-
tween the two categories, some data are very difficult to get. Mostly countries do not keep the record of the
outmigration of high skilled people. For example, Indonesia may record the outmigration of non-skilled labour,
but cannot track the high skilled outmigration. The only data available to be searched is by rough estimation,
without validating whether the data is correct or not.
Previous studies had several research focuses and looked from different angles. A study by Forstenlechner
(2009) [4] in Abu Dhabi, on the study of the perception of justice in the host country, found that self-initiated
expatriates perceive justice and support from their host countries even though the consequences may not follow
negative perception as quickly as they do in organizational context. Forstenlechner used 33 interviews to con-
clude the subjective points of views on the condition.
There are various impacts on highly skilled workers’ migration. One negative, yet distinctiv e, consequence is
brain drain in sending countries. Brain drain phenomenon has been studied for the last 50 years, originated from
the British Royal Society as an explanation for the exodus of scientists and technologists from the United King-
dom in the 1950s and 1960s (Gibson & McKenzie, 2011: 3) [5]. Whether brain drain increases over the years or
not, one argument explained that skilled migration is definitely increasing over time but skill levels in sending
countries are also increasing. Therefore, the brain drain rate may stay stable for long periods of time and may
have fallen in the past decade (Gibson & McKenzie, 2011: 7) [5].
2.2. Political Stability
Political stability of a country determines not only the nation’s security, but also economic and social condition
in a country. Many cases where political stability in a country is low, the migration rate is relatively high. Coun-
tries, such as Iran and several countries in Africa, have lost their high skilled workers to developed countries
merely because of the political situation in their home country.
Bertocchi and Strozzi (2008) [6] studied the determinants of international migration with special attention to
the role of institutional factors other than economic and demographic fundamentals, which resulted in significant
factors of attraction, even after controlling for their potential endogeneity through a set of instruments exploiting
colonial history and the institutions inherited from the past; and all is represented by political and migration in-
stitutions. A study by Breunig et al. (2012) [7] counter the cases of unstable political condition of a country;
they claimed that polity of the sending country has a positive effect on migration but negative effect on the re-
ceiving country, which means that the number of migrants is affected by the barriers to entry and freedom of ex-
it from sending and receiving country.
2.3. Career Path
Career development is the one motivation of people to move, whether it is to other companies or other countries.
In this context, the seeking for better level of professionalism with better social and economic benefits; and in

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some times, it can be found by moving to another country. People with tertiary degree generally look for the
better condition for them and for their loved ones. Within the context of this paper, people move to fill in the
highly qualified occupations, which the natives supplies qualified are not enough or not qualified enough. The
majority of skilled migrants are in the professions of computer specialists, accountants, managers, and scientists
and academics [5].
For highly skilled people, the opportunity to develop their career is important. For example, in some cases for
students, the push factors that influence them to remain the host countries are economic instability, bureaucratic
obstacles, lower expected income, and little possibility for advancing in career. Meanwhile, the pull factors are
better prospects for career advancement, greater opportunity for further development in the specialized area of
study, and the existence of a more organized and ordered environment in general [8]. While according to Fors-
tenlechner (2010) [4], working climate can be influenced by the national culture or relevant regulations. This
may affect the condition of a person to stay in a country or return because he or she does not feel comfortable to
work in particular countries.
Meanwhile, the countries where the research was implied show different results. The management of immi-
gration in France permits inflows of skilled migrants and yet presented strong barriers to their employment and
career advancement, which implied that receiving countries’ policies have impact on the development of highly
skilled workers [9].
2.4. Binary Logistic Regression Model
Binary logistic regression model is a common methodology to describe the relationship between independent
variables and dichotomy dependent variable. The important implication in this model is the probability in which
independent variables influence the dependent variable, another important implication is the odds ratio or like-
lihood ratio that the dependent variable is 1.
112 23 3
112 23 3
( ......)
( ......)
exp
1 exp
a
a
bx bxbx
bx bxbx
p
++ +
++ +
=
+
(1)
Equation (1) shows the mathematical function of logistic regression; which p is the probability that a case is
in a particular category. Exp is the exponential function (normally 2.72), a is the constant of the equation and b
is the coefficient of the predictor variables or as we call it independent variables.When the probability fail to
reach the 5% significance level, we retain the independent variables has no increased effects in predicting the
dependent.
There are two hypotheses in the model that needs to be considered:
1. The null hypothesis, which is when all coefficients in the regression equation take the value zero, and
2. The alternate hypothesis that explains that the models with predictors currently under consideration is accu-
rate and differs significantly from the null of zero (i.e. gives significantly better than the chance or random
prediction level of the null hypothesis) [10].
3. Methodology
In the past, we had conducted survey to collect several important values that would be seminal for the modelling
and simulation in this study. The target of respondents is divided into two main categories: students and profes-
sionals, each of which has finished or is currently studying in bachelor program level (minimum tertiary educa-
tion level). More importantly, the area of studies is concentrated in science and engineering level, although sev-
eral respondents may come from different background from the targeted fields. For professionals, the similar
education background applies for target respondents. However, the choices for professionals are more flexible.
For this paper, we combine the results from students and professionals, which include the characteristics, future
plans, and variables’ (given) importance.
The result then will be analyzed through descriptive statistics and later using binary logistic regression analy-
sis. So far, 50 replies have been collected (36 students and 14 professionals). Replies, even though considered
small, have shown influence in decision making and future estimation for mobility of Indonesian scientists and
engineers. The respondents are concentrated in three particular countries: Indonesia, Japan, and Germany; the
countries of education background for professionals, though, are more varied.

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4. Results
4.1. Descriptive Analysis
The initial analysis is to give descriptive information about respondents. In this study, as mentioned earlier, res-
pondents are limited to students and professionals who are expected to have minimum tertiary education back-
ground or currently pursuing education. The target respondents education background or profession is concen-
trated in science and engineering area, and respondents are currently studying or working abroad. Giving the
circumstance, respondents’ data has been considered not very plentiful. However, the results are expected to
gain its originality by receiving direct response, instead of searching from public data source.
The major proportion of respondents’ gender is male (80%) in total (students and professionals). In the case
of respondents’ age, for students, the majority of respondents are in the range of 20 - 24 years old, which indi-
cate most of the respondents are currently studying in bachelor level degree; then followed by the age range of
15 - 19 years old, which also indicate the same degree pursuit. For professionals, the age range is mostly 25 - 29
years old, followed by the age range of 30 - 34 years old. The result suggests that most respondents have worked
for less than 3 until 5 years. If we combine both types of respondents, 44 percent of respondents are in the age
range of 20 - 24 years old. For most of student respondents in this study, their marital status is single; which
means that it is in line with the age range below the average marital age. For professionals, most of respondents
are married, followed by single and widowed or divorced, respectively.
For students who currently study in tertiary level degree, sixty nine percent of them are now in the bachelor
degree; followed by master (17%) and doctor degree (14%). For professional respondents, half of the respon-
dents have master degree followed by bachelor and doctoral degree, respectively. In total, sixty percent of res-
pondents have or currently pursue bachelor degree; while twenty six percent of the respondents belong in master
degree and the rest is doctor degree.
For professionals, most of respondents receive their degree(s) in Indonesia, followed by Germany, Japan,
United Kingdom and Australia, respectively. This result indicates that Indonesia is still the main destination for
respondents to pursue education. However, the count of country where respondents pursue or had pursued their
education may overlap; it means that a respondent who graduated from master degree in Indonesia’s university
had previously graduated from bachelor degree abroad, or vice versa. For students, most of them are currently
pursuing their education in Germany (70%), which indicates the current domicile for most respondents are in
Germany. The second destination country is Japan (22%), while the rest is Indonesia (8%).
Even though the country where respondents are currently pursuing or had pursued their education is concen-
trated in several countries, the fields of study vary more than the domicile. Economy studies and Information
technology stand out among other fields; other fields of study include Energy and environment, Psychology,
Molecular biology, Geodesy, Marine bio-resources chemistry or fisheries science, public health science, elec-
tronics, industrial technology, transportation, chemical engineering, mechanical or machinery engineering, bio-
technology, mechanic electronic, and civil engineering.
Each student has his/her own point of view on future plans. In the survey, students were asked about their re-
turn intentions; if students are educated abroad whether they will return home or remain abroad, and if students
are educated in Indonesia whether they will move abroad or remain in Indonesia. For students abroad, over fifty
percent of students abroad choose to return home after they graduate. Almost forty percent of students abroad
choose to remain in their host countries, and the rest gave no answer to this matter (6%).
As for the future plan after graduation, students were given several options on what or where they will do: (1)
continuing studies, (2) working in management area in private companies, (3) working in management or ad-
ministration area in government institutions, (4) working based on specialization area in private companies, (5)
working based on specialization area in government institutions, (6) working in universities, and (7) other op-
tions.
As shown in Table 1, students prefer to continue their study and work based on their specialization area in
private companies, equally. For students who plan to continue their study, mostly are bachelor students. Aside
from that, the result indicates that private companies are more attractive for students as a working destination for
students. The next most popular option for students is working based on specialization area in government insti-
tution and “other” option, equally. “Other” option generally includes establishing their own company based on
the major of their study. Interestingly, the least interesting work field for respondents is working in management

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area in private companies. Logically, management area in private companies is very popular among students
because the career path is more distinctive and promising compared to other institutions or working in other
areas beside management. Working in universities is also an unpopular work field option for students with only
eight percent choose to work in this field. However, working in universities requires postgraduate degree (mas-
ter or doctor), meanwhile as mentioned earlier, most of respondents are bachelor students. Hence, it is expected
to have that kind of result.
For professionals, several questions had been asked differently from students respondents. When they were
asked to classify their occupations, first rank option was “other” occupation, and it was followed by researcher
occupation. “Other” occupation generally was management position in a company (i.e. banking) or in govern-
ment institution (i.e. Indonesian election institution and Indonesian embassy). In the survey, we cannot be cer-
tain that respondents’ major of study is in line with their profession currently. Therefore, what we can count on
is their current profession and trying to classify their occupation. After researcher (29%), Academician (21%)
followed, and then engineer (14%). Surprisingly, none of the respondents marked scientist as their occupation,
which ideally there should be.
The future plan for professional respondents varies accordingly to their occupations. For professionals who
work in management, most of them are more concerned about the career path where they work, or even try to
find another company to work for with faster career path and higher salary and position; and even some of them
choose to be entrepreneurs or continue their study for their future plan. For other occupations, their future plans
are not different from their current employment; instead of moving to other institutions or universities, they fo-
cus more on their improvements of their work, such as teaching, publication, and research improvements.
4.2. Binary Logistic Regression Analysis
But how much and how significant those variables affect the people’s decisions to stay in a country? One of the
purposes of this paper is to show the influence of people’s decision making on whether to be in Indonesia or
abroad for their future plans. The dependent variable is shown in the intention of staying for respondents:
1) For students abroad, the choice is whether to return home or remain abroad after they graduate.
2) For students in Indonesia, the choice is whether to remain in Indonesia or move abroad after they graduate.
3) For professionals abroad, the choice is whether to return home or remain abroad for their future plan (the
next 3 - 5 years).
4) For professionals in Indonesia, the choice is whether to remain in Indonesia or move abroad for their future
plan (the next 3 - 5 years).
Hence, the dependent variable only consists of two choices: staying in Indonesia and staying abroad. The
condition of these choices is reflected by 0 (zero) as staying in Indonesia and 1 (one) as staying abroad as their
future plans. This part discusses about the analysis of binary logistic regression using SPSS software.
Table 2 shows the classification table of step 0 when variables are not yet included in the calculation. It
shows that overall percentage is 66 percent, which means that the choice of people staying in Indonesia will be
correct 66 percent of the time. Next, we will see the comparison between Table 2 where variables are not in-
cluded and Table 3 where variables are included to see whether the adding of variables will increase the per-
centage of accuracy, with choice to stay in Indonesia (indicated by 0) by 93.9 % and choice to stay abroad (in-
dicated by 1) by 17.6%; and results the overall percentage of 68%. Therefore, we can conclude that the mode is
better than not having variables included at all.
-2 Log Likelihood scores 57.682; Nagelkerke R square indicates that the model has 16.7 percent relationship
between predictors and prediction. Based on chi-square test (p = 3.950 with degree of freedom 5), the model
shows that variables in this model is not independent. However, the correlation between political stability and
career path is small and negative.
The Hosmer and Lemeshow test shows that this predicted model is not significantly differ from the observed
case (Significance = 0.557). The result still indicates that there is almost certainty that students and professionals
choose to stay in Indonesia when they are educated or living in Indonesia, or moving to Indonesia after they are
educated or living abroad. Although the significance test is not what is expected, this result will be essential on
the relationship between career path and political stability, and the decision of respondents to stay in Indonesia.
For career path variable, the odds for people to move or stay abroad are almost 3 times. Meanwhile, the in-
crease of one unit of political stability will increase the chance of people to stay abroad by 50%.

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Table 1. Classification Tablea,b.
Observed
Predicted
Staying.Intention Percentage Correct
0.00 1.00
Step 0 Staying.Intention 0.00 33 0 100.0 1.00 17 0 0.0
Overall Percentage
66.0
a. Constant is included in the model. b. The cut value is 0.500
Table 2. Classification Tablea.
Observed
Predicted
Staying.Intention Percentage Correct
0.00 1.00
Step 1
Staying.Intention .00 31 2 93.9
1.00 14 3 17.6
Overall Percentage
68.0
a. The cut value is 0.500.
Table 3. Variables in the Equation.
B S.E. Wald df Sig. Exp(B) 95% C.I. for EXP(B)
Lower Upper
Step 1a
Career.Path 1.096 0.602 3.321 1 0.068 2.993 0.921 9.730
Pol.Stabil −0.551 0.350 2.481 1 0.115 0.576 0.290 1.144
Constant −03.420 2.646 1.671 1 0.196 0.033
a. Variable(s) entered on step 1: Career. Path, Pol. Stabil.
5. Conclusions and Further Improvement
This study tries to analyze the decision made by Indonesian students and professionals mainly in the science and
technology areas on staying preferences as their future plan. And this paper has collected 50 questionnaires,
which is enough to be analyzed using binary logistic regression. Descriptive analysis shows that the question-
naire is dominated by students. Therefore, most respondents are male, in the range of 20 - 24 years old, and have
not been married. Student respondents are dominated with the pursuit of bachelor degree while professionals
have graduated from master degree. For students, most are currently studying in Germany; and most profession-
als have their degree gained in Indonesia.
Student respondents’ field of study vary more than their country of studying, and their future plans are also
distributed with most choose to continue their studies. For professionals, their occupation is mostly in manage-
ment field in a company, followed by researcher, academicians, and engineer. For most respondents, their future
plans are going back to Indonesia or remaining in Indonesia rather than staying abroad.
Career path and political stability are analyzed in order to know their relationship with decision of students
and professionals as their future plans. First, the correlation between both variables is small and negative, which
means that both variables are independent. Second, career path will increase the chance of people to move
abroad or stay abroad almost 3 times likely, while political stability will increase the odds of people to stay
abroad by 50%.
Further improvement needs to be conducted in this paper. First of all, the samples of this paper are adequate,

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but not enough to make significant conclusion. By collecting more samples the result may be more significant
than previous one. Second, this paper combined both samples from students and professionals; for further im-
provement, if more samples can be collected, samples can be divided into two groups and then will be delibe-
rately distinguished the differences.
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