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THE RELATIONSHIP BETWEEN FINANCIAL BEHAVIOR WITH ITS
DETERMINANTS AND WELL-BEING OF COLLEGE STUDENTS IN BANDUNG
Samuel Santo Patarma Raja Panukunan Hasibuan
Undergraduate Program, School of Business and Management, Institut Teknologi Bandung, Indonesia
samuel_santo@sbm-itb.ac.idsamue
ABSTRACT
Financial Literacy has become a strategic national focus in Indonesia and the “youth” group, which includes
college students, have become a focus age group for this strategy. However, research have found that the
financial behavior exhibited by Indonesian college students is categorized as poor. Research studies have found
that financial behavior has an effect to financial well-being, which then would affect the subjective well-being
of these students. Thus, this research explored what may cause the financial behaviors of Indonesian college
students, and how these behaviors would affect their financial and subjective well-being. A quantitative
approach using questionnaire is employed and 305 responses of college students from universities in Bandung
City is collected. Then, descriptive statistics and PLS-SEM methodologies are used to analyze each variable
and the relationships between them. Among the determinants, only Financial Knowledge is found to affect the
Financial Behaviors, and this research does not support the relationship between Financial Behavior to
Financial Well-Being. A healthier financial condition is found to increase the frequency of positive feelings
over negative feelings in college students. Interestingly, a healthier financial condition is found to negatively
influence the life satisfaction of students. This study’s findings contribute to the research body of financial
literacy in Indonesia and explore a conceptual model that have not been studied on Indonesian college student.
The findings would encourage college students to strive towards getting heathier financially and help
policymakers or businesses who are targeting the segment of college students, particularly in Bandung City.
Keywords: Financial Behavior; Personal Financial Management Behavior; Financial Literacy; Financial
Well-Being, Subjective Well-Being; college students; Indonesia
INTRODUCTION
The phenomenon known as “Tanggal Tua”, which translates to “the end of the month” (Tim KBBI
Edisi Lima, 2016) illustrates the common period where people are living on the remains of their income,
and usually means someone must live more frugally to save money and survive until their next paycheck
(QM Financial, 2019). The lack of money could become a paramount concern for college students,
amidst juggling academic responsibilities and meeting personal or societal expectations. This
relationship between college students and their finances is the background of this research, and their
importance could be seen both on the extrapersonal side of college students and interpersonally.
Interpersonally, undergraduate students are going through a very crucial developmental period in
their life, in a stage called Emerging Adulthood, coined by Arnett for individuals in industrialized
country (2000). Throughout this period, emerging adults navigate through identity exploration,
instability, and focusing more on themselves, while still undergoing maturations that requires significant
care since it is fundamental for life success (Hochberg & Konner, 2020; Syed, 2015). In this period that
spans from 18-25 years old, young individuals encounter transitional events (including leaving their
parental home, finishing their education, searching for a job, and working toward marriage) and undergo
a character transition into becoming adults, such as being accountable for themselves, making decisions
by themselves, and taking care of their own finances to support themselves (Arnett, 2000). This last
characteristic of becoming “financially independent” is the reason why the personal role and relationship
of finance to emerging adults, specifically college students, has become an interesting topic of much
research. This means the that the relationship between college students and their finances is important
to focus on, given its potential to shape their future financial management behavior (Gonzalez-Ribeiro,
2018).
Additionally, academic performances are the most prominent metrics for student’s success during
college period, and many factors contribute to this end, including their behaviors, self-regulation, and
stress (Alyahyan & Düştegör, 2020; Kim, 2017). Notably, financial strains and stresses can significantly
impact college students’ performances, both academically and socially (Adams et al., 2016; Moore et
al., 2021). A student’s well-being is also interconnected to his or her academic performance, since
students with less stress and better mental health achieve greater academic success (Barbayannis et al.,
The Relationship Between Financial Behavior with its Determinants and Well-Being of College Students in
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2022; Cárdenas et al., 2022). Therefore, it is important to explore the link between the financial
conditions of college students and their own well-being, as it affects their success, which in turn has
long-term influence on success beyond college (Ray & Marken, 2014).
Figure 1 Generation Z as the Biggest Composition of Indonesian Population in 2020 (BPS, 2021)
On the extrapersonal side, financial Literacy has been a subject of focus for the Indonesian
Government. The government had already created the National Strategy on Indonesian Financial
Literacy (SNLIK) 2021 - 2025, which shows the strategic importance of Financial Literacy and
Inclusion since it eventually contributed to economic growth (OJK, 2021). The SNLIK aims to realize
a well-literate Indonesian society to achieve a sustainable financial welfare, with strategic programs to
improve financial competence, encourage wise financial attitudes and behavior, and promote financial
access (OJK, 2021). Pupils, Students, and Young People are among the priority target groups for these
programs, which shows the strategic importance of the 16–30-year-old “Youth” segment (Undang
Undang Republik Indonesia Nomor 40 Tahun 2009 Tentang Kepemudaan, 2009) for economic growth.
It is sensible, considering that this segment is composed mostly of the Generation Z population. This
segment already is and will continue to be the productive age group of Indonesia in the following year,
with promising impact to Indonesian society due to their size as a demographic bonus, high digital access
and understanding, and affinity towards money and job security (BPS, 2021; Dwidienawati & Gandasari,
2018; Hartanto, 2023; Limilia et al., 2022). In this Youth segment, lies the emerging adulthood period that
becomes the focus of this research; hence this research will be relevant and aligned to the current
financial literacy movement in Indonesia. Notably, Indonesian financial literacy index has shown a
consecutive rise from 21.8% in 2013 to 49.68% in 2022 (Annur, 2022).
Figure 2 Indonesia Financial Literacy Index 2013-2022
Despite the particular importance of college students and the rise in national financial literacy in
Indonesia, recent phenomenon indicates that this rise is not translated well to the college student
demographic. Nearing the end of 2022, a case of fraud had left around 121 students of Institut Pertanian
Bogor (located in West Java) in debt to online loan / fintech lending platforms, with debt amounting to
more than 650 million Indonesian Rupiah (Bestari, 2022). These students are led to believe that they
2%
7%
22%
27%
28%
14%
Indonesian Population Composition by
Generation 2020
Pre-Boomer Boomer Generation X
Millenials Generation Z Post-Generation Z
21,80%
29,70%
38,03%
49,68%
0,00%
10,00%
20,00%
30,00%
40,00%
50,00%
60,00%
2013 2016 2019 2022
Indonesian Financial Literacy Index
2013-2022
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will receive 10% commission after purchasing the products from the perpetrator’s online shop by using
the money from opening an online loan account. Some of the victims said that they participated in this
activity in hope of making money as a student and because their friends had already become a part of
the scheme (CNN Indonesia, 2022) . In the aftermath, Otoritas Jasa Keuangan (OJK) had coordinated
with the related online lending platforms to provide relaxation for the victims.
Despite being a strategical subject of focus for Indonesian government, Indonesian college
students are still not financially well-literate. Institut Pertanian Bogor ranks among the best university
in Indonesia and the best place in Southeast Asia to learn about agriculture and forestry (IPB, 2019,
2023; Quacquarelli Symonds, 2023a). For the students in one of the best universities in Indonesia to
exhibit this kind of behavior begs the question about the financial behaviors of other college students in
Indonesia, and whether these behaviors affect their well-being and furthermore, their academic
performance. This fact is corroborated by research that found Indonesian college student in the best
universities in Indonesia to exhibited poor levels of financial literacy and financial behavior (Khalisharani
et al., 2022; Lantara & Kartini, 2015).This phenomenon also brought attention to the province of West Java.
From the SNLIK, report shows that West Java province's financial literacy index (37.43%) in 2019 is
still below the national index (38.03%), however its financial inclusion index is above the national index
(OJK, 2021).
Figure 3 Financial Literacy Index by Province 2019
Among the most researched topic of college students’ finances are their financial behavior its
relations to financial well-being (Bartholomae & Fox, 2021; Sorgente & Lanz, 2017). Research on the
behaviors exhibited by American college students regarding money became the emphasis of the meta-
analysis done by Bartholomae, in which he explained the various determining factors, relation to well-
being, and directions for future research (Bartholomae & Fox, 2021). The determinants of behavior
mentioned in this research includes sociodemographic characteristics, developing into adulthood status
(such as living on their own, employment, and level of support by parents), financial knowledge and
attitude, and family background or process variable (such as financial socialization, communication, or
parenting style). The well-being variables mentioned in this research include financial well-being
(indicated by “financial stress” or “financial self-efficacy”) as well as life/personal well-being (indicated
by psychological distress or satisfaction with life). Although research on the relation between financial
behavior and well-being is common in America, similar research in Indonesia is very limited. That’s
why this research has the novelty of studying this relation in the context of Indonesian college students,
specifically in West Java.
Financial behavior, well-being, attitude, and knowledge are related to a vastly researched, broader
term which is Financial Literacy (Zait & Bertea, 2014). Financial Literacy is understanding concepts of
money, with confidence and skills in applying and communicating that understanding towards real use
DKI Jakarta
DI Yogyakarta
East Jawa
Central Java
Aceh
Kepulauan Riau
Riau
South Sumatra
East Kalimantan
Central Sulawesi
Banten
North Sulawesi
Bali
North Sumatra
North Maluku
West Java;
37,43%
Central
Kalimantan
Southeast
Sulawesi
West Kalimantan
Maluku
South
Kalimantan
Bangka Belitung
North
Kalimantan
Jambi
West Sulawesi
West Nusa
Tenggara
West Sumatra
Bengkulu
South Sulawesi
Gorontalo
Lampung
Papua
West Papua
East Nusa
Tenggara
0,00%
10,00%
20,00%
30,00%
40,00%
50,00%
60,00%
70,00%
Financial Literacy Index by Province 2019
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of money, to achieve individual financial well-being (Atkinson & Messy, 2012; Khan et al., 2017; Remund,
2010; Zait & Bertea, 2014).
One particularly interesting region as a place to study college students’ financial literacy in West
Java is Bandung City. Bandung city is named the best student city in Southeast Asia (Humas Kota
Bandung, 2022). It hosts the most college students out of any other region in West Java Province, hosting
79.194 students in 2021(Agustian, 2023). Bandung city is the place of many top-ranking universities of
Indonesia, such as Bandung Institute of Technology (ITB), Padjajaran University (Unpad), Indonesian
Education University (UPI), and Parahyangan Catholic University (Unpar) (Quacquarelli Symonds,
2023b). Bandung also have a high economic growth with societal lifestyle that sprouts many
consumptive characteristics which affects the financial behavior of its college students (Kartawinata et
al., 2021).
Therefore, this research is also inspired by the preliminary research that the author conducted to
investigate the current financial stress and financial well-being of Bandung college students, specifically
in Institut Teknologi Bandung. Institut Teknologi Bandung (ITB) ranks among the best universities in
Indonesia and is a large-sized university in Bandung (uniRank, 2023). By conducting exploratory
research in ITB, the researcher could get a view of the financial conditions in the top-university in
Bandung. It is conducted through a survey via Google Forms and distributed through a convenience
sampling which accumulated 38 responses from undergraduate students of ITB. Validity and Reliability
tests were then conducted via SPSS, which shows that the scale used for Financial Stress adapted from
the FSS-CV by (Northern et al., 2010) and the Financial Well-Being Scale adapted from the CFPB
Financial Well Being Scale (CFPB, 2017), are both valid and have very good reliability scores.
This preliminary research resulted in several interesting takeaways. In the Financial Stress Scale,
a set of financial stressors statements are presented, and the respondents are asked to scale whether each
statement crossed their minds within the past 6 months in a Likert Scale, starting from 0 (never) to 5
(always). The stressor with the highest average score was “Knowing you make less money than most of
your peers.” with 68.4% of the respondents admitting that it has crossed their minds. This indicates that
peer-pressure was one of the main causes of financial stress for college students in ITB.
Some stressors that are common among the respondents are related to bad personal financial
ratios, since most of the respondents had thought about: “living from paycheck to paycheck” (73.7%),
“Barely making enough money to cover expenses” (76.3%), “Not making enough money to be able to
cover unexpected expenses” (76.3%), and “Holiday Expenses” (57.9%). Another stressor that is
common among the respondents comes from possible future occurrences/situations, since most of the
respondents had thought about: “. Worrying about having enough money to retire” (65.8%) and “Paying
Taxes” (54.1%). These findings support the need to study the relations between financial and subjective
well-being with the financial literacy of undergraduate students in Bandung.
Even though many stressors are identified, most of the respondents had never thought about some
situations. Most of the respondents have never thought about events related to the activity of making a
loan or be in debt to another party, such as: “Being contacted by creditors” (86.8%), “Having large debt”
(84.2%), “Having loans with high interest rates” (81.6%), “Having a low credit score” (78.9%), and
“Getting something repossessed” (78.9%). Although one may argue this demonstrates the secure
financial standing of these students, a case can also be made that they lack the knowledge regarding the
activity of making a loan. This low knowledge may be related to the general negative sentiments of
Indonesian society towards borrowing/credit activities (Lestari et al., 2015; Putra et al., 2022), which
can be misleading since a loan can be an effective means of financing to attain a personal financial goal.
From the Financial Well Being scale, some situations/ statements that the respondents report
about themselves seem to be complimented by the financial stressors and indicate that there is a problem.
Most of the respondents say that they sometimes/often/always “behind with their finances” (65.8%).
The majority (65.8%) also stated that the statement “I am securing my financial future” did not or just
partially describe themselves. However, most of the respondents have also reported that they never
thought about “being behind on payments” or “having to declare bankruptcy”. These findings suggest
that these undergraduate students are not yet secured with their present and future finances, but they did
not think about the possibilities of being behind on payments or being bankrupt.
This research also gathers data of some determinants of financial behavior, as summarized from
the meta-analysis by (Bartholomae & Fox, 2021), which includes: financial autonomy from parents,
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employment, family socioeconomic background, parenting style, and family financial socialization.
Other financial related factors, such as income level, expenses items, and financial tracking habits. Most
of the respondents (61%) depend entirely on their parents as a source of income, although the majority
have unstable streams of income aside from their parents. Therefore, from the research of the
preliminary research, this research aims to capture a larger sample, which is the college students from
universities located in Bandung City, West Java.
RESEARCH METHOD
This research aims to explore and evaluate the relationship between financial behavior and its
determinants, financial behavior to financial well-being, and financial well-being to the subjective well-
being of college students in universities located in Bandung City, Indonesia. To reach this objective,
more than 300 respondents’ data were collected through quantitative approach using questionnaire. The
collected data is then analyzed with descriptive statistics and the methodology of Partial Least Square
Structural Equation Modelling (PLS-SEM). 9 latent variables are used in the model, and 9 hypothetical
relationships are established between them
PLS-SEM includes the evaluation of outer model / measurement model and inner model /
structural model. The evaluation of outer model includes the assessment of reflective indicators
(reliability and validity analysis), and the evaluation of inner model of formative indicators (Collinearity
test, Path Coefficients and Statistical Significance through bootstrapping, Coefficient of determination
[R
2
], Cross-validated redundancy [Q
2
], effect size [F
2
], total indirect and total effect, and mediation test).
PLS-SEM for this study will be done through the software SmartPLS.
RESULT AND DISCUSSION
Partial Least Square Structural Equation Modelling (PLS-SEM) Analysis Result
Each latent variables relate to manifest variables/ causal indicators from the measurement of each
latent variable, resulting in the initial outer model in the Figure 4 below:
Figure 4 Outer Model measurement results (Measurement Model)
Source: Smart-PLS Processing Results
For the PLS-SEM Analysis, two of the latent variables are formatively measured construct, which
are Financial Knowledge and Financial Behavior. This means that the indicators cause these latent
variables, and are not interchangeable among themselves, hence symbolized by the arrow pointing from
the yellow indicator to these blue latent constructs (Wong, 2013). The indicator for Financial Behavior
is the 4 dimensions of Financial Behavior: Budgeting (FBB), Active Saving (FBS), Making Ends Meet
(FBE), and Choosing Financial Product and Services (FBP). These indicators are metric and are
comprised of the final scores for each Financial Behavior dimension, which scoring has been explained
previously in the Descriptive Statistics subchapter. The researcher chose to use the final score of each
dimension as indicator for Financial Behavior as opposed of using the questions from each of these
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dimensions, is due to the scoring differences for each of the question, that may disrupt the outer model
evaluation (OECD, 2022).
1. Convergent Validity Analysis
a) Outer Loadings
Table 1 Outer Loadings of the revised outer model (Cont.)
Outer loadings
1
1
0.745
0.623
0.803
0.749
0.703
0.871
0.844
0.693
0.741
0.677
0.731
0.806
0.804
0.703
0.74
0.754
0.762
0.683
0.741
0.714
0.73
0.72
0.699
0.726
1
1
0.946
0.81
0.762
1
0.802
0.857
0.844
0.873
0.79
0.805
0.781
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Table 1 Outer Loadings of the revised outer model (Cont.)
Outer loadings
0.773
0.763
0.76
0.741
0.747
0.805
0.797
0.797
0.774
0.755
b) Average Variance Extracted (AVE)
All the reflective variables fulfilled the minimum required value, and therefore displayed
convergent validity. The AVE for each construct can be seen in Table 2 below:
Table 2 Average Variance Extracted of reflective constructs
Variable
Average variance extracted (AVE)
Result
Financial Well-Being
0.529
VALID
Life Satisfaction
0.695
VALID
Parental Financial Socialization
0.566
VALID
Peer Pressure
0.711
VALID
Positive-Negative Affect
0.601
VALID
Figure 5 Revised Outer Model of the research
2. Construct Reliability Analysis
Construct Reliability Analysis is done through measuring Cronbach Alpha and Composite
Reliability, and it is applicable for reflectively measured construct. Acceptable scores as
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mentioned in the previous chapter is 0.6 for both Cronbach Alpha and Composite Reliability. All
reflectively measured variable is reliable, as seen on the Table 3 below:
Table 3 Construct Reliability through Cronbach's Alpha and Composite Reliability
Cronbach's
alpha
Result
Composite
reliability
(rho_a)
Result
Composite
reliability
(rho_c)
Result
Financial
Well-Being
0.901
Very Good
Reliability
0.903
Good
Reliability
0.918
Good
Reliability
Life
Satisfaction
0.89
Very Good
Reliability
0.891
Good
Reliability
0.919
Good
Reliability
Parental
Financial
Socialization
0.961
Very Good
Reliability
0.682
Acceptable
0.948
Good
Reliability
Peer Pressure
0.828
Very Good
Reliability
1.316
Good
Reliability
0.88
Good
Reliability
Positive-
Negative
Affect
0.94
Very Good
Reliability
0.941
Good
Reliability
0.948
Good
Reliability
3. Discriminant Validity Analysis
Discriminant Validity Analysis will be assessed using Fornell& Larcker Criterion, Cross
Loading, and HTMT. The result can be seen in the tables below.
Table 4 Fornell Larcker Criterion Analysis
Financia
l Well-
Being
Incom
e
Level
Life
Satisfactio
n
Living
Arrangement
s
Parental
Financial
Socializatio
n
Peer
Pressur
e
Positive
-
Negativ
e Affect
Subjectiv
e Social
Status
Financial
Well-Being
0.727
Income Level
0.041
1
Life
Satisfaction
-0.779
0.029
0.834
Living
Arrangement
s
-0.018
0.013
-0.009
1
Parental
Financial
Socialization
0.66
0.073
-0.513
-0.028
0.752
Peer
Pressure
0.67
0.094
-0.614
-0.045
0.585
0.843
Positive-
Negative
Affect
0.849
0.097
-0.668
-0.025
0.729
0.69
0.775
Subjective
Social Status
0.086
0.052
0.014
0.005
0.109
0.019
0.04
1
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Table 5 Cross Loadings of each indicator (Cont.)
Table 6 HTMT Ratio
FB
FK
FWB
IL
LS
LA
PFS
PP
PNA
SSS
Financial
Behavior
Financial
Knowledge
0.43
Table 4.1. Cross Loadings of each indicator (Cont.)
Financial
Behavior
Financial
Knowledge
Parental
Financial
Socialization
Financial
Well-
Being
Income
Level
Living
Arrangements
Peer
Pressure
Subjective
Social
Status
Life
Satisfaction
Positive-
Negative
Affect
FBS
1
0.43
0.079
-0.058
0.071
-0.021
-0.027
0.004
0.028
-0.04
FK7
0.43
1
-0.001
-0.033
0.135
0.006
0.002
-0.086
0.003
-0.044
FS1
0.015
-0.006
0.745
0.552
-0.043
0.024
0.455
0.18
-0.402
0.607
FS11
-0.017
-0.04
0.623
0.575
-0.035
-0.073
0.555
0.054
-0.503
0.611
FS12
0.028
0.027
0.803
0.552
-0.009
-0.03
0.515
0.037
-0.47
0.642
FS13
0.008
-0.022
0.749
0.556
-0.018
-0.028
0.509
0.154
-0.423
0.613
FS14
-0.014
-0.076
0.703
0.562
0.002
-0.005
0.449
0.052
-0.409
0.611
FS15
0.069
-0.045
0.871
0.601
0.061
-0.045
0.529
0.075
-0.455
0.638
FS16
0.06
0.025
0.844
0.544
0.098
0.002
0.53
0.053
-0.444
0.622
FS2
-0.013
0.003
0.693
0.516
-0.01
-0.037
0.433
0.19
-0.365
0.578
FS3
0.029
-0.028
0.741
0.561
-0.01
-0.04
0.44
0.154
-0.41
0.609
FS4
-0.011
0.037
0.677
0.555
0.018
0.012
0.449
0.121
-0.419
0.607
FS5
0.005
-0.053
0.731
0.614
0.064
-0.048
0.516
0.13
-0.448
0.626
FS6
0.033
-0.017
0.806
0.565
0.011
-0.019
0.47
0.184
-0.43
0.639
FS7
0.025
0.002
0.804
0.544
0.038
-0.065
0.473
0.066
-0.408
0.619
FS8
-0.023
-0.052
0.703
0.505
-0.069
-0.045
0.476
0.099
-0.378
0.618
FWB1
-0.057
0.024
0.513
0.74
0.03
0
0.542
0.032
-0.66
0.683
FWB10
0.003
-0.044
0.505
0.754
0.099
0.013
0.46
0.047
-0.524
0.634
FWB2
-0.108
-0.029
0.464
0.762
-0.045
0.01
0.547
0.01
-0.674
0.624
FWB3
-0.032
-0.047
0.511
0.683
0.122
-0.052
0.483
0.051
-0.472
0.596
FWB4
-0.073
0.052
0.424
0.741
0.01
-0.017
0.563
-0.071
-0.682
0.608
FWB5
-0.009
-0.03
0.572
0.714
0.166
-0.011
0.426
0.166
-0.455
0.669
FWB6
-0.051
-0.08
0.473
0.73
-0.035
-0.026
0.47
0.135
-0.552
0.572
FWB7
-0.068
-0.069
0.438
0.72
0.023
-0.041
0.383
0.141
-0.468
0.61
FWB8
0.027
0.017
0.442
0.699
-0.122
0.006
0.523
0.052
-0.623
0.559
FWB9
-0.042
-0.057
0.471
0.726
0.068
-0.023
0.445
0.099
-0.499
0.612
IL
0.071
0.135
0.073
0.041
1
0.013
0.094
0.052
0.029
0.097
LA
-0.021
0.006
-0.028
-0.018
0.013
1
-0.045
0.005
-0.009
-0.025
PP2
-0.032
-0.014
0.485
0.569
0.044
-0.066
0.946
0.004
-0.531
0.596
PP3
-0.011
-0.004
0.565
0.647
0.155
0.021
0.81
-0.003
-0.571
0.635
PP4
-0.012
0.052
0.55
0.59
0.123
-0.024
0.762
0.07
-0.537
0.611
SSS
0.004
-0.086
0.109
0.086
0.052
0.005
0.019
1
0.014
0.04
SWBL1
0.027
0.055
-0.428
-0.637
0.019
0.038
-0.474
-0.031
0.802
-0.526
SWBL2
0.045
-0.017
-0.44
-0.66
-0.014
-0.016
-0.548
0.02
0.857
-0.55
SWBL3
-0.044
-0.027
-0.376
-0.628
0.058
-0.036
-0.493
-0.006
0.844
-0.536
SWBL4
0.04
-0.016
-0.399
-0.687
0.025
-0.029
-0.548
0.06
0.873
-0.572
SWBL5
0.046
0.021
-0.497
-0.632
0.036
0.006
-0.492
0.009
0.79
-0.602
SWBN1
-0.048
-0.039
0.521
0.72
0.06
0.004
0.599
0.037
-0.595
0.805
SWBN2
-0.108
-0.054
0.551
0.692
0.057
-0.044
0.556
0.053
-0.568
0.781
SWBN3
-0.069
0
0.603
0.745
0.061
0.002
0.681
-0.039
-0.643
0.773
SWBN4
-0.065
-0.074
0.501
0.667
0.048
-0.041
0.536
0.074
-0.583
0.763
SWBN5
-0.036
0.03
0.559
0.656
-0.003
0.013
0.532
0.039
-0.59
0.76
SWBN6
-0.042
-0.061
0.476
0.628
0.022
0.012
0.515
-0.01
-0.599
0.741
SWBP1
0.038
-0.013
0.56
0.594
0.091
-0.066
0.438
0.056
-0.407
0.747
SWBP2
-0.006
-0.013
0.621
0.671
0.155
-0.052
0.523
0.091
-0.457
0.805
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Financial
Well-Being
0.068
0.065
Income Level
0.071
0.135
0.104
Life
Satisfaction
0.052
0.034
0.861
0.039
Living
Arrangement
s
0.021
0.006
0.029
0.013
0.032
Parental
Financial
Socialization
0.031
0.039
0.735
0.043
0.567
0.042
Peer
Pressure
0.023
0.029
0.803
0.137
0.737
0.047
0.695
Positive-
Negative
Affect
0.057
0.053
0.918
0.102
0.726
0.034
0.798
0.802
Subjective
Social Status
0.004
0.086
0.116
0.052
0.032
0.005
0.139
0.033
0.055
From the analysis, there are some discriminant validity problems that can be identified. From
Table 6 regarding Fornell-Larcker Criterion. The acceptable criterion is that the square root of AVE by
a construct must be greater than any other construct relation in the model. However, the square root
AVE of Financial Well-Being (0.727) is smaller than the correlation between Financial Well-Being and
Positive Negative Affect, which may indicate that there is a lack of distinctiveness between the two
measures, due to the variance of the FWB indicator is explained more by the Positive-Negative Affect
(Cheung et al., 2023) .
From the cross-loading results in Figure 21, a minor discriminant validity is identified,
where the factor loading of indicator FS11 to its own latent variable Family Financial
Socialization, is lower than the cross loading of indicator SWBP3 to Financial Socialization,
therefore cross loading is identified. However, this cross-loading difference is relatively small,
with differences between the factor loading being 0.001.
From the HTMT Ratio in Figure 5, it is apparent that some of the HTMT Ratio falls above
the threshold of 0.85, namely between Life Satisfaction and Financial Well-Being (0.861), and
Positive-Negative Affect to Financial Well-Being (0.918), which would indicate that
discriminant validity problem is present. From these tests, there are indications of discriminant
validity problems in the constructs. However, it is probable that this problem is related to
multicollinearity, since multicollinearity may reduce discriminant validity (Kyriazos & Poga,
2023). Therefore, Collinearity Test is done next to see whether the problem persists.
4. Collinearity Test
Table 7 Iner Model VIF
VIF
Financial Behavior -> Financial Well-Being
1
Financial Knowledge -> Financial Behavior
1.028
Financial Well-Being -> Life Satisfaction
1
Financial Well-Being -> Positive-Negative Affect
1
Income Level -> Financial Behavior
1.032
Living Arrangements -> Financial Behavior
1.002
Parental Financial Socialization -> Financial Behavior
1.544
Peer Pressure -> Financial Behavior
1.535
Subjective Social Status -> Financial Behavior
1.027
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5. Coefficient of Determination (R2) and Cross-Validated Redundancy (Q2) Test
Table 8 R-squared and Q-squared value of endogenous variables
R-square
Result
Q²predict
Predictive
Relevance
Financial Behavior
0.201
Weak
-0.121
None
Financial Well-Being
0.003
Weak
-0.003
None
Life Satisfaction
0.606
Strong
-0.002
None
Positive-Negative
Affect
0.72
Strong
-0.001
None
The value outcome of R
2
(coefficient of determination) and Q
2
(Cross-Validated Redundancy) is
presented in Table 4.26. The R
2
value explains the variance in the endogenous variable explained by the
exogenous variables (a measure of the model’s explanatory power), and the Q
2
value explains the
predictive relevance (Hair et al., 2019). Rule of thumb for R2 is 0.67-0.75 (substantial / strong), 0.33-
0.5 (moderate), and 0.01-0.25 (weak) for predictive accuracy (Cohen, 1988; F. Hair Jr et al., 2014; Fauzi,
2022; Hair et al., 2019). Meanwhile, predictive relevance is considered as existent with Q2 above 0 and
categorized respectively as weak/small, moderate/medium, and strong/large degrees for Q2 value of: 0
- 0.02; 0.15 - 0.25; 0.32 - 0.5 (Fauzi, 2022; Hair et al., 2019).
From the results, the endogenous variable financial behavior and Financial Well-Being have a
weak coefficient of determination, which mean that they have weak predictive accuracy (F. Hair Jr et
al., 2014). R2 score of 0.003 would mean that only 0.3% of the change in Financial Well-Being is
explained by the exogenous variable Financial Behavior. Meanwhile the change in variable Life
Satisfaction and Positive-Negative Affect is greatly explained by the exogenous variable Financial Well-
Being. It can also be inferred that the overall model has no predictive relevance, which mean that the
model will not predict future samples as well as it did in the current research sample (Ivanescu et al.,
2016).
6. Hypothesis Testing
The hypothesis test is done through measuring structural path significance by Bootstrapping,
Path Coefficient, and Total Indirect and Total Effect.
a) Structural Path Significance through Bootstrapping and Path Coefficient
The complete illustration of the model along with the corresponding Path Coefficients and T-
values for each path can be seen in the Figure 6 below.
Figure 6 Path Coefficients and T-values of the inner model
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b) Path coefficient is also calculated to indicate whether the relationship between the constructs is
positive or negative. The summary of the Path Coefficients along with the T-Statistics of the
inner model can be seen in the Table 9 below:
Table 9 Summary of Path Coefficient and T-Statistics after bootstrapping
Original
sample
(O)
Sample
mean (M)
Standard
deviation
(STDEV)
T statistics
(|O/STDEV|)
P values
Financial Behavior ->
Financial Well-Being
-0.058
-0.058
0.058
1.007
0.314
Financial Knowledge ->
Financial Behavior
0.922
0.915
0.078
11.788
0
Financial Well-Being ->
Life Satisfaction
-0.779
-0.78
0.028
27.475
0
Financial Well-Being ->
Positive-Negative Affect
0.849
0.85
0.019
43.759
0
Income Level ->
Financial Behavior
0.012
0.011
0.053
0.236
0.814
Living Arrangements ->
Financial Behavior
-0.055
-0.056
0.117
0.473
0.636
Parental Financial
Socialization -> Financial
Behavior
0.141
0.067
0.146
0.964
0.335
Peer Pressure ->
Financial Behavior
-0.113
-0.069
0.095
1.188
0.235
Subjective Social Status -
> Financial Behavior
0.027
0.037
0.048
0.561
0.575
According to the Table 4.27 above, only three variable relationships have T statistics score more
than 1.96, in order of significance being between: (1) Financial Well-Being to Positive-Negative Affect;
(2) Financial Well-Being to Life Satisfaction; and (3) Financial Knowledge to Financial Behavior.
Therefore, the result of the Hypothesis Testing can be summarized in the Table 10 below:
Table 10 Hypothesis Testing Result
Hypothesis
Path
Path
Coefficien
t
T-
Statisti
cs
P-
value
St.
Dev
Result
Why?
1a
Financial
Knowledge ->
(+) Financial
Behavior
0.922
11.788
0
0.07
8
SUPPORTED
T-
statistic
s >
1.96; P-
value <
0.05
1b
Family
Financial
Socialization
-> (+)
Financial
Behavior
0.141
0.964
0.335
0.14
6
NOT
SUPPORTED
T-
statistic
s <
1.96; P-
value >
0.05
1c
Peer Pressure
-> Financial
Behavior
-0.113
1.188
0.235
0.09
5
NOT
SUPPORTED
T-
statistic
s <
1.96; P-
value >
0.05
1d
Living
Arrangements
-0.055
0.473
0.636
0.11
7
NOT
SUPPORTED
T-
statistic
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Table 10 Hypothesis Testing Result
Hypothesis
Path
Path
Coefficien
t
T-
Statisti
cs
P-
value
St.
Dev
Result
Why?
-> Financial
Behavior
s <
1.96; P-
value >
0.05
1e
Income Level
-> (+)
Financial
Behavior
0.012
0.236
0.814
0.05
3
Not Supported
T-
statistic
s <
1.96; P-
value >
0.05
1f
Socioeconomi
c Status -> (+)
Financial
Behavior
0.027
0.561
0.575
0.04
8
Not Supported
T-
statistic
s <
1.96; P-
value >
0.05
2
Financial
Behavior ->
(+) Financial
Well-Being
-0.058
1.007
0.314
0.05
8
Not Supported
T-
statistic
s <
1.96; P-
value >
0.05
3a
Financial
Well-Being -
> (+)
Positive-
Negative
Affect
0.849
43.759
0
0.01
9
Supported
T-
statistic
s <
1.96; P-
value >
0.05
3b
Financial
Well-Being -
> (+) Life
Satisfaction
-0.779
27.475
0
0.02
8
Not Supported
Path
Coeffici
ent < 0
7. F Square (F2) Effect Size
Table 11 F-square values
f-square
Result
Financial Behavior -> Financial Well-Being
0.003
No Effect
Financial Knowledge -> Financial Behavior
0.227
Large
Financial Well-Being -> Life Satisfaction
1.539
Large
Financial Well-Being -> Positive-Negative Affect
2.576
Large
Income Level -> Financial Behavior
0
No Effect
Living Arrangements -> Financial Behavior
0.001
No Effect
Parental Financial Socialization -> Financial Behavior
0.016
No Effect
Peer Pressure -> Financial Behavior
0.01
No Effect
Subjective Social Status -> Financial Behavior
0.001
No Effect
Cohen (1988) established the categorization for effect sizes as seen from the measure of F
2
(>=0.02 is small; >= 0.15 is medium;>= 0.35 is large). Through this analysis, weak relationship is
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detected in most of the path relation, except for some exogenous variable having a large effect on
endogenous variable, namely: Financial Knowledge to Financial Behavior, Financial Well-Being to Life
Satisfaction, and Financial Well-Being to Positive-Negative Affect. For interpretation example, this
means Financial Knowledge explains 22.7% of the variance in Financial Behavior.
Discussion
The findings of the research will be discussed in the following paragraphs. To begin, this research
confirms that Financial Knowledge is a driver to Financial Behavior in college students and confirms
the relation between Financial Well-Being of College Students in Bandung with both dimensions of
their Subjective Well-Being. However, the formulation of the final research model is not as
straightforward. Through validity and reliability analyses, several indicators for the variables needed to
be omitted, hence adding further notes to the conclusion of these hypotheses. The most notable change
is in the variable of Financial Knowledge, Financial Behavior, and Peer Pressure.
The remaining indicator with an acceptable outer loading for Financial Behavior is the Active
Saving Dimension, which means the only dimension where more than 50% of the variance in indicator
is explained by Financial Behavior. This might be due to this dimension being the most relevant in the
context of college students in Bandung. The Active Saving dimension reflects the various savings
behaviors that are exhibited by college students in Bandung. Much of the Indicator for Financial
Knowledge is omitted as well, with one remaining indicator FK7 which indicates the knowledge
regarding risk diversification in stock investment. For the Peer Pressure Scale, only 1 of the 4 indicators
are omitted, namely indicator PP1 which states, “I give into peer pressure easily”. However, the
remaining indicators still reflect the variable peer pressure through example peer pressure situations.
Future research on college student’s financial behavior might benefit better in using
measurements other than the OECD Financial Literacy survey, one that is particularly tailored towards
Financial Knowledge and Financial Behavior in the university level and one that is reflectively measured
and relevant in Indonesian context.
Through PLS-SEM analysis, some discriminant validity problems are indicated, however through the
multicollinearity test all the indicators showed acceptable VIF values, which means the analysis can
proceed to the hypothesis testing stage. The discussion for each of the hypothesis will be explained
below.
Hypothesis 1a: Financial Knowledge has a positive influence on Financial Behavior for
undergraduate students in Bandung.
Hypothesis 1a is supported since the research findings supported the positive relation of Financial
Knowledge to Financial Behavior, indicated by the positive Path Coefficient and T-statistics exceeding
1.96. This study findings are aligned with the previous research on Indonesian college students’ financial
literacy (Megananda & Faturohman, 2022; Suyanto et al., 2021) and proved differently than the results of
the research of Nyoto (2021) which said that financial knowledge has no significant influence on
Financial Behavior. However more specifically can be inferred, particularly from the findings on the
model, that the Financial Knowledge indicated by understanding of risk diversification proved to
influence the active saving behavior of Bandung college students significantly and positively.
Hypothesis 1b: Family Financial Socialization has a positive influence on Financial Behavior for
undergraduate students in Bandung.
Hypothesis 1b is not supported and therefore not supported, because the T-statistics value being
below 1.96 proved that it is not significant. More specifically, Family Financial Socialization is found
to have a positive correlation with Financial Behavior, only for the sample gathered in this research, and
cannot be used to generalize the population of Bandung College students. These findings might be
attributable to the lack of Financial Behavior indicators that passed the test on this research. However,
the descriptive statistics report that most of Bandung college students experience financial socialization
through their parents.
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Hypothesis 1c: There is a relationship between Peer Pressure and Financial Behavior of
undergraduate students in Bandung.
Hypothesis 1c is not supported since the T-statistics proved that the relationship is not significant.
This finding might be attributable to the measurements of Peer Pressure and Financial Behavior that is
not relevant for the context of Bandung College Students. Other measurements in peer pressure should
also be considered, one that is particularly designed for assessing Peer Pressure for Emerging Adults
age group or uses other measurement of pressure to affect certain behavior, such as the measurement of
perceived peer subjective norm (Watson & Barber, 2017). Therefore, it is concluded that Peer Pressure
does not influence the Financial Behavior of college students living in Bandung. The result from the
descriptive statistics also supports this finding, as Bandung college students reported that they feel
relatively low peer pressure.
Hypothesis 1d: There is a relationship between Living Arrangements and Financial Behavior of
undergraduate students in Bandung.
Hypothesis 1d is also not supported since the T-statistics value falls below 1.96, deeming the
relationship not significant for Bandung College Students Population. This result might come from the
lack of variance captured in the measurement for Living Arrangement, since it only has two options of
whether the students live in or away from their parental home. Future research might benefit in providing
more option of living arrangements away, such as detailing whether the students live away by renting
alone, renting with flat mates, or in a student housing (Watson & Barber, 2017). There might be a relation
between financial socialization, living arrangements, and financial behavior that can be studied on
Indonesian College students.
Hypothesis 1e: Income Level has a positive influence on Financial Behavior of undergraduate
students in Bandung.
Although the path coefficient of this relationship is confirmed to be positive, the result from this
research’s sample is not significant to be used to generalize the whole Bandung College student
population, as seen from the T-statistics score that falls below 1.96. These results might be attributable
to the lack of Financial Behavior dimension that’s eligible to measure this relationship. Therefore, it can
be concluded that Income Level has no influence Financial Behavior on Bandung College Student based
on the findings in this research.
Hypothesis 1: Socioeconomic Status has a positive influence on Financial Behavior of
undergraduate students in Bandung.
The path coefficient of this relationship is confirmed to be positive, which would confirm the
positive influence. However, the result from this research’s sample is not significant to be used to
generalize the whole Bandung College student population, as seen from the T-statistics score that falls
below 1.96. Therefore, this hypothesis is not supported. Socioeconomic Status, which is measured
through subjective social status, does not influence the Financial Behavior of college students living in
Bandung, as this study found.
Hypothesis 2: Financial Behavior has a positive influence on Financial Well-Being of
undergraduate students in Bandung.
This Hypothesis is not supported since the T-statistics value falls below 1.96. Although much
previous research has established this relationship (Atkinson & Messy, 2012; Brüggen et al., 2017; Goyal et
al., 2021; Megananda & Faturohman, 2022; Rahman et al., 2021; Sabri et al., 2023), this study is not aligned
with those findings. This might be attributable to the measurement of Financial Behavior, as previously
mentioned.
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Hypothesis 3a: Financial Well-Being has a positive influence on Positive-Negative Affect &
Hypothesis 3b: Financial Well-Being has a positive influence on Satisfaction with Life for
Bandung College Student
Both hypotheses are established to conclude the relation between Financial Well-Being and
Subjective Well-Being of college students in Bandung. The T-statistics for path of Financial Well-Being
to Positive-Negative Affect and Life Satisfaction is greater than 1.96, which would mean that these
relationships are significant. However, the path coefficient of Financial Behavior to Positive-Negative
Affect yields positive and to Life Satisfaction yields negative. Therefore, Hypothesis 3a is supported,
meanwhile Hypothesis 3b is not supported.
Financial Well-Being is found to positively influence subjective Well-Being in terms of Positive-
Negative Affect for Bandung college students. However, it is found to negatively affect Life
Satisfaction. These findings are partially aligned with previous study on the effect of Financial Well-
Being to Subjective Well-Being (Brüggen et al., 2017; Iannello et al., 2021; Netemeyer et al., 2018).
This might be due to measurement differences, since most of these studies use the CIT, BIT, or
Flourishing Scale by Diener, which combines aspects of positive-negative affect, life satisfaction, and
psychological Well-Being (Diener et al., 2009; Su et al., 2014). Another explanation to this finding
might come from the fact that the life satisfaction of Bandung college students is not determined solely
from being financially healthy, since the coefficient of determination for Life Satisfaction 0.606. This
means that there is a remaining 40% of the variance of Life Satisfaction that comes from variables other
than Financial Behavior.
This reasoning is supported by the average life satisfaction score of Bandung college students,
which ranks as having “Average” life satisfaction, which indicates that there are many areas that they
wish to improve in their life. Previous research on college students’ have listed many other factors that
significantly influence their life satisfaction: satisfaction with food and family life in the context of
developing countries (Schnettler et al., 2017), employment status, having children, quality of
relationship, spending time more usefully, and assertiveness in decision making (Behlau, 2010) ; self-
esteem and perceived poverty on poor college students (Liu & Fu, 2022). Future research may benefit
by looking into what constitutes life satisfaction for college students in Bandung.
CONCLUSION
This research provides conclusion by answering the 3-research question mentioned in the first
chapter.
RQ1: How does income level, living arrangements, socioeconomic status, family financial
socialization, peer pressure, and financial knowledge affect the financial behavior of undergraduate
students in Bandung? This research found that the relationship between income level, living
arrangements, socioeconomic status, family financial socialization and peer pressure to the financial
behavior of Bandung college students is not supported. However, this research confirms that Financial
Knowledge positively influences the Financial Behavior of Bandung college students. The descriptive
statistics result also indicate that Bandung college students learn a lot of things regarding finance from
their parents when they grow up. This research also gave insight that most college student responses
live away from their parental home, felt low level of peer pressure, have a monthly income between
Rp1.500.000 – Rp2.000.000, and perceive their social status tier at around the 7
th
mark. This study adds
to the body of knowledge that has provided different conclusions regarding this relationship, by
confirming this relationship in the context of college students in the city of Bandung. This study also
explores the relation that has studied limitedly in the context of Indonesian college students, which are
the relationship between Living Arrangements and peer pressure to Financial Behavior.
RQ2: How does Financial Behavior affect Financial Well-Being of undergraduate students in
Bandung? This study does not support the relationship between Financial Behavior and Financial Well-
Being in Bandung college students. However, through the descriptive statistics, this study has provided
insights on Bandung college student’s financial behavior. Most notable insights is that: (1) most college
students are personally responsible for their own money management; (2) save their money in saving/
deposit account; (3) did not save their money in stocks, bonds, or crypto-assets; (4) showed healthy
behaviors in scenario where they have to make ends meet and did not access credit from moneylender
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or personal loan (5) showed healthy behavior in choosing financial product by comparing between
different options and are significantly influenced by recommendation from their friends, family, and
peers.
RQ3: How does Financial Wellbeing affect Subjective Well-Being of undergraduate students in
Bandung? This study partially supports how Financial Well-Being relates with Subjective Well-Being,
by showing that it positively influences the positive-negative affect, but negatively influences the Life
Satisfaction of Bandung college students. From the descriptive statistics, we can see that most Bandung
college students have “Average” life satisfaction score, indicating general satisfaction but have many
areas in life where they wish to improve. However, they display mostly positive emotions and mostly
positive subjective well-being.
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