Available via license: CC BY 4.0
Content may be subject to copyright.
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
https://doi.org/10.24294/jipd9732
1
Article
Financial cognitive ability dimensions and investors’ behavioral intentions
to participate in the stock market: Mediated by financial capability
Rafid Ullah, Hishamuddin Bin Ismail*, Ali Zeb
Faculty of Business, Multi Media University, Cyberjaya 63100, Malaysia
* Corresponding author: Hishamuddin Bin Ismail, hisham@mmu.edu.my
Abstract: This study investigates how financial cognitive abilities influence individual
investors’ intentions to engage in the stock market, particularly considering the mediating role
of financial capability. It seeks to address the gaps in understanding the factors that drive
investors’ participation in emerging markets like Pakistan, highlighting the importance of
financial knowledge, financial planning, and financial satisfaction and financial capability.
Data were collected from 377 individual investors through a self-administered questionnaire
using a cross-sectional design and non-probability convenience sampling approach. Results
reveal that financial knowledge affects investors’ intentions both directly and indirectly, with
financial capability serving as a partial mediator. Financial planning influences intentions
indirectly through complete mediation, while financial satisfaction affects intentions in both
direct and indirect ways, with partial mediation. The study provides valuable insights for the
researchers, individual investors, governmental officials, policymakers, and stock market
regulators in context of emerging economies like Pakistan, highlighting key determinants of
stock market participation.
Keywords: financial knowledge; financial planning; financial satisfaction; financial
capability; behavioral intention
1. Introduction
Behavioral finance is crucial for understanding how individuals make decision-
making (Ainia and Lutfi, 2019), emphasizing the psychological aspects of financial
decisions (Hamza and Arif, 2019). This knowledge is essential for investors to make
informed choices (Nepal et al., 2023). Unlike traditional financial theories, which
assumes that investors behave logically and rationally (Ainia and Lutfi, 2019),
behavioral finance research shows that investors often act in ways that are neither
logical nor rational (Cervellati et al., 2024). Earlier research indicates that various
factors influence individuals’ financial decisions, leading them to display a mix of
cognitive and emotional responses that stray from purely rational decision-making
(Shehata et al., 2021). Behavioral finance supports the idea that cognitive errors and
thought processes affect financial investment choices (Mate and Dam, 2017). Stock
market investors frequently adhere to the concept of “bounded rationality,” making
decisions that are satisfactory rather than ideal, aligning with the “rational
expectations” theory (Garnier et al., 2024).
When making financial investment decisions, various factors significantly influence
the process, such as an investor’s cognitive abilities and beliefs (Dimmock and
Kouwenberg, 2010), their personal characteristics (Van Rooij and Teppa, 2014), their
behavioral inclinations (Georgarakos and Pasini, 2011), and their prior experiences (Lo,
CITATION
Ullah R, Ismail HB, Zeb A. (2025).
Financial cognitive ability
dimensions and investors’ behavioral
intentions to participate in the stock
market: Mediated by financial
capability. Journal of Infrastructure,
Policy and Development. 9(2): 9732.
https://doi.org/10.24294/jipd9732
ARTICLE INFO
Received: 18 October 2024
Accepted: 11 November 2024
Available online: 7 February 2025
COPYRIGHT
Copyright © 2025 by author(s).
Journal of Infrastructure, Policy and
Development is published by EnPress
Publisher, LLC. This work is licensed
under the Creative Commons
Attribution (CC BY) license.
https://creativecommons.org/licenses/
by/4.0/
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
2
2005) has determined to enact a massive role in the intention to partake in the stock
marketplace. The individuals’ behavioral biases and cognitive skills appear to affect their
stock market involvement decision. Therefore, in order to improve a country’s stock
market performance, regulators of market and governments should comprehend that how
investor decision are affected by the dimensions of the financial cognitive abilities and
their willingness to invest in the stock market (Akhter and Hoque, 2022).
In recent years, various well-founded research studies have aimed to investigate
the psychology pursuing stock market immersion. Evidence illustrates that the
investor’s financial literacy level directly affects their financial market involvement’s
intentions (Hadi, 2017). Development of financial asset management planning is
crucial segment of cognitive skills that will help to maximize individual’s opulence
(Bhaduri et al., 2023). Future financial decisions in a swiftly fluctuating extrinsic
environment are guided by financial planning (Yu et al., 2023). As such, it stimuli
behavioral intentions of an individual’s, lead to reliable financial decisions (Dogra et
al., 2024). Furthermore, as per previous research, an individual’s level of financial
satisfaction influenced their financial behavior (Atlas et al., 2019). Research has
shown that cognitive skills and abilities, such as acquiring information from the
surrounding environment, interpreting situations based on information, planning
actions, and performing behaviors (Shinohara, 2016), when combined with financial
capabilities, can strongly predict an individual’s financial behavioral intentions of the
individual in decision-making process (Khan et al., 2022).
Financial capability theory focuses on opportunities and abilities to act of an
individual, which allow people to live freely (Sen, 1993). As per this theory, financial
capability is related to the opportunities and abilities to act (Johnson and Sherraden,
2007). Brown (2020) gives a comprehensive elucidation, where financial capabilities
are categorized as internal-centric, encompassing financial knowledge, skills, and
behaviors, and those that also recognize one’s exterior environment. Further, studies
also explained that financial capability also comprises and merge the concept of
financial advice and financial inclusion (Viitasalo et al., 2024). Researchers see
financial capability as not just financial knowledge but also the ability of an individual
to apply that knowledge in daily life. According to Vyvyan et al. (2014) that core
elements of varying financial capability are financial attitudes, knowledge and
behavior. Evaluating financial capability should focus on a person’s ability to save,
make informed choices, manage financial products, plan, and build necessary
knowledge and skills for effective financial decision making (Appiah and
Agblewornu, 2024). Khan et al. (2022) and Appiah and Agblewornu (2024) also state
that prior studies support the mediating role of financial capability in assessing the
financial behaviors of investors.
The researchers observed that there is limited study on the financial capability’
mediating role in the relationship between individuals’ financial cognitive ability
dimensions and their intentions to invest in the stock market of Pakistan. As a result,
this study aims to examine financial cognitive ability dimensions’ influence on the
investors’ intentions to invest in the stock market and also investigated the mediating
role of financial capability. The research problem identified in this study is the
exploration of how financial cognitive abilities influence investors intentions to
engage in Pakistan’s stock market, with a specific focus on the role of financial
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
3
capability as a mediator. The study aims to understand the direct and indirect effects
of various financial factors—such as financial knowledge, financial planning, and
financial satisfaction—on investors’ intentions within the context of an emerging
economy. This involves identifying key determinants that impact stock market
participation among individual investors in Pakistan.
2. Literature review
Ajzen and Fishbein in 1975 advanced the “Theory of Reasoned Action” (ToRA),
which aimed to clarify the connection between individuals’ attitudes and their
intentions to act. Building on this, Ajzen further advanced the “Theory of Planned
Behavior” (TPB) in 1991, which suggests that an individual’s intention to perform a
particular behavior is influenced by both motivation and perceived control over the
behavior. As TPB points out, attitudes, subjective norms, and perceived behavioral
control are key factors that substantially impact individuals’ actions and intentions
(Pandurugan and Shammakhi, 2024). Behavioral intention refers to an investor’s
willingness and planned actions toward participating in the stock market. This is
influenced by cognitive and emotional factors, including financial knowledge,
financial planning, financial satisfaction, and financial capability. Investors with
strong behavioral intentions are more actively engage in market activities, driven by
the belief that they can make informed decisions based on their financial
understanding and planning (Hasan et al., 2024). This research work addresses a
unique paradox by integrating “the theory of planned behavior”, “the theory of well-
being” Wilson (1967), and “the theory of financial capability” Brown (2020) in
investor’s research on stock market participation in the context of behavioral intent.
By employing these theories, this empirical research seeks to understand how
investors’ financial cognitive skills influence their intent. In the context of financial
decision-making, an individual’s cognitive abilities are closely related to their
behavioral intentions (Akhter and Hoque, 2022).
2.1. Financial knowledge and investors’ behavioral intention towards stock
market investment
Financial knowledge encompasses a person’s grasp of essential financial
concepts, including budgeting, investing, risk assessment, and stock market
mechanisms. It is a key cognitive component that influences financial decision-making
and individuals with greater financial knowledge typically display higher confidence
in making investment decisions and are more inclined to engage in stock market
activities (Akhter and Hoque, 2022). According to standard portfolio selection models,
realistic and prudent decisions of investment in the stock market are expected from
financially literate individuals to maximize their utility over their lifetime (Dhole et
al., 2023). Insufficient financial knowledge, however, may lead people to decentralize
decision-making or avoid high-risk investments entirely (Calcagno and Monticone,
2015). In addition, according to the “theory of planned behavior” and its “perceived
behavioral control” component, the investors willingness to engage in the stock market
is influenced by their perception of the ease or difficulty of financial decision-making
(Yulandreano and Rita, 2023). Therefore, it can be inferred that the financial
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
4
education’s level of individuals affects both their behavior and intention of investment,
which is in line with the theory. In this context, several studies have explored the direct
impact of financial knowledge on individual investment choices and have concluding
that financial knowledge considerably influence decisions in high-risk investments
(Akhter and Hoque, 2022).
H1: Financial knowledge positively affects behavioral intent of investor to
towards stock market investment.
2.2. Financial Planning and investors’ behavioral intention towards stock
market investment
Financial planning involves the systematic approach of setting financial goals,
assessing current financial situations, and developing strategies to achieve those goals.
This includes budgeting, saving, investing, and retirement planning. In relation to
investors’ behavioral intentions, effective financial planning is crucial as it equips
individuals with the knowledge and skills necessary to make informed investment
choices, thereby enhancing their likelihood of engaging in stock market activities
(Raut and Kumar, 2024). An individual’s approach to financial planning combines
their prevailing financial situation with their long-term financial goals and objectives.
Plan of investment serves as a significant part of this process, helping individuals to
accomplish both short-run and long-run objectives (Che Hassan et al., 2023). Financial
planning incorporates “cognitive factors” as well as “affective factors” (Baker and
Ricciardi, 2014). Thus, when individual investor converted their financial plan, their
investment intentions and target to investment decision, it must be effected by their
system of beliefs and their attitude (Che Hassan et al., 2023). In accordance with TPB,
“perceived behavioral control” can directly affect an individual’s behavior (Cui et al.,
2024). If the factors are easily control by them, they feel motivated to utilize resources
to achieve desired results. Individuals believe that profitable investment decisions are
the result of sound financial planning (Asandimitra et al., 2019). Furthermore, research
by Arpana and Swapna (2020) revealed a strong link between financial planning and
financial behavior. As a result, well executed financial planning tends to enhance
investors’ willingness to invest in the stock market (Akhter and Hoque, 2022).
H2: Financial planning has a positive effect on investors’ intention towards stock
market investment.
2.3. Financial Satisfaction and investors’ behavioral intention towards stock
market investment
Financial satisfaction refers to an individual’s subjective assessment of their
financial situation. It encompasses feelings of contentment or happiness regarding
personal financial resources, income, savings, investments, and overall financial well-
being. In this context, financial satisfaction is an outcome that could influence or
reinforce the cognitive ability of investors, affecting their confidence in making
investment decisions and their likelihood of participating in the stock market (Akhter
and Hoque, 2022). In capital markets, investment decision is made by individual
investor in order to accomplish their desired financial satisfaction. In accordance with
the economic principle, utility maximization, logical and realistic choices were made
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
5
by individuals’ investor while making any investment decision (Omar, 2023).
However, the subjective “well-being theory” advanced by Wilson (1967) suggests that
“how good our lives are depending on our attitudes towards what we get in life, not
on the nature of the things themselves”. Proxies indicators of objective nature were
employed by the prior research studies such as income, literacy, expectancy of life,
and financial satisfaction to measure well-being, finding that the individual well-being
levels are distinct and depends on their subjective evaluations, such as perceptions
(Durand, 2015). Therefore, when the individual investor makes capital market
participation decision, it can be hypothesized that their satisfaction and well-being
level will affect the choices, they make, of the investment decision (Kushwaha et al.,
2023). Previous studies in this field, show that financial satisfaction have significant
direct impacts on risk tolerance, financial knowledge, and investor behavior (Akhter
and Hoque, 2022).
H3: Financial satisfaction has a positive effect on investors’ intention towards
stock market investment.
2.4. Financial knowledge and financial capability
Personal finance and economics understanding are known as financial literacy
(Lone and Bhat, 2024). It includes knowledge about saving and investing, banking,
insurance, taxation and debt (Khan et al., 2022). Prior research shows that investment
decision is influence by financial knowledge (Ashfaq et al., 2024). Process of making
investment decision are influenced by financial capability, which involves effective
funds management (Taylor, 2011). The familiarity of individual investor with these
key financial concepts and terms can effect positively their planning and investment
decisions (Ahmad, 2024). Understanding financial systems is a key component of
financial capability (Rothwell et al., 2016). Likewise, research highlights that
increased financial literacy may improve a person’s financial capabilities (Muat et al.,
2024). A study by Azwadi et al. (2015) showed a positive correlation between
financial literacy and individual financial capability. Additional findings suggest a
close link between financial literacy and financial capability (Pearson et al., 2024).
Since financial knowledge is a crucial component of financial literacy, improvements
in this area can directly enhance financial capability. It is therefore concluded that
greater financial knowledge can lead to enhanced financial capability (Khan et al.,
2022).
H4: Financial knowledge positively influences individuals’ financial capability.
2.5. Financial planning and financial capability
Planning propensity, serves as an important measure of financial capability,
showing a positive correlation with the financial capability factor, indicating that
financial planning is a desirable financial behavior (Lučić et al., 2023). Setting long-
term financial goals is viewed as a positive financial behavior and is often seen an
indicator of consumers’ financial capability (Lusardi and Mitchell, 2007). Planning
propensity refers to consumers’ tendency to make plans for long-term goals, which
promotes rational, goal-oriented actions (Xiao and O’Neill, 2018). In their study, Xiao
and O’Neill (2018) contribute to the understanding of financial capability by
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
6
investigating the association of indicators of financial capability, planning propensity
with other factors of financial capability through a detailed analysis. Individuals with
high planning tendencies are patient, realistic and logical, willing to take calculated
risks, and adept at budgeting, controlling spending, and saving. Stand on the planning
propensity concept (Baker and Ricciardi, 2014), planning is considered as an indicator
of money management skills and financial capability. The practice of setting goals and
planning for the future aligns with a variety of positive financial behaviors that
demonstrate financial capability. (Xiao and O’Neill, 2018) found a significant
correlation between planning propensity and all four dimensions of financial
capability.
H5: Financial planning positively influences individuals’ financial capability.
2.6. Financial satisfaction and financial capability
Both, financial satisfaction and financial capability have many influential
common factors (Pak et al., 2024). A comprehensive reassessment of the extant body
of literature predicate that a considerable number of researchers employ financial
satisfaction as an indicator to gradate and evaluate its repercussions on the financial
capability as a dependent variable (Pak et al., 2024). Research has found that financial
satisfaction positively affect perceived financial capability (Xiao and O’Neill, 2016).
Additionally, research by De Meza et al. (2008) highlighted that financial capability
is best assessed through intrinsic psychological traits, such as cognition, and emotion.
Other research has explored a close connection amid financial satisfaction and
financial capability, showing that they share several influencing factors like financial
behaviors and knowledge (Çera et al., 2020). Therefore, by extension, it is necessary
to investigate whether financial satisfaction impacts financial capability. Therefore,
the current study examines the potential positive impacts of financial satisfaction on
financial capability, addressing the gap in existing literature on this topic.
H6: Financial satisfaction positively influences individuals’ financial capability.
2.7. Financial capability and investors’ behavioral intentions towards stock
market investment
Financial capability theory focuses on opportunities and abilities to act of an
individual, which allow people to live freely (Sen, 1993). As per this framework,
financial capability is related to both the opportunities and abilities to act (Johnson and
Sherraden, 2007). Brown (2020) gives a comprehensive elucidation, where financial
capabilities are categorized as internal-centric, encompassing financial knowledge,
skills, and behaviors. Many researcher and financial behavior professionals agree that
financial capability is far broader concept as compare to financial literacy, which is
just the cornerstone of it (Kempson et al., 2013). Further, studies also explained that
financial capability also comprises and merge the concept of financial inclusion and
financial advice (Johnson and Sherraden, 2007). Not only do experts view financial
capability as knowledge, although they believe that the “financial capability” concept
includes an ability of individual to employ that knowledge in their daily life (Gandi
and Fikri, 2024). Concurring by Vyvyan et al. (2014) that pivotal element of varying
financial capability are financial attitudes, knowledge and behavior related to finance.
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
7
Since financial capability is linked to the effective management of resources (Taylor,
2011), consequently, impacting the process of financial decision making. An
assessment of financial capability must look at an individual’s capacity to save, make
choices, manage financial products, plan, and develop the necessary knowledge and
skills for sound financial decision (Lusardi and Mitchell, 2007).
H7: Financial Capability has a positive effect on participants’ intention to invest
in the stock market.
2.8. Mediating role of financial capability
Financial capability involves both the ability to utilize financial knowledge and
skills that allow individuals to make well-informed decisions regarding their finances.
This concept goes beyond understanding financial terms to include the confidence and
practical application of that knowledge in everyday situations (Sun, 2024). In this
context, financial capability plays a crucial role as an intermediary between financial
cognitive abilities (financial knowledge, financial planning, and financial satisfaction)
and behavioral intentions, supporting individuals in translating cognitive insights into
actual stock market participation. There is evidence that financial capability can also
act as a mediator when individuals’ evaluate and engage in financial behavior (Appiah
and Agblewornu, 2024). The studies concluded that financial education and financial
capability have positive correlation (Xiao and O’Neill, 2016), as well as financial
capability and financial satisfaction (Xiao et al., 2014), and financial capability also
mediates the link between financial education and financial well-being (Pak et al.,
2024; Xiao and Porto, 2017). These elements collectively contribute to strengthening
an individual’s financial capability, thereby supporting better financial decision-
making (Khan et al., 2022).
H8: Financial capability mediate the effect of individuals’ financial knowledge
on their intention towards stock market investment.
H9: Financial capability mediate the effect of individuals’ financial planning on
their stock investment behavior intention.
H10: Financial capability mediate the effect of individuals’ financial satisfaction
on their stock investment behavior intentions.
Figure 1. Conceptual framework.
3. Research methodology
To accomplish the goals of this research, data was gathered from both current and
potential stock market investors, uses the Pakistan Stock Exchange (PSE) as the study
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
8
population. Decision of investment are behaviorally biased by investors in developing
markets as compare to investors in developed markets (Mahmood et al., 2024). Due to the
existing limited financial literacy and awareness among PSE investors may lead to the
specious investment tendencies (Mate and Dam, 2017) and trading driven by market noise
rather than informed decisions (Chen et al., 2007).
3.1. Sample and data collection
“The study involved individual investors who were actively participating in
trading on the Pakistan Stock Exchange (PSE)”. For research analysis purpose, data
of the primary nature were collected from active and potential investors directly, who
visiting brokerage houses in PSE. This research work employed a convenience
sampling technique hinge on accessibility and approachability of the participant as
recommended by Zeb et al. (2024). The convenience sampling method was chosen
because of its facile approach to respondents which renders a high response rate
(Ahmad et al., 2022). Also, as compare to other techniques, the time taken by it
regarding surveys of self-reported is meager (Chauhan and Patel, 2024). Self-
administered questionnaires were utilized to gather empirical data, ensuring maximum
participation from respondents. Throughout the data collection phase, efforts were
made to ensure comprehensive coverage of the Pakistan Stock Exchange. To
determine an appropriate sample size, we followed the approach recommended by
Krejcie and Morgan (1970). According to their table, when the population is unknown
or large, the Krejcie and Morgan’s table suggests using a maximum sample size of
384 to achieve a 95% confidence level with a ±5% margin of error (Ali et al., 2023).
The “Krejcie and Morgan” Formula:
Rounding up, the required sample size is approximately 385. Among current and
prospective investors of the PSE 663 questionnaires were distributed. In total, we
received 410 questionnaires. However, some questionnaires were filled incorrectly
and some had missing values. Therefore, 33 questionnaires were excluded from the
analysis. This left 377 valid questionnaires for the data analysis, resulting in an
effective response rate of 56.86% (377/663 × 100 = 56.86%).
3.2. Demographic profile of the respondents
Respondent’s demographic are reported in Table 1. The distribution of gender
show that the frequency of male participants was 308 and female were 69, which
indicates 81.7% were male and 18.3% were female participants. Additionally, Table
1 also presents that 19.4% participants were single and 80.6% were married.
Furthermore, age of 14.1% participants has 25 years or less than 25 years, 35.3% have
26–35 years, 28.6% have 36–45 years, and 22.0% have 46 years or greater than 46
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
9
years’ age. Table also reported that education level of 3.2% participants has
intermediate, 30.8% has bachelor, 51.2% has master and 14.9% have higher education.
Regarding experience of the participants 27.1% have 5 years or less than 5 years,
37.7% have 6–10 years, while 26.0% have 11–15 years and 9.3% have 16 years or
greater than 16 years’ experience. The annual income of 2.9% have 1 lac or less than
1 lac, 31.6% have income of 2–3 lac, 45.5% have 4–5 lac and 20.2% participants have
6 lac or greater than 6 lacs annual income. In the context of frequency of investment
11.4% participants have investing daily in the Pakistan stock market, 62.1% have
weekly, while 26.0% have monthly and only 0.5% have invested annually.
The analysis reveals that the gender, with a mean of 1.183 indicates a slight male
predominance among respondents, with moderate variability (SD = 0.387). The
marital status, with a mean of 1.806 suggests a majority are married with low
variability (SD = 0.396). The mean age of 2.586 shows most respondents are aged 26–
35, with a wider age range (SD = 0.983). The education, with a mean of 2.777 indicates
a trend toward higher education, particularly Master’s degrees, with moderate
variability (SD = 0.732). The experience has a mean of 2.175 indicates most
respondents have 6–10 years of work experience, with considerable variability (SD =
0.935). The annual income with a mean of 2.828 suggests many respondents earn
between 4–5 lac, with moderate variability (SD = 0.778). Lastly, the investment
frequency’s mean of 2.157 shows that most invest weekly, with less variability (SD =
0.610).
Table 1. Demographic profile of the respondents.
Description
Frequency
(%)
Mean
S.D
Gender
1.183
0.387
1
Male
308
81.7
2
Female
69
18.3
Marital Status
1.806
0.396
1
Single
73
19.4
2
Married
304
80.6
Age
2.586
0.983
1
≥ 25 years
53
14.1
2
26–35 years
133
35.3
3
36–45 years
108
28.6
4
46 years ≤
83
22.0
Education
2.777
0.732
1
Intermediate
12
3.2
2
Bachelor
116
30.8
3
Master
193
51.2
4
MPhil/PhD
56
14.9
Experience
2.175
0.935
1
≥ 5 years
102
27.1
2
6–10 years
142
37.7
3
11–15 years
98
26.0
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
10
4
16 years ≤
35
9.3
2.828
0.778
Annual Income
1
≥ 1 lac
11
2.9
2
2–3 lac
119
31.6
3
4–5 lac
171
45.4
4
6 lac ≤
76
20.2
Frequency of Investment
2.157
0.610
1
Daily
43
11.4
2
Weekly
234
62.1
3
Monthly
98
26.0
4
Annually
2
0.5
3.3. Research instrument
The study adapted metrics for the constructs from the prior research studies,
tailoring them to the context of participants in the Pakistani stock market. Each
variable was evaluated on a five-point Likert scale, ranging from one (1) for “strongly
disagree” to five (5) for “strongly agree”. To measure financial knowledge, we used
5-item scale which has been developed by Robb and Woodyard (2011) that were used
by Çera et al. (2021). To examine financial planning, we adopted Azwadi et al. (2015)
scale with four items that were used by Akhter and Hoque (2022). To measure
financial satisfaction, we used a scale comprising five items, as developed by Azwadi
et al. (2015) that were used by Akhter and Hoque (2022). A 4-item scale were
employed from Tahir et al. (2021) to assess financial capability that were used by Çera
et al. (2021). Additionally, four items related to technology acceptance were adapted
from Hausman and Siekpe (2009) that were used by Akhter and Hoque (2022). While
the measurement items were initially developed within the context of technology
acceptance studies (Hausman and Siekpe, 2009), their relevance to behavioral
intention studies, particularly in stock market participation, is well established. Stock
market investment intention constructs share similarities across domains, allowing for
a validated and reliable approach to assessing participant intentions. By using these
established items, the study maintains consistency with previous literature (Akhter and
Hoque, 2022), ensuring both reliability and validity in measuring intentions to invest
in the stock market. Following recent studies related to behavioral intention toward
stock market investment (Akhter and Hoque, 2022; Khan et al., 2022), several
demographic factors, as control variables, have incorporated to enhance the accuracy
of the estimations as control variables.
4. Results and discussion
The PLS-SEM method involves two main steps: evaluating the measurement
model and assessing the structural model (Ringle et al., 2020; Zeb et al., 2022). For
this study, we used Smart PLS version 4.00 and adhered to the most recent analysis
guidelines proposed by Goek et al. (2024) and Zeb et al. (2024).
We utilized partial least squares structural equation modeling to conduct our data
analysis. This method is particularly effective for handling small sample sizes and data
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
11
that do not follow a normal distribution (Hair et al., 2011). Furthermore, predictive
approach, well-suited for exploratory research that aims to test theories in an
investigational manner (Ringle et al., 2020). PLS-SEM procedure involves two key
stages: evaluating the measurement model and assessment the structural model
(Ringle et al., 2020; Zeb et al., 2022). For this analysis, we employed the Smart PLS
4.00 software, and followed the latest data analysis guidelines recommended by Goek
et al. (2024) and Zeb et al. (2024).
4.1. Measurement model evaluation
The researchers evaluated the measurement models by determining the loading
factor of each items, along with calculating Cronbach’s alpha, composite reliability,
and evaluating both convergent and discriminant validity (Hair et al., 2010; Hair et al.,
2021). Before performing this analysis, we applied the Kaiser-Meyer-Olkin (KMO)
test and Bartlett’s test of sphericity to verify the appropriateness of factor analysis for
the survey data, as shown in Table 2. The KMO measure, with a value of 0.778,
suggests moderate to good sampling adequacy, indicating that the variables have
sufficient correlations to justify factor analysis. Generally, a KMO value above 0.6 is
acceptable for this purpose. (Khawaja and Alharbi, 2021). The significant result (p <
0.05) confirms relationships among the variables, supporting the data’s suitability for
factor analysis. Overall, the KMO and Bartlett’s test results validate that factor
analysis is appropriate for uncovering underlying data structures.
Table 2. Assessing suitability of data for factor analysis.
KMO and Bartlett’s test of Sphericity
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
0.778
Bartlett’s Test of Sphericity
Approx. Chi-Square
3676.86
Df
231
Sig.
0.000
4.1.1. Reliability analysis and convergent validity
Reliability analysis measure the questionnaire consistency. Indicator’s reliability
assessed the individual item’s evaluation. Internal consistency tests each latent
variable reliability. The factor loadings in the table highlight the strength of each
item’s relationship with its respective construct, indicating the validity of the
measurement model in the study (Hair et al., 2021). All constructs s demonstrates
adequate factor loadings (generally above 0.5), suggesting good indicator validity
across items (Hair et al., 2021). Table 3 exhibits each latent variable’s outer loading
that lies within the passable range and thus meets the retention criteria. Internal
consistency is also assessed through a broad method known as composite reliability
(CR). Werts et al. (1974) established CR and proffered over Cronbach’s alpha since it
yielded better estimates. The generally accepted threshold for composite reliability in
explanatory research is 0.7 or above (Hair et al., 2011). As shown in Table 3, the CR
coefficients for each latent variable range from 0.834 to 0.873, indicating that all
values exceed the 0.70 benchmark. These results demonstrate sufficient reliability for
internal consistency (Hair et al., 2011). To verify convergent validity for each
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
12
construct, it is recommended to use the average variance extracted metric, as
recommended by Fornell and Larcker (1981). An AVE value of 0.50 or above
indicates adequate convergent validity (Henseler et al., 2009). The value of AVE
(Table 3) indicated that the value of behavioral intention as a dependent variable in
the study was 0.633. The dimensions of financial cognitive capability as predictors in
the study have AVEs of 0.553, 0.561 and 0.526, respectively, while the AVE of
financial capability as a mediator is 0.627. These AVE values collectively confirm
satisfactory convergent validity (Henseler et al., 2009).
Table 3. Factors loadings, reliability, and validity.
Constructs
Factor Loadings
Alpha values
C.R
AVE
Financial Knowledge (FK)
0.795
0.858
0.553
FK.1
0.537
FK.2
0.810
FK.3
0.711
FK.4
0.795
FK.5
0.828
Financial Planning (FP)
0.729
0.834
0.561
FP.1
0.717
FP.2
0.833
FP.3
0.835
FP.4
0.581
Financial Satisfaction (FS)
0.756
0.841
0.526
FS.1
0.425
FS.2
0.757
FS.3
0.839
FS.4
0.839
FS.5
0.683
Financial Capability (FC)
0.800
0.869
0.627
FC.1
0.625
FC.2
0.838
FC.3
0.881
FC.4
0.799
Behavioral Intention (BI)
0.807
0.873
0.633
BI.1
0.795
BI.2
0.872
BI.3
0.783
BI.4
0.726
4.1.2. Discriminant validity
Henseler et al. (2015) introduced an advanced method for discriminant validity
estimation known is Heterotrait-Monotrait (HTMT) correlation ratio, which is a multi-
trait-multi-method matrix. Gold et al. (2001) propound HTMT ratio criterion value
which is 0.90, if the ratio’s value of HTMT is above the benchmark value it indicates
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
13
the presence of discriminant validity. The ratio’s value of HTMT must be less than the
standard value (0.90) or relatively not close to 1. Table 4 present the summary of
discriminant validity estimation computed by advanced method (HTMT ratio). These
values bespeak that there is no problem with discriminative validity, as all the ratio
value of HTMT is less than the standard value (0.9). Discriminant validity connotes
that various theoretical important concepts employ in the research model must be at
variance (Hair et al., 2010). Another important criterion Fornell and Larcker advanced
by Fornell and Larcker (1981) were also employed in this empirical research work to
evaluate and measures the |discriminant validity. Generally, an AVE value of 0.5 or
above is recommended, and the AVE square root should be larger as compare to the
correlation amid the latent variables. As shown in Table 3, all constructs display an
AVE value exceeding the threshold of 0.5, in this regard Table 4 shows that the square
root of each AVE surpasses the inter-variable correlations, indicating that this study
adequately supports discriminant validity.
Figure 2. Measurement model.
Table 4. HTMT ratio and Fornell-Larcker criterion.
HTMT Ratio
FK
FP
FS
FC
BI
Financial Knowledge
Financial Planning
0.332
Financial Satisfaction
0.502
0.270
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
14
Financial Capability
0.374
0.304
0.322
Behavioral Intention
0.565
0.332
0.431
0.480
Fornell-Larcker Criterion
FK
FP
FS
FC
BI
Financial Knowledge
0.744
Financial Planning
0.254
0.749
Financial Satisfaction
0.399
0.194
0.725
Financial Capability
0.302
0.240
0.247
0.792
Behavioral Intention
0.481
0.256
0.355
0.423
0.796
4.1.3. Coefficient of determination (R2) and predictive relevance (Q2)
R-squared (R2) value was used by several researchers to interpret the variance in
research model (Hair et al., 2010). Statistical measure, R2, elucidate the variance
proportion in dependent variable construe by the dependent variable, means that how
much independent variable elucidate and illustrate the dependent variable. In this
empirical research work the R2 value of 0.134 and Adjusted R2 of 0.127 suggest that
financial cognitive abilities explain about 13.4% of the variance in financial capability,
indicating a moderate influence while highlighting that other factors also play a role.
The slight difference between R2 and Adjusted R2 indicates a well-fitted model without
excessive complexity. The R2, coefficient of determination of behavioral intention of
investor toward stock market investment, is 0.341 signify that financial cognitive
ability dimensions explain about 34% of the variance. The value of R2 in this research
study was moderate (Chin, 2010). The Q-square statistic, also known as Stone-
Geisser’s Q2, assesses how well the model’s predictions align with actual outcomes,
known as the prediction accuracy criterion (Geisser, 1974; Stone, 1974). A Q2 value
below zero suggest poor fitness of model and therefore cannot provide an acceptable
predictive relevance between exogenous and endogenous variables (Hair et al., 2021).
In this research work a Q2 value of 0.110 indicates a small but positive predictive
relevance, showing that financial cognitive abilities contribute to predicting financial
capability. The value of the dependent variable’s Q2 = 0.254, being greater than zero,
indicates satisfactory predictive relevance. As a mediator, financial capability partially
transmits the effects of financial cognitive abilities on behavioral intention. Despite a
relatively low R2, the predictive relevance of Q2 suggests that enhancing financial
capability can upsurge an individual’s likelihood of positive financial decision-making
behaviors. Overall, the results highlight the role of financial capability in linking
financial knowledge, financial planning, and financial satisfaction to beneficial
financial behaviors.
Table 5. Coefficient of determination (R2) and predictive relevance (Q2).
R2
Adj R2
Q2 Predict
Financial Capability
0.134
0.127
0.110
Behavioral Intention
0.341
0.334
0.254
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
15
4.2. Structural model
This empirical research study applies standard bootstrapping procedures,
generating 5000 bootstrapped samples and analyzing responses from 377 participants
to evaluate the significance of path coefficients statistically (Hair et al., 2021; Henseler
et al., 2009). The results presented in Table 6 detail the direct effects derived from the
structural model estimates.
4.2.1. Direct structural path analysis
This study’s discussion centers on the empirical findings represent the impact of
financial cognitive ability dimensions on behavioral intention of the investor in
Pakistan stock market. It also explored financial capability mediating role within these
relationships, drawing on the theory of “planned behaviors” (Ajzen, 1991), “theory of
well-being” (Wilson, 1967), and the “theory of financial capability” (Brown, 2020;
Johnson and Sherraden, 2007; Sen, 1993). To achieve these objectives, we first
focused on the direct effect (path co-efficient) among these variables and then inspect
the indirect effect.
Hypothesis 1 states that financial knowledge have positive influences on
intention of investor to engage in the stock market. The results presented in Table 6
indicates that financial knowledge have positive significant effects on behavioral
intention of investor to participate in the stock market (β1 = 0.321; p-value = 0.000)
implying that H1 is supported. These findings align with previous research, such as
studies by Ashfaq et al. (2024), Dhole et al. (2023), Kumari (2020), Khan et al. (2022)
and Shehata et al. (2021). Hypothesis 2 states that financial planning have positive
effects on behavioral intention of investor. The analysis presented in Table 6 indicates
that financial planning have positive but insignificant impact on the investors’
behavioral intention (β2 = 0.080; p-value = 0.090) concluded that H2 is not supported.
Nonetheless, prior studies indicate that individual investors’ financial planning may
substantially impact their intention to engage in the stock market, as noted by Akhter
and Hoque (2022), Arpana and Swapna (2020) and Cui et al. (2024).
Table 6. Direct effect path analysis for hypothesis-testing.
Relationships
β values
t values
p values
Decision
H1: FK → BI
0.321
5.469
0.000
Supported
H2: FP → BI
0.080
1.694
0.090
Not Supported
H3: FS → BI
0.143
2.574
0.010
Supported
H4: FK → FC
0.207
3.736
0.000
Supported
H5: FP → FC
0.163
3.250
0.001
Supported
H6: FS → FC
0.132
2.334
0.020
Supported
H7: FC → BI
0.277
4.779
0.000
Supported
The current study’s findings on how financial planning effects investors’
intentions to invest in the stock market differ from previous empirical studies. This
contradiction in findings is due to existence of generally low level of financial literacy
and awareness observed among investors in the PSE (Mate and Dam, 2017). The most
important and notable reasons for these findings could be that investors in the PSE
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
16
have not long term oriented, which stems from their diminished confidence in the
country’s stock market (Akhter and Hoque, 2022), the main factors causing this low
confidence is largely attributed to the country’s recent political uncertainty (Ghani and
Ghani, 2024).
The third hypothesis states that financial satisfaction have positive effects on
investor’ intention, confirmed by the results presented in Table 6 (β3 = 0.143; p-value
= 0.010), validating H3. The results are consistent with the Akhter and Hoque (2022),
Omar (2023) and Yang et al. (2021). The fourth hypothesis states that financial
knowledge have positive effects on financial capability confirmed by the results
presented in Table 6 (β4 = 0.207; p-value = 0.000) implying that H4 is supported. This
aligns with prior studies (Appiah and Agblewornu, 2024; Çera et al., 2021; Khan et
al., 2022; Muat et al., 2024; Pearson et al., 2024). The fifth hypothesis states that
financial planning have positive impact on financial capability confirmed by the
results presented in Table 6 (β5 = 0.163; p-value = 0.000), validating H5. The results
are consistent with the Muat et al. (2024), Vyvyan et al. (2014) and Xiao and O’Neill
(2018). The sixth hypothesis states that financial satisfaction have positive impact on
financial capability confirmed by the results presented in Table 6 (β6 = 0.132; p-value
= 0.020) implying that H6 is supported. The results are an aligns with past findings of
Çera et al. (2020), Khan et al. (2022), Muat et al. (2024), Pak et al. (2024) and Xiao
and O’Neill (2018). The seventh hypothesis states that financial capability have
positive impact on intention of investor, confirmed by the results presented in Table
6 (β7 = 0.277; p-value = 0.000) implying that H7 is supported. The results are consistent
with the Gandi and Fikri (2024) and Khan et al. (2022).
4.2.2. Indirect path analysis
Table 7 reveals the indirect effect of the structural model estimates of the current
study. Hypothesis eight states that financial capability mediate the link amid financial
knowledge and intention of the investor to invest in the stock market. The results
presented in Table 7 (β8 = 0.057; p-value = 0.002), confirming this hypothesis. These
findings align with prior literature as the results reported by Appiah and Agblewornu
(2024), Gandi and Fikri (2024), Tahir et al. (2021) and Xiao and O’Neill (2018). The
ninth hypothesis proposes that financial capability mediate the link amid the financial
planning and investors’ behavioral intention to engage in the stock market. The results
in Table 7 (β9 = 0.045; p-value = 0.011) support this hypothesis, indicating that H9 is
supported. These findings align with the prior literature (Lučić et al., 2023; Muat et
al., 2024; Pearson et al., 2024; Tahir et al., 2021; Xiao and O’Neill, 2018). Hypothesis
ten proposes that financial capability mediate the link amid financial satisfaction and
investor’s behavioral intention. The data shown in Table 7 (β10 = 0.037; p-value =
0.041) confirms this hypothesis, implying that H10 is supported. These outcomes align
with the previous studies as, documented in previous research by Gandi and Fikri
(2024), Pak et al. (2024), Tahir et al. (2021) and Xiao and O’Neill (2018).
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
17
Table 7. Indirect effect path analysis for hypothesis-testing.
Hypotheses
β values
t values
p values
Decision
H8: FK → FC → BI
0.057
3.075
0.002
Supported
H9: FP → FC → BI
0.045
2.537
0.011
Supported
H10: FS → FC → BI
0.037
2.048
0.041
Supported
5. Conclusions and recommendations of the study
A primary aim of this research is to thoroughly explored and clarify both the
direct and indirect relationship between financial cognitive ability dimensions and
stock market investment intention of investors’. The findings show e that both
financial cognitive ability dimensions and financial capability are key factors
influencing investors’ willingness to invest. Additionally, the research highlights that
financial capability significantly mediates the link amid financial cognitive ability
elements and intentions to participate in the stock market. The results confirm that
when financial capability interact with financial cognitive ability dimensions, these
variables positively and significantly influence investor behavior. The empirical
findings presented in this study offer several policy and practical implications. To
increase stock market participation in Pakistan, various stakeholders—including
regulatory bodies, financial institutions, and educational organizations—can adopt
strategies focusing on enhancing financial knowledge, planning, and satisfaction.
Addressing these areas with targeted interventions can bridge the current knowledge
gap while utilizing financial capability as a mediator. This study also provides valuable
insights for investors in investment making process, who are intended to invest in
stock market.
First, this study elaborates how various aspects of financial cognitive ability
influence intentions of investor to engage in investment activities. It elaborates
existing research gaps in this area of previous research at stock market, therefore, a
research study is conducted in this context to enhance knowledge and is beneficial to
the said individual and policy maker. This study finds out the key financial cognitive
ability dimensions that effectively influence individual’s decision of investment.
Second, it examines how financial capability mediates the impact of various financial
cognitive abilities—such as financial knowledge, financial planning, and financial
satisfaction—on investment intentions of individuals. The analysis is framed by three
key theories: the “theory of planned behavior”, the “theory of well-being”, and the
theory of “financial capability”. Third, to the best of authors’ understanding, earlier
studies have mainly elucidated the direct association amid dimensions of financial
cognitive ability and investment intentions activities of individuals’. This study’s
findings shed light and contribute to the existing literature by providing clarity on the
relationship between measures of financial cognition and individuals’ market
participation intentions, highlighting that these connections are predominantly
influenced by financial capability. Therefore, it is important for policymakers and
market regulators to introduce measures aimed at restoring the confidence of
international investors in the domestic capital market. To achieve this, stakeholders
should organize educational workshops and online courses focused on stock market
fundamentals, risk analysis, and portfolio management, catering to diverse groups
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
18
such as students, professionals, and retirees. Additionally, incorporating financial
literacy programs into school and university curricula with an emphasis on key stock
market principles and long-term investment strategies can be beneficial.
Fourth, the growth of foreign investments is vital not only for enhancing the
country’s market capitalization but also for strengthening trust among local individual
investors, which serves as a key indicator of the market’s future potential. Individual
investors in developing nations, who often have limited financial knowledge, are
inclined to mimic the investment and divestment choices of institutional and foreign
investors (Georgarakos and Inderst, 2014). Consequently, it is crucial for
policymakers and market authorities to implement effective measures to rebuild
international investors’ confidence in the national capital market. Stakeholders should
provide workshops and online courses on stock market basics, risk assessment, and
portfolio management, accessible to different demographics like students,
professionals, and retirees. Integrate financial literacy into academic curricula,
emphasizing essential stock market concepts and long-term investing (Ullah et al.,
2024).
Fifth, financial planning is an important determinant of stock market participation
behavior. To encourage individuals to plan financially, governments must take steps
to revive national saving attitudes, this approach not only shields individuals from
financial uncertainties (Fox and Bartholomae, 2020), but also help them to participate
in positive behavioral intentions in the stock market. Sixth, PSE market regulators and
policymakers should focus on enhancing investor confidence so that PSE investment
decisions provide the financial satisfaction investors expect. This measure will help
increase the capitalization of the stock market, which will ultimately have a positive impact
on the growth rate of the country’s gross domestic product (Ullah and Khan, 2021).
Financial institutions should offer free or affordable advisory sessions to guide prospective
investors. Support fintech innovations like robo-advisors to provide low-cost, user-
friendly planning tools (Ullah et al., 2024). Campaigns showcasing long-term wealth-
building benefits and success stories can further boost confidence in financial planning.
Seventh, stakeholders offer programs on budget planning, income allocation, and
investment tracking, empowering individuals with decision-making confidence.
Simulated trading platforms and mobile apps with real-time stock updates can help
new investors practice and monitor their investments. To address fraud concerns,
stakeholders should enhance regulatory measures and work closely with the Securities
and Exchange Commission of Pakistan to promote policies that benefit investors.
Additionally, providing tax incentives and secure, government-backed investment
options could encourage participation from first-time and risk-averse investors. By
supporting research to address local barriers to market participation, stakeholders can
develop tailored solutions. Partnerships with NGOs focusing on financial
empowerment can help reach underserved populations and promote wider engagement
in Pakistan’s stock market.
Ultimately, this research work provides policy makers with a clear understanding
of how to improve financial capability, allowing policy makers to develop strategies
to achieve better outcomes and equip citizens with essential financial knowledge and
skills in capability in modern society (Çera et al., 2020). In this context, the triple helix
model (Kim et al., 2012) serves as a valuable approach to advancing individual
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
19
financial knowledge and financial capability, and the investment intention of
individuals to engage in the stock market. These strategies can help stakeholders
bridge the financial knowledge gap, simplify financial planning, and enhance investor
satisfaction, ultimately fostering a stronger culture of stock market participation in
Pakistan.
Limitations and the direction of future research
This research has certain limitations, much like many other empirical
investigations. Cross-sectional research methods make it difficult to comprehend how
investors’ behavioral intentions are transferred over time periods. Thus, longitudinal
study, encompassing pre- and post-training and workshops, may be the main focus of
future research. Similar studies on frontier markets (such as Iran, China, India, and the
Central Asian Republic) are necessary enhance the generalizability of the findings, as
the current research primarily focused on the Pakistani equities market. In addition, since
stock market investment involves real risk tolerance and online trading, exploring factors
such as risk tolerance behavior and digital literacy could yield valuable insights in future
studies. As a result, the researchers suggest that future studies evaluate the research
variables in other contexts, across various timescale, and with alternative metrics.
Author contributions: Conceptualization, RU; methodology, RU, HBI and AZ;
software, RU; validation, HBI; formal analysis, RU and AZ; investigation, RU and
AZ; resources, RU and AZ; data curation, RU; writing—original draft preparation,
RU and AZ; writing—review and editing, RU, HBI and AZ; visualization, RU;
supervision, HBI. All authors have read and agreed to the published version of the
manuscript
Conflict of interest: The authors declare no conflict of interest.
References
Ahmad, M. (2024). The role of recognition-based heuristics in investment management activities: Are expert investors immune?–
A systematic literature review. Qualitative Research in Financial Markets, 16(3), 401–422.
Ainia, N. S. N., Lutfi, L. (2019). The influence of risk perception, risk tolerance, overconfidence, and loss aversion towards
investment decision making. Journal of Economics, Business, & Accountancy Ventura, 21(3), 401–413.
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179–211.
Akhter, T., Hoque, M. E. (2022). Moderating Effects of Financial Cognitive Abilities and Considerations on the Attitude–
Intentions Nexus of Stock Market Participation. International Journal of Financial Studies, 10(1), 5.
Ali, A., Rahman, M. S. A., Bakar, A. (2015). Financial satisfaction and the influence of financial literacy in Malaysia. Social
Indicators Research, 120(1), 137–156.
Ali, A., Ullah, R., Khan, F. U., et al. (2023). Organizational Trust as a Mediator in the Relationship of Training & Development
and Organizational Performance: An Evidence from HEI’s of KP, Pakistan. Journal of Asian Development Studies, 12(3),
348–356.
Ali, A., Ullah, R., Ullah, A., et al. (2022). Nexus of Performance Appraisal, Organizational Trust and Organizational
Performance: An Empirical Evidence from Academicians. Journal of Positive School Psychology, 6(10), 374–384.
Appiah, T., Agblewornu, V. V. (2024). Financial Literacy, Financial Access, and Small Business Performance in Secondi-
Takoradi Metropolis of Ghana: The Mediating Effect of Financial Capability. African Journal of Business & Economic
Research, 19(2).
Arpana, D., Swapna, H. R. (2020). Role of planning and risk tolerance as intervening constructs between financial well-being and
financial literacy among professionals. International Journal of Economics and Financial Issues, 10(5), 145.
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
20
Asandimitra, N., Aji, T. S., Kautsar, A. (2019). Financial behavior of working women in investment decision-making. Information
Management and Business Review, 11(2), 10–20.
Ashfaq, M., Shafique, A., Selezneva, V. (2024). Exploring the missing link: Financial literacy and Cognitive biases in Investment
Decisions. Journal of Modelling in Management, 19(3), 871–898.
Atlas, S. A., Lu, J., Micu, P. D., Porto, N. (2019). Financial knowledge, confidence, credit use, and financial satisfaction. Journal
of Financial Counseling and Planning, 30(2), 175–190.
Baker, H. K., Ricciardi, V. (2014). Investor behavior: The psychology of financial planning and investing. John Wiley & Sons.
Bhaduri, S., Corradi, A. A., Kumar, H., Sheikh, F. A. (2023). Frugality in innovation processes: A heuristics-based perspective
from the ‘informal economy’. In: Handbook on Frugal Innovation. Edward Elgar Publishing. pp. 69–82.
Brown, J. T. (2020). Economic dignity and financial capabilities: Connecting principles and concepts.
Calcagno, R., Monticone, C. (2015). Financial literacy and the demand for financial advice. Journal of Banking & Finance, 50,
363–380.
Çera, G., Khan, K. A., Belas, J., Ribeiro, H. N. R. (2020). The role of financial capability and culture in financial satisfaction.
Economic Papers: A journal of applied economics and policy, 39(4), 389–406.
Çera, G., Khan, K. A., Mlouk, A., Brabenec, T. (2021). Improving financial capability: The mediating role of financial behaviour.
Economic Research-Ekonomska Istraživanja, 34(1), 1265–1282.
Çera, G., Phan, Q. P. T., Androniceanu, A., Çera, E. (2020). Financial capability and technology implications for online shopping.
E&M: Ekonomie a Management, 23(2), 156–172.
Cervellati, E. M., Angelini, N., Stella, G. P. (2024). Behavioral finance and wealth management: Market anomalies, investors’
behavior and the role of financial advisors. Virtus Interpress.
Chauhan, R., Patel, N. (2024). Unraveling Investor Behavior: Exploring the Influence of Behavioral Finance on Investment
Decision-Making. Journal of Economics, Assets, and Evaluation, 1(4), 1–13.
Che Hassan, N., Abdul-Rahman, A., Mohd Amin, S. I., Ab Hamid, S. N. (2023). Investment intention and decision making: A
systematic literature review and future research agenda. Sustainability, 15(5), 3949.
Chen, G., Kim, K. A., Nofsinger, J. R., Rui, O. M. (2007). Trading performance, disposition effect, overconfidence,
representativeness bias, and experience of emerging market investors. Journal of behavioral decision making, 20(4), 425–
451.
Chin, W. W. (2010). How to write up and report PLS analyses. In: Handbook of partial least squares. Springer. pp. 655–690.
Cui, S., Tian, L., Xu, Y., Wang, Y. (2024). Measuring acceptance of tradable credit scheme and its effect on behavioral intention
through theory of planned behavior. Transport Policy, 150, 174–188.
De Meza, D., Irlenbusch, B., Reyniers, D. (2008). Financial capability: A behavioural economics perspective. Consumer research,
69, 192–193.
Dhole, M. I., Soni, R., Bagesar, M. (2023). Impact of Financial Literacy on Behavioural Biases and Investment Decision.
Academy of Marketing Studies Journal, 27(5), 1–21.
Dimmock, S. G., Kouwenberg, R. (2010). Loss-aversion and household portfolio choice. Journal of Empirical Finance, 17(3),
441–459.
Dogra, P., Kaushal, A., Kalia, P. (2024). What drives the investment intentions of emerging economy millennials? Examining the
effect of financial advertisement with the PLS-SEM. Journal of Financial Services Marketing, 29(2), 276–291.
Durand, M. (2015). The OECD better life initiative: How’s life? and the measurement of well‐being. Review of Income and
Wealth, 61(1), 4–17.
Fornell, C., Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error.
Journal of marketing research, 18(1), 39–50.
Fox, J., Bartholomae, S. (2020). Household finances, financial planning, and COVID‐19. Financial Planning Review, 3(4), e1103 .
Gandi, T. R., Fikri, A. A. H. S. (2024). The Role of Financial Capability and Non-Impulsive Behavior in Moderated Mediation
Model on the Effect of Financial Literacy on Financial Well-Being. International Journal of Education, Language, Literature,
Arts, Culture, and Social Humanities, 2(4), 33–56.
Garnier-Brun, J., Benzaquen, M., Bouchaud, J.-P. (2024). Unlearnable Games and “Satisficing” Decisions: A Simple Model for a
Complex World. Physical Review X, 14(2), 021039.
Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101–107.
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
21
Geok, T. K., Shah, A., Goh, G. G. G., Zeb, A. (2024). The links between sustainability dimensions and green campus initiatives in
mountain universities. Journal of Infrastructure, Policy and Development, 8(9), 7653.
Georgarakos, D., Inderst, R. (2014). Financial advice and stock market participation. Available online:
https://econpapers.repec.org/paper/cprceprdp/9922.htm (accessed on 10 October 2012).
Georgarakos, D., Pasini, G. (2011). Trust, sociability, and stock market participation. Review of Finance, 15(4), 693–725.
Ghani, M., Ghani, U. (2024). Economic policy uncertainty and emerging stock market volatility. Asia-Pacific Financial Markets,
31(1), 165–181.
Gold, A. H., Malhotra, A., Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of
management information systems, 18(1), 185–214.
Hadi, F. (2017). Effect of emotional intelligence on investment decision making with a moderating role of financial literacy.
China-USA Business Review, 16(2), 53–62.
Hair, J. F., Anderson, R. E., Babin, B. J., Black, W. C. (2010). Multivariate data analysis: A global perspective. Pearson. Volume
7.
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M. (2021). A primer on partial least squares structural equation modeling
(PLS-SEM). Sage publications.
Hair, J. F., Ringle, C. M., Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2),
139–152.
Hamza, N., Arif, I. (2019). Impact of financial literacy on investment decisions: The mediating effect of big-five personality traits
model. Market Forces, 14(1).
Hasan, A., Sikarwar, P., Mishra, A., et al. (2024). Determinants of behavioral intention to use digital payment among Indian
youngsters. Journal of Risk and Financial Management, 17(2), 87.
Hausman, A. V., Siekpe, J. S. (2009). The effect of web interface features on consumer online purchase intentions. Journal of
business research, 62(1), 5–13.
Henseler, J., Ringle, C. M., Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural
equation modeling. Journal of the academy of marketing science, 43(1), 115–135.
Henseler, J., Ringle, C. M., Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In:
New challenges to international marketing. Emerald Group Publishing Limited.
Johnson, E., Sherraden, M. S. (2007). From financial literacy to financial capability smong youth. The Journal of Sociology &
Social Welfare, 34(3), 119.
Kempson, H. E., Perotti, V., Scott, K. (2013). Measuring financial capability: A new instrument and results from low-and middle-
income countries. World Bank.
Khan, K. A., Çera, G., Pinto Alves, S. R. (2022). Financial capability as a function of financial literacy, financial advice, and
financial satisfaction. E&M Ekonomie a Management, 25(1), 143–160.
Khawaja, M. J., Alharbi, Z. N. (2021). Factors influencing investor behavior: An empirical study of Saudi Stock Market.
International Journal of Social Economics, 48(4), 587–601.
Kim, Y., Kim, W., Yang, T. (2012). The effect of the triple helix system and habitat on regional entrepreneurship: Empirical
evidence from the US. Research Policy, 41(1), 154–166.
Krejcie, R. V., Morgan, D. W. (1970). Determining sample size for research activities. Educational and psychological
measurement, 30(3), 607–610.
Kumari, D. A. T. (2020). The Impact of Financial Literacy on Investment Decisions: With Special Reference to Undergraduates in
Western Province, Sri Lanka. Asian Journal of Contemporary Education, 4(2), 110–126.
Kushwaha, B. P., Shiva, A., Tyagi, V. (2023). How Investors’ Financial Well-being Influences Enterprises and Individual’s
Psychological Fitness? Moderating Role of Experience under Uncertainty. Sustainability, 15(2), 1699.
Lo, A. W. (2005). Reconciling efficient markets with behavioral finance: The adaptive markets hypothesis. Journal of investment
consulting, 7(2), 21–44.
Lone, U. M., Bhat, S. A. (2024). Impact of financial literacy on financial well-being: A mediational role of financial self-efficacy.
Journal of Financial Services Marketing, 29(1), 122–137.
Lučić, A., Barbić, D., Uzelac, M. (2023). Theoretical underpinnings of consumers’ financial capability research. International
Journal of Consumer Studies, 47(1), 373–399.
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
22
Lusardi, A., Mitchell, O. S. (2007). Baby boomer retirement security: The roles of planning, financial literacy, and housing
wealth. Journal of monetary Economics, 54(1), 205–224.
Mate, R. M., Dam, L. (2017). Role of an attitude and financial literacy in stock market participation. International Journal of
Management, IT and Engineering, 7(8), 137–149.
Muat, S., Mahdzan, N. S., Sukor, M. E. A. (2024). What shapes the financial capabilities of young adults in the US and Asia-
Pacific region? A systematic literature review. Humanities and Social Sciences Communications, 11(1), 1–15.
Nepal, R., Rajopadhyay, P., Rajopadhyay, U., Bhattarai, U. (2023). Interplay of Investor Cognition, Financial Literacy, and
Neuroplasticity in Investment Decision Making: A Study of Nepalese Investors. Journal of Business and Social Sciences
Research, 8(2), 51–76.
Omar, A. M. (2023). Utility Theory and Its Application on Investment Decisions in Kenya. East African Finance Journal, 2(1),
48–55.
Pak, T. Y., Fan, L., Chatterjee, S. (2024). Financial socialization and financial well‐being in early adulthood: The mediating role
of financial capability. Family Relations, 73(3), 1664–1685.
Pandurugan, V., Al Shammakhi, B. N. S. (2024). Modelling the theory of planned behaviour to evaluate the investment intention
of generation Z in the speculative market: Stocks, Forex and cryptocurrencies. Arab Gulf Journal of Scientific Research,
42(2).
Pearson, B., Korankye, T., Liu, Y., Qing, D. (2024). Knowing the “Don’t Knows” to Financial Literacy Questions in the US
National Financial Capability Study. Journal of Financial Counseling and Planning, 35(2), 292–304.
Raut, R. K., Kumar, S. (2024). An integrated approach of TAM and TPB with financial literacy and perceived risk for influence
on online trading intention. Digital Policy, Regulation and Governance, 26(2), 135–152.
Ringle, C. M., Sarstedt, M., Mitchell, R., Gudergan, S. P. (2020). Partial least squares structural equation modeling in HRM
research. The International Journal of Human Resource Management, 31(12), 1617–1643.
Robb, C. A., Woodyard, A. (2011). Financial knowledge and best practice behavior. Journal of Financial Counseling and
Planning, 22(1).
Rothwell, D. W., Khan, M. N., Cherney, K. (2016). Building financial knowledge is not enough: Financial self-efficacy as a
mediator in the financial capability of low-income families. Journal of Community Practice, 24(4), 368–388.
Sen, A. (1993). Capability and well-being. In: The quality of life. Oxford University Press. Volume 30. pp. 1–445.
Shehata, S. M., Abdeljawad, A. M., Mazouz, L. A., et al. (2021). The moderating role of perceived risks in the relationship
between financial knowledge and the intention to invest in the Saudi Arabian stock market. International Journal of Financial
Studies, 9(1), 9.
Shinohara, K. (2016). Perceptual and Cognitive Processes in Human Behavior. In: Cognitive Neuroscience Robotics B. Springer.
pp. 1–22.
Stone, M. (1974). Cross-validation and multinomial prediction. Biometrika, 61(3), 509–515.
Sun, S. (2024). Building financial capability and assets to reduce poverty and health disparities: Race/ethnicity matters. Journal of
Racial and Ethnic Health Disparities, 11(3), 1754–1773.
Tahir, M. S., Ahmed, A. D., Richards, D. W. (2021). Financial literacy and financial well-being of Australian consumers: A
moderated mediation model of impulsivity and financial capability. International journal of bank marketing, 39(7).
Taylor, M. (2011). Measuring financial capability and its determinants using survey data. Social Indicators Research, 102(2), 297–
314.
Ullah, R., Khan, B. (2021). Empirical Investigation of Fiscal, Monetary and Trade Policies Impact on Economic Growth of
Pakistan. Academic Journal of Social Sciences (AJSS), 5(1), 54–72.
Ullah, R., Ismail, H. B., Khan, M. T. I., Zeb, A. (2024). Nexus between Chat GPT usage dimensions and investment decisions
making in Pakistan: Moderating role of financial literacy. Technology in Society, 76, 102454.
Van Rooij, M., Teppa, F. (2014). Personal traits and individual choices: Taking action in economic and non-economic decisions.
Journal of Economic Behavior & Organization, 100, 33–43.
Viitasalo, K., Kaitsaari, T., Kaittila, A., et al. (2024). Promoting financial capability within the field of social work practice among
families with children: A systematic review. European Journal of Social Work, 27(3), 505–518.
Vyvyan, V., Blue, L., Brimble, M. (2014). Factors that influence financial capability and effectiveness: Exploring financial
counsellors’ perspectives. Australasian Accounting, Business and Finance Journal, 8(4), 3–22.
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
23
Werts, C. E., Linn, R. L., Jöreskog, K. G. (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and
psychological measurement, 34(1), 25–33.
Wilson, W. R. (1967). Correlates of avowed happiness. Psychological Bulletin, 67(4), 294–306.
Xiao, J. J., O’Neill, B. (2016). Consumer financial education and financial capability. International Journal of Consumer Studies,
40(6), 712–721.
Xiao, J. J., O’Neill, B. (2018). Propensity to plan, financial capability, and financial satisfaction. International Journal of
Consumer Studies, 42(5), 501–512.
Xiao, J. J., Porto, N. (2017). Financial education and financial satisfaction: Financial literacy, behavior, and capability as
mediators. International journal of bank marketing, 35(5).
Xiao, J. J., Chen, C., Chen, F. (2014). Consumer Financial Capability and Financial Satisfaction. Social Indicators Research,
118(1), 415–432. doi: 10.1007/s11205-013-0414-8
Yang, M., Mamun, A. A., Mohiuddin, M., et al. (2021). Predicting Stock Market Investment Intention and Behavior among
Malaysian Working Adults Using Partial Least Squares Structural Equation Modeling. Mathematics, 9(8), 873.
Yu, X., Liu, T., He, L., Li, Y. (2023). Micro-foundations of strategic decision-making in family business organisations: A
cognitive neuroscience perspective. Long range planning, 56(5), 102198.
Yulandreano, E., Rita, M. R. (2023). Investment decisions on the crowdfunding platform based on the theory of planned behavior.
Jurnal Manajemen Bisnis, 14(1), 36–52.
Zeb, A., Abdullah, N. H., Hussain, K., Misnah. (2022). Competing value framework model of organisational culture and job
performance: An examination of the mediating role of HPHR practices. International Journal of Services and Operations
Management, 42(1), 103–128.
Zeb, A., Bin Othayman, M., Goh, G. G. G., Shah, S. A. A. (2025). Exploring the mediating role of psychological factors in the
relationship between supervisor support and job performance. Journal of Modelling in Management, 20(1), 163–181.
Zeb, A., Gan, G. G. G., Wei, O. J., Karim, R. (2024). Examining the nexus between situational factors and job performance
through the mediating role of work engagement and self‐efficacy. Journal of Public Affairs, 24(2), e2915.
Journal of Infrastructure, Policy and Development 2025, 9(2), 9732.
24
Appendix
Table A1.
Constructs/Items/References
Financial Knowledge (FK) (Çera et al., 2021; Robb and Woodyard, 2011)
FK.1 I understand the cost of buying on credit.
FK.2 I am pretty good at calculation like profit and loss, percentage etc.
FK.3 An investment with a high return is likely to be highly risky
FK.4 High inflation means that the cost of living is increasing rapidly
FK.5 If price goes up rapidly, the money people have in saving accounts could lose much of its value
Financial Planning (FP) (Azwadi et al., 2015; Akhter and Hoque, 2022)
FP.1 I save money for retirement.
FP.2 At any time, I have some money saved for emergencies
FP.3 I ensure that with every pay, I save some
FP.4 My insurance/takaful coverage is sufficient to meet costs related to emergency events
Financial Satisfaction (FS) (Azwadi et al., 2015; Akhter and Hoque, 2022)
FS.1 I am satisfied with my current financial situation
FS.2 I can do little to improve my current financial situation
FS.3 I rarely run short of money
FS.4 Based on my current financial situation, I could easily obtain a loan if I needed one (e.g., car loans, personal loans)
FS.5 If I had a major loss of income I could manage for a period of time (e.g., for 3 months)
Financial Capability (FC) (Çera et al., 2021; Tahir et al., 2021)
FC.1 I am very organized when it comes to managing my money daily
FC.2 I do a good job of balancing my spending and saving
FC.3 I feel confident about the financial decision I make
FC.4 I feel comfortable dealing with banks and other financial institutions
Behavioral Intention (BI) (Akhter and Hoque, 2022; Hausman and Siekpe, 2009)
BI.1 I will invest in the share market
BI.2 I will speak favorably about investing in the share market
BI.3 I will recommend investing in the share market if someone asks for my advice
BI.4 I will encourage my friends and family to invest in the share market
