Determinants of Socio-Demographic Characteristics on Financial Inclusion of Women in Mataram City and West Lombok Regency

Taufiq Chaidir¹, Muaidy Yasin², Jalaludin³, Gst Ayu Arini⁴

Faculty of Economics and Business-Universitas Mataram, Indonesia

INFO ARTIKEL

ABSTRACT

Keywords:

The objective of this research is to demonstrate that various social factors, including education, employment status, and proximity to financial service locations, along with demographic factors such as age, marital status, number of family members, and number of family members who are employed, play a crucial role in determining the level of financial inclusion in Mataram City and West Lombok Regency. The research adopts a quantitative approach and falls under the category of explanatory research. Mataram City has six sub-districts (urban locality), and West Lombok Regency has ten sub-districts (rural locality). In this study, the sample was selected using a non-probability sampling technique, which was determined purposively. The number of samples is 200 women. Procedures and models for evaluation and testing hypotheses used Structural Equation Models (SEM) and Partial Least Squares (PLS). The coefficient of determination of the structural model (R2) and the adjusted R square value (Adj R2) are 0.1840 and 0.1670, respectively. The effect-size value (f2) is more than 0.02, namely 0.192 for social characteristics and 0.093 for demographic characteristics. The results of testing hypothesis 1 (H1) concluded that social characteristics do not significantly affect the financial inclusion of women while testing hypothesis 2 (H2) concluded that demographic characteristics significantly affect the financial inclusion of women in Mataram City and West Lombok Regency. It is recommended to the monetary authority that financial service offices and ATM outlets be closer and more easily accessible to the community.

socio-demographic characteristics, women's financial inclusion, effect size

INTRODUCTION

People's daily lives include economic activities (financial inclusion) such as transactions such as shopping, depositing or withdrawing cash from a bank or independent automated teller machine (ATM), credit or loan service, and so on. Financial inclusion is widespread and affects people differently depending on different communities' socio-demographic and economic characteristics. Individual financial inclusion is using financial products to gain livelihood benefits and improve living standards. According to (Cabeza-Garcï¿½a et al., 2019), financial inclusion can be summarised in two ways. First, the quantity of individuals and companies utilising financial services, or access to financial goods and services. Similarly, (M. Kim, 2018; D. W. Kim et al., 2018; Fareed, Gabriel, Lenain, dan Reynaud, 2017; Fareed, 2022) define financial inclusion as "all community activities in the economy, including credit or loans, payment transactions, savings, and demonstrated access to insurance." To increase capital stability, individuals can employ formal financial services rather than unofficial financial options by using reasonable, inexpensive, financial institutions that provide convenient services.

The significance of financial inclusion as a guideline for achieving seven of the seventeen 2030 Sustainable Development Goals (SDGs) has been widely acknowledged (UNCDF, 2020; Chitimira & Warikandwa, 2023): SDG 1: No Poverty; SDG 2: No Hunger; SDG 3: Healthy and Prosperous Lives; SDG 5: Advocating for fairness in access and empowering women to thrive economically.; SDG 8: Decent Work and Economic Growth; SDG 9: Driving progress in industries, fostering innovation, and establishing crucial infrastructure; and SDG 10: Reduced Inequality. Nonetheless, there is a significant gap in global financial inclusion. According to a GFI report (2017), approximately 1.7 billion adults worldwide are unbanked, indicating that approximately 23% of people are still unbanked or do not have an electronic money (e-money) account.

A crucial concern for governments, universities, and monetary authorities in recent decades has been financial inclusion. The significance of financial inclusion in enhancing people's lives and the well-being of society at large has been the subject of numerous studies. Financial inclusion can raise children's school attendance, income, healthcare spending, and consumption patterns at the household level, all of which can lead to superior welfare. (I Koomson, 2020; Sakyi-Nyarko et al., 2022), help reduce and alleviate poverty (Churchill & Marisetty, 2020; Isaac Koomson & Danquah, 2021), reduce gender disparities, and increase women's empowerment (Chakraborty & Abraham, 2021).ï¿½ Financial inclusion has been shown to boost regional development and economic growth rates, as well as reduce income inequality (Datta & Singh, 2019; M. Kim, 2018; Thathsarani et al., 2021; Ofosu-Mensah Ababio, Attah-Botchwey, Osei-Assibey, & Barnor, 2021; Barnor, 2021).

Participation in inclusive finance necessitates not just Bank Indonesia and the Financial Services Authority (OJK), with other regulatory bodies, government ministries, and various organizations collaborate to ensure the provision of financial services to the wider population,ï¿½ as the inclusive finance plan is not a piecemeal endeavour. The expectation is that the national inclusive finance plan would serve as a framework for collaboration between government departments and stakeholders. OJK conducted the National Survey of Financial Literacy and Inclusion (SNLIK) to measure the index of public financial literacy and inclusion (Otoritas Jasa Keuangan, 2022). SNLIK was conducted in 34 provinces covering 76 cities/districts from July to September 2022, with 14,634 respondents aged 15 to 79 years. Following the survey results, the Indonesian people's financial literacy index is 49.68 per cent, compared to 38.03 per cent in 2019. Meanwhile, the financial inclusion index in 2022 reached 85.10 per cent, an increase to 76.19 per cent in 2019. This shows that the literacy-inclusion gap is decreasing falling from 38.16 per cent in 2019 to 35.42 per cent in 2022. The results of SNLIK are expected to act as a basis for OJK and all stakeholders in developing policies, approaches and the development of financial services or solutions that meet customer needs while improving public finance accessibility and protection.

In terms of gender, women had a higher financial literacy index, at 50.33 per cent, compared to 49.05 per cent for men. From 2020 to 2022, OJK emphasizes women in the strategic direction of financial literacy. The male financial inclusion index, on the other hand, is higher at 86.28 per cent, compared to the female financial inclusion index of 83.88 per cent. Furthermore, the urban index of financial literacy and inclusion is 50.52 per cent and 86.73 per cent, respectively, higher than the rural index of 48.43 per cent and 82.69 per cent.

In this regard, the extent of financial inclusion in West Lombok Regency and Mataram City, as measured by the degree of financial inclusion in West Nusa Tenggara province, is still less than the national inclusion level of 62.7 per cent. In addition, the extent of financial inclusion does not correspond to the degree of public understanding of financial products, suggesting a lack of financial literacy. The NTB financial literacy rate is 34.6%, so it's lower than the national literacy rate of 38%. As a result, all efforts to accelerate financial inclusion that is evenly distributed and reaches frontier, surrounding, and underserved communities, as well as efforts to improve financial literacy, are both necessary and strategic.

Addressing the factors that contribute to limited financial inclusion in specific urban (Mataram City) and rural (West Lombok Regency) areas is crucial. This includes addressing the financial exclusivity experienced by individuals who are unable to access financial services due to affordability constraints(Carbï¿½ et al., 2005; Bashir et al., 2022). It is crucial to distinguish between financial exclusion that is voluntary and financial exclusion that is involuntary. Voluntary exclusion refers to the deliberate choice made by individuals not to engage with financial institutions for cultural or religious reasons. On the other hand, financial exclusion is the inability of individuals to access financial services due to social or economic factors. (World Bank, 2014). Figure 1 provides an overview of the various barriers to financial inclusion as perceived by individuals.

Trust, Inadequate product offering

Financial Barriers, Remote

Exclusive is not

voluntarily

Finansial Inklusif

Not financially literate, low understanding of fintech, use of other people's accounts

Finansial Eksklusif

Culture and Religious Beliefs

Voluntarily

exclusive

No need for financial services

Figure 1. Barriers to Financial Inclusion (Bashir et al., 2022).

The study focuses on how the sociodemographic traits of urban and rural women affect financial inclusion because it acknowledges the advantages of financial inclusion. In determining the perceived causes of the opposite phenomenon of financial exclusion and evaluating the perceived impact, it draws on several studies that indicate social variables are important. Urban and rural women's abilities and willingness to engage in the financial system are influenced by social variables. Empirical studies indicate that social factors play a significant role in shaping financial inclusion, on par with other factors. Variables such as age, health, education, financial literacy, gender inequality, and income are all recognized as crucial social factors that impact individuals' attitudes and behaviours toward financial inclusion. (Cabeza-Garcï¿½a et al., 2019; Demirgï¿½ï¿½-Kunt et al., 2013; Grohmann et al., 2018; Shaï¿½ban et al., 2019).

Additionally, the identification results showed that several factors discourage people from choosing financial services, including being close to monetary establishments, the cost of financial services, people's lack of trust in monetary establishments, financial constraints, people's religious beliefs, and the absence of a requirement to open a bank account. (Beckmann & Mare, 2017; Brown et al., 2016; Crï¿½pon et al., 2015; Girï¿½n et al., 2022). Financial inclusion for women in urban and rural areas is essential, as women play a significant role in the social and economic growth of households. Having a bank account can help women save more money, get loans at reasonable interest rates to grow their businesses, multiply their assets, and earn more income, by actively taking part in making decisions within the household, particularly those related to their health and children, individuals can ultimately contribute to poverty reduction (Efobi et al., 2014; Meurs & Ismaylov, 2019; Sierminskai et al., 2017; UN Women, 2022).

Several studies have highlighted a strong link between socio-demographic factors and financial inclusion. These factors include gender, age, income, place of residence, marital status, employment status, and household size. Financial literacy, access to the Internet, trust in financial institutions, required documentation for opening bank accounts, proximity to financial service providers, and the interplay between savings and loans are also considered relevant factors. (Allen et al., 2016; Demirgï¿½ï¿½-Kunt dkk., 2014;ï¿½ Fungï¿½čovï¿½ et al., 2016; Napier, Claire Melamed, 2012; Soumarï¿½ et al., 2016; Zins & Weill, 2016; Eze & Mark Jackson, 2020 ; Ogunleye, 2017; (Ozili, 2018).

Das Barwa (2015) finds the social conventions that could prevent women from obtaining financial services. Women's customary rules, such as their ownership of property and assets, suggest that they are unable to supply the collateral needed for bank lending facilities, which has an impact on bank account ownership generally. Other factors include women's poor bargaining strength and lack of decision-making ability. Given this phenomenon, understanding the various aspects of different regions, as well as policies to address them, is critical to increasing financial accessibility among women. According to the Alliance for Financial Inclusion (AFI, 2017)), rural women are more likely to be financially satisfied than urban women. It is commonly believed that rural women have limited access to digital resources and financial knowledge compared to their urban counterparts, leading to a lower likelihood of using formal financial services.

Expanding upon previous research that revealed varying impacts of determinants of financial access for urban and rural women, despite differences in local attributes, subsequent studies have identified notable distinctions in socio-demographic and economic characteristics between urban and rural areas. One way to help reach national financial accessibility policy targets is to develop location-specific strategies by identifying the elements that influence financial inclusion in both urban and rural locations. Overall, the final recommendations are expected to have a positive impact on women's empowerment and poverty alleviation for regional and national development, as well as the achievement of accelerated and synergistic sustainable development goals.

As a result, the reason for this investigation is to demonstrate and analyze social characteristics measured by indicators such as education, employment status, and distance to financial services office, as well as demographic characteristics measured by indicators such as age, marital status, number of household members, and number of working household members, as determinants of financial inclusion of urban-rural women in Mataram City and West Lombok Regency.

Financial Inclusion

Financial inclusion is the ability of individuals or groups to have access to formal financial products and services that are useful and affordable, and able to meet their needs, such as transactions, payments, savings, credit and insurance responsibly and sustainably (World Bank, 2014). Based on Financial Services Authority Regulation No. 76/POJK.07/2016 Concerning Improving Financial Literacy and Inclusion in the Financial Services Sector for Consumers and Communities article 1 paragraph 7, financial inclusion is the availability of access to various financial institutions, products, and services by the needs and abilities of the community to improve people's welfare (Financial Services Authority, 2016: 3).

According to Julie (2016), financial inclusion is an intervention strategy that seeks to address market frictions that prevent financial markets from operating for the poor or disadvantaged. The objective of these interventions is to bring individuals who do not have bank accounts into the formal financial system, enabling them to access a range of services including savings, payments, transfers, credit, and insurance. Bank Indonesia (2014) defines financial inclusion as encompassing any initiatives that seek to remove any obstacles, whether related to cost or other factors, that hinder the general public's ability to access financial services.

Financial Inclusion Objectives

Based on the Financial Services Authority regulation Number 76/POJK.07/2017 concerning Improving Financial Literacy and Inclusion in the Financial Services Sector for Consumers and the Community, the objectives of article 12 financial inclusion include (Financial Services Authority, 2016: 8): (1) Increasing community access to PUJK financial institutions, products and services. (2) Increasing the provision of financial products and services provided by PUJK to the needs and abilities of the community. (3) Increasing the use of financial products and services by the needs and abilities of the community. (4) Improving the quality of utilization of financial products and services under the needs and abilities of the community.

Benefits of Financial Inclusion

ï¿½ï¿½ Bank Indonesia has outlined several benefits of financial inclusion, as stated by Marginingsih (2021). These include: (1) Enhancing economic efficiency; (2) Promoting stability within the financial system; (3) Mitigating the impact of shadow banking and irresponsible financial practices; (4) Facilitating the deepening of financial markets; (5) Creating new market opportunities for banks; (6) Supporting the enhancement of Indonesia's Human Development Index (HDI); (7) Contributing positively to sustainable local and national economic growth; (8) Alleviating inequality and breaking free from the low-income trap, ultimately improving the welfare of the community and reducing poverty levels.

Financial Inclusion Measurement

The availability of inexpensive and economical access to formal financial services is a key factor in evaluating a country's inclusive finance. Furthermore, the frequency and duration of use of financial products and services, such as loans or insurance, can indicate the capacity to benefit from these services. Another aspect to consider is the quality of these financial products and services, particularly if they fulfil customer requirements. Finally, the influence of financial services on the overall well-being of those who use them can be assessed to determine their standard of living. (Ummah et al., 2018).

World Bank (2009) states that, in a perfect environment, the number of people, homes, and businesses that save money, use credit, make payments, and utilize other financial products from different financial institutionsï¿½both official and informalï¿½can be used to evaluate access to financial services. The number of persons using financial institutions' loan and savings services is the greatest way to gauge how accessible those services are to the general public (Ummah et al., 2018).

According to Sarma (2012), as cited in Simanjuntak (2019), three key indicators can serve as a reference point to evaluate the state of financial inclusion in a region. These indicators include the level of banking penetration, the availability of banking services, and the extent of their utilization. Given that the banking sub-sector holds a significant position within the formal financial sector compared to other sub-sectors, the use of banking indicators is crucial in assessing the state of financial inclusion within a specific region. (1). Accessibility, or the banking penetration dimension, is a measure of how much access to banking services a community has. Bank account ownership is an indicator that can illustrate that people have accessed banking services. (2). This aspect will pertain to the existing banking service infrastructure that is accessible to the community. The indicator used to assess the availability aspect of banking services is the number of bank branches or automated teller machines (ATMs) in a specific area. (3). The dimension of banking service usage serves to determine the extent to which people can utilize banking services. Bank loans and savings rates in a region are two indicators that can be used to measure how financial services are used.

According to Sanistasya (2019), Yanti (2019), Bongomin (2018), Wulandari (2019), financial access and welfare are the most popular indicators for gauging financial inclusion. Understanding financial products and services makes people more confident in using financial products and services effectively. The easier access to finance and the more protected they feel from transactions in financial institutions supported by the literate attitude of the individual, will make the individual use financial services according to their needs and abilities to improve welfare. Service Quality is the level of the good or bad condition of the services provided in realizing the fulfilment of consumer wants and needs, accuracy in delivery and consumer expectations (Tjiptono, 2014). Good service is needed to attract consumer desires. Online service providers who deal with consumers must provide good responsiveness, and friendly responses to gain the trust of consumers to make online transactions.

Hypothesis Development

Financial innovation includes the availability of new financial instruments, the availability of smart devices such as the use of smartphones for payment services, and the promotion of savings at the household level.ï¿½ Financial technology companies have a crucial role in boosting the number of Internet users and enhancing financial inclusion, particularly among women in Southeast Asia (Sumarsono et al., 2021). Kabakova and Plaksenkov (2018) examined various factors of financial inclusion in developing countries. This study highlights the importance of socio-economic and political factors that have a greater influence on developing countries. Turï¿½gano and Herrero (2018) examined how financial inclusion might help close the gap in income inequality in different nations.

Male members of the household dominate and have control over financial resources. Women do not have the opportunity to contribute financial resources that could help them increase their income-generating activities (Yadav et al., 2018). Women's economic empowerment and control over financial resources will be facilitated by their involvement in the business sector, particularly through access to the financial system and the development of entrepreneurial skills. Prior research has emphasized the significance of increased educational attainment and income levels for women in augmenting the degree of financial inclusion within a nation (Bhatia and Singh, 2019; Hendriks, 2019).

Social characteristics can play an important role in promoting financial inclusion as social well-being determines how people behave and make decisions in financial markets (Cull, Ehrbeck, & Holle, 2014). Previous research has demonstrated that people are more likely to avoid utilizing financial services and instead choose to use cash or even barter when their sociodemographic traits are poorer. As a result, fewer people will have bank accounts. Social welfare can also affect the depth of financial service use. However, this might not be an issue for the developed financial inclusion policies if the variety, complexity, and calibre of financial services are consistent with social growth.

The following is the study's hypothesis, which is based on the aforementioned description.

H1: Social characteristics measured by indicators of education, employment status, and distance of respondents' domicile to financial service offices have a significant and positive effect on women's financial inclusion in urban and rural areas (as measured by indicators of financial access, availability of financial products and services, use of financial products and services, quality of financial products and services).

H2: Demographic characteristics measured by indicators of age, marital status, the number of family members and the number of working family members in both urban and rural areas significantly and favourably affect women's financial inclusion (as determined by metrics for financial accessibility, availability, and use of financial services and products, as well as the calibre of those delivered).

RESEARCH METHODS

The research methodology is quantitative and falls under the category of explanatory research. There are two research locations: one in West Lombok Regency, which has ten sub-districts, and one in Mataram City, which has six sub-districts (urban locality). Using a non-probability sampling technique that was determined purposefully, the sample was chosen. The Slovin formula was used to determine the sample size for this investigation, which came out to be 200 women. methods for gathering data include documentation, interviews, and observation. A list of questions is used by the data collection tool (questionnaire). Procedures and data analysis models using PLS-SEM, with the stages of designing a structural model (inner model), and inner model equations:

η= β0 η+ γ ξ1+ γ ξ2

Design of measurement model (outer model).

Measurement model of Exogenous Latent Variable 1 (Social Characteristics)

X1i =λX1.1 ξ1+δ1 i

X1i =λX1.2 ξ1+δ2 i

X1i =λX1.3 ξ1+δ3 i

Measurement model of Exogenous Latent Variable 2 (Demographic Characteristics)

X2i =λX2.1 ξ2+δ4i

X2i =λX2.2 ξ2+δ5i

X2i =λX2.3 ξ2+δ6i

X2 i =λX2.4 ξ2+δ7

Endogenous Latent variable measurement model (financial inclusion)

Yi =λY1i η + λY2i η + λY3i η + λY4i η + εi

ï¿½Construction Model in Path Diagram

Finance accessibility (Y1)

Financial product and service availability (Y2)

Utilization of financial services and goods (Y3)

The calibre of financial services and goods (Y4)

Financial Inclusion (Y)

Education (X1.1)

Distance to financial service office (X1.3)

The number of family members who work (X2.4)

Age (X2.1)

Social Characteristics (X1)

Demographic Characteristics (X2)

Marital Status (X2.2)

Family size (X2.3)

Employment Status (X1.2)

H1(+)

H2(+)

Figure 2. Path Diagram Model

RESULTS AND DISCUSSION

RESULT

Inner Model Evaluation (Scrutural Model)

To assess the relevance between the structural model's constructs, the dependent construct of the path coefficient value or the t-value of each path is used to measure the structural model in PLS. This value is used to measure the level of variation in changes in the independent variable on the dependent variable. A higher test value indicates a stronger prediction model for the suggested research model (Jogiyanto & Abdillah, 2016: 62). This evaluation consists of three main criteria, namely Variance Inflation Factor (VIF), Coefficient of Determination (Rï¿½), and Effect Size (fï¿½).

Table 1. Outer VIF Value

Indicators and Variables		VIF
Education (X1.1)	Social Characteristics (X1)	1.228
Employment Status (X1.2)		1.261
Distance to financial service office (X1.3)		1.116
Age (X2.1)	Demographic Characteristics (X2)	1.609
Marital Status (X2.2)		1.943
Family size (X2.3)		1.519
The number of family members who work (X2.4)		1.261
Finance accessibility (Y1)	Financial Inclusion (Y)	4.190
Financial product and service availability (Y2)		2.211
Utilization of financial services and goods (Y3)		3.951
The calibre of financial services and goods (Y4)		4.060

ï¿½ Source: primary data (processed)

The Variance Inflation Factor (VIF) value for indicator variables (outer model) shows that all indicators have a value of less than 5.0, which means that there is no multicollinearity in the model. The results of the evaluation of the structural model based on the coefficient of determination (R²), and Adjusted R Square (Adj R²) are presented in Table 2 below.

The analysis is classified as moderate since the female financial inclusion construct's R square value is 0.184. This means that the construct of women's financial inclusion is influenced by the construct of socio-demographic characteristics by 18.40 per cent, while the construct outside the model by 81.60 per cent is influenced by other variables such as financial literacy, demographic characteristics, and culture, among others.

A substantial association between variables can be determined by looking at the Effect Size (f2) value. According to the analysis's findings, every variable is classified as influencing if its f2 value is more than 0.02. In other words, there is an influence of socio-demographic characteristics on women's financial inclusion in Mataram City and West Lombok Regency. The results of the fï¿½ value are shown in the following table 2.

Table 2. Results of f Square

	f Square (f² )
Demographic Characteristics (X2) -> Financial Inclusion (Y)	0.192
Social Characteristics (X1) -> Financial Inclusion (Y)	0.093

Source: primary data, processed

According to Wong (2013), a researcher should also assess the effect between variables with Effect Size (f square). The values of fï¿½ = 0.02 (small), fï¿½ = 0.15 (medium), fï¿½ = 0.35 (large), and the value of fï¿½ less than 0.02 can be ignored or considered no effect (Sarstedt et al., 2017). Next, evaluate the fit of the model (model fit) which includes, SRMR, Chi-Square and NFI values.

Table 3. Model fit

Criteria	Saturated Model	Estimated Model
SRMR	0.165	0.165
d_ULS	1.800	1.800
d_G	0.562	0.562
Chi-Square	263.541	263.541
NFI	0.567	0.567

ï¿½ Source: primary data, processed

Based on the results in Table 3, show that the three criteria for assessing suitability, namely SRMR, Chi-Square and NFI, have values of 0.165, 263.541, and 0.567 respectively. This means that the model is categorized as suitable (suitable).

After testing the outer model, convergent, discriminant, and reliability tests are conducted. Then, the next step is to test the hypothesis. Bootstrap analysis is employed to calculate the relationship coefficient of each variable, considering both direct and indirect effects. The t-statistic test value, which is compared with the t-table value at a certain alpha level, forms the foundation of the evaluation criteria. With an alpha value of 5%, the t-table value is 1.96, or it's compared with the P-value. A decision is made about rejecting the null hypothesis (H0) or accepting the alternative hypothesis (Ha) based on the t-statistic value exceeding 1.96 or the P-value being below 0.05. After processing the data, the outer loadings bootstrap results are derived, which include the statistical t value of each indicator on its variable, guiding the hypothesis testing to conclude. The results of outer loadings bootstrap and structural model diagrams are presented in the subsequent table and figure.

Table 4. Bootsrapping Outer Loadings Results

Indicator Relationship to Variable	Original Sample	Sample Average	Standard Deviation	t Statistic	P Values	Summary
X1.1 <- Social Characteristics (X1)	0.742	0.546	0.413	1.795	0.073	Significant
X1.2 <- Social Characteristics (X1)	0.893	0.657	0.452	1.975	0.049	Significant
X1.3 <- Social Characteristics (X1)	-0.489	-0.240	0.523	0.936	0.350	Not Significant
X2.1 <- Demographic Characteristics (X2)	-0.291	-0.126	0.419	0.693	0.488	Not Significant
X2.2 <- Demographic Characteristics (X2)	-0.603	-0.426	0.404	1.492	0.136	Not Significant
X2.3 <- Demographic Characteristics (X2)	0.787	0.651	0.307	2.567	0.011	Significant
X2.4 <- Demographic Characteristics (X2)	0.861	0.765	0.270	3.183	0.002	Significant
Y1 <- Financial Inclusion (Y)	0.922	0.910	0.109	8.444	0.000	Significant
Y2 <- Financial Inclusion (Y)	0.777	0.761	0.148	5.240	0.000	Significant
Y3 <- Financial Inclusion (Y)	0.945	0.926	0.117	8.055	0.000	Significant
Y4 <- Financial Inclusion (Y)	0.904	0.888	0.123	7.339	0.000	Significant

ï¿½ Source: primary data, processed

Figure 3: Structural Model Diagram

The next test result is to see the path coefficient according to the overall amount of the direct effect of social characteristics and demographics on women's financial inclusion in Mataram City and West Lombok Regency. The total direct effect value is displayed in Table 5 below.

Table 5. The entire direct effect's value

	Original Sample	Standard Deviation	t Statistic	P Values	Summary
Social Characteristics (X1) -> Financial Inclusion (Y)	0.289	0.192	1.504	0.133	Not Significant
Demographic Characteristics (X2) -> Financial Inclusion (Y)	0.415	0.159	2.615	0.009	Significant

Source: primary data, processed

Based on Table 5, it can be explained that the t-statistic value of social characteristics is 1.504 when compared to the t-table at 5 per cent alpha is 1.96, meaning that 1.504 is smaller than 1.96 (P value = 0.133), then the decision H0 is accepted (Ha is rejected). Thus the proposed hypothesis 1 (H1) which states that social characteristics have a positive and significant effect on women's financial inclusion is not proven (rejected).

Furthermore, from the same table (table 5) it can also be explained that the t-statistic value of demographic characteristics is 2.615 when compared to the t-table at 5 per cent alpha is 1.96, meaning that 2.615 is greater than 1.96 (P value = 0.009), then the decision H0 is rejected. Thus the proposed hypothesis 2 (H2) which states that demographic characteristics have a positive and significant effect on women's financial inclusion is proven (accepted).

DISCUSSION

According to the findings, social factors such as education, work status, and the distance between a respondent's place of residence and the financial services office do not significantly affect how financially included women are in both urban and rural areas (with indicators including financial access, understanding of the accessibility, utilization, and calibre of financial goods and services). Low financial access, including low bank account ownership, low access to bank financing, and little knowledge of banking goods and services, can be seen as a reflection of low financial inclusion, among other things.

The cause of low bank account ownership is more due to the gap in education level, employment characteristics, and individual women against the overall women who have access to finance (access to banking institutions). Contrary to popular belief, research from Allen et al., (2016), Alliance for Financial Inclusion (AFI, 2017), and improving Financial Innovation & Access (EFI, 2019) found that women are more likely to be financially included in rural areas (22.2 per cent) compared to urban areas (18.5 per cent).

The research findings on the second characteristic, namely demographic characteristics as measured by age, marital status, number of family members, as well as the number of those who are employed. It was revealed that demographic characteristics have a significant effect on the financial inclusion of women in urban and rural areas. The age factor has a diversity of levels that will also affect financial inclusion among urban and rural women. Women in urban areas have lower chances of financial inclusion, while women in rural areas have higher chances. The link between age and increased opportunities for financial inclusion supports the results of research conducted by (Abel et al., 2018; Allen et al., 2016; Kaur & Kapuria, 2020; Pena, et al., 2014; Soumarï¿½ et al., 2016).

This study's findings indicate differences in the level of financial inclusion between urban and rural women. These differences in locality are considered an important clue to increasing financial inclusion among women, as highlighted in some countries' financial inclusion strategies (Anyanwu et al., 2018). As evidenced in previous studies (Bhatia & Singh, 2019;ï¿½ Clarke & Kumar, 2016;ï¿½ Dimova & Adebowale, 2018), the research findings are not only important for empowering women and increasing the degree of women's independence in decision-making within their households but are also crucial for achieving gender equality (Adewoyin et al., 2022).

CONCLUSION

It is imperative to improve women's financial inclusion in both urban and rural areas because financial inclusion can boost the empowerment of women, and enable them to improve household economic resilience, control their health, and that of their children and family members, reduce poverty, and be a driver to achieve sustainable development goals. It was also revealed that the results of this study showed a financial inclusion gap between women in urban and rural areas (in Mataram City and West Lombok Regency) in particular, and on the island of Lombok, in general. It implicitly reveals that to achieve regional, and national financial inclusion policy targets, the strategy to be considered is to address the differences in socio-demographic characteristics between urban and rural areas through continuous financial education or literacy

REFERENCES

Abel, S., Mutandwa, L., & Le Roux, P. (2018). International Journal of Economics and Financial Issues A Review of Determinants of Financial Inclusion. International Journal of Economics and Financial Issues, 8(3), 1ï¿½8.

Adewoyin, Y., Nwosu, I. G., Ossai, O. G., & Onuh, J. (2022). Rural-Urban Differentials in Levels and Correlates of Financial Inclusion Among Nigerian Women Aged 18 to 49. Journal of Population and Social Studies, 30, 448ï¿½462. https://doi.org/10.25133/JPSSv302022.026

AFI. (2017). Bridging the gender gap: Promoting womenï¿½s financial inclusion. 1ï¿½88.

Allen, F., Demirguc-Kunt, A., Klapper, L., & Martinez Peria, M. S. (2016). The foundations of financial inclusion: Understanding ownership and use of formal accounts. Journal of Financial Intermediation, 27, 1ï¿½30. https://doi.org/10.1016/j.jfi.2015.12.003

Anyanwu, F. A., Ananwude, A. C., & Nnoje, A. I. (2018). Financial Inclusion: Nigeriaï¿½s Microfinance Model Effect Assessment on Women Empowerment. European Journal of Human Resource Management Studies, 1(2), 55ï¿½77. https://doi.org/10.5281/zenodo.1188521

Bashir, S., Nawaz, A., & Ayesha, S. N. (2022). Financial Inclusion Profile: Socio-Economic Determinants, Barriers, and the Reasons for Saving and Borrowing in Pakistan. International Journal of Asian Social Science, 12(10), 449ï¿½462. https://doi.org/10.55493/5007.v12i10.4622

Beckmann, E., & Mare, D. S. (2017). Formal and Informal Household Savings: How Does Trust in Financial Institutions Influence the Choice of Saving Instruments? SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3023711

Bhatia, S., & Singh, S. (2019). Empowering Women Through Financial Inclusion: A Study of Urban Slum. Vikalpa, 44(4), 182ï¿½197. https://doi.org/10.1177/0256090919897809

Bongomin, G. O. C. (2018). Mobile Money and Financial Inclusion in Sub-Saharan Africa: the Moderating Role of Social Networks. Journal of African Business, 19(3), 361ï¿½384. https://doi.org/10.1080/15228916.2017.1416214

Brown, M., Guin, B., & Kirschenmann, K. (2016). Microfinance Banks and Financial Inclusion. Review of Finance, 20(3), 907ï¿½946. https://doi.org/10.1093/rof/rfv026

Cabeza-Garcï¿½a, L., Del Brio, E. B., & Oscanoa-Victorio, M. L. (2019). Female financial inclusion and its impacts on inclusive economic development. Womenï¿½s Studies International Forum, 77(October 2018), 102300. https://doi.org/10.1016/j.wsif.2019.102300

Carbï¿½, S., Gardener, E. P. M., & Molyneux, P. (2005). Financial Exclusion. Financial Exclusion, 44ï¿½46. https://doi.org/10.1057/9780230508743

Chakraborty, R., & Abraham, R. (2021). The impact of financial inclusion on economic development: the mediating roles of gross savings, social empowerment and economic empowerment. International Journal of Social Economics, 48(6), 878ï¿½897. https://doi.org/10.1108/IJSE-02-2020-0077

Chitimira, H., & Warikandwa, T. (2023). Financial Inclusion Regulatory Practices in SADC. In Financial Inclusion Regulatory Practices in SADC. https://doi.org/10.4324/9781003369400

Churchill, S. A., & Marisetty, V. B. (2020). Financial inclusion and poverty: a tale of forty-five thousand households. Applied Economics, 52(16), 1777ï¿½1788. https://doi.org/10.1080/00036846.2019.1678732

Clarke, D. J., & Kumar, N. (2016). Microinsurance Decisions: Gendered Evidence from Rural Bangladesh. Gender, Technology and Development, 20(2), 218ï¿½241. https://doi.org/10.1177/0971852416639784

Crï¿½pon, B., Devoto, F., Duflo, E., & Parientï¿½, W. (2015). Estimating the impact of microcredit on those who take it up: Evidence from a randomized experiment in Morocco. American Economic Journal: Applied Economics, 7(1), 123ï¿½150. https://doi.org/10.1257/app.20130535

Datta, S. K., & Singh, K. (2019). Variation and determinants of financial inclusion and their association with human development: A cross-country analysis. IIMB Management Review, 31(4), 336ï¿½349. https://doi.org/10.1016/j.iimb.2019.07.013

Demirgï¿½ï¿½-Kunt, A., Klapper, L., & Singer, D. (2013). Financial inclusion and legal discrimination against women: Evidence from developing countries. World Bank Policy Research Working Paper, April, 45.

Dimova, R., & Adebowale, O. (2018). Does Access to Formal Finance Matter for Welfare and Inequality? Micro Level Evidence from Nigeria. Journal of Development Studies, 54(9), 1534ï¿½1550. https://doi.org/10.1080/00220388.2017.1371293

Efobi, U., Beecroft, I., & Osabuohien, E. (2014). Access to and use of bank services in Nigeria: Micro-econometric evidence. Review of Development Finance, 4(2), 104ï¿½114. https://doi.org/10.1016/j.rdf.2014.05.002

Fareed, Z. (2022). Financial inclusion and the environmental deterioration in Eurozone: The moderating role of innovation activity. Technology in Society, 69. https://doi.org/10.1016/j.techsoc.2022.101961

Fungï¿½čovï¿½, Z., Nuutilainen, R., & Weill, L. (2016). Reserve requirements and the bank lending channel in China. Journal of Macroeconomics, 50(March), 37ï¿½50. https://doi.org/10.1016/j.jmacro.2016.08.007

Girï¿½n, A., Kazemikhasragh, A., Cicchiello, A. F., & Panetti, E. (2022). Financial Inclusion Measurement in the Least Developed Countries in Asia and Africa. Journal of the Knowledge Economy, 13(2), 1198ï¿½1211. https://doi.org/10.1007/s13132-021-00773-2

Grohmann, A., Klï¿½hs, T., & Menkhoff, L. (2018). Does financial literacy improve financial inclusion? Cross country evidence. World Development, 111, 84ï¿½96. https://doi.org/10.1016/j.worlddev.2018.06.020

Kaur, S., & Kapuria, C. (2020). Determinants of financial inclusion in rural India: does gender matter? International Journal of Social Economics, 47(6), 747ï¿½767. https://doi.org/10.1108/IJSE-07-2019-0439

Kim, D. W., Yu, J. S., & Hassan, M. K. (2018). Financial inclusion and economic growth in OIC countries. Research in International Business and Finance, 43, 1ï¿½14. https://doi.org/10.1016/j.ribaf.2017.07.178

Kim, M. (2018). Mobile financial services, financial inclusion, and development: A systematic review of academic literature. Electronic Journal of Information Systems in Developing Countries, 84(5). https://doi.org/10.1002/isd2.12044

Koomson, I. (2020). Effect of Financial Inclusion on Poverty and Vulnerability to Poverty: Evidence Using a Multidimensional Measure of Financial Inclusion. Social Indicators Research, 149(2), 613ï¿½639. https://doi.org/10.1007/s11205-019-02263-0

Koomson, I., & Danquah, M. (2021). Working paper.

Marginingsih, R. (2021). Financial Technology (Fintech) Dalam Inklusi Keuangan Nasional di Masa Pandemi Covid-19. Moneter - Jurnal Akuntansi Dan Keuangan, 8(1), 56ï¿½64. https://doi.org/10.31294/moneter.v8i1.9903

Meurs, M., & Ismaylov, R. (2019). Improving Assessments of Gender Bargaining Power: A Case Study from Bangladesh. Feminist Economics, 25(1), 90ï¿½118. https://doi.org/10.1080/13545701.2018.1546957

Napier, Claire Melamed, G. T. and T. J. (2012). Promoting women ï¿½ s financial inclusion. Deutsche Gesellschaft Fï¿½r Internationale Zusammenarbeit (GIZ) GmbH Registered Offices Bonn and Eschborn | Germany Sector.

Ogunleye, T. S. (2017). Financial Inclusion and the Role of Women in Nigeria. African Development Review, 29(2), 249ï¿½258. https://doi.org/10.1111/1467-8268.12254

Otoritas Jasa Keuangan. (2022). SIARAN PERS INDEKS LITERASI DAN INKLUSI KEUANGAN MASYARAKAT MENINGKAT.

Ozili, P. K. (2018). Impact of digital finance on financial inclusion and stability. Borsa Istanbul Review, 18(4), 329ï¿½340. https://doi.org/10.1016/j.bir.2017.12.003

Pena, X. (n.d.). Determinants of Financial Inclusion in Mexico.

Sakyi-Nyarko, C., Ahmad, A. H., & Green, C. J. (2022). The Gender-Differential Effect of Financial Inclusion on Household Financial Resilience. Journal of Development Studies, 58(4), 692ï¿½712. https://doi.org/10.1080/00220388.2021.2013467

Shaï¿½ban, M., Girardone, C., & Sarkisyan, A. (2019). Financial Inclusion: Trends and Determinants. 119ï¿½136. https://doi.org/10.1007/978-3-030-16295-5_5

Sierminskai, E., Girshina, A., & Europäische Kommission Generaldirektion Justiz und Verbraucher. (2017). Wealth and gender in Europe. https://doi.org/10.2838/39491

Soumarï¿½, I., Tchana Tchana, F., & Kengne, T. M. (2016). Analysis of the determinants of financial inclusion in Central and West Africa. Transnational Corporations Review, 8(4), 231ï¿½249. https://doi.org/10.1080/19186444.2016.1265763

Thathsarani, U., Wei, J., & Samaraweera, G. (2021). Financial inclusionï¿½s role in economic growth and human capital in south asia: An econometric approach. Sustainability (Switzerland), 13(8), 1ï¿½18. https://doi.org/10.3390/su13084303

True, H. T. H. E. (2020). Harnessing the True Power of Capital :

Zins, A., & Weill, L. (2016). The determinants of financial inclusion in Africa. Review of Development Finance, 6(1), 46ï¿½57. https://doi.org/10.1016/j.rdf.2016.05.001

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