Student-staff partnership and university-based entrepreneurial venture: The nexus of internally generated revenue and financial inclusion

This systematic review of the literature includes an assessment of student-staff partnership, internally generated revenue (IGR), and financial inclusion in Nigerian universities with an eye toward entrepreneurial ventures. Financial inclusion promotes the development and entrepreneurial ventures. There have been studies on IGR student-staff partnerships and financial inclusion in Nigerian universities. This study synthesizes and evaluates previous research. During the systematic review, academic databases are searched. Fifty eligible studies were examined. We shed light on the student-staff partnership, financial inclusion, and IGR in Nigerian university entrepreneurial ventures. Financial inclusion in the analysis is defined as financial resources, financial literacy, and student and staff entrepreneurial venturing. It emphasizes IGR as a trustworthy source of funding for university entrepreneurial ventures. Student-staff partnerships as joint research, mentoring, and student-led businesses, according to the review, promote financial inclusion. The synthesis recommends a coordinated approach to evaluating financial inclusion from IGR and student-staff partnerships in Nigerian universities. More research on entrepreneurial venture and financial inclusion strategies, best practices, and policy recommendations is required. This systematic review of the literature summarizes financial inclusion, IGR, student-staff partnerships, and entrepreneurial ventures in Nigerian universities. The findings support the creation of targeted initiatives by policymakers, university leaders, and researchers to improve financial inclusion, empower students and members of staff, and foster a thriving entrepreneurial venture ecosystem in Nigerian universities.

Women’s financial literacy and financial inclusion have gained prominence in recent years. Despite progress, knowledge and access to finance remain common barriers for women, especially in emerging economies. Globally, domestic and economic violence has been recognized as a relevant social concern from a gender perspective. In this context, financial literacy and financial inclusion are considered to play a key role in reducing violence against women by empowering them with the necessary knowledge to manage their financial resources and make informed decisions. This study aims to evaluate the determinants that influence Peruvian female university students’ financial literacy and financial inclusion. To this end, a theoretical behavioral model is proposed, and a survey is applied to 427 female university students. The results are analyzed using a Partial Least Squares Structural Equation Model (PLS-SEM). The results validate all the proposed hypotheses and highlight significant relationships between financial literacy and women’s financial inclusion. A relevant relationship between financial attitude and financial behavior is also observed, as well as the influence of financial behavior and financial self-efficacy on financial literacy. The results also reveal that women feel capable of making important financial decisions for themselves and consider that financial literacy could help reduce gender-based violence. Based on these findings, theoretical and practical implications are raised. It highlights the proposal of a theoretical model based on antecedents, statistically validated in a sample of women in Peru, which lays the foundation for understanding financial literacy and financial inclusion in the Latin American region.

Financial inclusion is critical to supporting women’s entrepreneurial endeavors in today’s changing financial landscape. Despite representing the majority of micro and small businesses (SMEs) in Indonesia, women entrepreneurs continue to confront challenges to their development and sustainability. Supply-side discrimination, low financial literacy, restricted access to formal institutions, and a low demand for capital all hinder their ability to obtain finance, which is frequently biased against male entrepreneurs. This study looks at how financial literacy, financial inclusion, and financial access affect entrepreneurial development, firm performance, and sustainability among Indonesian women entrepreneurs. Five hundred forty-two responses were collected from women entrepreneurs during June–July 2024 and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that financial inclusion (β = 0.524) and financial literacy (β = 0.296) significantly improve financial access, which positively affects women’s entrepreneurial development (β = 0.484) and business performance (β = 0.383). Women’s entrepreneurial development also contributes to performance (β = 0.364), strongly affecting business sustainability (β = 0.502). Notably, the model explains 55.8% of the variance in women-owned SMEs’ business sustainability (R2 = 0.558), the highest among all endogenous constructs. This study enhances existing knowledge by emphasizing the interrelated roles of financial literacy, inclusion, and access in shaping women’s entrepreneurial ecosystems. This highlights the necessity for specific policies and initiatives aimed at tackling structural obstacles and gender inequalities in the financial sector. Enhancing these components can enable women entrepreneurs, improve SME performance, and foster sustainable, inclusive economic growth in Indonesia.

This study investigates the relationship between human capital development and financial inclusion in remote regions of Indonesia, highlighting the mediating role of the entrepreneurial mindset. The research surveyed 142 undergraduate students from Universitas Cenderawasih selected using Slovin’s formula and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS. Construct reliability and validity demonstrated strong measurement model performance, with Cronbach’s Alpha values ranging from 0.892 to 0.934 and AVE values above 0.50, confirming robust reliability and convergent validity. The structural model indicated moderate predictive capability with R² values of 0.652 for entrepreneurial mindset and 0.420 for financial inclusion. Hypothesis testing revealed that human capital development significantly affects both financial inclusion (β = 0.332; t = 2.310; p = 0.021) and entrepreneurial mindset (β = 0.808; t = 16.773; p = 0.000). Additionally, entrepreneurial mindset significantly impacts financial inclusion (β = 0.349; t = 2.691; p = 0.007). A significant indirect effect also confirmed entrepreneurial mindset as a mediator in the relationship between human capital development and financial inclusion (β = 0.282; t = 2.647; p = 0.008). These findings emphasize the strategic integration of entrepreneurial education and human capital enhancement to strengthen financial inclusion initiatives in marginalized regions

This study investigates the mediating roles of financial literacy and financial inclusion in the relationship between fintech and MSME financial performance in Denpasar City. Employing a quantitative associative design, the research utilized an online questionnaire to collect data from 130 MSMEs using fintech services, selected through snowball sampling. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS version 3. The results indicate that while fintech does not directly and significantly impact MSME financial performance, it significantly and positively influences both financial literacy and financial inclusion. Crucially, financial literacy was found to have a positive and significant effect on MSME financial performance, and it significantly mediated the relationship between fintech and MSME financial performance. Conversely, financial inclusion did not have a significant effect on MSME financial performance, nor did it significantly mediate this relationship. These findings highlight the critical importance of enhancing financial literacy among MSMEs to maximize the benefits of fintech adoption and improve their financial performance.

This study investigates the indirect relationship between FinTech adoption and sustainable financial behavior through the mediating roles of financial literacy and financial inclusion in the Indonesian context. While the proliferation of FinTech services is often seen as a catalyst for financial transformation, evidence remains limited regarding its behavioral impact, particularly in emerging markets. Using a quantitative explanatory design and data from 315 active FinTech users across diverse regions in Indonesia, this study applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine both direct and mediated effects. The results show that FinTech adoption significantly influences financial literacy and financial inclusion, but does not directly affect sustainable financial behavior. Instead, its influence is fully mediated by the users’ financial knowledge and access to financial services. These findings underscore the critical importance of capability and access in realizing the behavioral benefits of digital financial tools. The study offers theoretical contributions by extending the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) within a FinTech context and provides practical implications for inclusive financial policy and literacy-driven innovation strategies.

This review provides a comprehensive, step-by-step guide to the application of partial least squares structural equation modeling (PLS-SEM) for novice researchers. This is a conceptual and literature-based review that focuses on best practices and PLS-SEM literature. It highlights the rationale for using PLS-SEM, sample size, software tools, and essential metrics in PLS-SEM analysis. Drawing on best practices and recent literature, the review offers a framework for conducting and reporting PLS-SEM analysis. The review presents essential such as outer loadings, Cronbach’s alpha coefficients, average variance extracted (AVE), composite reliability, cross-loadings, Heterotrait-Monotrait ratio of correlations (HTMT), the Fornell-Larcker criterion, variance inflation factor (VIF), and redundancy analysis. Moreover, for more consistent results, the paper emphasizes on researchers to employ 10,000 bootstrap subsamples and Bias-corrected and accelerated (BCa) bootstrap in assessing the structural model. Insights regarding path coefficients, p-values, R-square (R2), f-square (f2), and Q-square (Q2), are also presented. Furthermore, the review underscores the trade-off between predictive power and model fit when applying PLS-SEM. The presented practical insights alert novice researchers in avoiding common pitfalls and enhance the methodological rigor of empirical research that utilizes PLS-SEM. This step-by-step guide supports early-career researchers and contributes to the ongoing debates on improving methodological clarity and transparency.

Purpose: This study investigates the perceived interplay of social capital, financial inclusion, financial literacy, and micro takaful in fostering post-conflict economic rehabilitation in Sudan. Methodology: A quantitative research design employing a survey questionnaire was utilized to collect data from a purposive sample of 98 respondents. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze the data. Findings: Micro takaful and social capital exhibited statistically significant positive effects on post-conflict economic rehabilitation, with medium effect sizes. Financial inclusion showed a positive but smaller effect, while financial literacy had no significant impact. The model demonstrated substantial explanatory power (R² = 0.490) and strong predictive validity. Importance-Performance Map Analysis (IPMA) highlighted micro takaful and social capital as key drivers of rehabilitation. Practical Implications: Policymakers should prioritize interventions strengthening micro takaful and social capital. Efforts to enhance financial inclusion should address contextual challenges limiting its effectiveness. The study’s predictive model can guide resource allocation for post-conflict recovery programs. Originality: The study provides an indepth understanding of the interplay between social capital, financial inclusion, financial literacy, and micro takaful in a post-conflict setting, offering suggestions for promoting economic rehabilitation in Sudan and potentially other similar contexts.

Artificial Intelligence (AI) integration in emerging economies like Pakistan presents a transformative opportunity to advance financial inclusion. This study investigates the influence of AI on financial inclusion through key mediating variables—financial literacy, user adoption, financial behavior practices, government support, and AI-based risk mitigation—using a quantitative methodology. Data from 250 financial service users were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that financial literacy (β = 0.558, p < 0.001) and user adoption (β = 0.368, p < 0.001) significantly mediate the relationship between AI and financial inclusion, with financial literacy showing the strongest effect. In contrast, financial behavior practices (p = 0.250), government support (p = 0.268), and risk mitigation (p = 0.111) were found to have no significant mediating influence. Theoretically, the study extends existing literature by integrating the Technology Acceptance Model (TAM), Financial Inclusion Theory, Diffusion of Innovation Theory, and Social Cognitive Theory, offering a multidimensional understanding of how AI adoption interacts with user behavior and systemic access. It challenges conventional assumptions about the sufficiency of institutional support, emphasizing instead the centrality of financial literacy and user readiness in AI-driven inclusion. Methodologically, the study demonstrates the value of PLS-SEM in validating complex structural models with multiple latent constructs in emerging market contexts. The results offer valuable insights for researchers and policymakers aiming to design AI-enabled strategies that improve financial literacy, boost user adoption, and foster inclusive financial ecosystems. Keywords: Artificial Intelligence, Financial Inclusion, Financial Literacy, User adoption, AI-Based Risk Mitigation, Financial Behavior Practices, Government Support.

Voluminous studies use Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze data. One of the reasons for using PLS-SEM is when the structural model is complex. Studies employing complex structural models with many constructs and indicators lead to PLS-SEM selection for the analysis. The purposes of assessing the measurement model are to examine basic dimensions for construct variables, validate the dimensions, and determine the number of dimensions for each construct. Assessment of measurement model includes composite reliability and average variance extracted (AVE) to assess reliability and validity, respectively. This study tests the validity and reliability of the attitude construct in the context of compliance behavior of income zakat that other studies can use. This study assesses the measurement model to examine basic dimensions for construct variables, validate the dimensions, and determine the number of dimensions for each construct. Assessment of measurement model includes composite reliability and average variance extracted (AVE) to assess reliability and validity, respectively. This study hopes future research can adapt and adopts the attitude items used in this study in their future research.

In contemporary research, Partial Least Squares Structural Equation Modeling (PLS-SEM) has emerged as a crucial statistical tool, particularly effective for analyzing complex structural models involving multiple constructs and indicators.This paper aims to elucidate the application of PLS-SEM in quantitative research, highlighting its advantages in extending theories and simultaneously estimating measurement and structural models.The methodological approach is divided into three primary stages: data screening and diagnostic tests, measurement model assessment, and structural model assessment.The data screening ensures dataset suitability by addressing missing data and outliers, while diagnostic tests fulfil normality, linearity, and multicollinearity assumptions.The measurement model assessment validates constructs through composite reliability and average variance extracted (AVE) metrics.The structural model assessment evaluates the significance and relevance of relationships between constructs, determines the coefficient of determination (R and adjusted R), assesses mediating effects, and analyzes the moderating variables.By detailing these methodological steps, the article provides a comprehensive guide for researchers aiming to employ PLS-SEM in their studies, emphasizing its rigour and practicality in handling complex theoretical models.

This study investigates the role of Financial Technology (Fintech) and Artificial Intelligence (AI) in strengthening financial governance accountability and improving national financial inclusion. While prior studies have largely examined fintech and AI separately, this research develops an integrated model that positions accountability as a key mediating mechanism linking technological integration to broader financial inclusion outcomes. Using a quantitative explanatory design, data were collected through a digital survey involving 300 respondents consisting of public sector stakeholders, fintech actors, and users of digital financial services. The data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results reveal that fintech integration positively and significantly affects accountability and financial inclusion. Likewise, AI implementation significantly improves accountability and financial inclusion. Accountability also exerts a strong positive effect on financial inclusion. Mediation analysis shows that accountability partially mediates the effects of fintech and AI on financial inclusion. These findings suggest that the integration of fintech and AI contributes not only to operational efficiency but also to the improvement of governance quality and the expansion of inclusive financial access. The study contributes to the literature by proposing an integrative fintech, AI, accountability, financial inclusion framework in the context of a developing economy and offers evidence-based implications for policymakers and financial regulators.

Objective: This study examines the determinants of financial inclusion among MSME owners in North Central Nigeria. Research Design & Methods: The study adopted a survey research design; the target population consisted of 11,607 MSME owners across North Central Nigeria. A combination of stratified and simple random sampling techniques was used to select participants. The sample size of 435 was determined using Krejcie and Morgan’s (1970) sample size formula. Data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings: The findings revealed that push-pull factors significantly explained variations in financial inclusion. Based on these results, the study concludes that push-pull factors have a positive effect on the financial inclusion of MSME owners in North Central Nigeria. Practical Implications: This study accentuates the imperative for financial regulatory bodies to adopt targeted financial inclusion management strategies tailored to the unique needs of Micro, Small, and Medium Enterprises (MSMEs). By doing so, these institutions can catalyze economic emancipation, particularly in emerging economies such as Nigeria. Recommendations: The study recommends that the government should implement financial literacy programs to raise awareness among MSME owners about the importance of financial knowledge and skills. Additionally, the government should collaborate with banks to provide lower interest rates and more flexible repayment options to ensure that financial support effectively reaches the intended beneficiaries. Contribution & Value Added: This research contributes to the literature by empirically demonstrating the influence of push-pull factors such as necessity-driven entrepreneurship (push) and opportunity-driven entrepreneurship (pull) on MSME performance in Kwara State, Nigeria.

Financial inclusion has emerged as a pivotal strategy to drive sustainable economic growth and reduce inequality in developing economies. In Indonesia, more than 66 million adults remain excluded from formal financial systems. This study investigates how Electronic Word of Mouth (eWOM) and perceived government support affect behavioral intention and motivation to adopt mobile banking, with the broader aim of promoting financial inclusion. Drawing from the Technology Acceptance Model 3 (TAM3), Prospect Theory, and Financial Inclusion Theory, the study proposes a structural model that incorporates perceived usefulness, perceived ease of use, perceived risk, perceived cost, and trust as mediators influenced by eWOM. A total of 252 unbanked respondents across six Indonesian regions were surveyed, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results show that perceived usefulness, ease of use, and risk significantly predict behavioral intention to adopt mobile banking. eWOM has a strong impact on shaping perceptions of trust and usefulness, while perceived government support significantly moderates the effect of perceived usefulness and risk on intention. The findings underscore the value of digital advocacy and policy alignment in overcoming adoption barriers and fostering inclusive financial ecosystems.

This study examines the relationship between Financial Inclusion (FI), Economic Empowerment (EE), and Social Empowerment (SE) through the mediating role of Entrepreneurial Intention (EI) among Rana University's students in Kabul. Understanding the significance of entrepreneurship and financial inclusion in enhancing empowerment socially and economically, this research shed light on the factors above within a developing context. The data was collected using physical and Google survey questionnaires. Partial Least Squares Structural Equation Modeling (PLS-SEM) was also employed to analyze the measurement model's internal consistency and convergent and discriminant validity. The findings revealed that EI has a statistically positive impact on household EE and SE, supporting the idea that students with strong EI tend to have a higher level of empowerment in both aspects. It was found that FI influences EI, underscoring FI's crucial role in encouraging entrepreneurial mindsets. FI alone does not immediately translate into empowerment without the influence of EI, as evidenced by the lack of significant direct effects of FI on EE and SE. The study additionally uncovers that EI mediates the relationship between FI and both forms of empowerment. This implies that by encouraging EI, FI indirectly supports SE and EE. The significant indirect effects underscore the importance of promoting FI and entrepreneurship as auxiliary strategies for enhancing empowerment. On the policy forefront, Policymakers, educators, and financial institutions may create an environment that encourages financial access and entrepreneurial growth, ultimately resulting in increased economic and social empowerment.