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How do informal lending institutions affect entrepreneurship? This paper aims to investigates the role of formal and informal credit market institutions in the decision to become an entrepreneur over the life cycle.

The author developed a dynamic Roy model in which a decision to become an entrepreneur depends on the access to formal and informal credit markets, nonpecuniary benefits of entrepreneurship, career-specific entry costs, prior work experience, education, unobserved abilities and other labor market opportunities (salaried employment and nonemployment). Using detailed Russian panel microdata (the Russia longitudinal monitoring survey) and estimating a structural model of labor market decisions and borrowing options, the author assesses the impact of the development of informal and formal credit institutions.

The expansion of traditional (formal) credit market institutions positively impacts all workers’ categories, reduces the share of entrepreneurs who borrow from informal sources and incentivizes low-type entrepreneurs to switch to salaried employment. The development of the informal credit market reduces the percentage of high-type entrepreneurs who borrow from formal sources. In the case of default, a higher value of the social network or higher costs of losing social ties demotivate low-type entrepreneurs to borrow from informal sources. The author highlights the practical implications of estimates by evaluating policies designed to promote entrepreneurship, such as subsidies and accessibility regulations in credit market institutions.

This study contributes to the literature in several ways. Unlike other studies that focus on individual characteristics in the selection for self-employment [Humphries (2017), Hincapíe (2020), Gendron-Carrier (2021), Dillon and Stanton (2017)], the paper models labor and borrowing decisions jointly. Previous studies discuss transitions between salaried employment and self-employment, taking into account entrepreneurial earnings, wealth, education and age, but do not consider the availability of financial institutions as a driving factor for the selection into self-employment. To the best of the author’s knowledge, this paper shows for the first time that the transition from salaried employment to self-employment is standard and consistent with changes in access to financial institutions. Another feature of this study is incorporating both types of credit markets – formal and informal. The survey by the European Central Bank on the Access to Finance of Enterprises (2018) shows 18% of small and medium enterprise in EU pointed funds from family or friends. Therefore, the exclusion from consideration of informal credit markets may distort the understanding of the role of the accessibility of credit markets.

Cost and schedule overruns are rife in dam projects. Normative evidence espouses overruns as though they are inimical to development and prosperity aspirations of stakeholders. This study examines the causal relationship between project financing and overruns.

Causative data were extracted from completion reports of 28 major dam projects in Africa. Each of the projects was financed jointly by up to 10 international development lenders. Relationships between causes of overruns and project outcomes were analysed.

Analyses elicit indicators of remarkable correlations between finance procedures and project outcomes. Lenders’ disposition to risk attenuation was the main debacles to project success. Interests had mounted, whilst release of fund was erratic and ill-timed. Finance objectives and mechanisms were grossly inadequate for projects’ intense bifurcations. Projects had slowed or stalled because lenders’ risks attenuation processes were purposed to favour lenders’ objectives, and not projects’ interests. In addition, findings also show project owners’ own funds and the number of lenders to a single project correlate with overruns.

Findings imply commercial complexities around major projects. They also show transactions are shaped by subtle (mis)trust behaviours in project finance procedures. Thus, scholarly solutions to project performance issues should consider behavioural issues of stakeholding parties more broadly, beyond contractors and project owners. Project finance ecosystems are vulnerable to major actors’ self-interests, opportunism and predatory conducts. Borrowers would manage this by developing and improving their capacity to build resilience and trust. Evidence shows intense borrower nations in Africa have limited capacity and acuity for these.

This study contextualises megaprojects in complexity rather than cost. Its additionality is in how finance steers absolute control of project environment away from project owners and how finance administration triggers risks and overrun.

The present study examines the determinants of households’ access to agricultural credit through institutional and non-institutional sources. The study evaluates the role of gender of the borrowers in accessing credit in rural India. Further, the paper also studies the impact of institutional variables in determining rural households’ access to credit.

The study used a multinomial logit model to identify the different factors that determine a farmer’s access to different credit sources.

The study reveals that substantial proportions of rural households do not access credit through any of the sources and the situation is very grim for the female-headed households (FHHs). The study highlights the importance of demographic, farm and institutional variables in determining households’ access to credit. Institutional variables significantly enhance rural credit access but favor male-headed households (MHHs). It highlights the need for policy intervention to target the specific needs of female borrowers. Further, the study also highlights the importance of adequate credit policy measures to address farmers’ vulnerability to natural disasters, mainly droughts.

The results of the study are based on recent unit-level data from the 77th Round of the National Sample Survey Organization (NSSO) survey. The survey covers a large number of farm households and reports information for the year 2018–2019.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-08-2022-0552

This paper examines why farmers self-select out of formal credit markets even though they need external funds.

We use probit and Bayesian probit estimators to detect the determinants of self-selection behavior based on a primary dataset of 2,212 rice farmers in Vietnam. After that, we use the multinomial probit (MNP) and Bayesian MNP estimators to reveal the impact of relevant factors on the decision to self-select for farmers belonging to each self-selection category.

The probit and Bayesian probit estimators show that the decision to self-select depends on household head age, income per capita, farm size, whether or not to have relatives or friends working for banks, the number of previous borrowings, risks related to natural disasters, diseases, and rice price, and the number of banks with which the farmer has relationships. The MNP and Bayesian MNP estimators give further insights into the decision of farmers to self-select in that determinants of the self-selection behavior depend on the reasons to self-select. In concrete, farm size and the number of previous borrowings mitigate the self-selection of farmers who did not apply for loans due to having access to other preferred sources of credit. The self-selection of farmers not applying for loans because of unfavorable loan terms is conditional on household head age, farming experience, income, farm size, the number of previous borrowings, natural disaster risk, and the number of banks the farmer has relationships with. Several factors, including education, income, the distance to the nearest bank, whether or not having relatives or friends working for banks, the number of previous borrowings, risks, and the number of banks the farmer has relationships with, affect the self-selection of farmers not applying for loans because of high borrowing costs. The self-selection of farmers not applying for loans because of complex application procedures depends on income and the number of previous borrowings. Finally, the household head’s age, gender, experience, income, farm size, the amount of trade credit granted, the number of previous borrowings, natural disaster risk, and the number of banks the farmer has relationships with are the determinants of the self-selection of farmers not applying for loans because of a fear not being able to repay.

This paper fills the knowledge gap by investigating why farmers self-select out of formal credit markets. It provides evidence of how the farmers’ subjective perceptions of rural credit markets contribute to their self-selection.

This paper shows that demand-side constraints are also vital for farmers’ access to bank credit. Improving credit access via easing supply-side constraints may not increase credit uptake without addressing demand-side factors. Given that finding, it recommends policies to improve access to bank credit for farmers regarding the demand side.

This study examines why low-wealth women entrepreneurs forgo mobile enabled money services and government supported micro finance for informal, community-based revolving loans in rural Nigeria.

Thematic analysis of 25 interviews with women in rural, south-west Nigeria. Entrepreneurial ecosystem theory, in the gendered context of micro finance and community-based lending, is employed.

This study explains the paradox of forgoing seemingly accessible mobile enabled credit, and formal credit schemes (e.g. micro-finance programs) for informal, one-on-one borrowing. Convenience and trust-based relationships with respected community members ease the burden of time scarcity and vulnerability associated with formal capital. Flexible terms, autonomy, self-reliance and knowing who one is dealing with make Esusu a preferred source of finance. Findings are discussed in the context of gendered entrepreneurial ecosystems in which participants conduct business.

The sample is not representative of women entrepreneurs in rural Nigeria. Survivorship bias is acknowledged. Further research is needed on the psychological risks of informal capital and the benefits of community-based lending.

Measures to scale mobile enabled credit, without commensurate interventions to address time management and other structural issues that confront women traders, limit their utility and impacts. Power differentials between women traders and lenders must also be considered in the design of lending products. Training of women traders and formal lenders should incorporate curricula about gender gaps in capital markets and systematic gender challenges to support entrepreneurs who seek to grow beyond subsistence enterprises.

This study documents decision criteria that motivate informal rural women traders to employ community-based revolving credit or Esusu. Findings inform measures to increase women entrepreneurs' access to capital in a rural sub-Saharan Africa contexts.

This study aims to address the critical need for innovative financing solutions in the global housing sector, focusing specifically on Malaysia’s distinct housing finance system encompassing both conventional and Islamic loans. The primary objective is to develop a transformative housing finance model that addresses affordability challenges and reshapes the Malaysian housing landscape.

The study presents an alternate housing finance model for Malaysia, integrating lower monthly payments and reduced household debt. Key variables include house price appreciation rates, interest rates, initial guarantee fees and loan-to-value ratios. Inspired by the Help to Buy (HTB) scheme, the model aligns with proven global initiatives for enhanced affordability, balancing payment amounts, loan interest rates and acceptable price thresholds.

The study’s findings promise to address affordability disparities and reshape Malaysia’s housing finance landscape. The emphasis is on introducing a structured repayment plan that offers a sustainable path to homeownership, particularly for low-income families. Incorporating the future value adaptation concept, inspired by reverse mortgages and Islamic finance, enhances adaptability, ensuring long-term sustainability despite economic shifts.

The proposed model promotes widespread access to homeownership, offering practical solutions for policymakers to improve affordability, prompting adaptable risk management strategies for financial institutions and empowering potential homebuyers with increased flexibility.

The study introduces a transformative housing finance model for Malaysia, merging elements from reverse mortgages, Islamic finance and the HTB scheme, offering potential applicability to similar systems globally.

This review aims to present the state of the art regarding the impact of financial technology (FinTech) on financial inclusion and its implications for consumers and institutions in terms of accessibility, usage and quality. An integrated framework is developed to illustrate the primary thematic areas for future research.

We performed a systematic literature review (SLR) to summarize and synthesize existing research published in peer-reviewed academic journals. Forty-two eligible studies were identified from the Web of Science database and a cross-reference search.

The results suggest that FinTech promotes financial inclusion for consumers and businesses by increasing the accessibility, usage and quality of financial products. We present a multidisciplinary integrative framework that links the three dimensions of financial inclusion (i.e. access, usage and quality) to financial technology. Finally, we propose several avenues for future research.

To the best of the author’s knowledge, this is the first SLR on how FinTech is associated with the accessibility, usage and quality of financial products. We provide an integrative framework for understanding the topic with implications in different fields.

The purpose of this paper is to compare nine different models to evaluate consumer credit risk, which are the following: Logistic Regression (LR), Naive Bayes (NB), Linear Discriminant Analysis (LDA), k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), Classification and Regression Tree (CART), Artificial Neural Network (ANN), Random Forest (RF) and Gradient Boosting Decision Tree (GBDT) in Peer-to-Peer (P2P) Lending.

The author uses data from P2P Lending Club (LC) to assess the efficiency of a variety of classification models across different economic scenarios and to compare the ranking results of credit risk models in P2P lending through three families of evaluation metrics.

The results from this research indicate that the risk classification models in the 2013–2019 economic period show greater measurement efficiency than for the difficult 2007–2012 period. Besides, the results of ranking models for predicting default risk show that GBDT is the best model for most of the metrics or metric families included in the study. The findings of this study also support the results of Tsai et al. (2014) and Teplý and Polena (2019) that LR, ANN and LDA models classify loan applications quite stably and accurately, while CART, k-NN and NB show the worst performance when predicting borrower default risk on P2P loan data.

The main contributions of the research to the empirical literature review include: comparing nine prediction models of consumer loan application risk through statistical and machine learning algorithms evaluated by the performance measures according to three separate families of metrics (threshold, ranking and probabilistic metrics) that are consistent with the existing data characteristics of the LC lending platform through two periods of reviewing the current economic situation and platform development.

The purpose of this paper is to explore the perceptions, experiences and behaviors of women entrepreneurs and industry professionals in raising finance for women-led businesses and associated problems faced by the women entrepreneurs.

This qualitative research adopts a narrative inquiry strategy. In-depth interviews are used to collect data from women entrepreneurs and women industry professionals in Pakistan. NVivo qualitative data analysis software is used to organize, analyze and find insights in the qualitative data.

This research finds that women entrepreneurs struggle to secure financing for their businesses, and most of them have not been successful in obtaining loans from banks. Women entrepreneurs have relied on various sources of funding, including microfinance banks, grants, personal finance and family members. Some of the barriers to finance attainment for women entrepreneurs include sociocultural inhibitions, lack of awareness and limited information dissemination by financial institutions. Women professionals suggest that entrepreneurs should maintain a bank account, have proper documentation and show dedication to their business to improve their chances of obtaining financing.

This research provides theoretical contributions and methodological advancements in the study of financial inclusion for women-owned businesses in Pakistan. This research raises awareness about the difficulties women entrepreneurs face when trying to obtain credit from banks and other financial institutions and provides policy recommendations to inform the government about financial inclusion policies and financing policies for women entrepreneurs. Overall, this research contributes to the literature on financial access and access to finance for women-owned businesses in developing countries.

Based on the vulnerable group theory and theory of discouraged borrower, this paper has two important theoretical and practical implications. First, the findings of this study reveal that the financial services are indifferent to women, and there is a denial of women being vulnerable in the financial system, hence requiring a major policy shift to not portray women as vulnerable, as they will rationally feel risky and prefer to opt out of the financial system. Second, the findings suggest that the issue of access to finance for women is not in the financial services but in the women's capabilities and awareness. Therefore, a policy shift is suggested from “financial services for women” to “capability and awareness of women” to avail and access the current services.

Despite a large stake of investment by retail investors and a growing number of peer-to-peer (P2P) lending platforms coupled with the initiation of secondary market and strong regulatory framework, less is known what leads investors to trust in P2P (TP2P) lending platforms in a multi-ethnic country, Malaysia. This study aims to investigate the effects of individual characteristics (gender, age, ethnicity, education and income), social influence of P2P (SIP2P) lending and privacy of P2P (PP2P) lending on the trust in emerging P2P platforms.

A cross-sectional survey was conducted to collect the data from retail investors in Malaysia. A variance-based partial least squares-structural equation modeling (PLS-SEM) model was applied to examine the significant predictors of TP2P lending platforms.

The results show that while investors' income is positively related to TP2P lending platforms, younger investors are less likely to have trust on P2P lending platforms. PP2P lending platforms increases retail investors' trust toward P2P platforms in Malaysia.

P2P service providers are suggested to give especial attention to investors' specific characteristics to develop trust and attract investors to the platforms. Service providers need to ensure the privacy of potential investors' personal and confidential data to build investors' trust.

This is the first study to assess retail investors' trust toward online P2P lending platforms in Malaysia, where this alternative financing platform gradually gaining popularity.