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This study aims to propose a model of entrepreneurial microcredit support that could address the problem of entrepreneurial support provided by microfinance institutions. This objective is justified by the need to produce scientific knowledge that could be of use to practitioners and political decision-makers who formulate and implement strategies of social inclusion and poverty reduction.

The study adopts a socio-constructivist research perspective. Social constructivism is a theoretical approach that posits that all social reality is constructed. In other words, individuals construct their knowledge of reality relative to their social setting. This justifies the use of the focus group to supplement and validate the data gathered in an individual interview. The socio-constructivist perspective allows us to better understand and develop knowledge based on the meaning that interviewees attribute to their experience. This perspective also justifies the choice of qualitative data collection method. The data were collected during semi-structured interviews.

Entrepreneurial microcredit support is distinguished from classic entrepreneurial support because it places the individual at the center of the process by emphasizing soft skills in the development of the entrepreneurial spirit. This approach engenders an efficient support process that comprises three main steps: determination of entrepreneurial potential, empowerment and reinforcement of autonomy and acquisition of managerial skills. The efficiency stems from the fact that the time factor is not a constraint in the entrepreneurial microcredit support process and from the relationship of proximity and trust between the credit agent and the micro-entrepreneur.

To the best of authors’ knowledge, this is the first paper to deal with the entrepreneurial microcredit support, which is completely different from the classical entrepreneurial support because of the uniqueness of microfinance and micro-entrepreneurs. The model clearly reveals that the support for the development of the skills required to successfully run a microenterprise is provided based on a socio-constructivist approach in which the micro-entrepreneur is the main actor in the construction of “mobilized knowledge” required to nurture promoters’ entrepreneurial spirit. Consideration of soft skills in a socio-constructivist perspective is, therefore, indispensable for entrepreneurial development.

The purpose of this paper is to calculate the financial inclusion index and analyze its dynamics in developing countries.

The authors use the two-stage principal component analysis (PCA) method and consider financial technology innovations to improve the accuracy of the financial inclusion index.

The authors found a downward trend in the financial inclusion index in most developing countries over the study period. The authors also found that a high financial inclusion index is linked to high scores in the Doing Business and high business climate regulation ranking. In addition, the authors observed that the rates of low financial inclusion in developing countries are due to low utilization of and unequal access to financial services.

The analysis suggests that policymakers in developing countries could invest in digital infrastructure to extend access to financial services in remote areas. They could also encourage financial innovation, particularly in financial technologies, by adopting flexible regulatory frameworks. Promoting the financial inclusion of marginalized groups through targeted initiatives tailored to their needs is another solution. They could also encourage the use of financial services by raising awareness and educating populations through training programs. Finally, to improve the business climate, governments could simplify administrative procedures and promote transparency and legal stability.

Unlike previous studies, the use of the two-stage PCA method and the consideration of financial technology (Fintech) innovations such as mobile money in the determinants of the financial inclusion index improve the accuracy of the index.