FinTech is a disruptive international phenomenon that is expected to shape the future of the financial sector. This study describes the features and characteristics of the current Saudi Arabian FinTech landscape and ecosystem. Examples of innovative financial startups in Saudi Arabia, including online banking, transfer and payment services, crowdfunding platforms, peer-to-peer lending, and blockchain initiatives, are discussed. Several changes have occurred within the ecosystem in the last five years; for example, Saudi banks are taking a more cautious approach. However, FinTech initiatives are also being internally developed, encouraging technology companies and startups to focus their efforts on innovations aimed at improving current processes rather than novelty. The government directs its effort mainly toward initiatives related to regulations and laws. Customers are interested in new products that are convenient and easy to use. We compare the Saudi FinTech ecosystem to the United Arab Emirates’ FinTech ecosystem and conclude with recommendations for the different stakeholders.

The present study investigates a conceptual research framework on financial literacy in various investment planning and decision-making stages. The study comprises a review of 2182 articles published in peer-reviewed journals from 2001 to 2022 (January). The study employed bibliometric techniques such as citation network analysis, co-citation analysis, content analysis, publication trends, and keyword analysis to analyze the literature on financial literacy. The study aims to add to the literature on financial literacy by proposing ten clusters to improve research on financial literacy in order to help investors learn better. Financial literacy has evolved from a fledgling discipline to a significant teaching and research tool. Therefore, it is vital to investigate and identify current research trends in this field. The results are essential to the financial community, given that institutions and society are increasingly emphasizing financial literacy to strengthen individual citizens’ responsibilities in designing their investment strategies.

This study is an effort for measuring the entrepreneurial orientation of the students and its linkage with their entrepreneurial intention. The study is based on entrepreneurial dimensions such as innovativeness, need for achievements, opportunity recognition, risk‐taking propensities, and entrepreneurship education. The study also used entrepreneurship education and gender as moderating variables. A 5‐point Likert‐type scale was designed by adapting the Individual Entrepreneurial Orientation measurement scale and Entrepreneurial Intention Questionnaire (EIQ). The authors postulated 7 hypotheses. Data analysis confirmed that underlying entrepreneurial dimensions have a positive correlation with students’ entrepreneurial intention. This paper concludes that entrepreneurial dimensions and proper delivery of entrepreneurship education will help the students in transforming their entrepreneurial intention into actual entrepreneurial action.

This study aims to explore Saudi students entrepreneurial orientation (EO) toward e-businesses in the line of achieving the strategic objectives of Saudi Vision 2030. Saudi Vision 2030 (hereafter, Vision 2030) is a strategic framework to attain the sustainable development of Saudi Arabia. It was first announced by Crown Prince Mohammad bin Salman in April 2016. Authors have proposed a Saudi Vision Linkages Model to show the role and importance of university education (UE) and entrepreneurial culture in fulfilling the specific requirements of the Saudi labor market to attain the ultimate strategic objectives of Vision 2030. The authors also proposed a conceptual model of the study to depict the relationships of EO with their entrepreneurial intention toward online businesses (e-EI). The study used a multidimensional model of the EO where three subdimensions, namely risk-taking propensities (RTP), innovativeness (INV), and pro-activeness (P-ACT), are used. The conceptual model of the study also shows UE and gender (GEN) as moderating variables. The authors used convenience sampling to collect cross-sectional data and conducted an online survey among the students at Saudi Electronic University (SEU) using a 5-point Likert-type scale to collect the data through a questionnaire, observing a total of 17 items and 408 filled questionnaires were received. Authors proposed six hypotheses where four hypotheses build the direct relations, namely, RTP (H1), INV (H2), P-ACT (H3), and UE (H4) with e-EI and hypotheses H5 and H6 are further divided into the subhypotheses, respectively, in H5a, H5b, H5c and H6a, H6b, H6c to show the moderating effect of UE (H5) and GEN (H6). SmartPLS 4.0 software is used to apply structural equation modeling for the analysis of data. Reliability, composite validity, discriminant validity, and model-fit indices of the measurement model are assessed before running a bootstrapping to measure the significance and standardized β estimates of the paths of hypotheses (structural model analysis). After analyzing the results, in the suggestions section, the authors have suggested that the university build a university business incubator for the students to promote entrepreneurial activities on all the campuses with a head office in the Riyadh campus.