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The main objective of this study is to investigate the factors that influence the adoption intention of cloud computing services among individual users using the extended theory of planned behavior.

A purposive sampling technique was used to collect a total of 339 data points, which were analyzed using SmartPLS to derive variance-based structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA).

The results obtained from PLS-SEM indicate that attitude towards cloud computing, subjective norms, perceived behavioral control, perceived security, cost-effectiveness, and performance expectancy all have a positive and significant impact on the adoption intention of cloud computing services among individual users. On the other hand, the findings from fsQCA provide a clear interpretation and deeper insights into the adoption intention of individual users of cloud computing services by revealing the complex relationships between multiple combinations of antecedents. This helps to understand the reasons for individual users' adoption intention in emerging countries.

This study offers valuable insights to cloud service providers and cyber entrepreneurs on how to promote cloud computing services to individual users in developing countries. It helps these organizations understand their priorities for encouraging cloud computing adoption among individual users from emerging countries. Additionally, policymakers can also understand their role in creating a comfortable and flexible cloud computing access environment for individual users.

This study has contributed to the increasingly growing empirical literature on cloud computing adoption and demonstrates the effectiveness of the proposed theoretical framework in identifying the potential reasons for the slow growth of cloud computing services adoption in the developing world.

In developing countries, banks play a major role by acting as a conduit for the effective mobilization of funds from the surplus sectors of an economy for onward lending to the deficit sectors for productive investments that will in turn increase the level of employment and economic growth. There has being a rising trend in unemployment rate in Nigeria and South Africa and hence, the need for the study to assess the effectiveness of banking system credit in curbing unemployment rate by making a comparative analysis of Nigeria and South Africa covering the period of 1991–2018.

The study employed the unit root test, Johansen cointegration test, vector error correction model and VAR impulse response function in determining the relationship between the variables.

The major findings revealed that banking system credit matters in curbing unemployment rate in South Africa than in Nigeria. Also, other macroeconomic factors such as lending rate, inflation rate, Government expenditure and population growth were significant enough in influencing unemployment rate in South Africa than in Nigeria. Foreign direct investment was a significant factor in reducing unemployment rate in Nigeria than in South Africa. The cointegration test showed a long-term relationship between the variables in both countries while the speed of adjustment coefficient of the vector error correction model is faster in South Africa than in Nigeria.

Previous empirical studies on the relationship between banking system credit and unemployment rate have focused much on other regions such as Asia and Europe. Thus, the study is unique as it focused on the African region and also made a comparative analysis by testing the Keynesian theory of employment, interest and money on two emerging African economies which are Nigeria and South Africa.