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In the burgeoning field of bitcoin research, a cohesive understanding of how knowledge and insights have evolved over time is lacking. This study aims to address this gap through an exploration of 4123 academic articles pertaining to bitcoin. Utilizing co-word analysis and main path analysis (MPA), it uncovers key themes and seminal works that have substantially influenced the field’s progression. The identified clusters, including safe haven, internet of things (IoT), proof of work (PoW), market efficiency, sentiment analysis, digital currency, and privacy, shed light on the multifaceted discourse surrounding bitcoin. The MPA, incorporating both forward and backward local paths, traces an evolving narrative, starting from an in-depth exploration of bitcoin’s structure, anonymity, and contrasts against traditional financial assets. It tracks the shift in focus to broader market dynamics, volatility, speculative nature, and reactions to economic policy fluctuations. The analysis underscores the transformation of bitcoin research, from its beginnings as a decentralized, privacy-oriented currency to its role in global economics and green financing, revealing a complex narrative of an innovative financial instrument to a multifaceted entity. Implications drawn from this analysis include the need for further research on the potential integration of bitcoin within emerging technologies like AI and cybersecurity, the implications of bitcoin’s interplay with traditional financial systems, and the environmental impacts of bitcoin and blockchain utilization. Overall, the current study not only enhances our understanding of the bitcoin field but also charts its dynamic evolution and stimulates further academic inquiry.

This paper analyzes the linear and non-linear relationship between non-performing loans and bank profitability measured by the Net Interest Margin for a sample of 74 Middle Eastern and North African banks over the period of 2005–2020. We used the System Generalized Method of Moments (SGMM) as a linear approach and the Panel Smooth Transition Regression (PSTR) model as a non-linear approach. The empirical results of the SGMM approach indicated that the ratio of NPLs negatively affects bank profitability. The findings of the non-linear relationship based on the PSTR model confirmed the existence of a threshold effect. We found that below the threshold of 4.42%, the effect of NPLs is negative but not significant, while after surpassing this threshold, the effect becomes negative and significant. As for bank specifics, we revealed that bank size is positively and significantly associated with bank profitability. For industry factors, we found that more bank concentration decreases bank profitability. Regarding the financial environment, we concluded that the global financial crisis exerted a negative impact on bank profitability. Moreover, we revealed a positive and significant impact of GDP on bank profitability as well as a negative impact of inflation on bank profitability. This study has some limitations regarding the social, economic, and financial differences of the whole sample, which includes banks from the Middle East and others from North Africa. Hence, decomposing the whole sample into two sub-samples could improve the results of this paper.

The main objective of this paper is to investigate determinants of non-performing loans in the Middle East and North Africa region by exploring the role of bank-specific and macroeconomic factors, particularly in the period of the global financial crisis, as well as the COVID-19 pandemic, as a health crisis that translates to an economic crisis. This study includes 74 banks belonging to 11 MENA countries over the period 2005–2020 and uses the two-stage system generalized method of moment estimator. To conduct a comparative analysis, the whole sample is divided into two sub-samples. The first one is related to the Middle East countries and the second one covers North African countries. The empirical findings indicate that the level of non-performing loans is more sensitive to bank specifics than macroeconomic factors. When it comes to macroeconomic factors, macroeconomic environment and institutional quality significantly affect the level of NPLs. However, no significant effect has been detected regarding the impact of the COVID-19 pandemic.