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Bidirectional Encoder Representations from Transformers (BERT) has gained increasing attention from researchers and practitioners as it has proven to be an invaluable technique in natural languages processing. This is mainly due to its unique features, including its ability to predict words conditioned on both the left and the right context, and its ability to be pretrained using the plain text corpus that is enormously available on the web. As BERT gained more interest, more BERT models were introduced to support different languages, including Arabic. The current state of knowledge and practice in applying BERT models to Arabic text classification is limited. In an attempt to begin remedying this gap, this review synthesizes the different Arabic BERT models that have been applied to text classification. It investigates the differences between them and compares their performance. It also examines how effective they are compared to the original English BERT models. It concludes by offering insight into aspects that need further improvements and future work.

The stiff competition in the market, and continuous pressures from various stakeholders such as customers, business owners, environmental authorities, and society, in general, to produce unique products and services, protect the environment, and obtain competitive advantage continue to challenge the sustainability of enterprises in the market, especially the small ones. Accordingly, to minimize the effect of these challenges and pressures, small enterprises can improve their performance by directing their practices and processes towards developing innovative products and services that can help obtain a competitive advantage, protect the environment and better market share. Accordingly, this study aimed to explore the necessary antecedents contributing to developing innovative green products and services among small enterprises in Saudi Arabia. The study targeted a sample of 284 small entrepreneurs across various regions of Saudi Arabia. The responses were collected with a convenience sample through an online questionnaire. The data were analyzed using partial least squares structural equation modelling (PLS-SEM). The findings revealed that both green entrepreneurial self-efficacy (GESE) and green entrepreneurial orientation (GEO) have a positive relationship with green innovation (GI). The findings also reported that GI mediates the relationship between GESE, GEO and economic performance (EP).

This study’s objective is to examine the influence of entrepreneurial self-efficacy and internal locus of control on the entrepreneurial intention of small Saudi entrepreneurs during adverse times, with entrepreneurial resilience as a moderator. The study, which targeted a sample of 207 small entrepreneurs working in various sectors in Saudi Arabia, gathered data through an online questionnaire sent to respondents and analysed the results using PLS-SEM. The study revealed intriguing findings, such as the existence of a positive significant relationship between entrepreneurial self-efficacy, internal locus of control and entrepreneurial intention amongst small Saudi entrepreneurs. It also demonstrated that in times of adversity, such as during the COVID-19 pandemic and other environmental challenges, entrepreneurial resilience can act as a moderator between entrepreneurial intention and entrepreneurial self-efficacy. Entrepreneurial resilience, in particular, has the potential to strengthen the relationship between entrepreneurial self-efficacy and entrepreneurial intention. Accordingly, the government, along with other sectors and stakeholders in Saudi Arabia, should continue to support the psychological characteristics of small Saudi entrepreneurs, notably their internal locus of control, entrepreneurial self-efficacy, and entrepreneurial resilience to ensure greater sustainability and the continuity of their small businesses.

This study examines the relationship between inflation and greenhouse gas (GHG) emissions in three major economies: the United States of America (USA), the European Union (EU), and China. The analysis spans from 1960 to 2021 for the USA and EU, and from 1971 to 2021 for China. A feedforward neural network model, optimized using the Levenberg–Marquardt backpropagation algorithm, was employed to predict GHG emissions based on annual inflation rates and fossil fuel energy consumption. The study integrates historical data on inflation trends with GHG emissions, measured in CO2 equivalents, and fossil fuel energy consumption, expressed as a percentage of total energy use. This multidimensional approach allows for a nuanced understanding of the economic-environmental interplay in these regions. Key findings indicate a nonlinear response of GHG emissions to inflation rates. In the USA, GHG emissions begin to decrease when inflation rates exceed 4.7%. Similarly, in the EU, a steep reduction in emissions is observed beyond a 7.5% inflation rate. China presents a more complex pattern, with two critical inflection points: the first at a 4.5% inflation rate, where GHG emissions start to decline sharply, and the second at a 7% inflation rate, beyond which further increases in inflation do not significantly reduce emissions. A critical global insight is the identification of a uniform inflation rate, around 4.4%, across all regions, at which GHG emissions consistently increase by 1%, hinting at a shared global economic behavior impacting the environment. This discovery is vital for policymakers, emphasizing the need for tailored regional strategies that consider unique economic structures, energy policies, and environmental regulations, alongside a coordinated global approach.

This study investigated the factors determining the behavioral intention of young Saudi entrepreneurs to use crowdfunding to finance their small enterprises. The capacity of behavioral intention to predict the use behavior of crowdfunding platforms was also assessed. Partial least squares-based structural equation modeling method (PLS-SEM) was used to analyze responses collected from 270 young Saudi entrepreneurs (qualified students) attending the Community College of Abqaiq in Saudi Arabia, which is affiliated with King Faisal University. The unified theory of acceptance and use of technology (UTAUT) with extensions of three constructs was employed. The findings revealed that performance expectancy, social influence, perceived trust and perceived risks predicted the behavioral intention of young Saudi entrepreneurs to use crowdfunding platforms to finance their small enterprises, whereas effort expectancy, facilitating conditions and trialability had no significant predictive effect on the same behavioral intention. It was further reported that behavioral intention could also predict the use behavior of young Saudi entrepreneurs on crowdfunding platforms. The overall results indicated that the model explained 55.4% of the variance in behavioral intention and 38.3% of the variance in use behavior of young Saudi entrepreneurs.

Micro- and small enterprises, despite their effective and significant role in strengthening the economy, especially in developing countries, continue to struggle, particularly in adverse conditions and unstable governments. Accordingly, there is a need to understand the key factors that can internally enhance micro- and small enterprises and support them in standing strong and becoming more resilient during adverse times, ultimately ensuring better economic contribution. This research investigates how coping with unexpected challenges, described as the ability to manage and adapt to unexpected challenges, and defining core purpose, defined as the ability to define core vision and values for the business, enhances micro- and small enterprises’ resilience during adverse conditions. This study further investigates whether business resilience, described as the ability of a business to adapt effectively to changing unstable environments, positively influences business economic sustainability. This study also examined whether business resilience can positively mediate the relationship between coping with unexpected challenges, defining core purpose and having business economic sustainability. Accordingly, a sample of 303 respondents was collected from micro- and small entrepreneurs operating different types of activities. This study’s findings reported that coping with unexpected challenges and defining core purposes positively influenced business resilience and economic sustainability. This study also revealed that business resilience can directly and significantly influence business economic sustainability and could partially mediate the connection between coping with unexpected challenges, defining core purpose and having business economic sustainability. This study concluded by offering theoretical and practical implications to entrepreneurs, policymakers and stakeholders.

The study investigates the impact of psychological capital on the employees’ innovative behavior through the mediating effect of employees’ job satisfaction and employees’ innovative intention in the small and medium enterprises (SMEs) sector of Saudi Arabia. A sample of 204 respondents participated from various enterprises working without restricting specific sectors to check employees’ common behavior in multiple sectors. The data and hypotheses testing analysis were made with the partial least squares–based structural equation modeling (PLS-SEM). The study revealed that psychological capital positively affects employees’ job satisfaction, innovative behavior, and innovative intention. Furthermore, the employees’ job satisfaction also positively correlated with the employees’ innovative behavior, while there was no connection between the employees’ innovative intention and the employees’ innovative behavior. Concerning the indirect relationships, the findings revealed that employees’ job satisfaction played a partial mediating role between psychological capital and the employees’ innovative behavior. However, the employees’ innovative intention did not mediate the relationship between the psychological capital and the employees’ innovative behavior. These findings suggest the importance of psychological capital in influencing the innovative behavior of employees. Hence, there is a need to continue developing it among employees to ensure a better output.

Micro- and small-sized enterprises (MSEs) play a key role in developing emerging countries’ economies. However, concerns remain about their resilience and continuity, especially during periods of conflict and crisis. To address this gap, this research explores key factors that enhance adaptive capacity (AC) and entrepreneurial resilience (ER) amongst MSEs. Data were collected from 301 micro- and small-sized entrepreneurs operating different business activities using an online questionnaire and on-site visits. Partial least squares–structural equation modeling was employed to analyze the data. Findings revealed that crisis management preparedness (CMP) and customer-centric adaptation (CCA) positively and significantly influence AC, which, in turn, positively affects ER. In addition, CMP and CCA directly influence ER. Moreover, AC partially mediates the relationship between CMP, CCA, and ER. This study offers significant practical and theoretical implications for policymakers in making strategic action plans.

Micro and small enterprises (MSMEs) play a positive and significant role in developing economies by creating job opportunities and mitigating poverty; this necessitates their attention and focus, mainly during challenging times. Accordingly, this study explored the key factors contributing to enhancing entrepreneurial competency (EC) and the intention to maintain business continuity among MSMEs in Yemen during adverse times. A sample of 280 responses was collected from MSMEs operating diverse types of businesses in the capital of Yemen, Sanaa. The collected data were analysed using partial least squares–structural equation modelling (PLS-SEM), which is considered suitable for this purpose. The data collection process included an online questionnaire and a physical visit to the business locations of the business owners. The findings of the study reported that entrepreneurs’ network ties (ENT), as well as recovering capability (RC), positively and significantly influence the EC of MSMEs in the context of the study. Additionally, EC positively and significantly influences business continuity intention (BCI). Finally, EC partially mediates the relationship between ENT, RC, and BCI. The study concludes by providing recommendations and implications for policymakers.

The swift advancement of the Internet of Things (IoT), coupled with the growing application of healthcare software in this area, has given rise to significant worries about the protection and confidentiality of critical health data. To address these challenges, blockchain technology has emerged as a promising solution, providing decentralized and immutable data storage and transparent transaction records. However, traditional blockchain systems still face limitations in terms of preserving data privacy. This paper proposes a novel approach to enhancing privacy preservation in IoT-based healthcare applications using homomorphic encryption techniques combined with blockchain technology. Homomorphic encryption facilitates the performance of calculations on encrypted data without requiring decryption, thus safeguarding the data’s privacy throughout the computational process. The encrypted data can be processed and analyzed by authorized parties without revealing the actual contents, thereby protecting patient privacy. Furthermore, our approach incorporates smart contracts within the blockchain network to enforce access control and to define data-sharing policies. These smart contracts provide fine-grained permission settings, which ensure that only authorized entities can access and utilize the encrypted data. These settings protect the data from being viewed by unauthorized parties. In addition, our system generates an audit record of all data transactions, which improves both accountability and transparency. We have provided a comparative evaluation with the standard models, taking into account factors such as communication expense, transaction volume, and security. The findings of our experiments suggest that our strategy protects the confidentiality of the data while at the same time enabling effective data processing and analysis. In conclusion, the combination of homomorphic encryption and blockchain technology presents a solution that is both resilient and protective of users’ privacy for healthcare applications integrated with IoT. This strategy offers a safe and open setting for the management and exchange of sensitive patient medical data, while simultaneously preserving the confidentiality of the patients involved.