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In this study, the researchers explored the predictive powers of corporate cultural factors and self-efficacy on Pakistan's public sector bank employees' organizational commitment.

The researchers designed a co-relational study based on cross-sectional data using a questionnaire to collect the data from the Pakistan public sector banks' managers, assistant managers and operational managers. Consequently, the researchers based this study's findings on the 270 valid responses to the questionnaire.

This study's findings reveal that, except for teamwork, together with self-efficacy, the corporate cultural factors comprising organizational communication, training and development and reward and recognition have positive and significant impacts on organizational commitment. More specifically, self-efficacy plays a mediating role in terms of the relationships between organizational commitment and organizational communication, training and development and reward and recognition.

From establishing the most relevant corporate cultural factors, the researchers consider that this study's findings are helpful to policymakers and organizations in developing organizational commitment among employees. More practically in the case of Pakistan's public sector banks, the employees can improve employees' performance by recognizing the significance of the corporate cultural factors on employees' organizational commitment. In addition, the researchers consider that this study's findings can improve managerial efficiency which, in turn, can lead to the organizations becoming more successful.

In the context of Pakistan's public sector banks, this study's findings provide empirical insights to the relationships between the corporate cultural factors and organizational commitment. In addition, the findings provide insights to the role played by self-efficacy in mediating these relationships.

The purpose of this study is to explore the effects of followers’ perceptions of their leaders’ authentic leadership behaviors on how followers become motivated to develop moral intention.

Using field survey data (n = 337), exploratory factor analysis and multiple regression, the authors suggest that perceived authentic leadership positively affects followers’ moral intent. The authors tested a self-determination theory-based model to explain the mediations.

The authors found that perceived authentic leadership is related to employees’ autonomous moral motivation through basic psychological need satisfaction, which in turn predicts their moral capacities and moral intent.

This study is unique in that it has examined various motivational variables to explain the mechanism by which authentic leadership influences morality. In addition, this is also novel in empirically using the autonomous motivation construct in the moral domain to explain how employees may develop moral capacities over time, impacting their moral intent. This research is also unique in testing the relationship between all moral capacities proposed in the literature and moral intent. The theoretical implications, practical implications and avenues for further research are also discussed.

This paper aims to examine how the diversity of educational levels within bank boards influences the efficiency and stability of banks operating in the Middle East and North Africa (MENA) region. Unlike previous studies, this analysis also investigates the role of board gender diversity in moderating the relationship between board educational level diversity and bank efficiency and financial stability in MENA.

In this study, a sample of 77 banks in the MENA region spanning the years 2011 to 2018 is used. The relationship between the presence of highly educated directors on the board, bank efficiency and stability is assessed using the ordinary least squares method. Additionally, the authors use the Generalized Method of Moments technique to correct endogeneity problem.

This study establishes a positive association between the presence of directors with advanced educational backgrounds on bank boards and bank efficiency and stability. Furthermore, the inclusion of women on the board strengthens this relationship.

These findings have important implications for policymakers and regulators in the MENA region, suggesting that promoting diversity policies that encourage the participation of highly educated directors on bank boards can contribute to enhanced efficiency and financial stability. Policymakers may also consider implementing quotas or guidelines to improve gender diversity in board appointments, thereby fostering bank performance in the region.

This study stands out for its innovation and distinctiveness, as it delves into the connection between board educational level diversity and bank efficiency in the MENA region. Notably, it surpasses previous research by investigating the moderating role of board gender diversity, thus offering valuable insights into the complex interplay between these two facets of board diversity. This contribution enriches the existing literature by providing novel perspectives on board composition dynamics and its influence on bank efficiency and stability.

The advent of ChatGPT has fundamentally changed the way people approach and access information. While we are encouraged to embrace the tool for its various benefits, it is yet to be known how to drive people to adopt this technology, especially to improve their life skills. Using implicit self-theories, the current research delineated the distinct way incremental (vs entity) theorists use ChatGPT, which in turn influences their attitude and hence the behavioural intention towards this technology.

The research employed a between-subject experimental design with 100 prolific participants. The manipulation materials were also pre-tested (N = 50). No confound effects such as content clarity, personal interest, and cognitive load were found. For the mediating effect, PROCESS Model 4 with bootstraps 5,000 and CI 95% were employed.

Individuals who believed that human ability to use technological applications was malleable, i.e. incremental theorists, were more likely to use ChatGPT to improve their life skills. On the other hand, when people believed that such an ability was fixed, i.e. entity theorist, they were less likely to use this new technology. The reason was that through the implicit belief, attitude towards ChatGPT was (more vs less) positively influenced which in turn motivated the behavioural intention. Further, the effect held beyond the impact of demographic factors such as age, gender, occupation, and educational level.

Even though implicit self-theories have received tremendous interest and empirical support, be it generic or domain-specific, the effect of implicit belief in technological applications was not clearly determined. The current research helps to extend the implicit self-theories into the technological domain, and in this case, the usage of ChatGPT. Moreover, the full mediating effect of attitude offers some thought about the revised models of technology acceptance. That is, perhaps it is the combination of (implicit) belief and attitude that may have better predictive power for technological adoption behaviour.

Deep learning (DL) is on the rise because it can make predictions and judgments based on data that is unseen. Blockchain technologies are being combined with DL frameworks in various industries to provide a safe and effective infrastructure. The review comprises literature that lists the most recent techniques used in the aforementioned application sectors. We examine the current research trends across several fields and evaluate the literature in terms of its advantages and disadvantages.

The integration of blockchain and DL has been explored in several application domains for the past five years (2018–2023). Our research is guided by five research questions, and based on these questions, we concentrate on key application domains such as the usage of Internet of Things (IoT) in several applications, healthcare and cryptocurrency price prediction. We have analyzed the main challenges and possibilities concerning blockchain technologies. We have discussed the methodologies used in the pertinent publications in these areas and contrasted the research trends during the previous five years. Additionally, we provide a comparison of the widely used blockchain frameworks that are used to create blockchain-based DL frameworks.

By responding to five research objectives, the study highlights and assesses the effectiveness of already published works using blockchain and DL. Our findings indicate that IoT applications, such as their use in smart cities and cars, healthcare and cryptocurrency, are the key areas of research. The primary focus of current research is the enhancement of existing systems, with data analysis, storage and sharing via decentralized systems being the main motivation for this integration. Amongst the various frameworks employed, Ethereum and Hyperledger are popular among researchers in the domain of IoT and healthcare, whereas Bitcoin is popular for research on cryptocurrency.

There is a lack of literature that summarizes the state-of-the-art methods incorporating blockchain and DL in popular domains such as healthcare, IoT and cryptocurrency price prediction. We analyze the existing research done in the past five years (2018–2023) to review the issues and emerging trends.