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Innovation is the basic input to organizational endurance; therefore, the study of processes that support innovation should be of interest to practitioners and researchers alike. Consequently, there is increasing attention for the supplementary research examination of the influencing elements of innovativeness.

The data were collected in 2018 using adapted questionnaires that were tested. The respondents were 446 employees of Pakistan Electric Power Company (PEPCO). Bivariate correlations and hierarchical regression were used for the data analysis.

The findings showed that the competing value framework (CVF) model of organizational culture may promote innovativeness that translates to the progress of PEPCO, which deserved barrier for everyone relying on the values made by the culture of the organization. The adhocracy culture is considered to be statistically suitable for the prediction of performance and enhancement of innovation in the organization. Based on the above findings, it may be deduced that innovation mediated the relationship between some particular types of organizational culture and performance.

The CVF model provides a supportive framework for the development of procedures that promote innovation in the organization. The focus of the CVF model highlighted employees' behavior and function of organizational culture, which can restrain or stimulate performance. This study reported and developed a basis for an empirical model based on the CVF model.

This paper found that the CVF model and innovation are mega sources of innovation at PEPCO. This work should be of interest in the area of innovation and performance improvement. There are very few empirical research studies on the relationship between organizational culture, innovation and performance, specifically in the context of developing countries. This is one of the very few studies conducted to empirically examine the influence of CVF model on performance through the mediating role of innovation in PEPCO.

The ethical issues arising at work demand the role of both leader and employees, but how both the levels are linked in determining the ethical responses is an area that has not gained due attention in the past. Against this backdrop, this study aims to address the influence of a leader’s authenticity and ethical voice on ethical culture and the role ethicality of followers.

Survey design has been used, and a questionnaire is used to elicit the responses. In total, 381 filled questionnaires were used for data analysis.

The findings of this study highlight the role of authentic leadership in predicting the role ethicality of followers both directly and through the mediation of ethical culture. Furthermore, a leader’s ethical voice strengthens the authentic leadership and outcome relationships (with ethical culture and followers’ role ethicality). The moderated-mediation mechanism has proved as the leaders’ voice foster the indirect mechanism.

There is a dearth of literature that has focused on leadership traits (authenticity) and behavior (ethical voice) in predicting the followers’ outcomes (perceptions – ethical culture and behaviors – role ethicality). The moderated-mediation mechanism has been unattended in the past.

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.