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The purpose of this paper is to assess whether there is an association between CEO age and analysts forecast properties (particularly forecast accuracy and bias/optimism). CEOs, having the central role in managing firms, can significantly influence the financial and non-financial decisions in an organisation. Furthermore, having been identified as key culprits in past major accounting scandals, it is also important to identify the CEO characteristics that affect financial reporting decisions.

This study adopts the upper echelon theory on the relationship between CEO age and analysts forecast properties. The authors use a sample of 2,730 Australian firm-year observations for the period 2004–2013 drawn from IBES, Connect 4 and SIRCA databases.

The authors find that analyst forecast accuracy increases and bias (optimism) reduces with the CEO age. The authors conclude that earnings and related information provided to analysts improves with the CEO age, which increases the forecast accuracy and reduces bias (optimism). Additional results suggest that the positive (negative) effect of CEO age on forecast accuracy (bias) remains until the CEOs reach the age of their retirement age (65 years). The results remain consistent with a number of sensitivity tests and provide implication for stakeholders such as firms, analysts, auditors, financial statements users and regulators.

The authors demonstrate that the relationship between CEO age and analyst forecast properties is not linear but is, in fact, curvilinear substantiating concerns that CEOs that are much younger or much older do not help increase the quality of the information environment. Consequently, firms hiring CEOs in the right age bracket also benefit by having higher-quality information environment leading possibly to reduce costs such as those relating to debt and/or equity ultimately increasing firm value.

Empirical studies on the association between CEO age and analysts earnings properties in Australia are scarce and this paper contributes to the determinants of the analysts forecast accuracy and bias (optimism) and the CEO age literature.

Bullying negatively affects victims’ mental health and has been shown to be associated with anxiety and depression. Moreover, many studies have reported the prevalence of mistreatment among medical students (MS), interns and junior physicians. However, there are limited studies on bullying in the Middle East, and no studies on higher education in Bahrain. The authors’ aim was to investigate and compare the prevalence of bullying between MS at a major public university and non-medical students (NMS) at a private university in Bahrain. The authors also sought to explore the associations between bullying, depression and anxiety.

The authors conducted a survey-based cross-sectional study from October 1 to December 31, 2018, using convenient sampling method. A total of 300 students (150 MS and 150 NMS) participated in the study by answering a questionnaire that explored exposure to different types of bullying. In addition, standard anxiety and depression instruments were distributed to students.

The results showed that MS were more exposed to bullying than NMS, with a significant number (41%) reporting mistreatment from multiple sources, including teachers, consultants and peers. Furthermore, the authors found that bullying was significantly correlated with psychological health, anxiety and depression.

There are limited studies on bullying in the Middle East and no studies on the topic of higher education in Bahrain. Furthermore, the learning environment of tertiary education institutions can be improved by addressing the concerns associated with bullying identified in this study.

Leadership literature has identified that the servant leadership style can reduce employee negative work outcomes, even in challenging work environments like the health-care sector as nurses play an important role in the performance of a hospital. That is why, the efficiency and effectiveness of the nurses are believed to be directly linked to improved health benefits to the public. So, this study aims to investigate the inter-relationship between servant leadership, organizational justice and workplace deviance of nurses in public sector hospitals.

A self-administrated questionnaire using a drop-and-collect method was used for collecting the data from nurses working in the public sector hospitals of Pakistan using a convenient sampling technique. In total, 370 questionnaires were distributed among the nursing staff, of which 201 completed and usable questionnaires were returned and used for data analysis. Further, the partial least squares structural equation modeling approach is used in this study using SmartPLS version 3 software to test the hypothesized model and determine the direct and indirect effects.

Results showed a negative relationship between servant leadership and workplace deviance, positive relationship between servant leadership and organizational justice, negative relationship between organizational justice and workplace deviance and that organizational justice mediates in the relationship between servant leadership and workplace deviance.

This study provides valuable recommendations and practical implications to address the nurses’ deviant workplace behaviors in the public sector hospitals of Pakistan.

This study is novel as it shows the significance of servant leadership behavior which has the ability to positively influence organizational justice perception leading to less likelihood of the emergence of nurses’ deviant workplace behavior, specifically in the context of public sector hospitals of Pakistan.

This study aims to investigate the mediating effect of innovation on the relationship between KM (KM) capabilities and organisational performance in the context of construction firms operating in Pakistan. Worldwide innovation predicts the performance of any firm. Today, the construction industry in Pakistan is booming, which reinforces the need for a study on innovation and KM in this sector.

This empirical study uses a correlational research design. An online survey questionnaire was used as a data collection method. Through convenient sampling, the sample comprised 277 employees from different construction firms working under the Defence Housing Authority (a construction company operating in major cities) in Pakistan. Data were analysed through partial least squares-structural equation modelling (Smart PLS-SEM version 3) to assess the hypothesis.

Data analysis reveals that KM dimensions, knowledge acquisition, application and protection positively and significantly influence organisational performance; however, knowledge conversion is insignificant. Furthermore, innovation positively and substantially mediates the relationship between knowledge acquisition, application, protection, organisational performance and the insignificant terms of knowledge conversion.

This study is limited to the construction industry, and future research should be conducted on larger scales for better generalisation. Other mediators between KM and organisational performance (i.e. organisational complexity, workplace environment, employee knowledge-sharing attitude) should be investigated.

These results are crucial and encourage managers in the construction industry, especially from a developing country like Pakistan, to understand the importance of innovation, the application of KM and the essential role it has in boosting business performance.

This research contributes to the scholarly debate on the mediating role of innovation in the relationship between KM and organisational performance. It also expands the literature on KM through an empirical investigation on the innovation of the construction industry in Pakistan from a management perspective.

This paper aims to incorporate a numerical investigation of unsteady flow of nano-fluid near the boundary wall and heat transmission over a flat sheet in porous media under the assumption that sheet is continuously stretching. A comprehensive study is accomplished to probe the impacts of different physical parameters on heat transmission and fluid flow.

The problem is designed mathematically by using Navier–Stokes equations and corresponding equations are transmuted into non-dimensional form, which are reduced to local non-similarity equations. Implicit finite difference scheme is used to attain a non-similar solution for values of similarity variable ranging in [0,1]

The reduced Nusselt number is a decreasing function of each dimensionless number, while the reduced Sherwood number is an increasing function of each considered value of parameters Pr, Sc, Nb and Nt.

Motivated by the industrial, technological and scientific importance, the objective of this study is to discuss the unsteady flow generated by linear stretching of the surface in Nano-fluid in a porous medium. However, the investigation of unsteady boundary layer flow and heat transfer of a Nano-fluid past a stretching surface immersed in a porous medium has not been discussed yet. Furthermore, finite difference scheme is used to solve the problem, and authenticate results are achieved which are in good agreement with published work.

The purpose of this study is to theoretically probe the shape impacts of nano-particle on boundary layer flow of nano-fluid toward a stretching cylinder with heat-transmission effects. The base fluid used for this study is pure water, and aluminum oxide nano-particles are suspended in it. Four different shapes of nano-particle, namely, cylindrical, brick, platelets and blades, are considered to carry out the study.

The problem is modelled mathematically and the nonlinear system of equations is attained by using appropriate transmutations. The solution of transmuted equations is achieved by utilizing a shooting technique with Fourth-Fifth order Runge–Kutta Fehlberg scheme. Numerically attained results are elucidated through graphs and tables which are further compared under limiting cases with existing literature to check the validity of the results.

It is observed that fluid velocity and temperature of cylindrical shaped water nano-fluids are more than the nano-fluid having brick-shaped nano-particles. Moreover, it is seen that the nano-fluids suspended with platelets-shaped nano-particles have higher velocity and temperature than the nano-fluids containing blade-shaped nano-particles. The curvature parameter and nano-particles volume fraction have increasing effects on flow velocity and temperature of nano-fluids containing all types of nano-particle shapes.

Numerous authors have examined the impacts of nano-particle shapes on characteristics of heat transfer and fluid flow. However, to the best of the authors’ knowledge, the shape impacts of nano-particles on boundary layer flow of nano-fluid toward a stretching cylinder with heat-transmission effects have not been discussed. So, to fulfill this gap, the present paper explicates the impacts of various nano-particle shapes on Al₂O₃–water-based nano-fluid flow past a stretching cylinder with heat-transfer effects.

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.

This study aims to investigate the effectiveness of two types of social media videos used for destination image development: induced/commercial-oriented content and organic content (where content is made without commercial interest, such as vlogs classified as user-generated content).

Experimental research using “Emotive EEG” (electroencephalogram) in a controlled environment was conducted with 30 participants (20 males, 10 females), age range 18 to 26. Emotive EEG recording was performed while the participants watched both types of video clips. Test results for both groups indicate that induced content is preferred over organic content.

This study opens up future research avenues where neuromarketing’s “Marketer Friendly” EEG equipment can be applied to the customer selection process.

Marketing analysts can gauge the interest and response of customers on different types of social media video content for destination marketing based on the findings of this study.

Utilizing affective event theory (AET), this paper aims to understand the affective reasoning behind choosing to speak up for or against abusive supervision. For this purpose, the authors examine the underlying mechanism of employee state paranoia in the relationship between abusive supervision and promotive and prohibitive voice of employees.

Data from 307 microfinance bank employees were collected using supervisor–subordinate nested design and time-lag approach. The analysis was performed through partial least square (PLS) structural equation modeling using Smart PLS software.

The results support the direct relationship of abusive supervision with promotive and prohibitive voice. They also support the mediating relation of paranoia arousal between abusive supervision and promotive voice. However, the results do not support the mediating relationship of paranoia arousal between abusive supervision and prohibitive voice.

In light of the literature drawn from AET and empirical data, this study forwards robust recommendations for theory and practice and may assist future researchers interested in the role of employee paranoia arousal.