Search results

The study hypothesized that the impact of board diversity on financial distress (FD) is not direct but rather mediated by the firm’s corporate social responsibility (CSR) activities. Consequently, the purpose of this study is to examine the impact of CSR as a mediator in the board diversity–FD relationship.

The study examined six board diversity dimensions – age, gender, nationality, education and tenure in 81 nonfinancial Pakistan Stock Exchange (PSX)-listed firms from 2010 to 2021. The CSR engagement of the sample firms is evaluated using a multidimensional financial approach and the likelihood of FD is computed using Altman’s Z-score. The system-generalized method of moments estimator is used to meet the study objectives. In addition, several tests are run to determine the robustness of the study’s findings.

Based on the procedure for mediation analysis outlined by Baron and Kenny (1986), the authors found that CSR is significantly inversely associated with the likelihood of FD. Second, board diversity variables age, gender and national diversity were positively associated with CSR. Third, board age, gender and national diversity are significantly inversely related to FD. Finally, it was found that there is partial mediation between board age diversity and FD, whereas full mediation is shown between board age diversity and FD and between board nationality diversity and FD.

This study provides practical insights into PSX’s board diversity for companies, regulators and policymakers.

This research studies the connection between board diversity and FD. In addition, the current study extended the analysis by testing for the first time the mediating role of CSR in the diversity–distress relationship, particularly in the context of an emerging economy.

This study aims to examine the impact of social media (SM) on the interactivity among teachers, among students and between students and teachers for sustainable academic performance and for achieving sustainable development (SD) in higher educational institutes. This study also investigates the moderating impact of knowledge creators (KNC) and knowledge seekers (KNS) on the collaborative learning environment using SM.

With the help of Vroom’s expectancy motivation theory (1964), collaborative learning theory and other theories, a theoretical model has been developed. This theoretical model has been tested using the structural equation modeling technique with 375 participants taken from different educational institutes. The respondent-–participants were both teachers and students.

The study found that SM plays a significant role in achieving SD al goals and enhances collaborative learning activities among teachers and students to improve academic performance to achieve SD in higher educational institutes. Also, the study highlighted that both “knowledge creators” and “knowledge seekers” have effective moderating impact on the linkage between “intention to use SM for knowledge sharing” and “collaborative learning using social media” to achieve SD al goals.

With the inputs from expectancy-instrumentality-valance theory and collaborative learning theory and existing literature, a theoretical model has been developed conceptually. Later, the model was successfully validated with an overall high explanatory power (72%) of this model. As the sample of the study do not represent a global representation of the population, thus the findings cannot be generalizable.

This study has provided valuable inputs to the SD practitioners and educational policymakers to formulate appropriate policies that enable SD al activities in higher educational institutes. This study also provides food for thought to the policymakers about the role of KNC and KNS toward the collaborative learning environment in achieving SD al goals in higher educational institutes.

The theoretical model developed in this study is unique. This study shows how both “knowledge creator” and “knowledge seeker” play a significant role toward collaborative learning and helps to achieve SD in higher learning institutes and improves their performance. The overall predictive power of the model is 72%, which also shows the effectiveness and uniqueness of the proposed model.

This study aims to test the relationship between knowledge sharing and employee engagement. In particular, the mediating and moderating roles of competency development and social climate, respectively, are also the focus of this research.

Of self-completed questionnaires collected from luxury hotels in India, 507 are usable for data analysis. The structural equation modelling (SEM) was used to examine the proposed hypotheses.

The structural equation modeling–based results illustrate a positive significant association between knowledge sharing and employee engagement. Also, there is a significant support to establish the mediating effect of competency development and the moderating effect of social climate on this relationship. The expansion of competencies of employees achieved through knowledge sharing leads to higher engagement.

This work is carried out in Indian hospitality sector and may not be generalizable to other cultural settings.

This study’s results add to the knowledge sharing scholarship by envisaging a possible association with an employee attitudinal outcome, i.e. employee engagement.

To the best of the authors’ knowledge, this is one of the first studies to unravel the social processes through which knowledge sharing enhances competency development, and subsequently employee engagement, mainly through the influence of social climate.

This review paper seeks to enhance knowledge of how pre-loading affects reinforced concrete (RC) beams under fire. It investigates key factors like deflection and load capacity to understand pre-loading's role in replicating RC beams' actual responses to fire, aiming to improve fire testing protocols and structural fire engineering design.

This review systematically aggregates data from existing literature on the fire response of RC beams, comparing scenarios with (WP) and without pre-loading (WOP). Through statistical tools like the two-tailed t-test and Mann–Whitney U-test, it assesses deflection extremes. The study further examines structural responses, including flexural and shear behavior, ultimate load capacity, post-yield behavior, stiffness degradation and failure modes. The approach concludes with a statistical forecast of ideal pre-load levels to elevate experimental precision and enhance fire safety standards.

The review concludes that pre-loading profoundly affects the fire response of RC beams, suggesting a 35%–65% structural capacity range for realistic simulations. The review also recommended the initial crack load as an alternative metric for determining the pre-loading impact. Crucially, it highlights that pre-loading not only influences the fire response but also significantly alters the overall structural behavior of the RC beams.

The review advances structural fire engineering with an in-depth analysis of pre-loading's impact on RC beams during fire exposure, establishing a validated pre-load range through thorough statistical analysis and examination of previous research. It refines experimental methodologies and structural design accuracy, ultimately bolstering fire safety protocols.

The purpose of this paper is to structure existing research on knowledge management (KM) in small- and medium-sized enterprises (SMEs) to offer a comprehensive overview of research strands and topics in KM in SMEs to determine their evolution over time.

The paper, which is considered a follow-up literature review, is based on a systematic literature review that covers 180 scientific papers that were published since the review paper by Durst and Edvardsson in 2012 that covered 36 papers.

The findings of this review and those of the aforementioned review are brought together in the form of an overview that structures research on KM in SMEs based on themes that, in turn, allow the derivation of promising research directions and research questions aimed at structuring future research on KM in SMEs.

By combining the findings of this review with the findings from the review published in this journal in 2012, this paper offers, to the best of the authors’ knowledge, the most comprehensive literature review on KM in SMEs produced to date.

This study aims to investigate the direct nexus between board characteristics, corporate social responsibility (CSR) disclosure and the cost of equity capital (CEQ). This is done by using agency theory, stakeholder theory and signalling theory, followed by an investigation into the indirect mediation impact of CSR disclosure in the board characteristics-CEQ nexus. It intends to present new experimental evidence from Jordan’s developing economy.

The study’s target population was services companies registered on the Amman Stock Exchange (ASE) between 2012 and 2020. As a result, the population and sampling of this study are represented by all services companies for whom complete data are available over the period, with a total of 43 services companies yielding 387 company-year observations. Data for our study were obtained from their annual disclosures and the ASE’s database.

The main findings demonstrated that board size, board gender variety and the number of board sessions positively affect CSR disclosure significantly. In addition, three board characteristics (i.e. board size, board independence and board gender variety) significantly negatively affect CEQ. Besides, CSR disclosure significantly negatively affects CEQ and it fully mediates the relationship between two board characteristics (i.e. board size and board gender variety) and CEQ, whereas it partially mediates the nexus between board independence, CEO/Chairman duality and the number of board sessions of board characteristics and CEQ.

This study varies from earlier studies, in that it builds a new research model by looking at the mediating role of CSR disclosure in the nexus among board characteristics and the CEQ.

Despite ongoing reports of insider-driven leakage of confidential data, both academic scholars and practitioners tend to focus on external threats and favour information technology (IT)-centric solutions to secure and strengthen their information security ecosystem. Unfortunately, they pay little attention to human resource management (HRM) solutions. This paper aims to address this gap and proposes an actionable human resource (HR)-centric and artificial intelligence (AI)-driven framework.

The paper highlights the dangers posed by insider threats and presents key findings from a Leximancer-based analysis of a rapid literature review on the role, nature and contribution of HRM for information security, especially in addressing insider threats. The study also discusses the limitations of these solutions and proposes an HR-in-the-loop model, driven by AI and machine learning to mitigate these limitations.

The paper argues that AI promises to offer many HRM-centric opportunities to fortify the information security architecture if used strategically and intelligently. The HR-in-the-loop model can ensure that the human factors are considered when designing information security solutions. By combining AI and machine learning with human expertise, this model can provide an effective and comprehensive approach to addressing insider threats.

The paper fills the research gap on the critical role of HR in securing and strengthening information security. It makes further contribution in identifying the limitations of HRM solutions in info security and how AI and machine learning can be leveraged to address these limitations to some extent.

Blockchain technology has created possibilities for environmental supply chain sustainability and climate protection. However, because of its early development stage, users tend to resist the adoption of this new technology. The purpose of this study is to investigate the effects of resistance on blockchain adoption intentions in the context of the foodservice industry. This study further explores if public pressures and climate change awareness could possibly weaken the negative relationships between blockchain resistance and adoption intentions.

Data were collected from managers and full-time employees in the foodservice industry, using an online research panel survey. A structural equation model was developed and tested to examine the hypothesized relationships. Additionally, a multi-group analysis was performed to test the moderating roles of public pressures and climate change awareness.

The findings from this study confirmed that foodservice employees’ characteristics, including traditional barriers, and blockchain technology factors, like perceived risk, are both significant in forming resistance to blockchain. This study also demonstrated the significant roles of internal and external stakeholders in weakening the negative associations between blockchain resistance and adoption intentions.

This study recommends that foodservice companies address how to reduce their employees’ negative perceptions about changes imposed by blockchain adoption. This study also suggests the joint consideration of the pressures from internal and external stakeholders to provide continued insights into developing environmental practices for the foodservice industry.

This study extends the theoretical underpinning of the innovation resistance theory by incorporating the stakeholder theory as a strong foundation for understanding how external pressures and internal awareness may influence foodservice employees’ responses to the implementation of blockchain technology to mitigate climate change.

Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.