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This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

Work-from-home (WFH) has gained popularity over the past years. This study aims to conduct a bibliometric analysis to systematically review and synthesize scholarly literature on the complex interplay between WFH, employee well-being and performance.

The study incorporates analysis of the bibliometric including performance analysis, content analysis and scientific mapping that is applied to 497 Scopus papers. VOSviewer software was used to evaluate the data.

This study posits an imbalance between the count of documents and the citations earned by each author. International Journal of Environmental Research and Public Health was regarded as a leading journal with maximum citations and publications. The highest count of publications came from most Asian countries such as India, China, Indonesia and Japan. The investigation indicated that the writers with the maximum citations were predominantly the authors of the majorly cited papers. Further, the text mining through co-occurrence of keyword analysis generated five clusters and cocited references revealed three themes.

The current research might benefit both research groups as well as human resource professionals since it also reveals the research necessity and gaps in the WFH domain.

This research delves into unexplored facets of WFH beyond traditional studies over the past decade by examining remote work arrangements in today’s economy, revealing previously unnoticed dynamics affecting employee well-being and performance. This innovative viewpoint enhances the literature and provides an empirical foundation for strategic organizational decision-making and future study.

This paper aims to investigate the associations between organizational justice dimensions and employees' knowledge sharing (KS) while studying the mediating role of psychological empowerment (PE) in context of the Indian hospitality industry. It is also aimed to investigate the association between KS and innovative work behavior (IWB).

A mediation model was verified utilizing three-wave survey data from 293 employees working in hotels situated in northern India. Hypotheses were tested using AMOS and PROCESS Model 4.

There are significant associations between justice dimensions and KS, and PE mediates these relationships. Additionally, employees' KS has a positive effect on their IWB.

Organizations must promote justice and psychologically empower their employees to facilitate KS. Our study also highlights the significance of employees' KS in encouraging their IWBs. HR leaders and managers have an important role in facilitating the right work environment, in which employees experience fairness and empowerment.

This paper is the first to investigate linkages between justice dimensions, PE, KS and IWB in context of the Indian hospitality industry. Furthermore, this study has made the maiden attempt of asserting the mediating role of PE in the relationship between justice dimensions and KS.

In recent times, ternary hybrid nanofluid has garnered attention from scientist and researchers due to its improved thermal efficiency. This study aims to delve into the examination of ternary hybrid nanofluid (Al₂O₃–Cu–TiO₂/water), particularly concerning axisymmetric flow over a nonlinearly permeable stretching/shrinking disk. In addition, the investigation of convective boundary conditions and thermal radiation effects is also considered within the context of the described flow problem.

Mathematical formulations representing this problem are reduced into a set of ordinary differential equations (ODEs) using similarity transformation. The MATLAB boundary value problem solver is then used to solve the obtained set of ODEs. The impact of considered physical parameters such as suction parameter, radiation parameter, nonlinear parameter, nanoparticle volumetric concentration and Biot number on the flow profiles as well as the physical quantities is illustrated in graphical form.

The findings revealed the thermal flux for the nonlinearly shrinking disk is approximately 1.33%, significantly higher when compared to the linearly shrinking disk. Moreover, the existence of dual solutions attributed to the nonlinear stretching/shrinking disk is unveiled, with the first solution being identified as the stable and reliable solution through temporal stability analysis.

Understanding ternary hybrid nanofluid behavior and flow has applications in engineering, energy systems and materials research. This study may help develop and optimize nanofluid systems like heat exchangers and cooling systems.

The study of flow dynamics across nonlinear stretching/shrinking disk gains less attention compared to linear stretching/shrinking geometries. Many natural and industrial processes involve nonlinear changes in boundary shapes or sizes. Understanding flow dynamics over nonlinear shrinking/stretching disks is therefore essential for applications in various fields such as materials processing, biomedical engineering and environmental sciences. Hence, this study highlights the axisymmetric flow over a nonlinear stretching/shrinking disk using ternary hybrid nanofluid composed of alumina (Al₂O₃), copper (Cu) and titania (TiO₂). Besides, this study tackles a complex problem involving multiple factors such as suction, radiation and convective boundary conditions. Analyzing such complex systems can provide valuable insights into real-world phenomena where multiple factors interact.

This study aims to investigate time-harmonic wave propagation in a chiral porous thermoelastic solid under strain gradient theory (SGT), focusing on identifying and characterizing distinct wave modes within the medium.

Using Iesan's gradient theory, which incorporates chiral effects and accommodates second sound phenomena, the authors derive mathematical formulations for the velocities and attenuations of eight propagating waves: four dilatational waves and two pairs of coupled shear waves (one left circularly polarized, the other right). Numerical simulations are performed for a specific model, exploring the influence of various parameters on wave propagation.

The authors establish that the medium supports four dilatational waves, including a microstretch-associated wave, and four shear waves, distinguished by their chiral-induced characteristics. The results highlight the frequency-dependent dispersive nature of all propagating waves and establish connections with existing theoretical frameworks, demonstrating the broader applicability of our findings.

The characteristics of wave propagation in chiral media examined here can enhance our understanding of chiral medium behavior. This knowledge is crucial for developing materials with pronounced chiral effects, surpassing those found in natural chiral materials like bone, quartz, sugar and wood. Advances in artificial chiral materials are driven by their superior toughness, durability and other beneficial properties. Consequently, this study has potential applications across various fields, including the design of chiral broadband absorbers and filters, the production of artificial bones and medical devices, aeronautical engineering and beyond.

This research extends existing theories and deepens the understanding by exploring wave behaviors in chiral media, advancing this emerging field.

Over the last 2 decades, supply chain sustainability research has become a highly dynamic and fruitful study area. This field has garnered significant attention due to its potential to reshape decision-making processes within supply chains. At the same time, the practical side of supply chain operations remains intensely competitive in today’s business landscape. Furthermore, the current academic research aims to outline effective strategies for achieving sustainability across supply chains, particularly in the manufacturing sector. In response to these challenges, this research has conducted an integrated multi-criteria decision-making approach to evaluate sustainable supply chain performance from the triple bottom line perspective, including financial, environmental, and social performance.

The initial stage involves selecting the crucial criteria (short-term and long-term) and alternatives for sustainable supply chain performance (SSCP) from experts and conducting an in-depth literature review. Initially, there were 17 criteria, but after a pilot test with co-authors and online discussions with experts, the number of criteria was subsequently reduced to 9. In the second phase, the Best-Worst Method (BWM) was applied to rank and prioritize the criteria. The third and final stage examined the causal relationship between the identified criteria, utilizing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique.

Based on BWM analysis results, the top three criteria in terms of prominence are: (1) return on investment (ROI), (2) product quality, and (3) manufacturing lead time. Out of the three alternatives, financial performance (FP) is the most crucial dimension for SSCP, followed by environmental performance (ENP) and social performance (SP). On the other hand, the DEMATEL approach showed that work health and safety (short-term criterion), asset utilization (long-term criterion), energy consumption (long-term criterion), waste disposal (long-term criterion), manufacturing lead time (short-term criterion), and on-time delivery (short-term criterion) are categorized within the cause group, while criteria such as return on investment (ROI) (long-term criterion), customer-service level (short-term criterion), and product quality (long-term criterion) fall into the effect group.

The proposed study has certain drawbacks that pave the way for future research directions. First, it is worth noting the need for a larger sample size to ensure the reliability of results, the potential inclusion of additional criteria to enhance the assessment of sustainability performance, and the consideration of a qualitative approach to gain deeper insights into the outcomes. In addition, fuzziness in qualitative subjective perception could be imperative when collecting data to ensure its reliability, as translating experts’ perceptions into exact numerical values can be challenging because human perceptions often carry elements of uncertainty or vagueness. Therefore, fuzzy integrated MCDM frameworks are better suited for future research to handle the uncertainties involved in human perceptions, making it a more appropriate approach for decision-making in scenarios where traditional MCDM methods may prove insufficient.

The proposed framework will enable decision-makers to gain deeper insights into how various decision criteria impact SSCP, thus providing a comprehensive evaluation of SSCP that considers multiple dimensions, such as financial, environmental, and social performance within the manufacturing sector.

The proposed study is the first empirical study to integrate both BWM and DEMATEL approaches to evaluate sustainable supply chain performance in the manufacturing context.

This study aims to investigate whether public attention influences corporate decisions on environmental disclosure, thereby revealing how society perceives and understands environmental issues and how corporations respond to these expectations.

We selected publicly listed Chinese firms as our sample. An “Environmental Disclosure Greenwashing” (EDG) Index was developed through textual analysis of their annual reports using natural language processing. Financial data were obtained from the CSMAR database, and multivariate regression was used for analysis.

The impact of public attention on EDG primarily manifests as an oversight pressure effect rather than a legitimacy incentive effect. As public attention intensifies, firms tend to adopt more substantial environmental actions instead of merely symbolic environmental disclosures. Formal regulatory frameworks might inadvertently trigger corporate EDG, but public attention can correct the adverse effects possibly introduced by formal regulations. Notably, in firms facing lower institutional pressure, the influence of public attention is more pronounced.

The evidence suggests that public attention reduces corporate EDG. These findings have significant implications for the regulation of environmental disclosures among firms in emerging economies.

The study integrates research in environmental disclosure with the concept of “greenwashing”, unveiling the limitations of the “disclosure as governance” viewpoint. It elucidates the impact of an informal external oversight mechanism (i.e. public attention) on complex corporate environmental disclosure decisions.

This research aims to understand the primary challenges encountered by entrepreneurs operating in emerging economies, where entrepreneurship plays a vital role. The study places a particular emphasis on entrepreneurs in Brazil.

The research methodology involved the analysis of data obtained from interviews, using both content analysis and Grey Relational Analysis techniques.

The analysis revealed several prominent difficulties that entrepreneurs face in these domains. These challenges encompassed issues such as grappling with intricate taxation systems and the associated tax burden, navigating government bureaucracy, securing access to essential financing and initial investments, contending with the absence of supportive government programs and addressing the dynamic nature of market conditions. The findings on the most critical barriers reveal potential pathways for entrepreneurs, policymakers and universities to act in developing the entrepreneurial ecosystem in emerging economies.

The insights garnered from this research have the potential to inform the formulation of robust public policies aimed at fostering entrepreneurship and innovation in emerging countries. Furthermore, these findings can serve as a valuable resource for planning initiatives designed to train engineers to become successful entrepreneurs.

This paper examines thematic discourses concerning business and the Sustainable Development Goals (SDGs) on X (formerly Twitter), aiming to uncover active user groups and evaluate engagement levels across various topics. The study also explores the engagement patterns among different user categories, ultimately seeking deeper insights into platform discourse regarding business and the SDGs.

Utilizing unsupervised machine learning technique Latent Dirichlet Allocation (LDA), we perform exploratory topic modeling on X data referencing business and the SDGs, generating 16 thematic clusters. Subsequently, we analyze user descriptions to categorize users involved in these discussions. Finally, we employ binomial logit models to assess the relationship between topics and engagement and chi-squared test to evaluate the relationship between users and topics.

The exploratory research identifies 16 business and SDG topics, while the analysis of users reveals 6 stakeholder groups contributing to these discussions. Business groups emerge as the most frequent contributors, posting on topics related to partnership, action advocacy, and economic outcomes. Topics about updates on progress and transformative initiatives garnered strongest support for engagement.

This research not only sheds light on the current state of business and SDG discourse on X, but also underscores the significance of engaging external stakeholders in driving positive social change globally.

This study conducts a meta-analysis to investigate the impact of board diversity, independence and size on carbon emission disclosure.

The results of 22 empirical investigations on the association between board qualities and carbon emission disclosure are synthesised using a meta-analysis approach. Inclusion and exclusion criteria are established, and search strategies are devised to locate relevant material. Data extraction entails gathering important information such as the names of the authors, variables and correlation coefficients. Fisher's z-transformation is used to compute and synthesise effect sizes and assumptions, sensitivity testing and subgroup analysis are performed to assess the robustness of the findings.

A substantial association was discovered between board characteristics and carbon emission disclosure. Board independence and gender diversity revealed small to medium-strength positive relationships, whilst board size had a medium-strength positive correlation. The study periods varied from 2011 to 2022, with 2018 having the most studies. However, highly heterogeneous groups were discovered; further subgroup analyses were then carried out to sort out this issue.

Several limitations were recognised due to the limited number of studies and heterogeneity, although subgroup analysis was used to reduce the influence of heterogeneity. To investigate alternate outcomes, more analysis of the heterogeneity level and potential modifications to the model assumptions may be required.

Companies should consider board size, independence and gender diversity when formulating long-term competitive strategies in the climate change movement. These characteristics can aid in bridging information gaps and garnering stakeholder support for carbon-reduction initiatives.

This meta-analysis addresses a gap in the literature by addressing prior studies' conflicting and inconsistent findings on the association between board characteristics and carbon emission disclosure. It employs a rigorous approach and synthesis strategy to provide a thorough and robust understanding of the crucial role of board characteristics in carbon emission disclosure.