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Financial and nonfinancial disclosures (sustainable accounting) are crucial in the annual financial reports of many firms. This study aims to explore the dynamic relationship between sustainability disclosure quality (SDQ) and financial performance (FP) within mandatory disclosure frameworks. SDQ is evaluated across six dimensions, encompassing both the quality and quantity of disclosures, aiming to understand their reciprocal influence.

Using the generalized method of moments (GMM), this research analyzes data from 2013 to 2019, focusing on 99 listed Indian firms within the S&P Bombay stock exchange (BSE) 500 index. The study uses rigorous measurement criteria to assess SDQ and uses statistical methods to unveil the causal link between SDQ and FP.

The results show a positive causal connection between SDQ and FP, where organizations with good FP make relatively higher disclosures across FP proxies than their counterparts. Additionally, the study investigates the impact of research and development (R&D) expenditure and dividend payments (DIVD) on SDQ. Notably, lower R&D spending is associated with higher quality SDs, and companies with superior SDQ exhibit increased DIVD.

The findings advocate for strengthened regulatory compliance, incentivized sustainable practices and heightened reporting standards for a transparent business environment and achieving the relevant United Nations Sustainable Development Goals.

This research contributes original insights by uncovering the intricate relationship between SDQ and FP, shedding light on the impact of R&D expenditure and DIVD on SDQ. These findings contribute to a nuanced understanding of the interplay between FP and sustainability reporting within the context of mandatory disclosure frameworks.

In this era of technological advancement, the capabilities of devices and telecommunications have changed the pattern of media consumption among consumers. This study examined the research landscape and advancements in OTT services.

This study adopted a hybrid review consisting of bibliometric and thematic analyses to present advancements in the OTT platforms. A hybrid review integrates both systematic and narrative approaches by emphasizing a literature search strategy and the study selection process.

This study focuses on previous literature to understand recent developments in the domain. The authors derive six major OTT themes: OTT infrastructure and technology advancement, OTT consumption behaviour, shifting trends towards OTT platforms, viewers’ engagement in digital media, OTT in the global market, OTT policies and regulatory mechanisms.

The findings of this study will be useful for marketers/stakeholders associated with the entertainment and media industries, such as sales promotion teams, media planners/advertisers, content management companies and policy regulators, to penetrate OTT viewers.

The literature related to OTT is progressively rising, but it remains highly fragmented because of inconsistencies in the methodologies and theories used in the domain of OTT. This study offers directions in terms of theory, methodology and future research on OTT services.

Natural disasters cause serious operational risks and disruptions, which further impact the food supply in and around the disaster-impacted area. Resilient functions in the supply chain are required to absorb the impact of resultant disruptions in perishable food supply chains (FSC). The present study identifies specific resilient functions to overcome the problems created by natural disasters in the FSC context.

The quality function deployment (QFD) method is utilized for identifying these relations. Further, fuzzy term sets and the analytical hierarchy process (AHP) are used to prioritize the identified problems. The results obtained are employed to construct a QFD matrix with the solutions, followed by the technique for order of preference by similarity to the ideal solution (TOPSIS) on the house of quality (HOQ) matrix between the identified problems and functions.

The results from the study reflect that the shortage of employees in affected areas is the major problem caused by a natural disaster, followed by the food movement problem. The results from the analysis matrix conclude that information sharing should be kept at the highest priority by policymakers to build and increase resilient functions and sustainable crisis management in a perishable FSC network.

The study suggests practical implications for managing a FSC crisis during a natural disaster. The unique contribution of this research lies in finding the correlation and importance ranking among different resilience functions, which is crucial for managing a FSC crisis during a natural disaster.

Flow induced by rotating disks is of great practical importance in several engineering applications such as rotating heat exchangers, turbine disks, pumps and many more. The present research has been freshly displayed regarding the implementation of an engine oil-based Casson tri-hybrid nanofluid across a rotating disk in mass and heat transferal developments. The purpose of this study is to contemplate the attributes of the flowing tri-hybrid nanofluid by incorporating porosity effects and magnetization and velocity slip effects, viscous dissipation, radiating flux, temperature slip, chemical reaction and activation energy.

The articulated fluid flow is described by a set of partial differential equations which are converted into one set of higher-order ordinary differential equations (ODEs) by using convenient conversions. The numerical solution of this transformed set of ODEs has been spearheaded by using the effectual bvp4c scheme.

The acquired results show that the heat transmission rate for the Casson tri-hybrid nanofluid is intensified by, respectively, 9.54% and 11.93% when compared to the Casson hybrid nanofluid and Casson nanofluid. Also, the mass transmission rate for the Casson tri-hybrid nanofluid is augmented by 1.09% and 2.14%, respectively, when compared to the Casson hybrid nanofluid and Casson nanofluid.

The current investigation presents an educative response on how the flow profiles vary with changes in the inevitable flow parameters. As per authors’ knowledge, no such scrutinization has been carried out previously; therefore, our results are novel and unique.

This research paper investigates the utilization of artificial intelligence (AI) among teachers in higher education (universities and colleges) in India and its impact on teaching activities. The study explores teachers’ perceptions, attitudes and the factors influencing the integration of AI in their teaching practices.

A questionnaire-based survey was conducted involving 500 teachers in higher education (university and college) in India. Data analysis included descriptive statistics, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structure equation modeling.

The study addresses teachers’ expectations and attitudes toward AI integration in teaching practices. Results suggest that AI can potentially enhance teaching practices among teachers in higher education in India. The findings contribute to understanding AI adoption in teaching, providing insights for educational institutions and policymakers. Further research is recommended to validate the results across different regions and academic settings, leading to the development of strategies and support systems for successful AI implementation in teaching practices.

The originality of this research lies in its investigation of the integration of AI in college teaching practices among teachers in India. It contributes to the existing literature by exploring teachers’ perceptions, attitudes and the factors influencing the adoption of AI, providing valuable insights for educational institutions and policymakers in the Indian context.

Small and medium-sized enterprises (SMEs) have contributed substantially to the global entrepreneurial environment and economic growth, particularly within emerging economies. However, the success rate of these enterprises is relatively low in most developing countries, particularly India. Therefore, this study aims to contribute towards creating a sustainable model for enhancing entrepreneurial performance by examining the impact of entrepreneur digital literacy, entrepreneurial attitude and innovative work behaviour on their sustainable performance. It also explores the role of innovative work behaviour as a mediator in the relationship between entrepreneurial digital literacy, attitude and SMEs’ sustainable performance.

Data was collected from a sample of 329 entrepreneurs registered with the Department for Promotion of Industry and Internal Trade portal in India using snowball random sampling and was analysed via the structural equation modelling technique.

The findings reveal that entrepreneurial digital literacy and attitude play a robust and critical role in supporting innovation and SMEs’ long-term success, respectively. Entrepreneurial digital literacy equips individuals with the skills to navigate digital tools effectively, fostering innovation within SMEs and enabling them to adapt to evolving market demands. Similarly, a positive entrepreneurial attitude, characterised by a proactive and risk-taking mindset, is essential for driving SMEs’ long-term success by facilitating growth and adaptation in competitive business environments. Moreover, the relationship between entrepreneurial digital literacy, attitude and sustainable performance was found to be partially mediated by innovative work behaviour. Innovative work behaviour, including creativity, proactivity and risk-taking, is a bridge, translating digital literacy and entrepreneurial mindset into tangible outcomes that contribute to sustainable entrepreneurial performance and resilience in dynamic market conditions.

The described research work offers a valuable contribution to the field by integrating digital literacy and entrepreneurial attitude within the context of entrepreneurship. Exploring how innovative work behaviour mediates the relationship between digital literacy, entrepreneurial attitude and sustainable entrepreneurial performance contributes to a deeper understanding of the mechanisms driving success in today’s digital economy.

This editorial review presents a bibliometric account of the convergence of the fields of artificial intelligence (AI) and human resource management (HRM) and an overview of the related contributions in this special issue. It also explores the expansive area where research on AI and HRM intersects, a domain experiencing rapid growth and transformation, faster than we envisaged.

This substantive editorial employs a range of bibliometric analytical tools to present a state of knowledge on the topic and also provides an analytical overview of the contributions in this Special Issue.

A thorough examination of scholarly publications spanning two decades illuminates the evolutionary path of themes, key contributors, seminal works and emerging trends within this interdisciplinary sphere. Leveraging co-word analysis, we distill essential themes and insights from an extensive dataset of 654 journal publications curated from the Web of Science database. Our analysis underscores critical research domains, highlighting the nuanced interplay between HRM and AI.

By integrating findings from the bibliometric analysis and the contributions from the papers in the Special Issue, we highlight and speculate where the field is heading and where scholars have crucial? Opportunities to contribute to going forward.

The paper focuses on bridging the existing literature gap on the role of leadership in influencing employee engagement considering the advancement in technologies. With this, the author explores how the three critical elements of service-based companies' business environment-artificial intelligence (AI) success, employee engagement, and leadership are interlinked and are valuable for raising the engagement level of employees.

A purposive sampling strategy was used to select the employees working in the respective companies. The survey was distributed to 150 senior management employees but responses were received from only 56 employees making the response rate 37.33%. Consequently, an empirical examination of these 56 senior management employees belonging to service-based companies based in Delhi NCR using a survey questionnaire was conducted.

The PLS-SEM (partial least squares structured equation modelling) revealed that AI has a positive role in affecting employee engagement levels and confirmed the mediation of leadership. The magnitude of the indirect effect was negative leading to a reduction in total effect magnitude; however, as the indirect effect model has a higher R square value, the inclusion of a mediating variable made the model more effective.

This study contributes to extending the existing knowledge of the academicians about the relationship theory of leadership, AI implementation in organizations, AI association with leadership and AI impact on employee engagement. The author extends the theoretical understanding by showing that more integration of AI-supported leadership could enable organizations to enhance employee experience and motivate them to be engaged. Despite its relevance, due to the limited sample size, focus on a specific geographic area (Delhi NCR) and the constraint of only using quantitative analysis, the findings open the scope for future research in the form of qualitative and longitudinal studies to identify AI-supported leadership roles.

The study findings are beneficial majorly for organizations to provide them with more in-depth information about the role of AI and leadership style in influencing employee engagement. The identified linkage enables the managers of the company to design more employee-tailored strategies for targeting their engagement level and enhancing the level of productivity of employees. Moreover, AI-supported leadership helps raise the productivity of employees by amplifying their intelligence without making technology a replacement for human resources and also reducing the turnover rate of employees due to the derivation of more satisfaction from existing jobs. Thus, given the economic benefit and societal benefits, the study is relevant.

The existing studies focused on the direct linkage between AI and employee engagement or including artificial intelligence as a mediating variable. The role of leadership is not evaluated. The leadership enables supporting the easy integration of AI in the organization; therefore, it has an important role in driving employee engagement. This study identifies the contribution of leadership in organizations by providing the means of enhancing employee satisfaction without hampering the social identity of the company due to the integration of AI.

The purpose of this research was to conduct a comprehensive bibliometric analysis to explore supply chain resilience and operations management practices in the construction industry, with a particular focus on the transition from Industry 4.0 to Industry 5.0. The study addressed a significant gap in the literature regarding the impact of these advanced technologies on the construction sector’s ability to anticipate, respond to and recover from disruptions.

The methodology employed a bibliometric analysis using the Scopus database to identify key trends, influential publications and emerging research areas using keywords such as “supply chain”, “operations management”, “Industry 4.0”, “Industry 5.0” and “construction”. This approach allowed for a quantitative evaluation of existing literature, offering insights into the intellectual structure of the field.

The findings revealed that while Industry 4.0 technologies, such as IoT and AI, have enhanced the construction industry’s supply chain visibility and efficiency, the shift towards the Industry 5.0 paradigm introduces a human-centric approach that further strengthens resilience through collaboration and sustainability.

The study’s practical implications suggest to both industry and academia that embracing Industry 5.0 principles could significantly enhance the construction industry’s resilience, enabling it to withstand disruptions better and maintain project quality, timelines, and budgets in an increasingly complex global environment.

This research examines the shift from Industry 4.0 to Industry 5.0 within construction supply chains, offering a novel perspective on integrating these technologies.

The purpose of this paper is to use three-dimensional printers to fabricate functionally graded porous (FGP) beams, carry out impact loading and provide innovative equations.

In this study, using the three-dimensional printer, polylactic acid beams containing internal holes with distribution two-dimensional FGP beams of type X are fabricated. A simple tensile test and also a drop-weight impact test are performed to determine the mechanical and low-velocity impact properties of the beams. Inverse-tangent shear–strain function theory, together with the energy method, is used to derive the motion equations of low-velocity impact on the beam. A range of impact energies from 1.5 to 12 J and holes with diameters of 2 and 3 mm are used in the drop-weight impact testing machine.

As the hole diameter enlarges, there is a decrease in contact force and energy absorption levels. The larger hole diameter results in an extended contact duration, increased maximum impactor displacement, and a higher remaining impactor velocity. The innovative linear equations with a maximum error of 5.18% and nonlinear equations with a maximum error of 0.01% provide an acceptable result for the maximum contact force. For predicting the absorbed energy, the linear equation with a maximum error of 90.69% does provide an unacceptable result, and the nonlinear equation with a maximum error of 4.51% provides a reasonable result.

The originality of this research is in fabricating FGP beams with a three-dimensional printer to conduct impact tests and generate creative equations.