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This paper uses the Technology Acceptance Model (TAM) to assess the readiness of the HR function within the UK Civil Service (CSHR) to implement AI to support performance. Academic literature in relation to AI acceptance in HR functions is currently limited, so this paper aims to establish a better understanding of the current landscape and level of ambition in this area.

A quantitative research approach was adopted to determine likely behavioral intentions of workers in the human resource (HR)function if AI were implemented, by investigating key aspects of the TAM (the perceived usefulness of AI and the transparency of the CSHR in adopting AI).

While the results suggest that the CSHR is not ready to harness AI opportunities, employees were personally ready, despite perceiving a lack of sufficient knowledge in this area. The paper identifies that more time needs to be spent on raising awareness and upskilling the HR function before the CS can be considered fully ready to harness these opportunities.

The penetration of artificial intelligence (AI) technologies into the global workforce brings transformative potential to the governance structures and use of digital platforms in public sector organizations. AI is likely to play a role in the operation of HR functions and influence how they might operate in the near future.

The increased digital interactions in the B2B industry have enhanced the importance of customer engagement as a measure of firm performance. This study aims to map and analyze temporal and spatial journeys for customer engagement in B2B markets from a bibliometric perspective.

The extant literature on customer engagement research in the B2B context was analyzed using bibliometric analysis. The citation analysis, keyword analysis, cluster analysis, three-field plot and bibliographic coupling were used to map the intellectual structure of customer engagement in B2B markets.

The research on customer engagement in the B2B context was studied more in western countries. The analysis suggests that customer engagement in B2B markets will take centre stage in the coming times as digital channels make it easier to track critical metrics besides other key factors. Issues like digital transformation, the use of artificial intelligence for virtual engagement, personalization, innovation and salesforce management by leveraging technology would be critical for improved B2B customer engagement.

The study provides a comprehensive reference to scholars working in this domain.

The study makes a pioneering effort to comprehensively analyze the vast corpus of literature on customer engagement in B2B markets for business insights.

In this era of rapid technological advancement, Artificial Intelligence (AI) has emerged as a crucial factor in reshaping organisational dynamics, notably in the realm of leadership. This systematic literature review (SLR) aims to investigate the emerging relationship between AI and leadership, focussing on defining AI-powered leadership, identifying prevalent themes, exploring challenges, and uncovering research gaps within the relevant literature.

A sample of 73 papers was chosen after carefully applying the inclusion and exclusion criteria to 1,387 research articles that were initially sought. Using the methodological framework presented by Denyer and Tranfield (2009), our study adopted a four-step procedure to obtain insights from the corpus of literature. The papers were analysed by employing content and thematic analysis to address four key questions.

The review explores various definitions of AI-powered leadership proposed in the literature based on real-world situations. The study further synthesises significant themes in the existing literature, such as the past, present and future of AI and AI in various facets of organisational leadership, transitional management, and urban management. The review revealed a range of key challenges in AI-powered leadership, including ethical dilemmas, complications in human-AI interactions, hurdles in AI implementation within leadership contexts, and long-term risks associated with AI integration. In addition, this study identified areas within AI-powered leadership research that require further investigation by revealing significant research gaps in the papers.

By adopting a comprehensive approach, this research advances understanding of the complex relationship between AI and leadership dynamics, thus facilitating comprehension of the current body of knowledge and enabling future scholarly investigations in the AI-powered leadership domain.

Nanofluids are used in technology, engineering processes and thermal exchanges. In thermal transfer processing, these are used for the smooth transportation of heat and mass through various mechanisms. In the current investigation, we have examined multiple effects like activation energy thermal radiation, magnetic field, external heat source and especially slippery effects on a bioconvective Casson nanofluid flow through a stretching cylinder.

Several studies used non-Newtonian fluid models to study blood flow in the cardiovascular system. In our research, Lewis numbers for bioconvection and the influence of important parameters, such as Brownian diffusion and thermophoresis effects, are also considered. This system is developed as a partial differential equation for the mathematical treatment. Well-defined similarity transformations convert partial differential equation systems into ordinary differential equations. The resultant system is then numerically solved using the bvp4c built-in function of MATLAB.

After utilizing the numerical approach to the system of ordinary differential equations (ODEs), the results are generated in the form of graphs and tables. These generated results show a suitable accuracy rate compared to the previous results. The consequence of various parameters under the assumed boundary conditions on the temperature, motile microorganisms, concentration and velocity profiles are discussed in detail. The velocity profile decreases as the Magnetic and Reynolds number increases. The temperature profile exhibits increasing behavior for the Brownian motion and thermal radiation count augmentation. The concentration profile decreased on greater inputs of the Schmidt number and magnetic effect. The density of motile microorganisms decreases for the increased value of the bio-convective Lewis number.

The numerical analysis of the flow problem is addressed using graphical results and tabular data; our reported results are refined and novel based on available literature. This method is useful for addressing such fluidic flow efficiently.

This study aims to explore the possibility of using magnetic biochar composite (MBCC) derived from Heglig tree bark (HTB) powder (agricultural solid waste) and cobalt ferrite (CoFe₂O₄, CFO) for oil spill removal from seawater surface.

One-pot co-precipitation route was used to synthesize MBCC. The prepared materials were characterized by X-ray diffraction, scanning electron microscopy-energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy. The densities of the prepared materials were also estimated. Crude, diesel engine and gasoline engine oils were used as seawater pollutant models. The gravimetric oil removal (GOR) method was used for removing oil spills from seawater using MBCC as a sorbent material.

The obtained results revealed that the prepared materials (CFO and MBCC) were able to remove the crude oil and its derivatives from the seawater surface. Besides, when the absorbent amount was 0.01 g, the highest GOR values for crude oil (31.96 ± 1.02 g/g) and diesel engine oil (14.83 ± 0.83 g/g) were obtained using MBCC as an absorbent. For gasoline engine oil, the highest GOR (27.84 ± 0.46 g/g) was attained when CFO was used as an absorbent.

Oil spill removal using MBCC derived from cobalt ferrite and HTB. Using tree bark as biomass (eco-friendly, readily available and low-cost) for magnetic biochar preparation also is a promising method for minimizing agricultural solid wastes (e.g. HTB) and obtaining value-added-products.

The study advances research on the high-performance work system (HPWS) and innovation performance (IP) linkage by empirically analyzing the serial mediation of human resource flexibility (HRF) and knowledge absorptive capacity (KAC). Previous research on the HPWS–IP linkage underscores the presence of a “black box.” Therefore, the present study aims to unravel the underexplored HPWS–IP relationship through HRF and KAC mediation in the context of the hotel industry.

Survey-based time-lagged data were collected from 303 mid-level managers in the hotel industry. Structural equation modeling (SEM) using Smart-PLS 4 was used to test hypothesized relationships.

The results reveal that HPWS has a significant positive direct relationship with innovation performance, human resource flexibility and knowledge absorptive capacity. Further, both human resource flexibility and knowledge absorptive capacity also serially mediate the HPWS–IP linkage.

The results of the study provide useful insights into the hotel industry in Pakistan by offering empirical evidence that building HPWS in the hotel sector can lead to increased human resource flexibility and enhanced knowledge absorptive capacity, ultimately contributing to improved innovation performance.

Notably, human resource flexibility and knowledge absorptive capacity together as dynamic capabilities represent a novel contribution rarely discussed in the literature, particularly their role as serial mediators between HPWS–IP relationships within the hotel industry.

This study aims to conduct a comprehensive assessment of the existing literature on green human resource management (GHRM) and its correlation with environmental performance (EP) and energy saving behavior (ESB) by using the PRISMA methodology.

A thorough examination was undertaken involving a total of 25 articles which included a diverse range of years and geographic areas.

The findings suggest a growing emphasis on the intersection of GHRM, EP and ESB, supported by a substantial increase in research in recent times. The literature in question was mostly contributed by Malaysia, Pakistan, Canada and Thailand. Majority of research endeavors were carried out within the context of manufacturing companies. The studies under scrutiny mostly used quantitative research methodologies and often applied the resource-based view (RBV) and theory of planned behavior (TPB) frameworks to investigate the relationships between GHRM, ESB and EP. In addition, structural equation modeling (SEM) has garnered significant attention as a commonly used analytical methodology. This analysis emphasizes the growing importance of GHRM strategies such as green recruiting, green performance management and green remuneration, in fostering sustainable organizational results.

This work offers significant contributions to the existing body of research in this particular sector; shedding light on its present condition and pinpointing prospective avenues for future inquiries.

This study attempts to assess the role that institutional quality (IQ) plays in influencing inflows and outflows of Foreign Direct Investment (FDI) for BRICS nations as burgeoning FDI is flowing into and out of these countries. Moreover, this paper explores the impact of individual governance indicators separately on the FDI flows.

The study analyses this nexus for these emerging economies for the period 1996–2019 using autoregressive distributed lag technique.

The study indicates a significant and positive coefficient for IQ in India and South Africa, suggesting that improving IQ would enhance the IFDI. However, for outward FDI (OFDI)–IQ linkage, the results show a negatively significant impact of IQ on OFDI for Brazil and Russia. Additionally, the authors observe control of corruption as a significant institutional component for attracting inward FDI for Brazil, India and South Africa, whereas it is an insignificant factor for Russia and China. Further, the authors notably find that upgrading the governance indicators will decrease the level of OFDI for Brazil, Russia, China and South Africa. On the contrary, findings suggest that improving the IQ will foster the OFDI for India.

This study uses time-series analysis instead of cross-country analysis (used extensively in literature), avoiding heterogeneity. Further, this study explores the IFDI–IQ link for BRICS nations, which are captivating a significant chunk of IFDI, and still not given much attention in the extant literature. Moreover, the authors identify the impact of IQ on the OFDI, neglected by the existing studies.

The heat transport phenomenon in which energy transfers due to temperature differences is an important topic of interest for scientists in recent times. It is because of its wide range of applications in numerous domains such as electronics, heat dispersion, thermoregulation, cooling mechanism, the managing temperature in automotive mobile engines, climate engineering, magnetoresistance devices, etc. On account of such considerations, the magnetohydrodynamic (MHD) entropy rate for nanomaterial (CoFe₂O₄/C₂H₆O₂) and hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) is analyzed. The Darcy–Forchheimer relation is utilized to describe the impact of a porous medium on a stretched sheet. Two nanoparticles molybdenum (MoS₄) and cobalt ferrite (CoFe₂O₄) are combined to make hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂). Heat flux corresponds to the Cattaneo–Christov model executed through heat transfer analysis. The influence of dissipation and heat absorption/generation on energy expression for nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) and hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) is described.

Nonlinear partial differential expressions have been exchanged into dimensionless ordinary differential expressions using relevant transformations. Newton’s built-in shooting method is employed to achieve the required results.

Concepts of fluid flow, energy transport and entropy optimization are discussed. Computational analysis of local skin friction and Nusselt number against sundry parameters for nanomaterial (CoFe₂O₄/C₂H₆O₂) and hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) is engrossed. Larger magnetic field parameters decay fluid flow and entropy generation, while an opposite behavior is observed for temperature. Variation in magnetic field variables and volume fractions causes the resistive force to boost up. Intensification in entropy generation can be seen for higher porosity parameters, whereas a reverse trend follows for fluid flow. Heat and local Nusselt numbers rise with an increase in thermal relaxation time parameters.

No such work is yet published in the literature.

This study aimed to investigate the impact of leader STARA competence (LSC) – managing and implementing smart technologies, artificial intelligence, robotics and algorithms– on green competitiveness (GC) in the tourism and hospitality sectors. It also investigated the role of employee green creativity (EGC) as a mediator between LSC and GC and the mediating role of green human capital (GHC) in the relationship between EGC and GC.

The study utilized PLS-SEM to analyze 320 responses obtained from middle-level management at five-star hotels and travel agencies in Egypt, using WarpPLS statistical software 7.0.

Leader STARA competence positively affects employee green creativity and green competitiveness. Employee green creativity positively affects green competitiveness and green human capital. Green human capital positively affects green competitiveness. In addition, the study demonstrated significant mediation roles of green human capital in the employee green creativity and green competitiveness relationship and employee green creativity in the leader STARA competence and green competitiveness relationship.

The study offers several practical implications for tourism and hospitality enterprises. It underscores the significance of leader STARA’s competence in advancing green competitiveness.

The study provides new insights into how emerging concepts like leader STARA competence, green human capital and employee green creativity simultaneously predict green competitiveness within tourism and hospitality enterprises. It also contributes significantly to enriching the social exchange theory.