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The recent proliferation of social media platforms has witnessed a growth in social commerce by using social media to facilitate interactivity between customers and vendors. While emergent studies on social commerce are growing, their focus tends to be on millennials and cross-age groups. Given the growth of digital natives in shaping the online shopping experience of the future, we deemed an application to Generation Z necessary and overdue.

We draw on the existing literature and develop a framework to understand social commerce dynamics for digital natives. We employ PLS and CB-SEM to test our proposed model.

Our findings demonstrate the importance of social commerce information sharing activities in facilitating social support, a sense of warmth and belongingness, and online trust for Generation Z platform users. We also investigate the roles of online trust and perceived risk on intention to purchase and find support for both relationships. Finally, we discuss the findings in terms of theoretical and managerial contributions and conclude the study with limitations and future research directions.

This research is unique by using social commerce theory to explore Gen Z platform users. The finding will contribute to information system literature by expanding the social commerce research stream.

The main objective of this research is to analyze satisfaction with tourist services linked to the concept of sustainability in the context of a visit to the so-called equestrian show. The equestrian show adds values from the cultures that passed through the city. Specifically, the study focuses on tourist loyalty based on satisfaction with tourist services, satisfaction with the equestrian show and its overall quality. The fieldwork has been conducted in Córdoba, Spain. There are few studies on the relationship between tourist services linked to the concepts of sustainability and loyalty from the perspective of equestrian show management, making this a novel contribution to research.

The methodology used is based on a partial least squares structural equation modeling (PLS-SEM) approach.

To achieve the proposed objective, a structured questionnaire was used, and the results obtained confirm that satisfaction with tourist services linked to the concept of sustainability and the assessment of quality positively influence tourist loyalty. Consequently, they recommend returning to the destination and repeating the visit.

Heritage in Córdoba, Spain, is internationally recognized. Its uniqueness, with four world inscriptions along with the cultures that inhabited it, left a material heritage legacy in the city. Over time, this legacy has made it a magnet for visitors, making it essential to delve into its management and how concepts such as satisfaction with tourist services, combined with sustainability, impact the improvement of the visit.

Intellectual capital (IC) is a paramount resource for competitiveness in the knowledge-based financial sectors of the economy. As financial technology advances, specifically in the banking industry, it is vital to understand the effect of IC on financial performance. This study aims to investigate the effect of IC on return on equity (ROE), with a unique emphasis on the moderating role of board attributes. Previous studies have overlooked this moderating role.

The study sample consists of 17 banks and a panel data set spanning 2016–2021, extracted from annual reports. Antel Pulic’s value-added intellectual coefficient (VAIC) model is used to compute IC. To analyze the data, a generalized least squares analysis is conducted. The robustness of the analysis is ensured by using the two-stage least squares (2SLS) econometric technique.

The findings indicate that both the VAIC and human capital efficiency (HCE) have a significant impact on the ROE of banks. In terms of moderation, it is observed that board size (BS) exerts a negative effect on the association between VAIC, HCE, structural capital efficiency and ROE. Additionally, BS positively compounds the connection between capital employed efficiency and ROE. Similarly, the presence of independent directors (IND) significantly moderates the effects of VAIC and its components on the ROE of banks in Pakistan.

Banks should focus on the HCE for a higher ROE. Moreover, banks ought to prioritize appointing more independent directors in the boardroom for effective utilization of IC and greater ROE.

The findings of the study, which analyzed data from Pakistan’s banking sector, are original and provide additional insights into the literature on IC and board attributes.

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.

This study aims to examine the direct effects of Green Human Resource Management (GHRM) practices on employee green behavior (EGB) in the university setting in Bangladesh and to find the indirect effects of how GHRM promotes EGB through sequentially mediating employee environmental knowledge management (EEKM) (environmental knowledge and knowledge sharing) and green self-efficacy (GSE).

For the empirical study, the researcher uses partial least squares structural equation modeling to test the proposed conceptual model built on existing literature for greening workplaces in the university in Bangladesh. The study has collected data from 288 Bangladeshi university employees using convenient sampling.

The findings that GHRM practices positively and significantly promote EGB, which captures the employee's tendencies to exercise green behavior in daily routine activities such as turning off lights, air conditioning, computers and equipment after working hours, printing on both sides, recycling (reducing, repair, reuse), disseminating good green ideas, concepts, digital skills and knowledge to peers and champion green initiatives at work. Moreover, the findings also revealed the sequential mediation of EEKM (environmental knowledge and knowledge sharing) and GSE of employees between the link GHRM and EGB. At last, the findings suggested that HR managers can implement the GHRM practices to promote green behaviors among the academic and non-academic staff of the university.

This study contributes to the field by extending knowledge of Social Cognition Theory and Social Learning Theory for greening workplaces in Bangladesh, particularly universities. Specifically, this empirical study is unique to the best of our knowledge and highlights the role of EEKM and GSE as mediation between GHRM and EGB association.

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.

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 focus on analysing the impact of green human resource management (GHRM) on the green performance (GP) of Spanish wineries, as well as the mediating effect of employee well-being (EW) on this linkage. In addition, age, size and membership in a protected designation of origin are introduced as control variables to increase the precision of the cause-effect relationships examined.

The study proposes a conceptual model based on previous studies, which is tested using structural equations partial least squares structural equation modelling with data collected from 196 Spanish wineries between September 2022 and January 2023.

The findings of the research reveal the existence of a positive and significant relationship between the GHRM development and the GP of Spanish wineries, as well as the partial mediation of EW in this association.

The uniqueness and significance of this study can be attributed to several crucial factors. First, it enhances the understanding and knowledge regarding the advantages associated with GHRM development. Second, no prior research has conducted a comprehensive study on GHRM as a catalyst for GP within the context of Spanish wineries. Third, to the best of the authors’ knowledge, no previous study has analyzed the mediating role of EW as a mediator in the relationship between GHRM and GP of wineries.

The purpose of this research is to systematically scrutinize the influence of macroeconomic determinants on trade openness, through the lens of various trade theories, with a particular focus on the economies of the GIPSI countries – Greece, Ireland, Portugal, Spain and Italy.

This study investigates the macroeconomic factors influencing trade openness in the GIPSI economies from 1995 to 2020. Methods include stepwise regression (SR) for model selection, Pedroni panel cointegration test and panel regression results. The analysis uses advanced panel regressions, including FMOLS, Panel OLS and FEM. The long-term dynamics were tested using Pedroni cointegration, while Granger causality testing was used to examine the causal direction between the trade openness ratio and trade determinant.

The results show both long-term and short-term relationships between trade openness and (1) foreign direct investment, (2) labor force participation rate, (3) trade reserves and (4) trade balance. The researchers also detected unidirectional and bidirectional causality relationships between trade openness and these four factors. The study also revealed that trade reserves (TR) emerge as the most influential determinant of trade openness, and per capita income does not exhibit economic significance concerning the trade openness of GIPSI economies.

This research is conducted within the context of the GIPSI nations (Greece, Ireland, Portugal, Spain and Italy). As such, the outcomes may not be universally applicable to other economic systems due to the distinct institutional settings and governance structures across different economic groups. Future investigations may explore the relationship between trade openness and its determinants by incorporating different variables.

To the best of the authors' knowledge, this is the first study investigating the theory that suggested trade drivers drive the trade openness of GIPSI countries context. By focusing on GIPSI countries, the study offers a unique perspective on the dynamics of trade openness in economies that have experienced financial crises and stringent austerity measures.

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.