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Research in the field of intrapreneurial behaviour (IB) is developing in terms of the personality results of employees in various occupations. An important developing field is the study of how personality traits (PTs) influence occupational results. While previous theories like situationism focus on the impact of situations, the role of situations as a catalyst for personality in the context of IB has not been explored. Theories like person-job fit have also established the personality-job resemblance for performance measures. This paper aims to conceptualize the activation of PTs for IB responses from employees using trait activation theory (TAT).

The TAT explains the personality-triggering effect in diverse situations for performance measures. Plenty of research studies have established IB of employees as a performance measure at the individual level that further rejuvenates organisational performance measures. The current study aims to conceptualise how personality and situational factors interact to affect IB outcomes in firms using the TAT. Employees in different occupations utilise personality coherent conflict handling styles (CHS) to manage conflict situations, which might serve as situational cues to activate personality effects in employees engaged in IB.

A theoretical framework for understanding how situational cues activate PTs for IB development has been proposed in this study.

The findings of the study have repercussions for pedagogy and the practices that are currently used in human resource management.

The study concludes with a series of propositions by arguing and supporting literature on existing conceptions of the trait activation process. Attempting to advance the conceptualisation of TAT, the study also offered implications for theory, pedagogy and practice regarding the relationship between PTs, CHS and IB.

The purpose of this paper is to investigate the mediating role of satisfaction (SAT) in relation to mobile banking service quality (MB-SQ) and continuance intention (CI) among Nepali mobile banking users.

The paper adopted a quantitative approach and cross-sectional survey research design. Data were collected with structured questionnaires from 326 mobile banking users. A partial least squares structural equation modeling (PLS-SEM) and artificial neuro network (ANN) approach were applied to examine hypotheses.

Results confirm a significant positive influence of MB-SQ on SAT and CI of mobile banking adoption. Moreover, MB-SQ partially mediates the relationship between SAT and CI of mobile banking adoption.

Based on the findings of this research, theoretically, this paper attempted to investigate the mediating role of MB-SQ in the CI of mobile banking, and managerially, mobile banking service providers could have insights on designing mobile banking service marketing strategy.

This paper is among the earliest studies to investigate the role of MB-SQ as a higher-order reflective-reflective construct on CI. Moreover, the endogeneity issue has been tested, and ANN has been applied to investigate the predictive relevance of SAT and MB-SQ on CI of mobile banking users. Furthermore, the authors have delved into the ongoing discourse surrounding Generation Y and Generation Z, exploring their implications on CI within the realm of mobile service quality. It provides a critical juncture for understanding continuance intention in the mobile service quality context.

This research investigates the impact of Industry 4.0 technologies (I4.0) on the resilience of manufacturing firms against the COVID-19 pandemic. The study explores the mediating effects linked to the firm’s supply chain resilience and absorptive capacity in this relationship.

The empirical analysis involves 304 manufacturing firms and uses Partial Least Squares Structural Equation Modeling (PLS-SEM). A two-step hierarchical component model has been employed, considering the statistical analysis validation (reliability and validity) of the LOC and HOC models. The choice of the manufacturing industry is justified due to its degree of automation in emerging economies, such as Mexico, and its significant impact on job creation and the national gross domestic product.

The results confirm the positive impact of I4.0 technologies on companies’ resilience to COVID-19. They also support the indirect effects of the firm’s supply chain resilience and absorptive capacity. Absorptive capacity was found to have a higher significant indirect effect than supply chain resilience. Consequently, the study accentuates the significance of leveraging external knowledge and highlights the role of acquisition, assimilation, transformation, and exploitation capabilities in enhancing absorptive capacity.

The implications of this research extend to both manufacturing companies and public administrations, suggesting the need for I4.0 technologies implementation and supportive policies aimed at fostering absorptive capacity.

This research contributes to the literature by filling gaps in empirical studies in the context of developing economies. It provides valuable insights into the effects of I4.0 on absorptive capacity, supply chain resilience, and COVID-19 resilience, particularly in non-essential supply chains. It enriches the understanding of how I4.0 impacts the absorptive capacity and resilience of the supply chain during the COVID-19 crisis.

Although virtual worlds, such as the Metaverse, can disrupt the hospitality sector, few empirical investigations have critically evaluated the scope and scale of this disruption from an industry perspective. This study aims to rectify this knowledge gap by exploring the opportunities and challenges of the Metaverse as seen by hospitality professionals.

This is a Delphi study conducted with UK-based senior hospitality industry practitioners experienced in designing and implementing digital innovations within their organisations.

The Metaverse is most likely to be adopted by hospitality organisations willing and able to take risks, such as large and/or chain-affiliated enterprises. The Metaverse will not replace traditional hospitality services but supplement and enhance them with new layers of service. The main applications are in the context of events and experiences. The Metaverse will also provide the “try before you buy” option, revealing the opportunities to design digital twins of physical businesses. Young and technology-savvy individuals are most likely to first adopt the Metaverse. The key challenges of the adoption are attributed to the technological unpreparedness of hospitality organisations; market immaturity; inflated customer expectations; a skills gap among hospitality employees; and regulatory issues. These challenges require the engagement of various stakeholders to create an operational and monitoring framework for hospitality organisations to embrace the Metaverse.

This study highlights how the Metaverse can disrupt the hospitality industry at the level of strategic planning and business operations.

To the best of the authors’ knowledge, this is one of the first empirical investigations of the potential of the Metaverse from the viewpoint of hospitality industry practitioners.

In the evolving digital work landscape, where cyberloafing has become a notable challenge, this study aims to investigate the mechanisms through which organizations can effectively reduce such behaviors. Specifically, the research explores the role of employee adaptability in mitigating cyberloafing, taking into account the influences of temporal leadership, teamwork attitudes, and competitive work environments.

Utilizing the broaden-and-build theory and the job demands-resources (JD-R) model, we analyzed data from 245 employees through structural equation modeling (SEM) to investigate how various factors influence cyberloafing.

The results indicate that employee adaptability significantly mitigates cyberloafing and serves as a mediating factor between temporal leadership, teamwork attitudes, and the impact of competitive work environments on cyberloafing. Temporal leadership and teamwork attitudes positively correlate with increased adaptability, thereby reducing cyberloafing. Conversely, competitive work environments, while slightly enhancing adaptability, substantially increase cyberloafing.

The study contributes new insights into the dynamics of cyberloafing, emphasizing the critical roles of adaptability, teamwork attitudes, and temporal leadership in reducing such behaviors. It underscores the need for organizations to foster a supportive culture that minimizes competitive pressures and promotes teamwork and leadership strategies conducive to high productivity and minimal cyberloafing. This research offers practical implications for designing workplace strategies aimed at boosting productivity and curbing undesirable online behaviors during work hours.

The present study examines the incremental validity of engaging leadership in predicting five fundamental organizational outcomes (followers’ organizational commitment, work engagement, task performance, organizational citizenship behaviour and counterproductive work behaviour) over transformational leadership.

The study is cross-sectional in nature and a survey questionnaire was used for data collection. Data were collected from 402 workers in different fields. Hierarchical multiple regression was used in order to determine the incremental validity of engaging leadership.

Our results indicated that engaging leadership contributes additional variance over and above transformational leadership in predicting the five organizational outcomes.

The results of the study suggest that combining engaging leadership interventions with transformational leadership interventions may lead to better results.

The present study supports the empirical distinction of engaging leadership from transformational leadership, addressing possible concerns regarding construct redundancy.

Wall-modeled large eddy simulation (LES) is a practical tool for solving wall-bounded flows with less computational cost by avoiding the explicit resolution of the near-wall region. However, its use is limited in flows that have high non-equilibrium effects like separation or transition. This study aims to present a novel methodology of using high-fidelity data and machine learning (ML) techniques to capture these non-equilibrium effects.

A precursor to this methodology has already been tested in Radhakrishnan et al. (2021) for equilibrium flows using LES of channel flow data. In the current methodology, the high-fidelity data chosen for training includes direct numerical simulation of a double diffuser that has strong non-equilibrium flow regions, and LES of a channel flow. The ultimate purpose of the model is to distinguish between equilibrium and non-equilibrium regions, and to provide the appropriate wall shear stress. The ML system used for this study is gradient-boosted regression trees.

The authors show that the model can be trained to make accurate predictions for both equilibrium and non-equilibrium boundary layers. In example, the authors find that the model is very effective for corner flows and flows that involve relaminarization, while performing rather ineffectively at recirculation regions.

Data from relaminarization regions help the model to better understand such phenomenon and to provide an appropriate boundary condition based on that. This motivates the authors to continue the research in this direction by adding more non-equilibrium phenomena to the training data to capture recirculation as well.

This paper aims to reflect on the outcomes of a community-based video-conferencing intervention for depression, predating the COVID-19 pandemic. The study investigates the potential implications of its findings for enhancing adherence to digital mental health interventions. The primary objective is to present considerations for researchers aimed at minimising the intention-behaviour gap frequently encountered in digital mental health interventions.

A randomised control feasibility trial design was used to implement a telehealth model adapted from an established face-to-face community-based intervention for individuals clinically diagnosed with depression. In total, 60 participants were initially recruited in association with a local mental health charity offering traditional talking-based therapies with only eight opting to continue through all phases of the project. Modifications aligning with technological advancements were introduced.

However, the study faced challenges, with low uptake observed after an initial surge in recruitment interest. The behaviour-intention gap highlighted technology as a barrier to service accessibility, exacerbated by participant age. Furthermore, the clinical diagnosis of depression, characterised by low mood and reduced interest in activities, emerged as a potential influencing factor.

The limitations of the research include its pre-pandemic execution, during a nascent stage of technological mental health interventions when participants were less familiar with online developments.

Despite these limitations, this study's reflections offer valuable insights for researchers aiming to design and implement telehealth services. Addressing the intention-behaviour gap necessitates a nuanced understanding of participant demographics, diagnosis and technological familiarity.

The study's relevance extends to post-pandemic society, urging researchers to reassess assumptions about technology availability to ensure engagement. This paper contributes to the mental health research landscape by raising awareness of critical considerations in the design and implementation of digital mental health interventions.

Reflections from a pre-pandemic intervention in line with the developments of a post-pandemic society will allow for research to consider that because the technology is available does not necessarily result in engagement.

The present study enriches the person-situation debate by developing and testing a theoretical model on the nexus between empowering leadership (EL) and intrapreneurial behaviour (IB) in the presence of a strong organisational situation of perceived organisational support (POS).

Cross-sectional survey data collected from 237 engineers working for Pakistani automakers were used to evaluate the suggested theoretical framework. The survey results were analysed using the partial least square structural equation modelling (PLS-SEM) method.

The results from the analysed data revealed a significant and positive relationship between EL and IB. POS significantly moderate the relationship between EL and IB as per the conceptualisation of situation strength theory (SST) and is established as a strong organisational situation that generates situational cues for IB outcomes from employees.

The present study provides new insights into determining employees' workplace behaviour as viewed from the organisational situations. Hence, top management in organisations can create a conducive environment by improving employees' POS for valued work behaviours like IB.

Currently, massive multiple-input multiple-output (m-MIMO) antennas are typically designed using complex trial-and-error methods. The purpose of this study is to determine an effective optimization method to achieve more efficient antenna design processes.

This paper presents the design stages of a m-MIMO antenna array compatible with 5G smartphones operating in long term evolution (LTE) bands 42, 43 and 46, based on a specific algorithm. Each antenna element in the designed 10-port m-MIMO antenna array is intended to perfectly cover the three specified LTE bands. The optimization methods used for this purpose include the Nelder–Mead simplex algorithm, covariance matrix adaptation evolution strategy, particle swarm optimization and trust region framework (TRF).

Among the primary optimization algorithms, the TRF algorithm met the defined objectives most effectively. The achieved antenna efficiency values exceeded 60.81% in the low band and 68.39% in the high band, along with perfect coverage of the desired bands, demonstrating the success of the design with the TRF algorithm. In addition, the potential electromagnetic field exposure caused by the designed m-MIMO antenna array is elaborated upon in detail using computational human models through specific absorption rate analysis.

The comparison of four different algorithms (two local and two global) for use in the design of a 10-element m-MIMO antenna array with a complex structural configuration and the success of the design implemented with the selected algorithm distinguish this study from others.