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The study investigated the predictive role of supportive leadership and psychological safety for mindful organizing and the subsequent impact of mindful organizing on individual task performance. Mindful organizing, a concept from high-reliability organizations (HROs), can improve performance in various industrial settings. The limited availability of novel predictors for mindful organizing necessitates exploring this concept in the context of adventure tourism.

Through a cross-sectional research approach, 394 respondents were selected from the adventure tourism industry in Malaysia. The proposed causal research model was evaluated through structural equation modeling (SEM), aggregation and bootstrapping.

Psychological safety and supportive leadership significantly impacted mindful organizing. Mindful organizing, in turn, was positively associated with individual task performance. The mediating role of mindful organizing between psychological safety and task performance was statistically significant. However, the mediating role of mindful organizing between supportive leadership and task performance was not statistically significant.

Managers in the adventure tourism industry should consider applying mindful organizing to increase employee productivity and develop collective sensemaking. Also, developing a culture of support among managers and coworkers, emphasizing the team's psychological safety, may boost the morale and productivity of the workforce.

This research has identified and empirically tested new antecedents, psychological safety and leadership for mindful organizing in the adventure tourism context and has addressed a significant research gap (Sutcliffe et al., 2016) by broadening the scope of mindful organizing research to encompass contexts beyond those exclusively considered HROs.

The purpose of this study is to develop a scale for measuring service inclusion for tourists with disabilities in tourism and hospitality services. Transformative service research serves as the basis for the conceptualization and dimensionality.

To develop and purify the items as well as develop dimensions, standard scale development procedures were applied. Two studies were undertaken. In Study 1, the factorial structure of the service inclusion was constructed and confirmed using exploratory and confirmatory factor analysis. In Study 2, the field study was conducted to validate the scale.

The study developed a new scale for measuring service inclusion. The results show that service inclusion is a higher-order construct with four dimensions, namely, enabling opportunity, offering choice, relieving suffering and fostering happiness. Furthermore, service inclusion has a significant effect on tourists’ well-being perception, which results in more favorable behavioral responses. The newly constructed scale is declared as valid and reliable by the study that examined it for nomological validity by examining the relationship between service inclusion and tourists’ perceptions of their well-being.

To the best of the authors’ knowledge, this study is the first to develop measurement scale for service inclusion in the tourism and hospitality industry. The scale is proven as reliable and valid and is well suitable for measuring service inclusion for tourists with physical disabilities. It has potential to use for other relevant service contexts.

The purpose of this study is to examine the role of financial and nonfinancial information in determining individual investor's investment decisions by analyzing the mediating effect of corporate reputation.

The approach of this study is deductive; therefore, the quantitative strategy is used for data collection. Primary data are collected from individual investors actively involved in stock trading at Pakistan Stock Exchange (PSX). Structural equation modeling is used to assess structural relationships.

The key findings of this study posit that financial and nonfinancial information positively influence an individual investor's investment decision. This study also provides empirical evidence confirming the mediating role of corporate reputation. Categorically, the findings indicate that financial and nonfinancial information remain significant to build perceived corporate reputation and influence investor's investment decisions.

he proposed model presents novel insight into the individual investor's investment decision in the context of Pakistan. The findings of this study remain robust for firms listed on the stock exchange and individual investors involved in stock trading. The results of this study are substantial to individual investor's and broker for making informed financial choices. Moreover, the firms listed on the PSX can use the findings to establish improved corporate reputation through reporting detailed financial and nonfinancial information.

Studies based on subjective measures in finance are lacking. This study contributes to the existing literature of behavioral finance by analyzing variations in investor's investment decisions explained by informational factors. The proposed model testifies the mediating role of corporate reputation in guiding investor's investment decisions, which has been overlooked by past studies. Therefore, this study seeks to fill this gap in the context of the PSX.

Ontologies are used to formally describe the concepts within a domain in a machine-understandable way. Matching of heterogeneous ontologies is often essential for many applications like semantic annotation, query answering or ontology integration. Some ontologies may include a large number of entities which make the ontology matching process very complex in terms of the search space and execution time requirements. The purpose of this paper is to present a technique for finding degree of similarity between ontologies that trims down the search space by eliminating the ontology concepts that have less likelihood of being matched.

Algorithms are written for finding key concepts, concept matching and relationship matching. WordNet is used for solving synonym problems during the matching process. The technique is evaluated using the reference alignments between ontologies from ontology alignment evaluation initiative benchmark in terms of degree of similarity, Pearson’s correlation coefficient and IR measures precision, recall and F-measure.

Positive correlation between the degree of similarity and degree of similarity (reference alignment) and computed values of precision, recall and F-measure showed that if only key concepts of ontologies are compared, a time and search space efficient ontology matching system can be developed.

On the basis of the present novel approach for ontology matching, it is concluded that using key concepts for ontology matching gives comparable results in reduced time and space.

This study aims to model the important flow response quantities over a shrinking wedge with the help of response surface methodology (RSM) and an artificial neural network (ANN). An ANN simulation for optimal thermal transport of incompressible viscous fluid under the impact of the magnetic effect (MHD) over a shrinking wedge with sensitivity analysis and optimization with RSM has yet not been investigated. This effort is devoted to filling the gap in existing literature.

A statistical experimental design is a setup with RSM using a central composite design (CCD). This setup involves the combination of values of input parameters such as porosity, shrinking and magnetic effect. The responses of skin friction coefficient and Nusselt number are required against each parameter combination of the experimental design, which is computed by solving the simplified form of the governing equations using bvp4c (a built-in technique in MATLAB). An empirical model for Cf_x and Nu_x using RSM and ANN adopting the Levenberg–Marquardt algorithm based on trained neural networks (LMA-TNN) is attained. The empirical model for skin friction coefficient and Nusselt number using RSM has 99.96% and 99.99% coefficients of determination, respectively.

The values of these matrices show the goodness of fit for these quantities. The authors compared the results obtained from bvp4c, RSM and ANN and found them all to be in good agreement. A sensitivity analysis is performed, which shows that Cf_x as well as Nu_x are most affected by porosity. However, they are least affected by magnetic parameters.

This study aims to simulate ANN and sensitivity analysis for optimal thermal transport of magnetic viscous fluid over shrinking wedge.

This study investigates the flow and heat transfer in a magnetohydrodynamic (MHD) ternary hybrid nanofluid (HNF), considering the effects of viscous dissipation and radiation.

The transport equations are transformed into nondimensional partial differential equations. The local nonsimilarity (LNS) technique is implemented to truncate nonsimilar dimensionless system. The LNS truncated equation can be treated as ordinary differential equations. The numerical results of the equation are accomplished through the implementation of the bvp4c solver, which leverages the fourth-order three-stage Lobatto IIIa formula as a finite difference scheme.

The findings of a comparative investigation carried out under diverse physical limitations demonstrate that ternary HNFs exhibit remarkably elevated thermal efficiency in contrast to conventional nanofluids.

The LNS approach (Mahesh et al., 2023; Khan et al., 20223; Farooq et al., 2023) that we have proposed is not currently being used to clarify the dynamical issue of HNF via porous media. The LNS method, in conjunction with the bvp4c up to its second truncation level, yields numerical solutions to nonlinear-coupled PDEs. Relevant results of the topic at hand, obtained by adjusting the appropriate parameters, are explained and shown visually via tables and diagrams.

The main focus is to provide a non-similar solution for the magnetohydrodynamic (MHD) flow of Casson fluid over a curved stretching surface through the novel technique of the artificial intelligence (AI)-based Lavenberg–Marquardt scheme of an artificial neural network (ANN). The effects of joule heating, viscous dissipation and non-linear thermal radiation are discussed in relation to the thermal behavior of Casson fluid.

The non-linear coupled boundary layer equations are transformed into a non-linear dimensionless Partial Differential Equation (PDE) by using a non-similar transformation. The local non-similar technique is utilized to truncate the non-similar dimensionless system up to 2nd order, which is treated as coupled ordinary differential equations (ODEs). The coupled system of ODEs is solved numerically via bvp4c. The data sets are constructed numerically and then implemented by the ANN.

The results indicate that the non-linear radiation parameter increases the fluid temperature. The Casson parameter reduces the fluid velocity as well as the temperature. The mean squared error (MSE), regression plot, error histogram, error analysis of skin friction, and local Nusselt number are presented. Furthermore, the regression values of skin friction and local Nusselt number are obtained as 0.99993 and 0.99997, respectively. The ANN predicted values of skin friction and the local Nusselt number show stability and convergence with high accuracy.

AI-based ANNs have not been applied to non-similar solutions of curved stretching surfaces with Casson fluid model, with viscous dissipation. Moreover, the authors of this study employed Levenberg–Marquardt supervised learning to investigate the non-similar solution of the MHD Casson fluid model over a curved stretching surface with non-linear thermal radiation and joule heating. The governing boundary layer equations are transformed into a non-linear, dimensionless PDE by using a non-similar transformation. The local non-similar technique is utilized to truncate the non-similar dimensionless system up to 2nd order, which is treated as coupled ODEs. The coupled system of ODEs is solved numerically via bvp4c. The data sets are constructed numerically and then implemented by the ANN.

This paper aims to investigate the role-play of Protean Career Attitude (PCA) and Career Success (CS) in Affective Organizational Commitment (AOC).

A cross-sectional study on 376 employees from 55 hotels in Malaysia were conducted. The co-variance-based structural equation modeling was employed to analyze the data to test the direct and indirect relationships of PCA and CS with AOC.

The findings reveal that self-directed career attitude (SDCA) has a positive direct influence on AOC as well as indirect influence through the mediation of OCS and SCS. However, the value-driven career attitude (VDCA) neither influences AOC nor the OCS.

This is a first paper to body of knowledge in Asian context which identify mediating role of career success (SCA and OCS) to PCA and AOC. The findings of this research are the workplace learning in hospitality management. The authors argue that hotels should not assume spontaneously PCA with diminishing AOC, but rather hotels' attention is required to identify the most important preferences of these butterfly career attitudes such as OCS and SCS. Most importantly the research negates many negative labels of PCA and adds new perception to the contemporary career literature. Higher education institutions, government, and primary, secondary, and post-secondary education departments can play a significant role in developing PCA dispositions like SDCA and VDCA toward career success. Therefore, further study should examine PCA and their relevance to career outcome like job searching and employability of students in Malaysia. The paper is the first, to one's knowledge, to assess organizational commitment with specific measures of PCA. While the results are simple, they refute many stereotypes of the new career and, in that sense, add an important perspective to the career literature.

This study aims to focuse on the flow behavior of a specific nanofluid composed of blood-based iron oxide nanoparticles, combined with motile gyrotactic microorganisms, in a ciliated channel with electroosmosis.

This study applies a powerful mathematical model to examine the combined impacts of bio convection and electrokinetic forces on nanofluid flow. The presence of cilia, which are described as wave-like motions on the channel walls, promotes fluid propulsion, which improves mixing and mass transport. The velocity and dispersion of nanoparticles and microbes are modified by the inclusion of electroosmosis, which is stimulated by an applied electric field. This adds a significant level of complexity.

To ascertain their impact on flow characteristics, important factors such as bio convection Rayleigh number, Grashoff number, Peclet number and Lewis number are varied. The results demonstrate that while the gyrotactic activity of microorganisms contributes to the stability and homogeneity of the nanofluid distribution, electroosmotic forces significantly enhance fluid mixing and nanoparticle dispersion. This thorough study clarifies how to take advantage of electroosmosis and bio convection in ciliated micro channels to optimize nanofluid-based biomedical applications, such as targeted drug administration and improved diagnostic processes.

First paper discussed “Numerical Computation of Cilia Transport of Prandtl Nanofluid (Blood-Fe₃O₄) Enhancing Convective Heat Transfer along Micro Organisms under Electroosmotic effects in Wavy Capillaries”.