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Although the need for cultural competence in clinical care has been well articulated for over four decades, the goal of integrating and addressing cultural issues in care remains elusive. The challenges can be attributed to a lack of clarity on definitions and a lack of understanding of what constitutes cultural competence. What to know and what to do are questions that are frequently raised in discussions of cultural competence. Previous literature has described cultural competence in terms of affective, behavioural, and cognitive domains. The purpose of this paper is to build on this discourse by discussing key attributes within each domain and extending the framework to highlight the dynamics of difference, clarify the goal of equity, and recognise the importance of practice environments in the development of cultural competence in clinical care.

This paper aims to organize the existing empirical research on women entrepreneurs (WEs) in India, highlight the research areas that have not received attention and present opportunities for future research.

A systematic literature review (SLR) was performed on 74 scholarly articles focusing on WEs in India and published between 1993 and 2020. This review is structured around the 4W framework used in previous SLRs. The review is directed by the following foci: what do we know about academic research on WEs in India? How were these studies conducted? Where were these studies conducted? Why should academicians and practitioners consider WE research?

The authors arrived at four main themes underlying the empirical research on WEs: success factors for WEs, challenges faced by WEs, factors that attract and motivate WEs and performance measures for WEs. While challenges and success factors have received attention from researchers, there is a distinct lack of papers on factors that attract or motivate WE and performance measures. The main gaps identified were a lack of theoretical basis in studies, reliance on interview and survey-based methodology and a lack of context-specific studies.

The findings of this review are limited to WEs operating in India. Only Scopus-indexed journals listed in the Australian Business Dean's Council Journal Quality List (ABDC JQL) were included in the final SLR list.

This is one of the first studies to use a systematic approach to provide a detailed account of the state of the literature on women's entrepreneurship research in India.

With the advancements in photo editing software, it is possible to generate fake images, degrading the trust in digital images. Forged images, which appear like authentic images, can be created without leaving any visual clues about the alteration in the image. Image forensic field has introduced several forgery detection techniques, which effectively distinguish fake images from the original ones, to restore the trust in digital images. Among several forgery images, spliced images involving human faces are more unsafe. Hence, there is a need for a forgery detection approach to detect the spliced images.

This paper proposes a Taylor-rider optimization algorithm-based deep convolutional neural network (Taylor-ROA-based DeepCNN) for detecting spliced images. Initially, the human faces in the spliced images are detected using the Viola–Jones algorithm, from which the 3-dimensional (3D) shape of the face is established using landmark-based 3D morphable model (L3DMM), which estimates the light coefficients. Then, the distance measures, such as Bhattacharya, Seuclidean, Euclidean, Hamming, Chebyshev and correlation coefficients are determined from the light coefficients of the faces. These form the feature vector to the proposed Taylor-ROA-based DeepCNN, which determines the spliced images.

Experimental analysis using DSO-1, DSI-1, real dataset and hybrid dataset reveal that the proposed approach acquired the maximal accuracy, true positive rate (TPR) and true negative rate (TNR) of 99%, 98.88% and 96.03%, respectively, for DSO-1 dataset. The proposed method reached the performance improvement of 24.49%, 8.92%, 6.72%, 4.17%, 0.25%, 0.13%, 0.06%, and 0.06% in comparison to the existing methods, such as Kee and Farid's, shape from shading (SFS), random guess, Bo Peng et al., neural network, FOA-SVNN, CNN-based MBK, and Manoj Kumar et al., respectively, in terms of accuracy.

The Taylor-ROA is developed by integrating the Taylor series in rider optimization algorithm (ROA) for optimally tuning the DeepCNN.

This paper aims to investigate the impact of risk culture on employee performance by exploring the mediating roles of employee satisfaction and employee engagement in the relationship between risk culture and employee performance.

The study employed partial least squares-based structural equation modeling (PLS-SEM) to assess both the direct effects and mediation effects, using a sample of 311 employees from the banking and insurance sectors. In contrast to PLS-SEM, a fuzzy set qualitative comparative analysis (fsQCA) technique was also applied to discern the causal configurations that lead to improved employee performance.

The findings revealed a significant direct effect of risk culture on employee performance, employee satisfaction and employee engagement. The findings also revealed that employee satisfaction significantly mediated the relationship between risk culture and employee performance, whereas the mediating role of employee engagement is partially significant. The fsQCA findings illustrated that a diverse combination of risk culture dimensions, employee satisfaction and employee engagement can result in enhanced employee performance.

This study provides important implications for the banking and insurance industries, suggesting that organizations should prioritize the development of a strong risk culture to improve employee-related outcomes such as performance, satisfaction and engagement, which are key factors for achieving optimal organizational success.

The paper specifically highlights the importance of integrating risk culture into human resource management, providing valuable insights for organizations seeking to enhance their risk management practices and culture.

Elucidating on the concrete outline of conservation of resource theory, this study aims to explore the links between work-family conflict and workplace thriving. In particular, this study has integrated depersonalization as a mediator and tested the moderated mediation effects of intrinsic motivation in work-family conflict and depersonalization relationships.

Data were collected using a sample of 357 doctors working across various public hospitals in India over two waves (T1 and T2) and was tested using AMOS and Process Macros.

Exploration reveals that work-family conflict is negatively associated with workplace thriving. The mediating role of depersonalization in between work-family conflict and workplace thriving was established. Moreover, the moderating role of intrinsic motivation in work-family conflict and workplace thriving via depersonalization was also established.

The present study makes a theoretical addition to the literature by investigating nuances through which work-family conflict relationships and thriving at the workplace can be affected. To date, such a relationship has not been established. The study also extends the role of depersonalization as an underlying mechanism between work-family conflict and workplace thriving, making an imperative contribution. This study also tested the moderating role of intrinsic motivation. Overall, these relationships are novel and have been seldom reported.

This paper aims to examine the state of research on the symbiotic relationship between knowledge management and learning management systems in advancing the mutual strategic agenda of the two initiatives in higher education institutions (HEIs), so as to uncover the themes that have been studied, identify gaps in the existing studies and suggest future areas of research work.

The study adopted systematic literature review (SLR), in which 64 articles published between 2010 and 2022 were identified and analyzed.

Whereas the review revealed some focus areas that have been researched, it also found that only few studies have explicitly explored the symbiotic relationship between knowledge management and learning management systems, with fewer articles exploring this relationship finding their way to mainstream journals. Thus, the findings showed that examination of the interlink between knowledge management and learning management systems in HEIs is still less explored and has multiple possibilities for future research with potential benefits to the higher education industry.

Although different SLRs exist separately in the fields of knowledge management and learning management systems, there seem to be no reviews on the interconnection between the two fields in the context of HEIs. Additionally, this review offers insights into future research avenues for theory, content and context of interplay between knowledge management and learning management systems in HEIs.

Global climate can be defined as the average of all the regional trends of weather over a long time period (National Science Foundation [NSF], 2009). The researchers all over the world have concluded that the Earth's climate is changing as a whole. There are basically two factors that have impacts on the climate, the natural (climatic and environmental variability) and the anthropogenic (infrastructure development and land use land cover change). The causes of past changes are believed to be related to changes in ocean currents, solar activity, volcanic eruptions, and other natural factors (ISDR, 2008). But in recent times, human activities have accelerated this rate of climate change (IPCC, 2007; Sperling & Szekely, 2005; ISDR, 2008). As the developmental activities increase, the amount of emission of greenhouse gasses and aerosols increases, which, in turn, leads to global warming and snow melting, thus increasing the sea level and the frequency and intensity of cyclones, floods, droughts, and many other disasters (IPCC, 2001).

This study explores how strategic human resource practices enhance the competitive capability of differentiation and cost-effectiveness by leveraging knowledge resources in Indian IT/software organizations. It examines the mediating effect of knowledge management (KM) processes in the relationship between strategic HR practices, competitive differentiation and cost-effectiveness capabilities.

An online questionnaire survey collected data from 380 knowledge workers in 25 IT/software and consultancy firms. The authors checked data reliability and validity by conducting exploratory factor analysis in SPSS and confirmatory factor analysis in AMOS. The authors evaluated hypotheses using path analysis in structural equational modeling in AMOS.

Strategic HR practices significantly and positively affect KM processes and competitive capabilities-differentiation and cost-efficiency. Both strategic HR practices and KM processes have a closer association with differentiation than cost-effectiveness. Knowledge management processes significantly and positively mediate between strategic HR practices and competitive capabilities. The mediation is more substantial in predicting differentiation than cost-effectiveness.

It is a cross-sectional study with a constrained capacity to predict accurate causal inferences; The authors call for future studies with longitudinal design and objective measures. Further studies are required to explore the impact of various strategic HR configurations on KMP to understand how different routes stimulate a particular competitive strategy. This conceptual framework can be validated across different industry types and sizes.

This study provides practical insights to HR and knowledge managers regarding devising HR and KM processes to accomplish the goals of differentiation and cost-effective, competitive strategies. This study highlights that leveraging human capital for effective KM is crucial for gaining a competitive advantage.

The paper adds to the strategic HR and KM literature by exploring the mediating role of KM processes in enabling strategic HR processes to enhance differentiation and cost-effective, competitive strategies. It provides original empirical evidence from knowledge-intensive IT/software consultancies, particularly in India's emerging economy. It indicates the current state of HR practices adopted for optimum utilization of knowledge resources and the importance of differentiation strategy for Indian knowledge-intensive IT/software firms.

This paper develops a decision-analysis model to prioritize and select the site to establish a new hospital over different indicators such as cost, market conditions, environmental factors, government factors, locations and demographics. In this way, an integrated model is proposed under the intuitionistic fuzzy information (IFI), the standard deviation (SD), the rank-sum (RS) and the measurement of alternatives and ranking using the compromise solution (MARCOS) approach for ranking hospital sites (HSs).

The IF-SD-RS model is presented to obtain the combined weight with the objective and subjective weights of diverse sub-criteria and indicators for ranking sites to establish the hospital. The IF-MARCOS model is discussed to prioritize the various sites to establish the hospital over several crucial indicators and sub-criteria.

The authors implement the developed model on a case study of HSs assessment for the construction of new hospital. In this regard, inclusive set of 6 key indicators and 18 sub-criteria are considered for the evaluation of HSs. This study distinguished that HS (h₂) with combined utility function 0.737 achieves highest rank compared to the other three sites for the given information. Sensitivity analysis is discussed with different parameter values of sub-criteria to examine how changes in weight parameter ratings of the sub-criteria affect the prioritization of the options. Finally, comparative discussion is made with the diverse extant models to show the reasonability of the developed method.

This study aims to develop an original hybrid weighting tool called the IF-SD-RS model with the integration of IF-SD and IF-RS approaches to find the indicators' weights for prioritizing HSs. The developed integrated weighting model provides objective weight by IF-SD and subjective weight with the IF-RS model. The model presented in the paper deals with a consistent multi-attribute decision analysis (MADA) concerning the relations between indicators and sub-criteria for choosing the appropriate options using the developed IF-SD-RS-MARCOS model.