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The purpose of this paper is to develop a multistakeholder scale for assessing an excellent human resource (HR) function to demonstrate the extent to which it is focused on creating value from the perspective of its key internal and external stakeholders.

At the first stage, an in-depth literature review was conducted to extract the best practices for an excellent HR function. Then, to test the validation of the developed framework, it was sent to HR academics and practitioners in different countries. The survey responses were analyzed using the methods of the structural equation modeling (SEM) and confirmatory factorial analysis.

This study proposes an excellent HR multistakeholder assessment scale consisting of ten criteria based on the perceptions of internal and external HR stakeholders.

This study suggests a framework for assessing overall HR excellence based on the perceptions of key internal and external HR stakeholders. In addition, it is recommended that future researchers empirically test the developed scale across various industries and firm sizes.

HR managers, by using this framework, could continuously assess their HR excellence and compare their HR excellence with other companies’ HR excellence in the industry and then plan for continuous improvement in different HR areas to improve their stakeholders’ experiences.

This paper identifies the enablers and results of an excellent HR department and designs a multistakeholder feedback scale to better understand key internal and external HR stakeholders’ perceptions.

Despite talent management’s (TM) importance for improving organizations' competitiveness and resilience, the pandemic highlighted the weakness of organizational-level TM strategies. Therefore, the objective of this study is to investigate the moderating impact of HR analytics on the relationship between TM and its individual outcomes (talent motivation and quality of hires) and subsequently, their impact on organizational outcomes (talent retention).

The structural equation modeling (SEM) technique was used to analyze 219 online questionnaires administered to HR managers from European companies.

A positive relationship exists between TM activities and talent motivation as well as the quality of hires. Furthermore, HR analytics positively moderates these relationships. Finally, talent motivation and the quality of hires are positively related to talent retention.

This study offers several contributions to theory, as it analyzes TM from an individual perspective and provides further empirical confirmation of the potential benefits of HR analytics and additional grounding to the contingency theory.

Our results will allow practitioners to better orient their HR investments, with positive effects for their organizations and their employees.

This study demonstrates that HR analytics can help organizations adopt a human-centric approach to TM, thus increasing the chances for talents to fully express their potential.

This study takes a step forward toward considering TM outcomes from an individual perspective, responding to new generations' need to pay more attention to their individualities. HR analytics can be a suitable tool to do so, as it can provide insights and suggestions based on the actual organizational context, making TM a more data-driven process.

The purpose of this study is to highlight and demonstrate how the study of stress and related responses in construction can best be measured and benchmarked effectively.

A range of perceptual and physiological measures are obtained across different time periods and during different activities in a fieldwork setting. Differences in the empirical results are analysed and implications for future studies of stress discussed.

The results of this study strongly support the use of multiple psychometrics and biosensors whenever biometrics are included in the study of stress. Perceptual, physiological and environmental factors are all shown to act in concert to impact stress. Strong conclusions on the potential drivers of stress should then only be considered when consistent results apply across multiple metrics, time periods and activities.

Stress is an incredibly complex condition. This study demonstrates why many current applications of biosensors to study stress in construction are not up to the task and provides empirical evidence on how future studies can be significantly improved.

To the best of the author’s knowledge, this is the first study to focus explicitly on demonstrating the need for multiple research instruments and settings when studying stress or related conditions in construction.

The purpose of this paper is to analyze the incorporation, prioritization and depth of equity, diversity and inclusion (EDI) initiatives in tourism industry restart policies of Canadian provinces and territories. This study investigates how the detailing of EDI in policies determine the priority in emancipating tourism workers from the inequities exacerbated during the pandemic. Such investigation enables a better understanding of the complexities, tendencies and rationale of involving EDI in the tourism industry’s recovery.

The research investigated the presence and prioritization of equity, diversity, and inclusion using systematic text analytics of 38 publicly available restart plans and statements from 52 government and non-government agencies. Using web-based software Voyant Tools to assist in text analytics, a hybrid deductive-inductive coding approach was conducted.

Key outcomes from the analysis revealed scarce to no full and dedicated content on EDI as a holistic initiative necessary for tourism industry relaunch. This lack of EDI content was a result of the greater impetus to prioritize economic generation and limited data due to practical and ideological issues. Results also suggested the tokenizing of EDI in some policies.

Difficulties in data used for research include the lack and availability of restart policies specifically for tourism; most policies were generalized and referred to economic recovery as a whole. Studies of tourism-specific EDI issues were also limited.

The research is revelatory for investigating EDI prioritizations in restart policies even among well-developed and worker-diverse tourism industries such as in Canada, where inequities and injustices to women, Black, Indigenous, gender-diverse, and newcomer tourism workers among others have been withstanding.

This paper investigates the interactional relationships between sustainable human resource management (SHRM) and organizational performance (OP). Sustainable HRM is an approach that links HRM and sustainability. These studies focused on integrating HR with sustainable developments, such as economic and social aspects, in favour of focusing on the environmental aspect. Organizational change is an ongoing process that has to be managed effectively to keep the change in place for a long time.

A framework was offered to estimate the cause-and-effect relation of the SHRM and OP factors. Data is gathered from professionals from various pharmaceutical industries. This study applied two methods, Fuzzy AHP and DEMATEL Type II. These techniques are used to understand the cause-and-effect factors and their interactions.

It was observed from the findings that the factor of SHRM, such as Social Justice (F2), Green Job Design (F5), Green Training (F6) and Implementation of Green Policy (F8), was the most critical for the pharmaceutical sector that effects Financial performance (F13), Customer Satisfaction (F15) and Market performance (F14). Pharmaceutical firms ought to coordinate public health advocacy efforts, engage in healthcare initiatives and provide financial support for environmentally friendly efforts that improve social and economic conditions.

For this sustainability, managers concentrate on creating an environment that is healthy and acceptable, and they work hard to mitigate the impact of natural factors and repair damage done to the environment; it is essential to move towards sustainable development to resolve environmental problems. Improving HR efficiency is among essential HRM responsibilities, as they expand the knowledge base of the workforce, enhance human capital, and eventually create valuable intangible assets and promote and encourage sustainable pharmaceutical products for some years.

This research paper has presented exclusive worth to the SHRM and organizational performance literature as it employs fuzzy FAHP and DEMATEL type 2. There is less research on SHRM in the pharmaceutical sector with these factors. In addition, FAHP and TYPE 2 DEMATEL are used in very few researches on SHRM approaches.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

The purpose of this study was to investigate the relationship between job crafting and work engagement and the potential mediating effect of organizational happiness on this relationship.

A sample of 256 full-time employees from various industries such as automobiles, retail, real estate, petrochemicals, investment, industrial and education, working at top 50 Forbes Middle East companies in UAE, were surveyed to gather data on job crafting, organizational happiness and work engagement. The study used an empirical research design, with data collected through surveys.

The results of this study, obtained through a two-step structural equation modelling approach, indicate that job crafting has a positive and direct influence on both organizational happiness and work engagement. The findings also suggest that the relationship between job crafting and work engagement is partially mediated by organizational happiness.

The findings emphasize the need for human resources (HR) professionals to develop programmes and training workshops focused on cultivating these concepts, particularly as remote and blended working arrangements become more prevalent. In addition, the study highlights the global impact of employee disengagement on financial losses and stresses the importance of revising HR policies in the UAE to mitigate potential risks. Lastly, the study suggests that enhancing happiness and reducing disengagement can be achieved through training managers and employees in task structuring techniques, emphasizing the teachability of job crafting skills through interventions that align tasks with employees’ interests.

To the best of the author's knowledge, this is the first study to theoretically explore and empirically test a proposed model on the relationships between job crafting, organizational happiness and work engagement in the context of the UAE.

Exposure to a public health threat of significant proportions made current models inadequate to explain the failure phenomenon in small businesses. Hence, the need to reimagine the phenomenon. Borrowing from the principles of biology, this study extended theoretical and empirical perspectives on the failure phenomenon by unpacking its constituent elements and the measurement metrics using the regeneration lens.

Based on a cohort tracked over time, the study estimated the survival probabilities of small and medium-scale enterprises (SMEs) with and without regeneration using the Kaplan–Meier method. The study investigated the factors that predict enterprise regenerative capacity using the multivariate Cox proportional hazard ratios.

Rates of interruption in business activity, by month, ranged between 0% and 18% during the follow-up period. True mortality rates hovered between 0% and 4% over the same period. Over three in five SMEs that experienced interruption in business activity without ceasing operations regenerated at some point in time during the follow-up period. The survival probabilities beyond the follow-up period were 0.85 and 0.44 with and without regeneration effects, respectively. Fresh capital injection (+), the introduction of new/improved processes or products/services (+), perceived business outlook (+) and the presence of debt (−) influenced the capacity to regenerate.

The cohort was followed for only six months. There is a need to continue interrogating the failure phenomenon in other contexts over longer periods using the regeneration lens. Bringing on board academia, financial institutions and other SME-related ecosystem players will be strategic.

The approach provides a more nuanced understanding of the life and well-being of enterprises under conditions of disruption. Improving the precision and validity of failure-related statistics enhances their utility in policy and remediation-related discussions.

The results did not show significant differences in SME mortality rates between male and female-owned enterprises. The results provide further evidence that the failure phenomenon is ungendered. As such, financial institutions and the SME ecosystem at large must eliminate perceptual gender biases in the financing and other support to SMEs.

The study used the principles of biology to reimagine the failure phenomenon in small businesses. The approach breathes life into entrepreneurship research and policy.

This study is the maiden attempt to understand the effect of specific human resource practices (HRPs) on employee retention (ER) with the mediation of job satisfaction (JS) and moderation of work experience (WE) and job hopping (JH) in the context of the textile industry.

This study adopted a quantitative methodology and applied quota sampling to gather data from employees (n = 365) of leading textile companies in India. The conceptual model and hypotheses were tested with the help of Partial Least Squares-Structural Equation Modelling (PLS-SEM).

The findings of a path analysis revealed that compensation and performance appraisal (CPA) have the highest impact on JS followed by employee work participation (EWP). On the other hand, EWP had the highest impact on ER followed by grievance handling (GRH). The study revealed that JS significantly mediates between HRPs like CPA and ER. During Multi-group analysis (MGA) it was found that the importance of EWP and health and safety (HAS) was more in employee groups with higher WE, but it was the opposite in the case of CPA. In the case of JH behavior, the study observed that EWP leads to JS in loyal employees. Similarly, JS led to ER, and the effect was more pronounced for loyal employees.

In the context of the Indian textile industry, this work is the first attempt to comprehend how HRPs affect ER. Secondly, it confirmed that JS is not a guaranteed mediator between HRPs and ER, it could act as an insignificant, partial or full mediator. Additionally, this study establishes the moderating effects of WE and JH in the model through multigroup analysis.