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The success of the organization depends on its sustainability and growth in the competitive market. Retention and attraction of talent in the organization are strongly associated with organizational performance. Employer branding is an outcome activity that helps organizations show their strength to attract and retain talent. Talent management practices are mostly essential in the current context for retaining talent. This study aims to explore and identify the contributing factors in efficient talent management and to examine whether the factors contributing to employer branding differ concerning different demographic profiles of the employees for information technology organizations.

Data were collected from 617 adult participants using an 85-item questionnaire on talent management comprising 25 domains, developed for the present study.

Principal component analysis of the data indicated that 20 different factors make an impact in developing strong talent management practices. Three broad areas were identified, namely, personal benefits and growth, transparent organizational culture and social commitment of the organizations.

Present research has not taken care of few other factors associated with the organization where employees’ retention gets adversely effected such as evaluation of performance and compensation management, training and development, etc. So, future research can be conducted these areas. These aspects are also required to be incorporated in future research.

Several implications of the present research can be presented in the following areas. It is found in the present research that the effectiveness of the talent management system mostly depends on personal benefits and growth, organizational culture and climate and the organizational out. Apart from the academic implications of the present research, practical implications of the present study cannot be ignored. The components and elements of the talent management in the perspectives employer branding can also appropriately applied by the organizations.

The contribution of the study lies in exploring and identifying three important aspects of the organization in talent management. Findings will have implications for different organizations in understanding, developing and implementing policies related to employer branding and talent management.

Our proposed machine learning model contributes to improving the quality of Hire by providing a more nuanced and comprehensive analysis of candidate attributes. Instead of focusing solely on obvious factors, such as qualifications and experience, our model also considers various dimensions of fit, including person-job fit and person-organization fit. By integrating these dimensions of fit into the model, we can better predict a candidate’s potential contribution to the organization, hence enhancing the Quality of Hire.

Within the scope of the investigation, the competencies of the personnel working in the IT department of one in the largest state banks of the country were used. The entire data collection includes information on 1,850 individual employees as well as 13 different characteristics. For analysis, Python’s “keras” and “seaborn” modules were used. The Gower coefficient was used to determine the distance between different records.

The K-NN method resulted in the formation of five clusters, represented as a scatter plot. The axis illustrates the cohesion that exists between things (employees) that are similar to one another and the separateness that exists between things that have their own individual identities. This shows that the clustering process is effective in improving both the degree of similarity within each cluster and the degree of dissimilarity between clusters.

Employee competencies were evaluated within the scope of the investigation. Additionally, other criteria requested from the employee were not included in the application.

This study will be beneficial for academics, professionals, and researchers in their attempts to overcome the ongoing obstacles and challenges related to the securing the proper talent for an organization. In addition to creating a mechanism to use big data in the form of structured and unstructured data from multiple sources and deriving insights using ML algorithms, it contributes to the debates on the quality of hire in an entire organization. This is done in addition to developing a mechanism for using big data in the form of structured and unstructured data from multiple sources.

The determination of human behaviours due to individual characteristics (personality traits) or situational factors has long remained inconclusive. Although the literature stream on personality as the determinants of behaviour is voluminous, the interest of researchers is also growing towards organisational situational cues as the determinant of behaviours. According to situation strength theory (SST), behaviours are determined by situations in strong situations and by personality in weak situations. This study aims to propose a theoretical model of intrapreneurial behaviour (IB) emanation from empowering leadership (EL) by extending the epistemology of SST under the influence of organisational strong situations of job autonomy (JA) and perceived organisational support (POS).

Using SST, the present study argues that strong situations play a key role in determining human behaviours, and the same can be viewed deductively to assess IB.

The study attempts to propose whether EL is capable of predicting IB under the strong situation effect of JA and POS while dampening the impact of human personality characteristics.

The current study offers a significant departure from current human resource practices in person-situation dialectics, moving away from personality assessments and toward the creation of cues from strong situations for fostering human behaviour. As a result, personality researchers are being encouraged to conduct a reality check on the extensive personality research conducted in occupational settings. Considering organisational situational cues can impact human resource scope in areas such as talent management, selection, promotion and employment.

The author aims to develop an employee competency framework for a volatility, uncertainty, complexity and ambiguity (VUCA) environment and propose learning and development (L&D) interventions for organisations and employees to develop competencies for thriving in a VUCA environment.

The framework synthesis method was used to determine employee competencies that are essential in a VUCA world.

The author identified 10 competencies that are essential for employee development in a VUCA world. The author categorised these employee competencies as cognitive (cognitive flexibility, agility mindset and personal ambidexterity), cross-cultural (cross-cultural intelligence and cross-cultural collaboration), analytical (creativity and complex problem solving) and personal effectiveness competencies (personal resilience, continuous learning and adaptive mindset).

The proposed competencies could be used for the personal development of employees and organisations. The VUCA competency framework developed in this study includes behavioural dimensions for each competency, which could be used in self-assessment, recruitment and selection and talent and performance management. Furthermore, the author proposes L&D interventions required for developing these competencies. Overall, this study contributes to human resources (HR) development in the VUCA era by proposing the development of specific individual competencies as necessary conditions for survival and growth.

VUCA competencies empower employees to not only survive but also thrive in an unpredictable and rapidly changing world. By incorporating these competencies in L&D interventions, organisations can help employees develop the necessary competencies to thrive in a VUCA environment, thus contributing to their personal and organisational success.

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.

The importance of mental wellbeing and the need for organizations to address it is increasing in the post-pandemic context. Although Artificial Intelligence (AI) is increasingly being adopted in HRM functions, its adoption and utility for enabling mental wellbeing is limited. Building on the Open System Theory (OST) and adopting the technology-in-practice lens, the authors examined the roles of human and technology agencies in enabling mental wellbeing.

The study was conducted in two stages; in Stage 1, the authors adopted a case methodology approach to examine the feasibility of a technology company's offerings to assess mental wellbeing. In Stage 2, the authors followed the grounded theory approach and interviewed 22 key stakeholders and HR leaders of diverse organizations. The authors used Gioia's approach to analyze the data.

The study demonstrates the interdependence and inseparability of human activity, technological capability and structured context. Specifically, the authors observe that AI adoption is pushing the boundaries of how organizations could support employees' mental health and wellbeing. These technological advancements and adoption are likely to facilitate the evolution of agentic practices, routines and structures.

This study carries two important implications. While the advent of cutting-edge technologies appears to affect employees' mental wellbeing, the study findings indicate the assistive role of technology in supporting mental wellbeing and facilitating changes in organizational practices. Second, the ontology of technology-in-practice shows how human–machine agencies gain newer relevance from the interactions that unite them. Specifically, per OST, technology (from an external context) can potentially change how mental wellbeing practices in organizations are managed. The authors extend the existing literature by suggesting that both human agents and internal contexts effectively limit the potential of technology agents to change existing structures significantly.

The authors address the need for more research on the technology-management interface, and the boundaries of technology-enabled wellbeing at work. While AI-HRM scholarship has primarily relied on micro-level psychological theories to examine impact and outcomes, the authors borrow from the macro-level theories, such as the OST and the technology-in-practice to explain how AI is shifting the boundaries of human and machine agencies for enabling mental wellbeing.

This article empirically tests the impact of risk appetite of the executive team on the re-innovation strategy after technological innovation failure using a panel regression model from the perspective of regional financial development level of enterprises.

By means of time series global principal component analysis and panel regression model method, the study validated and analyzed the impact of risk appetite of the executive team on the re-innovation strategy after enterprise technological innovation failure.

The research found that the higher the risk appetite of executive team, the more inclined the enterprise is to choose the “focusing on quantity, ignoring quality” re-innovation strategy after technological innovation failure. The better the financial development level of the region where the enterprise is located, the better it can effectively reduce the re-innovation strategy of “focusing on quantity, ignoring quality” of the enterprise due to the high risk appetite of the executive team.

The findings of this study are helpful in improving the financial development level of the region where the enterprise is located. It can help the executive team of the enterprise to more objectively choose the innovation strategy after technological innovation failure, and reduce the phenomenon that the executive team of the enterprise only pays attention to the quantity of re-innovation and underestimates the quality of re-innovation after technological innovation failure due to its high risk appetite.

The purposes of this paper are to delve into the “liability of foreignness” among immigrants and to explore factors that may enhance or moderate such liability while obtaining jobs in host countries. We explore the competition for jobs in a host country among foreign-born individuals from various backgrounds and local residents, by examining such factors as their human capital, as well as, for the foreign-born, their duration of residence in the host country.

Applying configurational theorizing, we propose that the presence of specific human capital can help reduce the challenges associated with the “liability of foreignness” for migrants who have shorter durations of stay in the host country, and, to a lesser extent, for female migrants. Our study draws upon extensive career data spanning several decades and involving 249 employees within a Danish multinational enterprise.

We find that specific human capital helps established immigrants in general, although female immigrants are more vulnerable. We furthermore find a strong “gender liability” in the industry even for local females, including returnees in the host countries. Our findings suggest that for immigrants, including returnees, career building requires a mix of right human capital and tenure in the host country, and that career building is especially challenging for female immigrants.

While the concept of “liability of foreignness” – focussing on discrimination faced by immigrants in the labour market – has been brought to the fore, a notable gap exists in empirical research pertaining to studies aiming at disentangling potential means to overcome such liability, as well as in studies seeking to explore this issue from a stance of gendered experience.

This meta-analytical review aims to clarify the relationships between three bundles of human resource management (HRM) practices—competency-enhancing, motivation-enhancing and opportunity-enhancing—and organizational innovation by addressing two questions: (a) Which types of HRM bundles are most strongly related to different forms of innovation (i.e. process and product innovation)? And (b) Which mechanism provides a stronger explanation for the positive effects of HRM bundles on innovation?

Based on data from 103 studies, a meta-analysis was conducted to quantitatively summarize existing HRM–innovation studies at the organizational level.

The results showed that the competency-enhancing bundle was more positively related to product innovation than the motivation-enhancing and opportunity-enhancing bundles. The opportunity-enhancing bundle was most strongly associated with process innovation. The authors further found that knowledge management capability (KMC) and employee motivation mediated the positive relationship between the three HRM bundles and innovation outcomes. In comparing the two mechanisms, this review suggests that KMC better explains both the impact of the competency-enhancing HRM bundle on product innovation and the effect of the opportunity-enhancing bundle on process innovation.

Based on behavioral and knowledge management perspectives, this study takes a sub-bundle approach to providing an integrative review by comparing the direct effects and mediating paths of HRM bundles on product and process innovation.

This paper utilizes generativity to explore the relationship between mentoring support and organizational identification, turnover intention and reciprocated mentoring in protégés.

The paper used a cross-sectional design with surveys administered to 351 working adults in the USA to test the hypotheses on the relationship between mentoring and turnover intention through organizational identification with first-stage moderation of generativity.

Employees who were high in generativity, mentoring support was positively associated with organizational identification and negatively associated with turnover intentions. Generativity was also positively related to reciprocated mentoring through the choice to mentor others, the number of mentees and the mentoring support provided.

The authors' results suggest organizations receive the greatest benefits when providing mentoring support to generative employees.

This study applies generativity to the context of mentoring by exploring the impact of mentoring support on identification with the organization, turnover intentions and willingness to mentor others by comparing the conditional effects of high generativity versus low generativity.