Search results

Talent management research today is increasing as organizational requirements attempt to meet the challenges of effectively managing talent to achieve organizations’ strategic agendas. However, in learning organizations specifically, investigations of talent management practices are limited, with this study exploring the role of talent management practices in employee satisfaction and organizational performance in Pakistan.

The study was conducted in various universities (public and private) in Pakistan using a quantitative approach. Cross-sectional data are collected through a questionnaire, with analysis and conclusions based on completed questionnaires from 403 respondents.

The study’s findings from the analysis by structural equation modeling (SEM) emphasize the positive and significant effects of most talent management practices (i.e. talent identification, talent development, talent culture and talent retention) on employee satisfaction and organizational performance (talent attraction is the exception). Employee satisfaction positively and significantly affects organizational performance and is found to have a mediating effect, bridging the relationships of most talent management practices (talent identification, talent development, talent culture and talent retention) with organizational performance.

The study’s findings support human resource professionals, academics and policymakers in managing talent practices to enhance organizational performance. The findings assist in developing core skills and talent-related competencies to achieve organizational goals and success.

The study fills the research gaps by developing a framework of talent management practices for employee satisfaction and organizational performance in learning organizations, which warrants further consideration.

This study aims to examine the relationship between self-perceived talent status (SPTS) and positive employee outcomes (work engagement and organisational commitment), mediated by organisational justice (distributive and procedural justice). The authors define SPTS as employees’ self-conceptualisation of talent, formed by inferring the organisation’s initiatives regarding training and development opportunities and through informal recognition by others.

The authors measured SPTS using eight items on a five-point scale. Through an internet survey company, the authors initially surveyed 1,207 full-time employees from 300 Japanese companies with ≥ 300 employees. In the second round of the survey, conducted after approximately two weeks, 876 (82.9%) responses were collected from the initial 1,207 respondents, which were used for the final analysis.

SPTS was directly and positively related to work engagement, organisational commitment, distributive justice and procedural justice. In learning organisations, SPTS was positively but indirectly related to work engagement and organisational commitment, mediated by distributive justice. In non-learning organisations, SPTS was positively but indirectly related to work engagement and organisational commitment, mediated by procedural justice.

Given SPTS’s positive impact on employee outcomes, to eliminate the information asymmetry between organisations and talent due to strategic ambiguity, organisations should increase SPTS by helping talents perceive the plethora of development opportunities in the talent pool.

The results demonstrate the utility of SPTS for improving employee outcomes based on strategic talent management (TM) mechanisms including talent rewards, talent development opportunities and promotions. Furthermore, the results demonstrate that distributive justice plays an important role in the build-based TM context of learning organisations.

Cloud computing, a dominant technology, significantly impacts organizations, necessitating talent management strategies for sustained growth. This study aims to explore the impact of cloud adoption on large French organizations through a “learning organization” perspective.

Interviews were conducted with business and IT stakeholders from 35 multinational organizations in France.

Cloud services have a high impact on large organizations, leading to a demand for cloud-related skills, a power shift from IT to business departments and increased shadow IT activities. Effective utilization requires organizational learning and a change management project, transforming organizations into productive and innovative learning organizations.

This paper contributes to cloud computing, organizational learning and talent management literature, offering managers a novel approach to handling cloud services.

The purpose of this review is to evaluate existing learning agility measures and offer recommendations for their use in organizational and scholarly contexts.

This is a general review paper assessing the psychometric qualities of prevalent learning agility measures. Measures were selected based on their predominance and use in the learning agility literature and organizational settings.

Learning agility measurement is an area requiring further research. Multiple conceptualizations of learning agility exist, making the true structure of learning agility unclear. The learning agility measures in the academic literature deviate from learning agility’s traditional conceptualization and require further validation and convergent validity studies. Commercial measures of learning agility exist, but their development procedures are not subjected to peer review and are not widely used in academic research, given the cost associated with their use.

Learning agility is prevalently used in organizational settings and is receiving increased scholarly attention. Various conceptualizations and measurement tools exist, and it is unclear how these theories and measures relate and differ. This paper contributes to practice by providing practical guidelines and limitations for measuring learning agility.

Learning agility was initially conceived as a multidimensional construct comprising people agility, results agility, change agility and mental agility. As the construct has evolved, the dimension structure of the measure has evolved as well. This study addresses a gap in our current understanding of how to conceptualize and measure learning agility.

Global talent shortages, new skill demand and rising numbers of unfilled posts are fuelling an increasingly challenging job market, exacerbated by economic uncertainty and transformational digital change. Seeking creative solutions in response, the authors examine talent management’s (TM) theoretical and conceptual foundations, specifically the identification and selection of talent and TM programme design to explore the challenges and benefits of side-of-desk projects as interventions.

Taking an inductive qualitative approach, questionnaires, focus groups and semi-structured interviews gathered data from three employee groups in a UK digital communications organisation.

The authors reveal inconsistencies in the definition and selection of talent, highlighting programme quality challenges to expose a direct correlation between participant experience and motivation and retention, along with the longer-term challenges of balancing talented human capital, shareholder expectations and sustainable workforce resourcing.

The authors' research extends existing knowledge concerning the effect of organisational culture, context and workforce demands upon TM programmes, providing theoretical and practical implications for leaders and policymakers in designing enrichment activities to motivate, develop and retain talent. The authors make recommendations to inform the future design of TM programmes, revealing new opportunities to develop hidden talent and presenting a realistic and sustainable toolkit for future practice in the form of an organisational logic model.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Cloud computing services provide firms with increased scope to grow and prosper. Successful adoption of cloud demands a focus on organizational learning and talent management to ensure that individuals, groups and units are equipped with relevant skills and capabilities needed to perform effectively in their roles as they evolve in the digital age.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

T Education is a leading educational science and technology enterprise in China with technology-driven, talent intimacy and quality leadership as the core development objectives. Since its inception, it has been committed to creating better learning experience for children. As the predecessor of T-education, X-education was founded in Beijing in 2003. At first, it mainly provided after-school math counseling for school-age children. Over the past 10 years, its business has been expanding, covering almost every aspect of school-age education. This case studies accounting issues and business ethics challenges that firms may face when they transform from a single (traditional education) line of business to a multiple channel business.

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.