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This study explored partnerships between community colleges and businesses, focusing on the role of these partnerships in workforce development to address skill gaps in various sectors. It addressed the questions \"Why do industry practitioners choose community colleges for talent development solutions?\" and \"How do businesses perceive community colleges in their staffing and talent pipeline development efforts?\" Utilizing an exploratory case study approach, the research gathered insights into talent challenges in various sectors from 12 senior private sector executives who had at least 10 years of experience. Data were collected through interviews, questionnaires, and artifacts, such as strategy documents and memoranda, and thematic analysis techniques were used to code and categorize themes. The findings identified six themes in robust community college-industry partnerships, and the study examined the development of staffing strategies for industry-facing roles at community colleges to ensure those strategies are aligned with industry expectations.

PurposeThe aim of this paper is to identify and analyse workforce development challenges in the digital age by first, presenting these challenges and relationship between them, and then proposing a structural model that categorizes these challenges and proposes suggestions for managers to improve human resources practices and firm performance.Design/methodology/approachFuzzy total interpretive structural modelling (TISM) is used as the methodology, which gives an interpretive structural model by presenting direct and transitive relationship between workforce development challenges and categorizes them under autonomous, dependent, independent and linkage groups.FindingsIn total, 13 different workforce development challenges are presented in this study. Results showed that lack of IT/digital skills has a critical role in workforce development in terms of affecting other challenges. Dependent group includes requirements for longer learning time and specialized training, lack of analytical thinking and dealing with complexity, and lack of interdisciplinary thinking and acting. On the other hand, lack of ability in decentralized decision-making and shortage of workforce with adequate skillset within the labour market have more macro-impacts on others. Most of the challenges located in the linkage group, which means that most of the challenges are interrelated with each other.Originality/valueOriginality of this paper is presenting a systematic structure for workforce development in Industry 4.0 that considers challenges systematically.

The advancement of data technology such as machine learning and artificial intelligence has broadened the scope of human resources (HR) analytics, commonly referred to as \"people analytics.\" This field has seen significant growth in recent years as organizations increasingly rely on algorithm-based predictive tools for HR-related decision making. However, its application in the public sector is not yet fully understood. This study examined the concepts and practices of HR analytics through a thematic review, and proposed a five-step process (define, collect, analyze, share, and reflect) for implementation in the public sector-the process aims to assist with the integration of HR analytics in public personnel management practices. By analyzing cases in both the public and private sectors, this study identified key lessons for functional areas such as workforce planning, recruitment, HR development, and performance management. This research also identified the necessary conditions for introducing HR analytics in public organizations, including data management, staff capabilities, and acceptance, and discussed the potential challenges of privacy, integrity, algorithmic bias, and publicness.

PurposeThe era of work 4.0 demands organizations to expedite their digital transformation to sustain their competitive advantage in the market. This paper aims to help the human resource (HR) department digitize and automate their analytical processes based on a big-data-analytics framework.Design/methodology/approachThe methodology applied in this paper is based on a case study and experimental analysis. The research was conducted in a specific industry and focused on solving talent analysis problems.FindingsThis research conducts digital talent analysis using data mining tools with big data. The talent analysis based on the proposed framework for developing and transforming the HR department is readily implementable. The results obtained from this talent analysis using the big-data-analytics framework offer many opportunities in growing and advancing a company's talents that are not yet realized.Practical implicationsBig data allows HR to perform analysis and predictions, making more intelligent and accurate decisions. The application of big data analytics in an HR department has a significant impact on talent management.Originality/valueThis research contributes to the literature by proposing a formal big-data-analytics framework for HR and demonstrating its applicability with real-world case analysis. The findings help organizations develop a talent analytics function to solve future leaders' business challenges.

Purpose The purpose of this paper is to offer a critical analysis of talent acquisition software and its potential for fostering equity in the hiring process for underrepresented IT professionals. The under-representation of women, African-American and Latinx professionals in the IT workforce is a longstanding issue that contributes to and is impacted by algorithmic bias. Design/methodology/approach Sources of algorithmic bias in talent acquisition software are presented. Feminist design thinking is presented as a theoretical lens for mitigating algorithmic bias. Findings Data are just one tool for recruiters to use; human expertise is still necessary. Even well-intentioned algorithms are not neutral and should be audited for morally and legally unacceptable decisions. Feminist design thinking provides a theoretical framework for considering equity in the hiring decisions made by talent acquisition systems and their users. Social implications This research implies that algorithms may serve to codify deep-seated biases, making IT work environments just as homogeneous as they are currently. If bias exists in talent acquisition software, the potential for propagating inequity and harm is far more significant and widespread due to the homogeneity of the specialists creating artificial intelligence (AI) systems. Originality/value This work uses equity as a central concept for considering algorithmic bias in talent acquisition. Feminist design thinking provides a framework for fostering a richer understanding of what fairness means and evaluating how AI software might impact marginalized populations.

The current business environment is volatile and complex. Companies must constantly identify creative and environmentally friendly solutions. The emphasis on employees and workforce agility has become an attribute of sustainable and competitive organizations simultaneously. The purpose of our study is to validate the hypothesis that there is a direct positive relationship between ranking as important top position of human resources in a company and the extent to which specific practices to increase workforce agility were adopted. Our survey is based on an original questionnaire, with a 92% response rate. We focused on large, independent decision-making companies from Western Romania, for which the implementation of sustainable principles is more difficult than for multinationals. The statistical analysis was performed using SPSS23 (Statistical Package for the Social Sciences). The results indicate an average extent of the adoption of management practices aiming to increase workforce agility (45%) and a ranking of human resources in first place as the most important resource (31.7%). Using the Pearson Chi-Square Test, the hypothesis was confirmed (significance = 0.026). Our main conclusion is that if managers intend to develop a sustainable and competitive business, they should attribute a strategic role to employees and adopt practices to increase their agility.

PurposeThe study aims to identify the essential competencies for Industry 4.0 within the manufacturing sector, to prioritise developing them among the workforce in creating a competitive advantage for the organization.Design/methodology/approachThe study employs the Analytic Hierarchy Process (AHP), a multi-criteria decision-making (MCDM) methodology to prioritize competencies. Literature review and expert input guided the identification of competencies, which were ranked by experts for their relevance, through pairwise comparisons.FindingsSeven competency groups, encompassing 21 sub-groups, were identified as essential for the Industry 4.0 workforce. Digital-technical and industry-specific competencies emerged as the most prominent to be developed on priority, followed by cognitive and business competencies. Despite their smaller representation, core/generic competencies remain the foundation for developing the newer and more specialised competencies.Research limitations/implicationsRecognising the need for empirical studies in early-adopting organisations of Industry 4.0, future research should explore competencies across industries as well as talent development mechanisms, for a nuanced understanding of competency requirements.Practical implicationsThe study informs organisations, educators and policymakers guiding workforce training, talent management and development, educational curriculum aligned with the demands of Industry 4.0 to bridge the competency gaps. It can support India’s strategic initiatives like “Make in India” by fostering a digitally ready and competent workforce.Originality/valueThis research provides an empirically validated, structured framework for Industry 4.0 competency prioritization specific to the manufacturing sector in India. It integrates expert inputs with AHP to rank competencies, offering a contextual understanding of competency requirements. It also contributes to human capital theory by advancing competency mapping for Industry 4.0.

PurposeThere is a substantial void in the understanding of the effect of talent management (TM) practices specifically targeted at females on firm performance. This paper investigates the relationship between female-focused TM and firm performance with the aim of demonstrating the importance of gender diversity in firms.Design/methodology/approachThe authors developed and empirically tested a contextually embedded model using data from 103 multinational corporations in Russia to examine the effect of female-focused TM on firm performance.FindingsThe authors found an overall positive relationship between female-focused TM and firm performance. The authors’ analysis also revealed significant positive effects of female-focused talent development and talent retention, but not talent attraction, on firm performance.Originality/valueThis paper contributes to the vibrant TM scholarship by focusing on female-focused talent attraction, development and retention practices.

To identify and systematically review current scholarship on talent management of international nurses in healthcare organizations. As nurse shortages persistently pose challenges for healthcare organizations globally, one of the primary strategies employed to address these shortages is employment of international nurses. To date little has been done to systematically review and collate contemporary research on talent management of this strategically important cohort. Talent management is a holistic construct that can support healthcare organizations to attract, develop, motivate, and retain talented employees to drive organizational performance. This systematic review isolates, appraises and collates available evidence on talent management practices for international nurses. Systematic literature review. Searches of PubMed, EBSCO and Scopus were made covering literature from 2012-2022. This study followed Cochrane protocol for Systematic Reviews and key search terms were developed in consultation with University of Limerick library. As a key aim of the review was to provide evidence for the development of effective talent management practices, only peer-reviewed academic papers and empirical studies were included. Initial articles screening was conducted by two reviewers and full articles review was conducted by the entire research team. Findings were combined in a data extraction template for further analysis. This review includes 62 articles thematically analysed under the headings recruitment and selection, retention and turnover, career progression, professional development, discrimination and racism, culture and communication. No articles were found that directly address talent management for international nurses. Although there are studies that address aspects of talent management independently, more research is required on talent management as a holistic process for international nurses to inform evidence-based practice. This research emphasizes the importance of talent management for retention of international nurses in healthcare settings. It provides a knowledge base for healthcare organisations to enhance employee retention and ensure quality care for patients, as well as setting the foundation for future studies in this area.

In light of the increasing recognition among modern business communities regarding the importance of implementing environmentally sustainable practices, this study thoroughly examines the concept of green recruitment (GR) and its subsequent impact on organizational sustainability performance (OSP). Situated within the shift from conventional to contemporary organizational frameworks that prioritize capacity, this study emphasizes the crucial importance of integrating sustainability into recruitment processes. This alignment ensures that human resource practices are in line with both environmental and organizational goals. The primary purpose emerges as a thorough examination and identification of sixteen critical factors that intersect GR and OSP, using insights from both the current literature and expert viewpoints, so this fills a crucial gap in the existing research. This study utilizes an integrated ISM-DEMATEL strategy to systematically reveal the hierarchical and relational patterns that are inherent in the connections between GR and OSP variables. This technique allows for a thorough comprehension of how these variables interact with each other. The findings highlight several important variables, emphasizing the complex network of interdependencies among the elements studied. The suggested model in this research encapsulates its originality, as it not only sheds light on the interdependent interactions for policy- and decision-makers but also establishes a foundation for future research in this field.