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Since new digital micro-credential technologies emerged a decade ago, there has been a rapid rise in micro-credentials in the education landscape. Much has been promised about these educational technologies, yet there is much confusion by key stakeholders in the digital micro-credential ecosystem. This confusion has led to significant efforts globally to define micro-credentials to ensure quality learning and generate beneficial impacts to learners, employers, education providers and edtech organisations.

This commentary reviews relevant literature on digital micro-credentials and other alternative credentials to determine how these educational technologies can meet the demands of the Fourth Industrial Revolution to nurture lifelong learning for working learners.

Universities are being challenged to address the changing needs and uncertainty being introduced by the Fourth and Fifth Industrial Revolutions, particularly with implications for workforce upskilling and lifelong learning. To adapt, universities will need to rethink their roles and shift their institutional mindsets in how they may approach the challenges through mechanisms such as digital micro-credntials.

This paper focuses on the analysis of five policy statements about micro-credentials. While these policy statements represent a sample, there is a representation of Western education-related systems. Thus, they skew the findings towards Western education systems thinking.

Understanding how micro-credentials are being positioned within education-related systems is useful for applying the educational technologies by, for example, universities, learners and employers.

Provides an overview of how these educational technologies may provide beneficial impacts for society as it plans to adapt to economic uncertainty and change.

The commentary provides a policy context for the emerging use of micro-credential technologies to examine demands for workforce upskilling.

The authors illustrate that there are significant differences in the wage performance across companies in relation to the digital content of their production and training activities.

Using company-level data from three waves of the Continuing Vocational Training Survey (2005, 2010 and 2015), this paper provides an overview on European firms implementing training and the magnitude of their training effort.

The authors conduct a regression analysis documenting that a wage premium of 9% is associated with companies undertaking training and that an additional 8% is paid by firms arranging training for IT skills-intensive workers. The latter effect is pervasive across sectors and is not strictly related to industry exposure to the digital transformation.

The authors assess the wage effect of training, in relation to the digital content of firm production or job tasks, using a large set of European companies (112,000), from countries with different degree of specialisation and institutional setting. The analysis covers a significant period of time of the last wave of digitalisation (2005, 2010, 2015).

Degree apprenticeships in the UK have grown exponentially since they were introduced. While claims and speculations about their impact have been made by high-profile politicians, lobbyists and training providers, the evidence base for these claims has never been systematically scrutinised. The purpose of this paper is to analyse and present up-to-date peer-reviewed evidence on the impact of degree apprenticeships on social mobility and productivity and their influence on future policy.

The authors critically and systematically review over 4,000 data points from relevant sources and synthesise the results qualitatively and quantitatively with a combined method approach. Quantitative evidence has been aggregated where possible and tested for statistical significance. Qualitative evidence has been critically reviewed and comparatively analysed.

The analysis reveals that there is a shortage of depth and breadth of concrete and peer-reviewed evidence on the impact of degree apprenticeships. Nevertheless, existing data demonstrate that degree apprenticeships are meeting their intended purpose of contributing positively to the UK Government’s high-level goals for productivity and social mobility. They are an alternative route into higher education and serve as a vital talent pipeline providing opportunities for young people, existing employees and learners from diverse backgrounds.

This paper provides the first systematic and peer-reviewed synthesis of the impact of degree apprenticeships. It brings together existing evidence and statistically validates outcomes to inform researchers, educators, training providers, policymakers and other stakeholders in their recommendations moving forward.

Since the early 2000s there has been increased attention on the professionalisation of the Early Childhood Education and Care (ECEC) workforce in many OECD countries. This study focuses on what Australian early childhood educators holding the lowest level of qualification – Certificate III are experiencing in relation to their professional capital in a sector that is experiencing wide-spread and ongoing reform. The study identifies the human capital, social capital and decisional capital of these educators, then explores the interconnections.

This paper was funded by the Australian Research Council. The qualitative data consider the capabilities of certificate-qualified educators and how these are enabled or constrained within the workplace. The corpus of data for this study consists of 14 interviews with Certificate III-qualified educators from three locations across Victoria, Australia. Hargreaves and Fullan’s (2012) forms of professional capital (human, social and decisional) act as organisers for the themes identified through a thematic analysis.

Themes identified in the data speak to inequity in access to professional learning, the valuing of life experiences, clear divisions of labour that impact what knowledge is valued, and differences in educator agency in the decision-making process. Many certificate-qualified educators experience a workplace culture that lacks trust in an individual’s professional competence and does not appreciate collegial knowledge and skill building as a collective enterprise.

The conceptual framing of this study provides a unique way to explore the experiences of certificate-trained educators. The study introduces the idea of using exploratory categories and the identification of levels of human, social and decisional capital. This type of study involving this cohort of educators is unique.

The research explores the shift to Quality 4.0, examining the move towards a data-focussed transformation within organizational frameworks. This transition is characterized by incorporating Industry 4.0 technological innovations into existing quality management frameworks, signifying a significant evolution in quality control systems. Despite the evident advantages, the practical deployment in the Indian manufacturing sector encounters various obstacles. This research is dedicated to a thorough examination of these impediments. It is structured around a set of pivotal research questions: First, it seeks to identify the key barriers that impede the adoption of Quality 4.0. Second, it aims to elucidate these barriers' interrelations and mutual dependencies. Thirdly, the research prioritizes these barriers in terms of their significance to the adoption process. Finally, it contemplates the ramifications of these priorities for the strategic advancement of manufacturing practices and the development of informed policies. By answering these questions, the research provides a detailed understanding of the challenges faced. It offers actionable insights for practitioners and policymakers implementing Quality 4.0 in the Indian manufacturing sector.

Employing Interpretive Structural Modelling and Matrix Impact of Cross Multiplication Applied to Classification, the authors probe the interdependencies amongst fourteen identified barriers inhibiting Quality 4.0 adoption. These barriers were categorized according to their driving power and dependence, providing a richer understanding of the dynamic obstacles within the Technology–Organization–Environment (TOE) framework.

The study results highlight the lack of Quality 4.0 standards and Big Data Analytics (BDA) tools as fundamental obstacles to integrating Quality 4.0 within the Indian manufacturing sector. Additionally, the study results contravene dominant academic narratives, suggesting that the cumulative impact of organizational barriers is marginal, contrary to theoretical postulations emphasizing their central significance in Quality 4.0 assimilation.

This research provides concrete strategies, such as developing a collaborative platform for sharing best practices in Quality 4.0 standards, which fosters a synergistic relationship between organizations and policymakers, for instance, by creating a joint task force, comprised of industry leaders and regulatory bodies, dedicated to formulating and disseminating comprehensive guidelines for Quality 4.0 adoption. This initiative could lead to establishing industry-wide standards, benefiting from the pooled expertise of diverse stakeholders. Additionally, the study underscores the necessity for robust, standardized Big Data Analytics tools specifically designed to meet the Quality 4.0 criteria, which can be developed through public-private partnerships. These tools would facilitate the seamless integration of Quality 4.0 processes, demonstrating a direct route for overcoming the barriers of inadequate standards.

This research delineates specific obstacles to Quality 4.0 adoption by applying the TOE framework, detailing how these barriers interact with and influence each other, particularly highlighting the previously overlooked environmental factors. The analysis reveals a critical interdependence between “lack of standards for Quality 4.0” and “lack of standardized BDA tools and solutions,” providing nuanced insights into their conjoined effect on stalling progress in this field. Moreover, the study contributes to the theoretical body of knowledge by mapping out these novel impediments, offering a more comprehensive understanding of the challenges faced in adopting Quality 4.0.

The purpose of this study is to examine how the implementation of edge computing can enhance the progress of the circular economy within supply chains and to address the challenges and best practices associated with this emerging technology.

This study utilized a streamlined evaluation technique that employed Latent Dirichlet Allocation modeling for thorough content analysis. Extensive searches were conducted among prominent publishers, including IEEE, Elsevier, Springer, Wiley, MDPI and Hindawi, utilizing pertinent keywords associated with edge computing, circular economy, sustainability and supply chain. The search process yielded a total of 103 articles, with the keywords being searched specifically within the titles or abstracts of these articles.

There has been a notable rise in the volume of scholarly articles dedicated to edge computing in the circular economy and supply chain management. After conducting a thorough examination of the published papers, three main research themes were identified, focused on technology, optimization and circular economy and sustainability. Edge computing adoption in supply chains results in a more responsive, efficient and agile supply chain, leading to enhanced decision-making capabilities and improved customer satisfaction. However, the adoption also poses challenges, such as data integration, security concerns, device management, connectivity and cost.

This paper offers valuable insights into the research trends of edge computing in the circular economy and supply chains, highlighting its significant role in optimizing supply chain operations and advancing the circular economy by processing and analyzing real time data generated by the internet of Things, sensors and other state-of-the-art tools and devices.

Introduction: Artificial intelligence (AI) has progressed significantly over the past few years, evolving into a collection of innovative tools that provide a competitive advantage to businesses. The acceptance and investment in AI are skyrocketing over the globe. The entry of AI in the workplace automates tasks and impacts making a timely decisions. At the same time, the workforce is not ready to welcome the new technology due to the skill gap. The organisation has to face many challenges in reskilling and convincing the workforce to incorporate AI in their work.

Purpose: With this study, the authors aim to analyse and highlight the introduction of AI in the organisation and the call for the reskilling of the workforce. To figure out what skills are most important for employees to learn to advance their careers.

Methodology: Given the deductive nature of the study, the researchers used secondary data collected and compiled from research papers, publications, websites, HR blogs, survey reports, etc. Research papers from reputed journals, reports of consultancies and agencies have been considered to synthesise the information and present it in a systematic manner and to derive the conclusion.

Findings: The findings indicate AI’s capabilities and applications have grown considerably, which shows the importance of AI in a growing number of fields, yet several hurdles need to be overcome, the most prominent one being the issues concerning upskilling the workforce for the future of AI. This study reveals the change in the perceived importance of the skills in the present and future times. Reskilling and upskilling the workforce and creating new talent to meet the changing employment demands is becoming increasingly important.

Introduction: Human resource management (HRM) is going through a transformation phase due to the pandemic. The COVID-19 crisis compelled the employees to work virtually. To mitigate the effects of COVID-19, several organisations heavily invested in artificial intelligence (AI) in the realm of HRM.

Purpose: With limited studies on the paradigm shift in HRM post-pandemic and the role of AI, the study investigates and proposes a conceptual framework for the paradigm shift in HRM practices post-COVID-19 pandemic and the significance of AI. Furthermore, the study investigates the outcomes of the use of AI in HRM for organisations and employees.

Methodology: A comprehensive review of the literature based on the guidelines of Tranfield, Denyer, and Smart (2003) and Crossan and Apaydin (2010) has been followed. A systematic literature review assisted in critically analysing, synthesising, and mapping the extant literature by identifying the broad themes involved.

Findings: COVID-19-related economic disruption has led to a paradigm shift in HRM practices. AI-enabled HRM practices are now centred around remote and contingent workforce management, mindfulness, social capital, increasing employee engagement, reskilling and upskilling towards new competencies, etc. AI is making remote work seamless through smooth recruitment and selection process, onboarding, career and development, tracking and managing the performance, facilitating learning, and talent management. Post-pandemic, AI-powered tools based on data mining (DM), predictive analytics, big data analytics, natural language processing (NLP), intelligent robots, machine learning (ML), virtual (VR)/augmented reality (AR), etc., have paved the way for managing the HRM practices effectively, thereby leading to enhanced organisational performance, employee well-being, automation, and reduced cost.

The accelerated digital transformation and the growing emphasis on privacy, safety and security present ongoing challenges for cybersecurity experts. Alongside these challenges, the multidisciplinary, everchanging and complex nature of the cybersecurity domain has further challenged the acquisition and retention of cybersecurity talent. Empowering reskilling and upskilling in cybersecurity necessitates efficacious educational endeavours which promote self-confidence and foster a growth mindset. The purpose of this paper is to highlight that cultivating self-efficacy in cybersecurity education can help promote competency development and effectively address the prominent skills gaps. This notion applies equally to both aspiring individuals pursuing a career in cybersecurity and professionals in the field who may wish to better articulate the skills they already possess, the skills they lack and newly surfacing skills that need to be developed.

The study discusses the imminent need for adopting a “skills-first” approach in cybersecurity and explores innovative pedagogies and professional frameworks that can inform and frame such an approach. Subsequently, a critical analysis of the importance of self-efficacy towards motivating and supporting upskilling in cybersecurity is performed. A case study is presented, expanding the authors’ previous work on cybersecurity professional development, to demonstrate the mediating role that self-efficacy can play in developing core cybersecurity competencies. The case study presents the design of a new cybersecurity curriculum in the context of postgraduate, synchronous distance cybersecurity education, and it is utilised as a basis to discuss how the proposed curriculum cultivates self-efficacy attitudes.

A skills-first approach is becoming the new norm in contemporary workplaces. This work highlights the importance of actively nurturing self-efficacy attitudes through innovative cybersecurity curricula that can be tailored to the learners’ needs, instigating a drive for learning and, ultimately, helping learners effectively upskilling by portraying a self-directed learning path and a professional growth mindset in cybersecurity.

The authors present the importance of cultivating self-efficacy in higher and lifelong education to foster reskilling and upskilling in cybersecurity. An innovative cybersecurity curriculum was constructed and delivered with a group of learners demonstrating how self-efficacy can be leveraged through interactive, reflective and self-assessment educational activities that enhanced motivation and self-awareness, curiosity, attention to detail and resilience – key skills for a successful career in cybersecurity.

Purpose – The purpose of this research is to provide empirical evidence on the relationships among new technologies, innovative work practices and upskilling in the Spanish case. Design/methodology/approach – Using detailed plant‐level data from a survey of Spanish manufacturing firms, we apply estimation methods, such as tobit and ordered probit models, to test the hypothesis that the use of ICT, AMT, and innovative work practices is positively related to upskilling. Findings – As available empirical evidence shows for other countries, we have found that AMT, ICT and innovative work practices are positively related to skills, although they have different effects on workforce composition and training. We have also found several significant effects of the interactive terms of the three technologies and work practices considered on the selected variables of upskilling. Research limitations/implications – The main limitation is the lack of time series data. Cross‐sectional data do not allow the use of lagged variables and make it impossible to analyse the evolution of the adoption of new technologies and work practices by firms and their dynamic effects on skills, or to study causalities among variables. In addition, the study relates only to manufacturing industries. Further research should consider expanding the analysis to the service sector and studying possible complementarities between technology and work practices, in terms of labor cost savings. Originality/value – This paper offers empirical evidence for Spain on the relationship between new technologies, innovative work practices and upskilling considered jointly. It analyses two different technologies: ICT and AMT. The paper also focuses on different dimensions of upskilling.