The Editors of the Human Resource Management Journal (HRMJ) invite applications for special issue proposals on themes related to the core aims and scope of the Journal. Special issue proposals will need to be cutting edge in terms of theoretical contributions, methodological innovation and rigour, with a level of critical scholarship that engages with policy and/or practice.

Timeline

• August 25, 2026: Submission deadline for special issue proposals

This special issue explores the fundamental shift from traditional Human Resource Management (HRM) to Artificial Intelligence Management (AIM), examining how algorithms are reshaping the governance of people at work. As organizations increasingly deploy algorithmic systems to manage recruitment, performance evaluation, scheduling, and other HR functions, we need to critically understand the implications for workers, organizations, and society.

The collection seeks to bring together diverse perspectives on how algorithms are transforming workplace governance, the mechanisms through which algorithmic management operates, and the consequences for employment relationships, worker agency, and organizational practices. We welcome contributions that examine both the promises and perils of algorithmic management across different sectors, geographies, and worker populations.

Potential topics

• AI and algorithmic management in organizational contexts
• The role of algorithms in HR decision-making and workforce management
• Transformation of HR practices through artificial intelligence
• Governance of people at work in the age of algorithms
• Impact of AI on employment relationships and worker autonomy
• Ethical considerations in algorithmic management
• Data-driven HR and talent management systems
• Worker surveillance and monitoring through algorithms
• Resistance and adaptation to algorithmic management
• Regulatory and policy frameworks for AI in HR

Timeline

• October 15, 2026: Extended abstract submission deadline

Asta Luksyte, +affiliation not provided in source

Overqualification—when employees possess education, skills, or experience exceeding job requirements—represents a significant and growing challenge in contemporary organizations. This phenomenon has become increasingly prevalent due to economic fluctuations, technological disruption, and shifting labor market dynamics. Despite its prevalence, overqualification remains under-researched in human resource management (HRM) literature, with limited guidance for practitioners navigating its complexities.

The sustainability of talent management practices depends on effectively addressing overqualification to ensure organizational viability, employee well-being, and long-term competitive advantage. Overqualified employees often experience underutilization of their capabilities, which can lead to reduced engagement, increased turnover, and diminished organizational performance. Conversely, organizations that strategically manage overqualified talent may unlock opportunities for innovation, enhanced performance, and sustainable competitive advantage.

This special issue seeks to advance scholarly understanding of overqualification and its implications for sustainable HRM. We welcome empirical studies, theoretical contributions, and practical insights that illuminate how organizations can effectively manage overqualified talent while promoting employee well-being, organizational effectiveness, and sustainable talent management practices. Research exploring the intersection of overqualification with diversity, equity, and inclusion initiatives, as well as global perspectives on this phenomenon, is particularly encouraged.

Potential topics

• Overqualification and person-job (PJ) fit
• Overqualification and person-organization (PO) fit
• Overqualification and sustainable HRM practices
• Career development and advancement opportunities for overqualified employees
• Retention strategies for overqualified talent
• Underemployment and its organizational consequences
• Skills utilization and employee engagement among overqualified workers
• Diversity, equity, and inclusion implications of overqualification
• Global perspectives on overqualification and talent management
• Technological change and overqualification trends
• Organizational culture and overqualification
• Psychological contract violations and overqualified employees
• Training and development for overqualified talent
• Selection and recruitment practices addressing overqualification
• Organizational performance implications of overqualification

Timeline

• March 1, 2027: Submission window

This section lists previous calls for papers from the Human Resource Management Journal. The calls include topics such as reconsidering careers in post-Covid-19 workplaces, caring for healthcare workers and advancing human resource management research in healthcare contexts, research methodologies that offer insights, and interfacing artificial intelligence technologies with human resource management in new firms.

Maarten Renkema, University of Twente

Laura Lamers, University of Twente

Christoph Lutz, BI Norwegian Business School

Anna B. Holm, Aarhus University

Artificial intelligence (AI) is being rapidly adopted across organisations, driven by promises of effectiveness and efficiency, yet accompanied by well-documented risks such as algorithmic bias and opacity. As competitive pressures compel AI adoption regardless, AI literacy—defined as the knowledge, skills, and attitudes that allow individuals (i.e., employees and HR-professionals) to engage effectively and critically with AI technologies—becomes crucial. This urgency is further underscored by the EU's AI Act, which includes the requirement for a sufficient level of AI literacy in organisations.

AI literacy research stands at a critical point. While widely acknowledged as necessary, it remains insufficiently understood in organisational and HRM contexts. Extant research on AI literacy has produced conceptual frameworks and measurement tools, but this work is predominantly embedded in educational research and is focused on individual learners, leaving the organisational perspective largely under-researched and under-theorised.

This special issue addresses that gap directly. It places AI literacy at the core of organisational development, learning and consequences for HRM, and invites contributors across varied disciplines and methodologies to advance understanding of what AI literacy means as an organisational phenomenon, how it is facilitated by HRM, and the role HR managers play in AI-literate organisations. The aim is to contribute to theory and practice at a moment when the need for actionable insights into AI literacy could not be greater.

This special issue aims to advance theoretical understanding of AI literacy by moving beyond two common perspectives in the current literature: uncritically optimistic framings that treat AI literacy as a solution to unlock AI's strategic potential and neutralise AI's risks and challenges, and dismissive pessimistic framings that treat AI literacy as little more than a legitimising instrument for AI adoption. Rather, critically engaged, practically relevant, and empirically grounded perspectives are advocated that position AI literacy between these two extremes, as a significant challenge for organisations and HRM, generating knowledge that genuinely benefits organisations and HR professionals.

Theoretical perspectives are welcomed that conceptualise AI literacy as a broader organisational capability than a set of individual competencies, for example, as emergent, relational, or organisationally constituted phenomenon. The scope is organisational, focusing on AI literacy within organisations and its implications for HRM, rather than on AI literacy at the national, legal policy or individual employee levels. To make a substantial theoretical contribution, manuscripts are invited that view AI literacy across organisational levels, adopting a multilevel organisational perspective.

Given the current state of the literature on AI literacy, empirical work is strongly encouraged with varied methodological approaches—qualitative, quantitative, and mixed-methods. Innovative and non-traditional research designs and approaches are welcomed as long as they respect the standards of rigor and relevance, such as interventions, action research, ethnographies, and longitudinal studies. Studies that conceptualise AI literacy as an organisational, dynamic, context-dependent phenomenon rather than a static individual attribute are particularly valued. All authors are encouraged to aim for societal and practical impact and ethical conduct of science. High-quality conceptual contributions that advance extant theoretical understanding are also welcome. The issue will not include systematic literature review papers. Submissions should have an explicit link to HRM theory and practice.

Submissions are welcomed from diverse sectors, organisation types (from small to large; public and private) and geographical contexts, including studies from the Majority World and from contexts that remain underrepresented in AI and HRM research.

Potential topics

• Implications of AI literacy for core HRM functions, systems, policies and practices, including recruitment and selection, learning and development, performance management, and employee well-being
• Organizational AI literacy: definition, design, implementation, and governance of HRM activities
• Emergence mechanisms of individual AI literacy into collective organizational capability and HRM contributions
• Relationship between organizational AI literacy and adjacent constructs such as organizational AI readiness, antecedents and outcomes
• Competition for AI talent in the labour market and inequality implications inter- and intra-organizationally
• Team reshaping and creation to enable, develop and foster AI literacy
• HRM and HRD practices supporting development of AI-literate teams through workforce planning, staffing, job design, training and allocation of responsibilities
• AI literacy levels and combinations needed across different teams and roles, and HRM practices supporting capability building
• Manifestation of AI literacy in everyday work practices and its transformation of work
• Technical, ethical and practical dimensions of AI literacy in AI-mediated recruitment, fairness perceptions, and AI overreliance
• AI literacy of HR professionals and influence on adoption of AI tools

Timeline

• Invalid DateTime: Special issue completion
• September 1, 2026: Special Issue announced
• February 1, 2027: Submission window opens
• April 30, 2027: Submission deadline
• July 1, 2027: Decision on first submissions

Matej Černe, University of Ljubljana

Marko Orel, Prague University of Economics and Business

Fabiola Mancinelli, University of Barcelona

Stefanie Reissner, Durham University

Brian Harney, Dublin City University

Digital nomadism combines location-independent, digitally mediated work with sustained or recurring geographic mobility. It has often been discussed as a lifestyle, tourism, migration, or mobility phenomenon, including in research on transformational travel, destination ecosystems, workation practices, and digital nomad visas. Yet, digital nomadism also raises central questions for human resource management: how organizations attract, organize, support, govern, develop, and retain workers whose employment relationships, work locations, and social embeddedness are increasingly fluid. This special issue invites HRM scholarship that treats digital nomadism as both a distinctive empirical setting and an analytically powerful context for rethinking work, workforce, and workplace in an international and digitally mediated economy.

The special issue is motivated by a simple premise: digital nomadism exposes the limits of HRM models built around stable organizational membership, fixed work sites, nationally bounded employment systems, and co-located employment relationships. It foregrounds the spatial, contractual, social, and institutional fragmentation of work and speaks directly to recent calls to rethink HRM in light of distributed, fragmented, and fluid work arrangements. It also brings together developments that are usually studied separately, including remote and hybrid work, global mobility, platform and freelance work, flexible staffing, coworking, workation practices, digital infrastructures, destination ecosystems, and transnational employment regulation. In this sense, digital nomadism sits at the intersection of new global ways of working, technology-enabled change, and the shifting boundaries of talent management and careers.

We seek theory-driven conceptual and empirical papers that use digital nomadism and related forms of mobile, distributed, or location-independent work to advance HRM theory and practice. Recent reviews show that digital nomadism is a growing but still fragmented research field, with much of the literature developing outside HRM and organization studies. At the same time, emerging work on digital nomads' online conversations shows how this form of work is deeply connected to career management, community building, portability of career capital, and the broader future of work. Papers should make clear how their arguments speak to HRM phenomena, systems, practices, functions, or outcomes. We are especially interested in contributions that move beyond describing digital nomads as a lifestyle group and instead examine the implications of mobile digital work for organizations, workers, HR professionals, and institutional actors.

We welcome conceptual papers and empirical studies using qualitative, quantitative, mixed-method, longitudinal, comparative, multilevel, ethnographic, experimental, diary, or archival designs. We particularly encourage studies that capture movement across places, organizations, roles, communities, and regulatory environments, and studies from underrepresented regions including Africa, Latin America, South and Southeast Asia, and Central and Eastern Europe.

Potential topics

• Work design, job demands and resources, autonomy, flexibility, isolation, insecurity, time-zone dispersion, infrastructure variability, and performance
• Leadership, coordination, voice, psychological safety, performance management, and feedback in mobile and distributed work arrangements
• The implications of digitalization, AI, algorithmic management, and digital platforms for where, how, and under what contractual conditions work is performed
• Talent attraction, selection, retention, and employer branding for mobile and location-independent workers
• Careers, employability, career self-management, protean careers, sustainable careers, and boundaryless or globally mobile talent pathways
• Wellbeing, recovery, work-nonwork boundaries, social embeddedness, loneliness, identity, and community among digital nomads and other mobile workers
• Onboarding, socialization, belonging, organizational identification, informal learning, and knowledge sharing when workers are geographically mobile
• Destination ecosystems, coworking spaces, local communities, employers, governments, and intermediaries as actors shaping mobile digital work
• Comparative research on digital nomadism across countries, regions, sectors, occupations, employment forms, and regulatory regimes
• Employment relationships, psychological contracts, commitment, fairness, inclusion, and duty of care in remote, freelance, contractual, hybrid, or employee-based arrangements
• International HRM, global mobility, digital nomad visas, taxation, labor law, social security, cross-border compliance, data protection, and institutional complexity
• HR architecture and governance: balancing flexibility, autonomy, coordination, control, equity, risk management, and organizational support

Timeline

• April 30, 2027: Manuscript deadline

Sandra Fisher, FH Münster

Janet Marler, University at Albany - SUNY

The 10th e-HRM Conference in Muenster, Germany (June 2026) provided a platform for scholars from around the world to share research and leading-edge insights into electronic/digital human resource management in the midst of another major technological revolution. This special issue highlights key research papers presented at the conference and also invites authors who were unable to attend the conference to submit their related research to this special issue.

Artificial intelligence and robotics may prove as transformative for economic growth and human potential as electrification, mass production, and electronic telecommunications in their eras. The release of ChatGPT in November 2022 highlights the rapid advance of AI technologies, illustrating that such advancement is not necessarily continuous but can occur in sudden bursts. Previously heralded as a tool for automation and increased efficiency, narratives about AI now make a broader claim of a new era of human-AI collaboration in which AI performs routine tasks freeing professionals to take on more value-added work. But this claim is not new. Such promises were made 20 years ago with the introduction of the internet and the expansion of electronic telecommunications, and use of ERP and HRIS technologies.

One goal of the conference is to examine the ways in which AI can advance the science and practice of human resource management, but we also want to remain mindful of the potential limitations and boundaries of AI, such as concerns with inequality and bias, hallucinations, lack of transparency, issues with trust or distrust in the technology and skill erosion. Given these limitations, which HRM processes and workflows can or should be automated, and which augmented? What other technologies might be used along with AI or instead of AI? What can we imagine is next after the big wave of AI?

To advance scholarship and to provide evidence-based, independent guidance, academic researchers have a crucial role to play in influencing how AI technologies are used in organizations to improve outcomes for all stakeholders. It is important therefore to build on the well-developed management literature that already exists. Over the last two decades research on e-HRM, also referred to as digital HRM or d-HRM, shows how a wide range of configurations involving computer hardware, software and electronic networking resources which both enable intended or actual HRM activities not only automates but also transform HRM processes in intended and unintended ways. Digital transformations have also been extensively researched in the traditional HR functions of recruitment, selection, leadership, learning and development, and compensation.

Research in e-HRM has been enriched with such concepts as cloud computing, big data and people analytics, social media, chatbots, gamification, the internet of things, robots, artificial intelligence, machine learning, and other emerging technologies. E-HRM has also evolved to include new forms of organizing, such as industry 4.0 and digital-platform business models. Industry 4.0 redefines the relationship between human workers and machines, and requires a new approach to HRM, or HRM 4.0. Moreover, the emergence of advanced systems, software agents and/or robots which work alongside human workers has resulted in human-robot 'white-collar teams'. The platform or gig economy has created a new type of contingent worker, gig workers who have little or no connection to job providers, who are managed algorithmically through platforms. The digital platform is an important vehicle of their employment relationship, since it creates a new ecosystem for employment/work relations and institutes the use of algorithms/software robots for executing HRM activities. These developments pose new challenges to and opportunities for the e-HRM field, as well as expand and enrich its scope.

With the release of large language models (LLMs) like ChatGPT, Claude, and Gemini, generative AI and AI agents now make communicating with and accessing information from information technology much easier, democratizing insights from HR data and HR analytics. There has been an explosion of AI for HRM start-ups. Despite these impressive advances, the question remains, what is different about AI in the e-HRM context? Do many of the traditional challenges and agendas of e-HRM remain or are there other characteristics that need further study? How is AI different from the preceding electronic technologies and how does this make a difference to the practice of HRM?

AI has three specific material characteristics—constant change, invisibility, and inscrutability—that may challenge traditional approaches to the study of technology and work. Individually these characteristics are not problematic but in combination they challenge applying earlier research frameworks to the study of AI in organizations. The production and use of AI involves a broad swathe of stakeholders in and across organizations whose assumptions and interests influence design, development, implementation, and use. This calls for a broader view, tracing interactions across contexts and expanding analysis upstream from use.

To deliver value for all stakeholders, HR professionals need to be aware of the technology-driven context in which they work and the assumptions about HRM processes and practices that are embedded in the technology. Rather than accepting the dictates of software developers external to the organization, HR leaders need to develop HRM practices that deliver value to their organization and employees. Thus, the aim of much current e-HRM research is to uncover e-HRM outcomes or consequences that lead to an enhanced value of HRM for both organizational members and other stakeholders, eschewing determinative technological pressures. Given that e-HRM aims to create value within and across organizations for targeted employees and management and covers all possible integration mechanisms and content between HRM and Information Technology (IT), this call invites papers dealing with a broad scope of technology application to managing people inside and across organizations.

Potential topics

• New theories and methodologies to study AI/HRM
• New HRM strategies
• AI-Human collaboration at work
• e-HRM/AI value propositions
• AI/Technology-enabled HR roles
• AI Agents' roles and intended and unintended outcomes in HRM
• AI/Technology-enabled HR functions: recruitment, selection, performance management, leadership, training and development, coaching, compensation and employee relations
• Algorithmic management of employees or gig workers
• Gig-worker management and employment/work relations
• e-HRM and employee experience
• e-HRM and employee wellbeing
• AI and Bias in decision-making
• AI and job design/crafting
• HR data management and confidentiality
• People Analytics and AI
• Digital talent management
• Employee and digital onboarding systems
• Gamification in HRM
• Robots and artificial intelligence (AI) in HRM
• Employer branding and digital communication
• AI/e-HRM and trust/ethics

Timeline

• Invalid DateTime: Special issue completed
• July 1, 2026: Submission portal opens
• October 31, 2026: Special Issue Submissions due

Sanjay Singh, University of Dundee

Sateesh Shet, Northumbria University

Tanya Bondarouk, The University of Twente

Paresha Sinha, University of Waikato

James Duggan, Cork University Business School

The acceleration of digital transformation across industries has reshaped the nature of work and the workforce. In this evolving landscape, a new kind of employee has emerged, one that is digitally fluent, technology-enabled, and increasingly reliant on digital tools to perform, collaborate, and innovate. This digitally-savvy workforce brings with it a unique set of expectations, behaviors, and capabilities that are fundamentally altering traditional models of Human Resource Management.

As organizations navigate this shift, HRM must move beyond conventional practices to align with the realities of a workforce deeply embedded in digital ecosystems. The integration of emerging technologies such as artificial intelligence, machine learning, virtual collaboration platforms, and HR analytics is not only transforming operational HR functions but also reshaping strategic priorities around talent acquisition, workforce planning, performance management, employee engagement, and learning and development.

The significance of this transformation extends beyond technology adoption, requiring the need for redefining work design, leadership, culture, and employee experience in a digital-first world. The increasing demand for flexibility, autonomy, continuous learning, and meaningful digital interactions places HRM at the centre of driving organizational agility and future-readiness. Questions around digital equity, ethics in algorithmic decision-making, surveillance, digital fatigue, and the digital divide call for exploration and evidence-based solutions.

The rise of the digitally-savvy workforce marks a structural inflection point in the evolution of work and HRM. The digitally-savvy workforce encompasses a broader, cross-generational cohort of employees who have acquired advanced digital competencies through education, experience, or continuous upskilling. This workforce does not merely use technology, they strategically engage with digital tools, platforms, and data as core enablers of their work, collaboration, and innovation.

There is a critical gap in research concerning the mental health and well-being challenges unique to digitally-savvy employees in the workplace, such as digital burnout, blurred boundaries between work and life, and stress from social media. Furthermore, HRM has long been concerned with employee well-being, yet digitally-savvy employees' constant connectivity and digital-centric lifestyles introduce new risks that are underexplored in the literature.

For HRM, this presents both transformative potential and considerable complexity. On one hand, digitally-savvy employees are key assets in driving automation, agility, and innovation. On the other hand, their expectations for real-time feedback, flexible work structures, digital autonomy, and continuous learning challenge the static assumptions that underpin many legacy HRM practices. There is an increasing mismatch between the agility of the workforce and the inertia of HR systems still grounded in procedural and administrative logic.

While there is growing interest in digital transformation, there remains a critical gap in our understanding of how HRM can effectively align with and support a digital-savvy workforce. Issues such as workforce planning for digital roles, work design for tech-mediated environments, AI-driven performance management, and ethical concerns around digital monitoring remain under-theorized. Equally, the psychological impacts, such as techno-overload, digital presenteeism, and the erosion of work-life boundaries, are insufficiently addressed within the current HRM discourse.

This Special Issue seeks to explore these challenges and opportunities by reframing the HRM research agenda through the lens of digitally-savvy workforce readiness and transformation. It calls for contributions that examine how HRM can evolve to strategically manage and empower a digitally capable workforce while balancing human-centric values and organizational imperatives. Furthermore, it seeks to investigate the technological expectations that digitally-savvy workforces bring to the workplace, including their demand for flexibility, autonomy, digital communication, and purpose-driven work.

This Special Issue seeks to advance new theoretical contributions that reflect the shifting realities of HRM in the context of a digitally-savvy workforce. Contributions should foreground digital capabilities as core constructs in HRM theory and examine how the integration of digital technologies into daily work life reshapes the employee experience. Technological affordance theory, digital transformation theory, HRM systems theory, social exchange theory, ecological systems theory, and the job demands-resources model offer valuable frameworks for examining these issues.

A fundamental transformation is underway in how talent is managed across borders, driven by the growing presence of a digitally-savvy workforce. Across diverse international contexts, digitally savvy employees are challenging long-established HRM systems through expectations shaped by AI-enhanced workflows, platform-based collaboration, hybrid work models, and a heightened demand for flexibility, autonomy, and continuous development. These expectations are filtered through local institutional logics, labor market structures, and cultural norms, creating varying patterns of digital adoption, employee engagement, and HRM innovation around the world.

This call for papers seeks to illuminate how multinational organizations, international institutions, and global HR functions are reevaluating leadership, organizational culture, performance systems, learning pathways, and inclusion practices in response to the evolving digital capabilities of their workforce. As the digitalization of work becomes increasingly global in scale but locally embedded in practice, the need for comparative, cross-national HRM research becomes critical.

Potential topics

• Strategic workforce planning for the digital era, including forecasting digital talent needs, digital upskilling frameworks, and bridging digital skills gaps
• Work design for digitally enabled workforce, encompassing job roles in technology-mediated environments, digital flexibility, autonomy, work-life integration, and remote work impacts
• Emerging digital technologies and HRM transformation, including AI, blockchain, virtual reality, chatbots, intelligent automation, and HR digital twins
• Redefining talent acquisition for digitally-savvy workforce through social media recruitment, gamified assessments, AI in recruitment, and employer branding
• Performance management in tech-driven organizations, covering digital dashboards, algorithmic evaluation, surveillance, real-time feedback, and fairness implications
• Employee engagement and experience in digital workspaces, including digital platforms, AI-driven personalization, digital fatigue, and tech-enabled burnout
• Ethics, privacy, and surveillance in digital workplace, addressing algorithmic monitoring, employee autonomy, and ethical HR technology adoption
• Inclusion, equity, and accessibility in digital HR practices, focusing on digital exclusion reduction, neurodiverse talent support, and fair AI-driven decision-making

Timeline

• Invalid DateTime: Publication of Special Issue
• August 1, 2026: Manuscript submission window opens
• September 30, 2026: Manuscript submission deadline

Ingyu Oh, Kansai Gaidai University

Jie Wu, University of Aberdeen

Ho Kwong Kwan, China Europe International Business School

Hyun Jeong Kim, Inha University

Low fertility is emerging as a critical challenge in international human resource management (HRM). Ultra-low fertility—defined as a total fertility rate (TFR) of 1.3 or lower—is no longer confined to East Asia. It is now present across diverse regions, including parts of Southern and Eastern Europe (e.g., Italy, Spain, Poland), high-income Asian economies (e.g., South Korea, Japan, Singapore), and is increasingly affecting advanced economies in North America and Oceania. As of 2022, around 20 countries face ultra-low fertility, while 152 nations fall below the replacement level of 2.1.

This demographic crisis is transforming HRM from a support function into a strategic imperative. Policymakers around the world are sounding the alarm—South Korea warns of 'national extinction,' Japan calls it a 'quiet emergency,' and several European nations are grappling with labor market stagnation. The risks of shrinking workforces, declining productivity, and rising costs for talent acquisition and retention are now central economic concerns.

In response, a wave of HRM innovation has emerged globally. Strategies include expanded parental leave, work-life balance initiatives, AI-enabled workforce planning, and inclusive hiring to integrate underutilized groups such as women, older workers, and immigrants. Scholars are also extending and rethinking foundational HRM frameworks—such as the Resource-Based View, Institutional Theory, and Social Exchange Theory—to address the complexities of demographic scarcity.

Key causes of ultra-low fertility vary by context but often include insufficient work-family support, gender inequality, and cultural norms that discourage caregiving among working professionals.

The Resource-Based View (RBV) assumption of heterogeneous resource access must be revisited when human capital becomes universally scarce. Contributions are encouraged that develop a 'Scarcity-Based View' of HRM, theorizing competitive advantage amid widespread labor depletion, extend dynamic capabilities theory to define 'demographic agility,' and propose new mechanisms for integrating human and technological resources in response to labor shortages.

Classic human capital theory models presume labor stability. Contributors may theorize the 'demographic premium,' where labor scarcity amplifies the value of specific skills, and offer models for 'human capital preservation' to mitigate knowledge loss in shrinking organizations.

Neo-Institutional Theory perspectives advance institutional analysis by exploring how HRM navigates competing logics, reconciling global HR 'best practices' with local fertility norms, and theorizing 'institutional fertility regimes'—blends of regulatory, normative, and cultural influences on HRM. New theories are also needed to explain cultural paradoxes such as the 'Asian Paradox' where strong family values coexist with ultra-low fertility, and how cultural tightness-looseness shapes policy uptake.

Beyond adapting existing theories, this special issue encourages the creation of context-specific models capturing emerging HRM dynamics. Submissions should adopt multi-level approaches—linking national policy, organizational HRM, fertility behavior, and labor force participation. Comparative, cross-national research is especially welcome, as despite similar TFRs, HRM consequences vary widely. The special issue also seeks to theorize why conventional family-friendly HRM policies often fall short—due to patriarchal norms, cultural resistance, or inadequate personalization. Innovations such as AI-augmented work, radical flexibility, and diversity-centered talent strategies offer promising directions.

This Special Issue aims to fill a critical research gap by examining the global HRM implications of ultra-low fertility and exploring diverse, human-centered strategies for building sustainable, inclusive, and resilient workforces in response to demographic decline.

Potential topics

• Work-Life Balance Challenges: Family-friendly HRM policies and workplace cultures affecting fertility decisions
• Work-Life Balance Challenges: Gender inequality, maternity/paternity leave, and childcare support impacts on career and family planning
• Work-Life Balance Challenges: Cultural expectations and traditional gender roles influencing fertility rates
• Work-Life Balance Challenges: Implementing on-site childcare, generous parental leave, and financial incentives for families
• Work-Life Balance Challenges: Fostering inclusive environments prioritizing work-life balance and psychological safety
• Adapting HR Practices: Flexible work policies including remote work, reduced hours, and enhanced parental leave
• Adapting HR Practices: Upskilling and reskilling programs addressing workforce shrinkage
• Adapting HR Practices: Inclusive benefits such as childcare support, eldercare programs, and fertility treatments
• Adapting HR Practices: Diversity and inclusion strategies tapping underutilized labor pools (older workers, women, immigrants)
• Adapting HR Practices: Innovative international recruitment strategies and talent pipeline development
• Human-Centered AI Solutions: Deploying AI tools enhancing productivity without undermining employee wellbeing or autonomy
• Human-Centered AI Solutions: AI-assisted work-life balance through predictive analytics and personalized leave planning
• Human-Centered AI Solutions: AI-facilitated servant leadership and psychological safety reducing family planning fears
• Human-Centered AI Solutions: AI-driven personalized work schedules for dual-earner couples
• Human-Centered AI Solutions: Digital twin modeling simulating and optimizing career-family pathways
• Human-Centered AI Solutions: AI and automation addressing labor shortages and optimizing workforce management
• Rethinking Core HRM Theories: Developing scarcity-based view and demographic agility in HRM
• Rethinking Core HRM Theories: Human capital preservation and the demographic premium concept
• Institutional and Cultural Complexity: Reconciling global HR best practices with local fertility norms
• Institutional and Cultural Complexity: Institutional fertility regimes and institutional entrepreneurship in gender-equity reforms
• Institutional and Cultural Complexity: Cultural paradoxes and the influence of cultural tightness-looseness on policy uptake

Timeline

• Invalid DateTime: Publication of Special Issue
• September 1, 2026: Manuscript submission window opens
• November 30, 2026: Manuscript submission deadline
• December 1, 2026: Review process (1st round)
• March 1, 2027: Review process (2nd round)
• May 1, 2027: Final submission of accepted manuscripts

This Special Issue aims to advance understanding of how AI is reshaping work and employment for underrepresented groups, and to stimulate research on how HRM can foster more inclusive, equitable, and human-centered AI-enabled workplaces. It seeks to bring together multidisciplinary scholarship examining both the opportunities and risks of AI for women, migrants, refugees, older workers, people with disabilities, and Indigenous employees. These aims will be met by inviting conceptual, empirical, and review-based contributions that examine bias, accessibility, trust, human–AI collaboration, inclusive design, and responsible governance in AI-HRM systems. In doing so, the Special Issue will generate new theoretical insights, practical implications, and future research directions that position HRM scholarship to respond more effectively to the challenges and possibilities of AI-driven organizational change, while helping organizations foster more equitable, inclusive, and human-centered human–AI interactions.

This Special Issue offers an original contribution by bringing AI, HRM, and diversity management into one integrated conversation, rather than treating them as separate streams. Its novelty lies in advancing understanding of how AI reshapes workplace inclusion, exclusion, and inequality for underrepresented groups, while also showing how HRM can design more fair, ethical, and human-centered AI systems. The issue moves beyond predominantly technical and productivity-focused debates by encouraging new theory on algorithmic bias, intersectionality, trust, and human–AI collaboration, alongside practical insights on inclusive AI design, reskilling, AI literacy, equitable adoption, and governance. It also highlights the importance of human oversight, minority voice, and cross-sector collaboration in reducing bias and improving responsible AI implementation. By bridging the fields of HRM, organizational behavior, information systems, and diversity and inclusion, this Special Issue contributes to positioning HRM scholarship at the forefront of debates on responsible AI and inclusive organizational transformation.

Potential topics

• AI in Talent Acquisition and Selection: How do AI-based recruitment and selection systems create, reproduce, or mitigate biases against candidates from underrepresented groups (e.g., people with disabilities, older workers, migrants), and what mechanisms can ensure equitable outcomes in AI-assisted hiring?
• Accessibility and Inclusion in Employment: In what ways can AI technologies be designed to enhance workplace accessibility, enable equitable participation, and expand employment opportunities for employees with disabilities or other marginalized groups?
• Human–AI Collaboration and Bias Mitigation: How can human oversight, input from minority employees, and inclusive design processes help AI systems learn more equitably—reducing bias and performing more human-like or human-better tasks in HR contexts?
• Talent Development, Reskilling, and Learning in the Age of AI: How can HRM leverage AI-enabled learning, development, and reskilling systems to support diverse employees and prepare both workers and organizations for ethical AI use? How can organizations use talent development strategies to train both humans and AI systems toward ethical and inclusive performance?
• Ethical, Legal, and Governance Challenges in AI-HRM: What are the ethical and legal implications of using AI in managing diversity and disability inclusion, and how can organizations establish responsible AI governance frameworks aligned with human rights and DEI principles?

Timeline

• January 9, 2026: Opening date for manuscripts submissions
• January 3, 2027: Closing date for manuscripts submission