The lifelong development (LLD) of workers is gaining increasing attention owing to its benefits for individuals, organizations, and the society. However, not all workers participate, as various personal and contextual factors influence their LLD engagement. This study applies the Capability Approach (CA) of Amartya Sen to examine the multiple factors shaping individuals’ freedom to learn and develop and its implication for HRD. Based on a narrative review it categorizes 14 LLD capabilities (e.g., capability to aspire, capability of voice) and 6 conversion factors (institutional, economic, organizational, job characteristics, social, and personal) that either enable or constrain individuals’ abilities to realize these capabilities. The findings demonstrate that learning behavior is shaped by the interaction of dynamic personal, social, work-related, and institutional factors, rather than isolated variables. The resulting integrative framework advances HRD theory and research by providing a context-sensitive, dynamic, and social justice-informed perspective on freedom to learn and develop.
Evidence-based and translational human resource development (HRD) seek to connect research with practice, yet availability does not ensure influence. This article develops the HRD Intuition Dominance Cycle, a four-stage, multilevel process explaining how research-based HRD evidence may lose influence after entering decision contexts. Experience-based intuition directs attention toward familiar cues; sensemaking privileges experience-consistent explanations; conflicting evidence may be discounted, reinterpreted, or dismissed; and repeatedly enacted, socially reinforced decisions may become organizational routines shaping subsequent framing. Time pressure and uncertainty amplify initial intuitive framing but are neither necessary nor sufficient for the Cycle. Intuition is not inherently inaccurate; displacement occurs when evidence loses its capacity to influence decisions independently of its consistency with prior experience. This post-translation knowledge-weighting mechanism connects individual cognition to organizational retention and feedback, extending evidence-based and translational HRD theory and identifying opportunities to interrupt displacement.
Despite its losses, job rotation has long been an established organizational practice across sectors. This study examines when and why short-term losses from job rotation are transformed into long-term gains through an organizational learning process. Existing job-rotation research has identified both losses and gains, but has paid less attention to how these effects are connected through a learning process unfolding over time. This study argues that the transition from short-term losses to long-term gains does not occur automatically. Immediately after job rotation, employees experience practice discontinuity. Learning then begins when employees re-enter practice in a new role and participate in the actual work of that role. The central mechanism proposed in this study is interaction-based reconstruction, through which employees and their colleagues reconstruct the meaning of work and context-sensitive standards of judgment and performance. Through this process, individual learning can expand into interpersonal or local-level learning. When the learning generated through this reconstruction is sustained over time and retained for reuse at the organizational level, it can further develop into organizational learning capability. However, this transition unfolds as a conditional learning process and may stall at the individual or local level. The proposed mechanism provides implications for HRD managers and practitioners to diagnose the losses that arise immediately after job rotation from a learning perspective, identify potential stall points, and support the sustained reuse of learning.
We present a systematic review of 64 empirical studies that examine the links between ageism and career-related outcomes. Adopting a social cognitive theory lens, our review distinguishes between and integrates various manifestations of ageism under the umbrella of age stereotypes toward others and perceived age-related stereotypes/discrimination. We suggest two stages of career outcomes, with Stage 1 comprising three pathways that mediate the links to Stage 2 outcomes. Our review shows that when employees experience ageism, their relationships with employers, work, stress, and abilities can change, shaping career behaviours and outcomes in both positive and negative directions. Our findings provide insight for both individuals and human resource development (HRD) practitioners on how ageism at work influences career outcomes and, more broadly, offer learning around how age-friendly environments can be supported.
As generative artificial intelligence (AI) reshapes scholarly practice, non-empirical research in human resource development (HRD) faces distinct challenges that existing guidance has not addressed. Non-empirical scholarship—including systematic reviews, bibliometric analyses, conceptual articles, and theory articles—makes its contribution through the quality of the author’s intellectual engagement with ideas, a process that AI can support but cannot replace. This editorial articulates why non-empirical work demands careful attention to AI use, proposes a typology distinguishing legitimate, contested, and illegitimate applications across six research touchpoints, and establishes reporting expectations for non-empirical submissions. Grounded in the Academy of HRD Standards on Ethics and Integrity , we address AI’s current limitations for conceptual and review scholarship, its implications for scholarly equity, and the pragmatic-substantive distinction central to transparent disclosure. We offer eight reporting expectations and discuss implications for reviewers, editors, and the field.
