John Robert Turner

Purpose: The purpose of the current study is to identify emergent collective leadership theories, compare these theories, capture the characteristics of each theory, and to identify the multilevel and multidimensional characteristics around these theories. Design/methodology/approach: This study conducted a systematic literature review looking at current collective leadership theories. The leadership theories reviewed included collective leadership, adaptive leadership, agile leadership, complex adaptive leadership, complexity capacity, complexity leadership, sapient leadership, system leadership, distributed leadership, network leadership, relational leadership, shared leadership, and team leadership. Findings: This study synthesized the literature and compared each theory by looking at its associated levels of analysis, epistemology, and how each is integrated with other theories or constructs. This study also highlighted four main levels of analysis (higher-level, team, psychological, leader) found in collective leadership theories. The current study introduced the collaboration, open systems, reflection, and empowerment (CORE) framework as a unifying model for understanding the multidimensional phenomenon of collective leadership. Originality/value: This study synthesized collective leadership theories into multilevel, multidimensional characteristics and presented the CORE leadership framework. This framework connects disparate collective leadership theories into a dynamic, multilevel, holistic framework that better represents how leadership is practiced in the real world. This framework can serve as a guide for future research and for practitioners evaluating leadership within their organizations.

Explainable artificial intelligence (X-AI) techniques aim to make the actions and decisions of autonomous systems understandable to humans interacting with these systems. In human–AI teams, explainability supports individual understanding and coordination, shared mental models, and collective decision-making among humans and AI agents. Research has shown that X-AI enhances trust in autonomous systems, improves human–AI team performance, and supports collaboration across domains including aviation, finance, healthcare, hospitality, and sports. However, X-AI technologies face difficult challenges, including a lack of transparency and interpretability due to complex underlying models, also known as the “black-box” nature of AI systems. These technologies also lack any universally accepted evaluation metrics and have limited generalizability across applications. One deficit in the X-AI literature is that most frameworks focus on individual-level outcomes, with limited attention to team-level processes. The current study conducted a systematic literature review adhering to PRISMA guidelines and the SALSA framework. This study introduces the Implementation-Design (I-D) framework that organizes X-AI approaches along two dimensions: implementation, ranging from visual to interactive approaches, and design, ranging from isolated explanations to workflow-integrated systems. This framework captures lower-level engagement, involving individual users, to higher-level understanding that is necessary for teams and collectives. Findings indicate that visual explanation approaches support user engagement, while interactive workflow approaches promote deeper understanding, appropriate reliance, and distributed cognition within human–AI teams. Implications highlight the need for team-oriented explainability grounded in shared mental models, transactive memory systems, and collaborative X-AI artifacts. Practical guidelines are included to support researchers and practitioners in selecting appropriate X-AI techniques based on their context and level of analysis. The I-D framework is offered as a conceptual organizing model to guide research and practice, and empirical validation is identified as a priority for future work.

Problem: The increasing complexity and interconnectedness of modern organizations have amplified the need for professionals who can operate across boundaries. Yet, the role of boundary spanners, especially within Human Resource Development (HRD), remains underexplored. This study addresses the problems of limited conceptual clarity and empirical understanding of boundary spanners in HRD, which hinders practitioners’ ability to facilitate collaboration, manage knowledge, and drive organizational change. Solution: Through an integrated literature review, we identify and synthesize 10 key characteristics that define effective boundary spanners, offering a comprehensive framework for HRD practitioners to navigate ambiguity, build trust, and foster innovation across diverse contexts. Stakeholders: The findings provide actionable insights for HRD scholars and practitioners, organization development practitioners, and organizational leaders who routinely manage across epistemic, intellectual, institutional, organizational, and role boundaries.

Virtual collaboration is now common, yet the everyday realities of Women of Color (WoC) in virtual teams remain underexamined. This study investigated how WoC experience virtual teamwork, the barriers they face, and the strategies that sustain performance and well-being. A basic qualitative design was used. Purposeful sampling yielded 13 WoC in the United States, ages 25 to 49, working across banking, oil and gas, retail, healthcare, and higher education. Semi-structured Zoom interviews of approximately 45 min were recorded and transcribed. Analysis followed a reflexive thematic approach supported by NVivo, with credibility strengthened through transcript verification, member checking, and analytic triangulation. Five themes emerged: (1) intersectional barriers intensify online, shaping access, belonging, and advancement; (2) marginalization produces recurring emotional and psychological strain; (3) virtual practices can obscure contributions, creating visibility and recognition gaps; (4) participants mobilize resilient tactics such as asserting presence, setting boundaries, building relationships, and amplifying ideas, alongside women for women support; and (5) structural and social supports, especially inclusive leadership, mentoring networks, and confidence building, enable fair participation and growth. Overall, virtual work can magnify inequities while also revealing practical levers that organizations can use to improve psychological safety, make contributions visible, and create equitable paths to advancement for WoC in distributed teams. Implications for Human Resource Development (HRD) include auditing visibility practices in virtual workflows, aligning evaluation with collaborative outputs, and targeting supports where inequities cluster.

The multidimensional characteristic of learning has received little attention in the network literature, resulting in fragmented empirical evidence on learning networks. To address this gap, we introduce a framework that allows a better understanding of the multidimensionality of learning networks by employing the concept of multiplexity in the network literature. Our proposed conceptual framework for multiplex learning networks includes a 3-E typology (exploration, exploitation, and exaptation), which serve as distinct layers within the multiplex networks. We also provide a hypothetical scenario to demonstrate the potential of our multiplex learning networks framework for HRD scholars and practitioners. Moreover, we extend our framework to a multilevel model that connects individual-level learning relationships to team-level relationships. Our framework’s theoretical and practical implications are discussed, and future research directions are suggested.

There are several key sensemaking models and theories that have attracted a lot of attention among researchers and practitioners in the last few decades. The adaptation and application of sensemaking has varied by field of study, organizational type, and industry. This study explored these sensemaking models and theories to better answer the following questions: what is sense-making/sensemaking? How is sensemaking practiced today compared to the original sensemaking frameworks, models, and theories? To answer these questions, the current study conducted a systematic literature review and content analysis of current research involving sensemaking methods, practices, and techniques. As a result, topic modeling and data analytic techniques were used to construct a multifaceted conceptual framework that has been contrasted and compared with previous sensemaking frameworks, models, and theories to show its coverage and coherence. The new multifaceted sensemaking (MSM) theory consists of nine stages with defining characteristics for each stage that were either derived from the data analysis or conceptualized by the researcher based on the literature review. The new theory presented demonstrates how previous sensemaking theories evolved and have influenced both practice and research today. The multifaceted sensemaking theory is influenced by previous sensemaking theories while also representing sensemaking in current practice. The multifaceted sensemaking theory contributes to the sensemaking field of study a new theory with nine stages and defining characteristics.

The process of publishing research is guided by a set of principles that aid in developing and sustaining a high level of trust in the dissemination of