Journal of Leadership Studies最新文献

Research on CEOs’ social media communication as a leadership instrument remains scarce. The current study addresses this gap by exploring the relationship between CEOs’ leadership-oriented language and user engagement (i.e., sharing behavior). Based on an automated text analysis of 24,719 posts from 172 CEOs of Global Fortune 500 companies on X, one of the largest social media platforms previously known as Twitter, this research examines how CEOs’ leadership-oriented language influences users’ sharing behavior. In particular, it focuses on transformational leadership (TFL), a crucial approach in social media contexts. Utilizing hierarchical linear modeling, the findings revealed that CEOs’ use of linguistic indicators reflecting TFL affects users’ sharing behavior in partially unexpected and contradictory ways. Specifically, using positive emotional language and exclusive words in social media posts can diminish users’ sharing behavior. Conversely, content-rich posts, replies that open a dialogic loop, and posts reflecting psychological closeness all positively influence users’ sharing behavior. These findings underscore the complex nature of leadership-oriented language and provide novel insights into its effectiveness on social media. The current study offers specific guidelines for how CEOs can effectively utilize TFL-oriented language to engage their audiences while minimizing the risk of unintended negative consequences.

Haskell, C. (2025). Leadership at the Threshold: Meaning, Ethics, and Adaptation in the Age of Generative AI. Journal of Leadership Studies, 19, e70012. https://doi.org/10.1002/jls.70012

After the publication of the aforementioned article, the following errors were discovered and subsequently corrected as outlined below.

The sentence “This issue of the Leadership & Organization Development Journal does not treat that shift as neutral.” was incorrect. It has been corrected to “The current symposium does not treat that shift as neutral.”

In “Signals of the Current Climate,” the following sentence was incorrect: “We live in a climate that prizes performance over reflection—where power performs expertise, and those who challenge epistemic overreach, from women scholars to high-profile critics like Gary Marcus, are told they're rude, too dark, or depressing, while complexity is waved away as an inconvenience.”.

It has been revised to remove the term “women”: “We live in a climate that prizes performance over reflection—where power performs expertise, and those who challenge epistemic overreach, from scholars to high-profile critics like Gary Marcus, are told they are rude, too dark, or depressing, while complexity is waved away as an inconvenience.”.

The em dash was replaced with parentheses in the following sentences:

Their contributions (frameworks, case studies, and provocations) reclaim leadership as an act of care, critique, and cultural memory.

It identifies the interpretive layers (human, institutional, and algorithmic) that leaders must navigate.

The “Acknowledgments” section was missing and has now been included:

Spiritual leadership and happiness have garnered considerable attention among leaders and followers in contemporary organizations. Building upon Fry's theory of spiritual leadership (2003), this study seeks to examine the impact of spiritual leadership on individuals' happiness, with a particular focus on the mediating role of the sense of calling. A quantitative investigation was carried out via a questionnaire administered to 151 Portuguese nutritionists employed at a national pharmaceutical company. Structural equation modeling, facilitated by SPSS AMOS 22, was employed to test the hypotheses. The findings indicate that spiritual leadership exerts a positive influence and can effectively predict individuals' happiness. Furthermore, the study reveals that the sense of calling serves as a mediator in the relationship between spiritual leadership and individuals' happiness. This research presents a novel quantitative analysis of the pivotal role played by the sense of calling in the nexus between spiritual leadership and happiness, thereby contributing to the ongoing debate on the challenges posed by a new organizational paradigm that endeavors to fulfill individual aspirations for holistic well-being through spiritual leadership.

As generative AI (GenAI) tools rapidly evolve and become more accessible, their application in leadership education and research demands critical reflection and experimentation. The current practitioner-focused study presents two use cases exploring how GenAI tools—including Retrieval-augmented generation platforms like NotebookLM and large language models like ChatGPT and Claude—can support qualitative data analysis in leadership contexts. The first case analyzes open-ended responses from 237 participants about their “best” and “worst” bosses, while the second examines semi-structured interviews from a phenomenological study of leadership educators. These methods were piloted with graduate students through a three-way comparison methodology. Students conducted AI-assisted analysis, compared findings with expert human coding, and examined peer variations in analytical approaches. The comparative analysis reveals key differences across AI tools regarding transparency, analytic depth, usability, and ethical implications, highlighting both affordances and limitations, including variable output quality, learning curves, and the need for methodological rigor. Student outcomes demonstrate that AI tools can effectively support various phases of qualitative methodology while requiring human oversight for interpretive depth, bias detection, and validation of outputs. GenAI can be a helpful analytical partner in leadership research when integrated thoughtfully through pedagogical frameworks emphasizing human–AI collaboration rather than replacement, preparing emerging researchers to leverage technological capabilities while maintaining—and at times enhancing—the interpretive richness essential to qualitative inquiry in leadership studies.

Stories form the foundation of human connection, shaping perception, engagement, and relationships across diverse contexts. Storytelling or narration, as a powerful leadership tool, shapes public perception and behavior, influencing measurable outcomes. The significance of strategic storytelling is evident in high-stakes U.S. presidential debates. For instance, the 2024 Harris-Trump debate, which attracted massive viewership, illustrates how these events captivate audiences and influence public sentiment and electoral outcomes. Data focuses the significant impact of narratives in these debates on performance metrics such as financial campaign contributions and voter turnout. This study introduces bond ambition, a model that integrates narrative-driven leadership with elements of charismatic and transformational leadership—adaptability, relationship building, and initiating positive organizational change. By synthesizing insights from narrative paradigm theory (NPT) with established leadership frameworks, the model offers a robust approach to building trust and enhancing engagement in political as well as educational and commercial settings. Through strategic storytelling and active relational maintenance, bond ambition equips leaders with a dynamic methodology to harness narrative influence effectively.

Artificial intelligence (AI) is spreading rapidly in organizational settings, yet limited research examines how culture shapes leaders' readiness to adopt these technologies. The current study addresses that gap by exploring cross-cultural differences in AI acceptance among 434 leaders from Western and Eastern regions, guided by the unified theory of acceptance and use of technology (UTAUT). A cross-sectional, quantitative design, supplemented by short, open-ended responses, assessed five UTAUT constructs: performance expectancy, effort expectancy, social influence, facilitating conditions, and behavioral intention. Results showed that Western leaders report significantly higher average effort expectancy, social influence, facilitating conditions, and behavioral intention than Eastern leaders, although both groups find AI beneficial. Multiple regression analyses reveal that Western leaders' intention to adopt AI is primarily related to ease of use, whereas Eastern leaders intention is related to organizational support and peer encouragement. Open-ended responses demonstrate that leaders across regions share ethical and privacy concerns, but Western participants emphasize security and training, while Eastern leaders highlight transparency and real-time insights. These results imply that AI implementation strategies require cultural adaptation, such as prioritizing the quality of user interfaces and training for Western leaders and ensuring organizational endorsements for Eastern contexts. By identifying how leaders evaluate and integrate AI, the current research delivers practical insights for multinational organizations and deepens theoretical dialogues on leadership and technology acceptance. These findings also address current leadership journal calls by spotlighting AI bias, inclusivity, and ethical governance in distinct regional settings.

Persistent complex environmental and socioeconomic challenges, political turbulence, and accelerating technological innovation create an intricate and dynamic environment. Artificial intelligence (AI) offers potential solutions for navigating complexity. However, its deployment introduces its own multifaceted challenges—technological, ethical, and regulatory—all embedded within environmental complexity. Conceptualizing AI implementation as a “nested complexity” recognizes AI as a dynamic phenomenon contributing to the complexity within which organizations operate, thus encouraging organizational leaders to be cognizant of the intricacies, constraints, and evolving nature of AI, and to utilize an adaptive and iterative approach to its implementation.

In healthcare settings where structural change is slow and leadership is distributed across roles, the integration of artificial intelligence (AI) into leadership education introduces both promise and complexity. The current paper distinguishes between generative AI, systems that create new content and insights, and algorithmic AI, which automates predefined tasks within leadership training contexts. Yet, these tools risk embedding algorithmic bias and reinforcing Western-centric leadership ideals, raising ethical, cultural, and pedagogical concerns. The current paper examines the implications of AI-enabled leadership education through theoretical lenses, including complexity leadership, cultural dimensions theory, and relational pedagogy. It explores how AI systems reshape power within learning environments, shifting emphasis from relational mentorship to behavioral optimization. Drawing on Foucauldian concepts of discipline and visibility, the analysis shows how data-driven models may prioritize conformity over ethical discernment and reduce leadership to a technical artifact. To address these risks, the paper proposes a Relational-AI Pedagogy Model that positions AI as a supportive tool within a relational and culturally adaptive leadership education framework. This approach balances the efficiencies of AI with human judgment, mentorship, and cultural responsiveness. By integrating technological and relational strengths, the model offers a path for pharmaceutical organizations to develop KOLs who are not only scientifically credible but also ethically grounded and culturally responsive within diverse leadership contexts.

The rapid ascent of generative artificial intelligence (AI) presents higher education leaders with urgent challenges of pedagogy, ethics, and institutional adaptation. Yet many leadership responses have been top-down or vendor-driven, sidelining the faculty who are closest to teaching and learning. The current reflective case study examines The Generator, a faculty-led interdisciplinary AI lab at Babson College, as a model of distributed and relational leadership in the AI era. Drawing on theories of distributed leadership, relational leadership, and collective action, we explore how The Generator enacts a values-driven leadership practice through its decentralized lab structure, faculty-led programs, and signature “Family Conversations.” These practices foreground care, trust, and inclusion in decisions about AI adoption, which offers an alternative to purely efficiency-driven models of technological leadership. We argue that The Generator provides a transferable model for how faculty can lead institutional adaptation to AI in ways that are mission-aligned and pedagogically informed while emphasizing that each institution must adapt leadership practices to its own context, mission, and values. The case contributes to broader conversations about leadership and governance amid technological disruption, suggesting that distributed, relational leadership practices may be essential for guiding higher education through the uncertainties of the AI age.