Timeline

• September 15, 2026: Submission deadline

Timeline

• January 31, 2027: Full paper submission deadline

This special issue of The Leadership Quarterly seeks empirical research that advances our understanding of leadership through rigorous causal inference methods. We invite submissions that employ experimental designs, quasi-experimental approaches, longitudinal studies, or other methodologically sound approaches to establish causal relationships in leadership phenomena.

Timeline

• November 22, 2026: Full paper submission deadline

Iris K. Gauglitz, University of Bamberg

Peter Harms, University of Alabama's Culverhouse College of Business

Urszula Lagowska, NEOMA Business School

Birgit Schyns, NEOMA Business School

Kimberley Breevaart, Erasmus University Rotterdam

Leader behaviours and their perception across organisational levels are a critical and evolving area in leadership research. In particular, the distinction between leaders' behaviours and the ways in which these behaviours are perceived by others have been widely discussed in the field. While there have been recent calls among leadership scholars to focus more on leader behaviours rather than to rely on how they are perceived, understanding leadership requires an examination of how leader behaviours are enacted and interpreted across different levels of the organization.

The topic is relevant both for theory and practice as it relates to the ongoing debate on how leadership should be measured, developed, and defined. Research shows that to get a more complete picture of leadership effectiveness, there is a need to focus on both leader behaviours and how these behaviours are perceived and interpreted by different actors within the organization. Leadership research often splits behaviour and perception, sometimes even treating them as rival lenses. This special issue brings them together by asking how behaviour changes across settings and how different groups make sense of those changes.

By proposing such themes as a bilateral relationship between leader behaviours and their perception, as well as the dynamics of this relationship over time, this special issue hopes to showcase research demonstrating the value of studying both "sides of the coin". In addition, we hope to encourage submissions on many current and underexplored topics that would advance our understanding of leadership as a process in a complex, modern workplace.

Perceptions of leader behaviour outside of the dyad of leader and follower are not well understood yet. Also, more research is needed on discrepancies between leader intentions and follower perception of intentions, especially in polarized social contexts and new forms of work.

The topic has key importance for practice and the elaboration of leadership training programs. The effectiveness of such programs depends on a strong foundation of scientific evidence, which can only be achieved by gaining a deep understanding of both enacted leader behaviours and how they are interpreted by perceivers at different levels in the organization.

Incorporating within- and between-person methods at various levels of analysis is essential to fully capture the complexity of leaders' actions and their interactions with followers. In this special issue, we aim to contribute to a deeper understanding of leadership dynamics and to the development of more effective leadership practices.

Potential topics

• Theoretical models proposing new or conceptually advanced configurations of leader behaviour and its perceptions, which consider the role of new working contexts in shaping leader behaviours and their perceptions
• Multi-level conceptualizations of the impact of leader behaviour at multiple levels of organizations with a view to understand how and why perceptions across levels differ
• Studies including models that explain why and under which conditions leader behaviour and its perceptions affect workplace outcomes, notably when leaders and others differ in their perceptions/(perceived) intentions or when behaviour is perceived as inconsistent or ambivalent
• Research that investigates polarisation in follower perceptions—why perceptions of the same behaviour may diverge significantly
• Studies looking at leader and follower behaviour and their interaction, such as how behaviours from one party trigger behavioural reactions of the other party and what that means for an effective collaboration
• Studies considering the role of organisational hierarchy in how leaders behave and how their behaviour is perceived
• Contributions considering interactions between personality traits (e.g., leader–follower trait congruence) in shaping behavioural expressions and perceptual accuracy; team outcomes of leader behaviour, for example, perception differences between team members and how this affects outcomes; and relative leader behaviour, that is, perceptions of how one follower is treated compared to others
• Studies that develop and validate new measures of leader behaviour (e.g., behavioural indicators)
• Studies that develop new measures that allow for the measurement of perceptual biases in leadership ratings and studies using advanced statistical approaches (e.g., polynomial regression analyses, multilevel modelling, pattern approaches)

Timeline

• February 1, 2026: Abstract deadline
• April 1, 2026: Decision on abstract
• December 1, 2026: Full paper submission deadline
• December 1, 2026: Review Round 1
• March 1, 2027: Decision on first revision communicated
• June 1, 2027: First revisions due
• June 1, 2027: Review Round 2
• September 1, 2027: Decision on second revision communicated
• November 1, 2027: Second revision due
• December 1, 2027: Final decision communicated
• February 1, 2028: Publication of special issue

Upper echelons research has long argued that organizational outcomes reflect the characteristics of those who lead them. Scholars have shown that personality plays a central role in shaping how executives interpret information, make decisions, interact with stakeholders, and steer their organizations. Yet, despite a rapidly expanding literature on CEO personality and related constructs, recent reviews highlight persistent challenges: conceptual narrowness, methodological limitations, geographic concentration, and a tendency toward insularity rather than theoretical integration.

This Special Issue seeks to advance the study of personality in the upper echelons by encouraging submissions that challenge existing assumptions, expand theoretical lenses, deepen methodological rigor, and broaden contextual diversity. A recent comprehensive review emphasizes the need to move beyond overreliance on broad traits such as the Big Five and narcissism, integrate insights from personality psychology, employ multi-method assessment and reduce dependence on proxy measures, articulate mechanisms linking personality to organizational outcomes, explore non-Western contexts and alternative governance systems, and bridge macro–micro perspectives to understand how individual dispositions influence firm-level outcomes.

The Special Issue aims to deepen theoretical understanding of how personality operates within and shapes the upper echelons, encourage methodological innovation in assessing executive personality including multi-method designs and longitudinal approaches, broaden contextual relevance by examining executive personality across diverse governance systems and cultural settings, and integrate micro- and macro-level perspectives to illuminate how leaders' psychological characteristics influence organizational structures, strategic actions, culture, and performance.

Potential topics

• How do motives, values, traits, and narratives of organizational leaders shape firm behavior?
• Under what conditions do personality effects strengthen or weaken?
• How can scholars better measure personality in the upper echelons?
• How do institutional, cultural, and governance contexts shape the expression and consequences of executive personality?
• Broadening the conceptualization of executive personality beyond Big Five and narcissism traits
• Integrating insights from personality psychology including motives, values, identity, and life stories
• Mechanisms linking personality to strategic outcomes such as CSR, M&A, innovation, and risk-taking
• Personality dynamics over time including personality change and developmental experiences
• TMT dynamics, leadership styles, and power distributions shaped by executive personality
• Contextual, cultural, and institutional moderators of personality effects across national cultures and governance systems
• Measurement and assessment of executive personality using multi-method designs and unobtrusive indicators
• Personality composition and complementarities within boards, TMTs, and collective leadership
• CEO selection, evaluation, and succession planning incorporating personality
• Executive personality influence on ethical decision making and societal outcomes

Timeline

• August 1, 2026: Submission window opens
• September 30, 2026: Submission window closes
• December 31, 2026: Decision notification
• June 1, 2027: Target publication

William Y. Degbey, University of Vaasa

Maria Pajuoja, University of Vaasa

Matti Pihlajamaa, VTT Technical Research Centre of Finland

Baniyelme D. Zoogah, McMaster University

Waymond Rodgers, University of Texas

Artificial Intelligence (AI) is defined as the frontier of computational advancements that references human intelligence in addressing ever more complex decision-making problems. A key development is Generative Artificial Intelligence (Gen AI), particularly Large Language Models (LLMs) like ChatGPT, which can process and generate human-like language, extract insights, and produce creative outputs. Gen AI has enormous potential to significantly boost national economies. Its widespread adoption could increase GDP in the EU region by +8% (EUR 1.2–1.4 trillion) over the next ten years, provided innovators are equipped with the necessary skills and capabilities.

Yet, adoption remains uneven. For instance, European countries average a 54 percent adoption rate, below the global average of 61 percent. This uneven adoption is compounded by the global competition for skilled talent and persistent workforce shortages, particularly in digital and AI-related fields. McKinsey estimates that up to 12 million job transitions may be required due to AI, underscoring the urgent need for reskilling and entrepreneurial innovation.

This Special Issue aims to advance empirical understanding of how, when, and why humans engage with Gen AI in innovation. The focus is on Gen AI as an innovation enabler, inviting submissions to explore innovation processes, human capital resources, and organizational capabilities. The call welcomes single- and multi-level studies that examine Gen AI's role in shaping innovation within and across organizations and encourages contributions that take an interdisciplinary perspective. Submissions should address managers' pressing challenges in finding new ways to support and improve innovation by investigating how managers can effectively enhance how employees and executives use Gen AI.

Technological advancements have made Gen AI more accessible and affordable across industries. Gen AI's impacts are not limited to what organizations innovate but also change how they innovate. Gen AI can be used to replace existing innovation processes, reinforce them, or reveal unforeseen ways of developing new products and services. It may assist in the identification of opportunities, idea generation, and evaluation of innovation potential, reshaping the front-end of innovation processes, and enable more rapid experimentation and improved customer understanding. Yet, experiences and use cases remain evolving and fragmented, creating uncertainty for managers.

Furthermore, Gen AI transforms innovation processes at multiple interrelated levels, whereas existing research has mostly examined them in isolation. Consequently, this Special Issue encourages a multi-level perspective, including individual, team, and organizational level processes.

Microfoundations research shows that innovation is fundamentally driven by people, not organizations, since it is individuals who identify opportunities, generate solutions, and implement them. To understand how Gen AI enhances innovation outcomes, such as faster development of better-quality products, services, and processes, it is necessary to examine how individual innovators use Gen AI, what influences its use, and what results emerge from these AI-augmented efforts. Team-level dynamics are equally important, as teams have become the core unit of modern organizations. Gen AI can support team innovation by sparking dynamic discussions and promoting diverse thinking in design processes, supporting ethical decision-making, and by helping overcome challenges in group decision-making. Finally, scholars have called for more research on how leadership can support AI adoption and digital transformation. Leaders must build new capabilities as AI implementation is often challenging, human-AI interaction may involve complications, and a new range of ethical concerns must be considered.

The rapid evolution of Gen AI demands not only technical adaptation but also new approaches to manage the associated processes, tensions, and frustrations. As Gen AI profoundly alters work design, skill requirements, and professional identities, employees face both new opportunities and psychological challenges. To ensure they can develop the AI-related skills needed for the evolving roles, organizational and managerial support mechanisms have to be developed. Yet, there is limited understanding of the organizational capabilities required to implement this change successfully. Effective support may involve building Gen AI literacy, fostering experimentation, and promoting continuous learning.

At its best, AI is strategically deployed to generate business value and competitive advantage, but without targeted support, organizations risk de-skilling, employee resistance, and ineffective adoption that undermines innovation goals. Organizational practices for managing innovation are also being challenged by Gen AI, especially in terms of ethical governance. While the benefits of Gen AI in innovation are promising, ethical concerns remain underexplored. Key principles include respect for intellectual property, truthfulness, robustness, recognition of malicious uses, sociocultural responsibility, and human-centric design.

Overall, the Special Issue seeks papers that provide empirical contributions on the evolving role of Gen AI in innovation to deepen psychological and social insights into management practices to support, improve, and offer practical guidance to help managers navigate Gen AI adoption and integration. The listed themes are neither exhaustive nor exclusive; authors are encouraged to explore other themes aligned with the aims of the Special Issue. The journal welcomes contributions from scholars of innovation, organizational behavior, management, HR, strategy, technology, and practitioners.

Potential topics

• How is Gen AI being used in innovation processes at different levels?
• How do organizations apply Gen AI to replace, reinforce, or reveal innovation activities, and what are the resulting effects on, for example, process efficiency, novelty, and responsiveness to market needs?
• How do varied patterns of Gen AI use across process phases and organizational levels influence the dynamics and management of innovation processes?
• How do individual innovators use Gen AI in their work, what influences this usage, and what are the measurable outcomes of AI-augmented innovation efforts in terms of product, service, or process quality and speed?
• In what ways does Gen AI influence innovation team dynamics, including collaboration, resilience, and decision-making, particularly in virtual or hybrid team environments?
• What psychological and behavioral effects emerge from using Gen AI in innovation settings, such as changes in employee engagement, collaboration dynamics, or perceptions of autonomy?
• How do managerial competencies influence the successful implementation of Gen AI in organizational innovation efforts?
• What organizational capabilities need to be developed to successfully implement, integrate, and support the use of Gen AI in innovation efforts?
• How are organizations supporting continuous learning and skill development for employees working with Gen AI, and what mechanisms are most effective in enabling the strategic use of Gen AI?
• What ethical challenges do organizations face when deploying Gen AI in innovation activities, and how are they addressing issues such as intellectual property, transparency, and sociocultural responsibility?

Timeline

• January 15, 2026: Opening date for manuscripts submissions
• August 31, 2026: Closing date for manuscripts submission