Among the toughest aspects of most formal organizational leaders' jobs is that they are not just leaders, but also followers. Yet despite the challenges managers face in navigating the potentially clashing expectations associated with these two roles, the majority of previous research treats individuals as either leaders or followers, resulting in a lack of theory on the intrapersonal leader-follower interface. Drawing on a narrative analysis of critical incidents from 180 current and former managers, we examined how conflicts between the leader and follower roles may shape individuals' interpretations of their role responsibilities. We identified four dual role orientations based on managers' beliefs about their joint obligations as followers and leaders, and validated our categorization of these role orientations using a large language model. In addition, managers reported distinct developmental consequences associated with each dual role orientation, including leadership and followership behavior, leadership self efficacy, and organization or role exit. Recommendations for theory and practice are discussed.
We know that two dancers who do not know each other can move fluidly within seconds because they share a learned interaction script (e.g., salsa or tango). In this paper, we theorize and test the idea that the same principle holds for leadership among strangers. Drawing on interaction ritual and interpersonal theory, we hypothesize that leading–following interactions among strangers can emerge when they rely on shared behavioral interaction scripts, whereby dominance invites submissiveness and relational warmth invites warmth. To empirically uncover and test these expectations, we measured actual behavioral interactions of 127 leader–follower dyads on a second-by-second basis during a 15-min task-completion exercise. The results support the presence of a behavioral interaction script, such that (1) manipulated formal power influences the rules of the interaction script (e.g., more powerful interactants generally exhibit higher agency), (2) leaders and followers dynamically take turns in relative dominance and submissiveness over the course of an interaction, and (3) the extent to which interactions followed this “script” predicts indices of relationship quality. We discuss the implications of these findings, namely that leadership in its early phases is not learned ex nihilo, but is instead recognitional in nature.
Over the last five decades, leader compensation has risen substantially, with the median CEO:worker pay ratio skyrocketing from 20:1 to around 268:1. This has raised concerns for both internal and external stakeholders. However, observational studies have difficulty isolating the causal impact of leader pay on employees and other stakeholders due to endogeneity issues. To address this, the present research synthesized findings from 23 experimental studies (11 third-person evaluative tasks, 7 first-person hypothetical scenarios, 5 immersive experiments) to examine how information about leader pay causally influences employee and stakeholder responses. Results indicate that higher leader pay has a significant negative effect on employee outcomes (g = −0.53, 95%CIs [−0.68, −0.38], kstudies = 12, neffect sizes = 83) as well as on external stakeholder outcomes (g = −0.38, 95%CIs [−0.51, −0.26], kstudies = 11, neffect sizes = 57). These negative effects did not depend on whether pay is presented in absolute terms or relative to employee pay. Counterintuitively, providing justification for high pay was ineffective in eliciting more positive responses. Dose-response analysis indicated that detrimental responses appear even at low pay ratios with no evidence of an incrementally compounding penalty. These findings highlight the need to do a better job of balancing the interests and demands of leaders with those of the broad range of stakeholders that they are notionally striving to lead.
The open science movement has gained considerable momentum in advancing the transparency, credibility, and rigor of scientific research across disciplines. Within this broader landscape, leadership scholars have played a prominent role in developing formal guidance to strengthen open science practices in organizational research. To date, most recommendations have focused on quantitative research rooted in post-positivist traditions. However, qualitative scholars working from interpretivist perspectives share core values such as openness, integrity, and reproducibility with open science and enact them through practices grounded in inductive, context-sensitive inquiry. Bringing these two conversations into closer dialogue offers meaningful opportunities for both domains. Leadership research provides a particularly generative context for this exchange, as qualitative methods have influenced the field by illuminating the socially constructed and value-laden nature of leading. Drawing on these contributions, we present a set of 12 established practices through which interpretivist qualitative researchers have historically embodied open science values in leadership research, followed by six additional practices that can further enhance the openness, integrity, and reproducibility of interpretivist scholarship. By articulating how open science principles can be enacted in qualitative paradigms, we show that leadership scholars are well-positioned to extend the open science conversation across methodologies and communities of practice.
With Artificial Intelligence (AI) entering the white-collar workforce at scale, employees will increasingly operate multiple AI agents which, once aligned, can (semi-) autonomously handle a wide array of tasks. Our commentary explores this prospective reality and its implications for employees. Specifically, we argue that employees in these scenarios will effectively have to become vertical multi-level managers, that is, continuously code-switching between the top, middle, and lower management roles when interacting with their AI agents. Against this background, we outline anticipated benefits and potential challenges for the involved employees. Finally, we discuss the implications of this transformative shift for future management research and the requirements we foresee for educational practices within our field.
Scale centering has traditionally been used in congruence research for two reasons: reducing multicollinearity and facilitating interpretation. Recent studies, however, have raised several methodological concerns about this option. To advance this debate, we first review emerging concerns about scale centering, clarifying the extent to which they are supported. We then revisit the traditional two criteria, showing that they offer limited guidance on the conceptual role of scale centering. Building on the premise that research questions should drive centering decisions, we propose that a proper centering option for congruence research should satisfy five criteria: preserving commensurate compatibility and scale equivalence within and across studies, preserving the theoretically defined fit and misfit lines and the intended response surface tests, and maintaining the interpretive validity of response surfaces. We argue that only scale centering satisfies all five criteria, whereas alternative centering options can unintentionally change the meaning of fit and misfit, change surface tests, and bias inferences. Accordingly, we elevate scale centering to the status of a fundamental assumption for congruence research, alongside commensurate compatibility and scale equivalence. Empirical illustrations and simulations further demonstrate how centering choices shape theorization, estimation, and surface interpretation. Overall, the study offers a theory-driven basis for making centering decisions in congruence research.
Conversational AI agents—systems capable of holding intelligent conversations with human users—are rapidly reshaping how organizations operate, from leadership development and employee training to internal communication. Consequently, researchers across leadership, management, and the broader social sciences are beginning to examine how these agents affect organizational processes, employees, and workplace outcomes. Yet, existing studies still often rely on scenario-based methods that—while offering experimental control—are limited in ecological validity. Recent advances in no-code platforms mark a turning point:researchers can now design and deploy customized, conversational AI agents without requiring any technical expertise. This development makes it more feasible to conduct empirical studies based on real-time, interactive experiences with functional AI agents rather than imagined scenarios. These agents can represent a variety of organizational actors, including leaders, coworkers, or subordinates; display diverse characteristics and behaviors; and be implemented in complex study designs across lab and field, experimental and observational, and both quantitative and qualitative methodologies. We demonstrate the power of this approach through three empirical studies (N = 789), showing how interactions with customized, conversational AI agents can meaningfully shape participants’ perceptions, attitudes, and behaviors in incentivized settings. Introducing a novel, open-source tool called ResearchChatAI as an illustrative example, we outline how such studies can be designed and deployed—and critically reflect on the practical and methodological trade-offs involved. We showcase how such tools enrich the methodological toolkit of scholars and pave the way for more valid, realistic, and scalable leadership and management research on as well as with AI.
Our aim in this paper is to add to the methodological toolbox of qualitative research in leadership by illustrating how corpus linguistics (CL) can be used to study large-scale datasets comprised of text or talk. CL differs from other approaches to analysing large-scale textual data, such as topic modeling and sentiment analysis, because it enables detailed quantitative and qualitative analysis of linguistic choices on the level of vocabulary and grammar. CL can be used to study text or talk produced by leaders (such as CEO speeches, letters to shareholders, or interviews) or written about leaders (such as newspaper or magazine articles, social media posts, or biographies). Whilst CL methods can be applied using R or Python, here we demonstrate how a user-friendly proprietary software, Sketch Engine, can be used. We illustrate the relative strengths of the method using a corpus of media texts comprising leader profiles published in The Times (UK) newspaper where senior executives (n = 733) answered the question "What does leadership mean to you?". We conclude by discussing the potential that CL offers for informing future research and theory development, spanning positivist, interpretivist and social constructionist styles of theorizing. We also outline the practical benefits the method offers for improving leadership practice and for people involved in leadership teaching and training by providing robust evidence about concrete and learnable behaviors.
Credible leadership signals are observable pieces of information emitted by potential leaders that credibly convey the state of unobservable leadership qualities. Credible signals bridge information asymmetries between leaders and followers and play a crucial coordination role in the leadership process by assisting followers in identifying competent leaders. Yet, despite empirical work on leadership signaling, its theoretical foundation remains underdeveloped. We thus integrate Spence’s signaling model into a theoretical framework for better understanding signaling in the leadership process. Specifically, we propose three conditions for credible leadership signals: 1) an unobservable leadership quality that followers care about, 2) an observable signal, and 3) signaling costs that are negatively correlated with the quality. We then systematically review the literature on leadership signaling, showing that conditions for credible signals are not respected in a majority of cases. We conclude by deriving theoretical implications and providing practical guidelines for future research on credible leadership signals. This manuscript advances the discourse on leadership signaling by clarifying when signals effectively guide followers to discern capable leaders.
This study explores the enduring influence of military imprints on corporate leaders and their implications for corporate narrative disclosures. Drawing upon insights from imprinting, upper echelons, and strategic leadership theories, we argue that military experiences shape executives’ decision-making and communication styles persistently. Utilizing a dataset of 29,633 firm-year observations from 2010 to 2021, we find that military imprints translate into distinct communication patterns, evident in a positive tone in corporate disclosures. We further explore the relationship within varying ownership structures, identifying contextual factors that modulate this dynamic. Our findings have withstood rigorous tests for robustness, thereby providing additional strength to the credibility of our research. Our findings contribute to the literature on imprinting theory, leadership, and corporate communication, underscoring the multifaceted influence of military experience on executives’ decision-making and disclosure styles. Simultaneously, it imparts pragmatic insights for both corporate leaders and stakeholders alike.
What makes leadership and management theories practical? Theories are practical to the extent that practitioners can enact proposed cause (X)-effect (Y) relationships. Accordingly, I distinguish three types of practical theories. Manipulate(X) theories give practitioners levers for action. These theories have causal constructs, whose operationalizations' levels practitioners can set by themselves. For example, in a theory on charismatic leader signals, practitioners can use fewer or more signals. In select(X) theories, practitioners cannot themselves vary a construct's levels but select the desired level. An example are trait theories of job performance. They inform practitioners at what trait level to select employees. Lastly, in observe(X) theories, practitioners can only measure levels of a causal construct. For example, managers can measure employee trust, but they cannot fix this trust at a certain level. I focus on manipulate(X) theories because they are actionable and rigorous. I discuss criteria for constructs in such theories (e.g., construct unity) and three flaws undermining the development of manipulate(X) theories: (1) the simplification fallacy involves the abstraction of complex phenomena like culture into single constructs, (2) the endogenous-cause problem, when endogenous constructs are treated as exogenous, and (3) construct conflation, the lumping of several constructs under one label.
Two important factors for accessing leadership positions are the ability to signal leadership qualities and to be perceived by others as having such qualities. Yet, research shows that women tend to be evaluated less positively when signaling leadership, which can be explained by two mechanisms. First, there may be actual differences in how women and men signal leadership qualities. Second, there may be differences in how women and men are perceived by others when doing so. We tested these two explanations within one setting for the key leadership quality of exerting influence on others. We conducted an experiment with 160 women and 160 men who delivered a speech in which they signaled their ability and intent to perform well in a subsequent real-effort task, with the goal of persuading observers to invest money in their future performance. The speeches (audio and body movements) were transposed onto both women and men avatars. A total of 320 different participants then watched a random subset of six speeches each and made incentivized decisions as to which speaker(s)’ task performance to invest in based on their evaluation of the speeches. Neither actual nor perceived speaker gender predicted speakers’ ability to exert influence in terms of attracting investments. In the context of our study, we thus do not find evidence that women and men differ in their ability to exert influence, or that others are biased towards women when evaluating their speeches.
In this integrative review, we spotlight the skip-level leader - an often-overlooked yet highly influential figure in organizations. Although empirical interest in skip-level leaders has grown across disciplines, research to date remains dispersed, inconsistent in conceptualization, and disconnected from the broader organizational literature. To provide a clear and comprehensive understanding of skip-level leaders, we organize our review around four key emergent functions, skip level leaders': 1) direct relationship with employee outcomes, 2) indirect relationship with employee outcomes via direct supervisors, 3) interactive relationship via skip-level leader attributes, and 4) the relationship of employee attributes with skip-level leader attributes (i.e., upward relationship). We present these functions both graphically and thematically as a roadmap for future research. Importantly, existing scholarship on skip-level leadership research is dominated by non-causal studies, limiting the field's ability to draw robust causal inferences. We critically evaluate the methodological rigor of this literature, and propose remedies to strengthen future scholarship. By systematically reviewing and synthesizing prior work, we bring greater visibility to skip-level leaders as key actors in leadership science and aim to stimulate deeper inquiry into the diverse ways they shape organizational dynamics.
Leader interpersonal emotion management (IEM), such as leader humorous behaviors and the provision of emotional support, represents a distinct yet integrative leadership construct that highlights leaders’ deliberate efforts to manage others’ emotions. It extends beyond existing leader behavioral constructs by emphasizing the management of others’ emotions as a fundamental behavioral mechanism underpinning effective leadership. Research on IEM has made notable progress over the past few decades; however, critical limitations remain that hinder further development of the literature. In this article, I clarify the conceptualization of leader IEM as the behavioral processes through which leaders manage the emotions of relevant stakeholders and integrate existing research findings into an input-process-output (IPO) framework. This framework comprises three key components: (a) inputs, which consist of ability, motivation, and opportunity factors; (b) processes, which capture broad strategies and specific tactics organized hierarchically; and (c) outputs, which include both immediate and extended outcomes at multiple levels. I further evaluate methodological rigor and propose directions for future research.
Collective leadership emergence—how influence patterns naturally form in groups without formal designation—is a fundamental social dynamic. Understanding this interactive process unfolding over time is hindered by theory proliferation, creating disconnected perspectives and fragmented knowledge. To address this, we utilize agent-based modeling (ABM) to develop formal, testable theories of the dynamic “how” and “why” behind emergence. We synthesize literature identifying foundational components: observable Behavioral Acts, distinct Internal Structures guiding behavior, and crucial Contextual Factors. Building on this, we formalize two distinct theoretical frameworks capturing different proposed mechanisms underlying emergence, focusing on how internal structures process information. Using a shared ABM architecture, we systematically compare these frameworks under varying Contextual Factors, specifically environmental uncertainty and resource cost. Simulations reveal that the distinct mechanisms produce divergent leadership patterns whose relative influence varies systematically with context. This finding supports integrating these perspectives into a comprehensive, context-contingent dual-process theory. Our work demonstrates how ABM can overcome theory fragmentation by enabling formalization, comparison, and integration of process theories via explicit modeling of contextual contingencies, offering a nuanced understanding of collective leadership emergence.
Recent reviews portray humble leadership as a near-universal asset, yet a close inspection of 217 journal articles (274 studies) suggests the construct rests on shaky ground. Prevailing definitions conflate self-insight, appreciation of others, and teachability, variables rooted in other literatures, creating tautologies and valence-based halo. Measurement issues compound the problem: 84% of studies rely on surveys, so ratings of “humble leadership” are conflated by various mechanisms (e.g., evaluative judgments, performance-cue effects, omitted variables) and should not be used as independent variables. We argue that progress on this topic depends on shifting attention from traits and evaluations toward the behaviors that humility denotes: voluntary, public, status-minimizing acts through which leaders redirect credit away from themselves. With this definition, we integrate signaling theory with an idiosyncrasy-credit perspective, arguing that self-effacement behaviors function as costly signals: they translate into humility perceptions only when paired with accrued credit that is placed at risk. It follows, for instance, that signaling humility in the absence of established credit is likely to backfire. We develop testable propositions, a conceptual model linking accrued credit to signal credibility, and an incentive-compatible laboratory paradigm that enables identification of the causal effects of instrumented humility signaling. We conclude with recommendations for behavioral coding, archival text analysis, and experimentally grounded field designs that can replace halo-laden survey inferences with more credible evidence on when humility signaling helps, when it harms, and when it goes unnoticed.
Responsible leadership (RL) has gained growing attention in both academia and organizational practice. However, extant research faces three key limitations: a lack of conceptual clarity (i.e., tautologies and overlaps with other leadership constructs), a conflation of leader behaviors with follower evaluations, and overreliance on surveys, which typically capture supervisory rather than top-executive perspectives. To address these issues, we introduce a novel behavioral measure of responsible CEOs based on linguistic markers. We leverage computeraided text analysis (CATA) to develop and validate a keyword-based CEO RL measure, combining deductively derived words with inductively derived words from machine learning (ML) and human raters. We then empirically examine the relationship between CEO RL and firm Corporate Social Responsibility (CSR). Using a sample of 955 CEOs over 19 years, we find that CEO RL is positively associated with CSR. Finally, we derive a taxonomy of RL behaviors (RLBs) and show overlaps and distinctions with Ethical Leader Signals (ELS). We conclude with a roadmap for future research.
Saturation is a central concept in qualitative research, generally referring to the point at which new data collection no longer yields additional insights. Despite its critical role and widespread application, saturation remains a vague and ill-defined concept with limited practical guidance, manifesting in definitional, methodological, and epistemological contradictions across studies and disciplines. Ambiguity in defining, assessing, and reporting saturation affects a study’s trustworthiness and has detrimental implications for theory development and testing. Moreover, inadequate saturation practices can result in premature cessation of data collection, incomplete theoretical frameworks, and potentially flawed conclusions about leader–follower dynamics and many other phenomena. In addition, when studies lack transparency about saturation, subsequent research can inherit and perpetuate these methodological limitations. To address these challenges, we reviewed 429 sources on saturation and offer a framework: A systematic three-step process for defining, assessing, and providing evidence of saturation with eight critical decision points. We operationalize this framework through actionable, best-practice recommendations, composed of structured questions and corresponding actions, enabling researchers to systematically define, assess, and report saturation in ways that align with their philosophical perspectives, research objectives, methodological choices, and contexts. Through this framework, we advance research in leadership and other domains by strengthening saturation practices necessary for theory development, enhancing our understanding of leadership processes and contexts, and facilitating trustworthy theory development and testing.
Research on Upper Echelons (UE) theory and strategic leadership (SL) has grown substantially. Yet, much of this work remains confined to Western contexts, leaving a gap in understanding how UE theory and SL unfold in non-WEIRD settings—those that are not Western, Educated, Industrialized, Rich, and Democratic. To address this gap, we focus on China, a non-WEIRD context that contrasts sharply with prevailing Western approaches. Drawing on 273 studies, we develop a contextualized strategic leadership framework that advances understanding of the what, how, when, and why of SL in China. To address the what of SL, we introduce a typology of constructs with China-related salience (attributes that gain salience in China), China-related meaning (attributes that acquire additional nuance), and China-related content (attributes shaped by context). We examine the how and when by highlighting China-related contingencies. We assess how primary studies addressed endogeneity, finding that nearly three-fourths engaged with this issue, with considerable variation in their extensiveness. Our study offers several contributions. First, it provides the first contextually integrated SL review that places the national context at the forefront. Second, it extends SL research beyond a Western-centric lens. Finally, it contributes to broader leadership research by responding to calls for greater consideration of context in leadership studies.
