Leadership Quarterly最新文献

This article presents results from two complementary experiments that examine the effects of a potential obstacle to female leadership: gendered language in the form of masculine leadership titles. In the first experiment (N = 1753), we utilize an unobtrusive writing task to find that a masculine title (“Chairman” vs. “Chair”) increases assumptions that a hypothetical leader is a man, even when the leader’s gender is left unspecified. In the second experiment (N = 1000), we use a surprise recall task and a treatment that unambiguously communicates the leader’s gender to find that a masculine title increases the accuracy of leader recollection only when the leader is a man. In both studies, we find no significant differences by gender of respondents in the effects of masculine language on reinforcing the link between masculinity and leadership. Thus, implicitly sexist language as codified in masculine titles can reinforce stereotypes that tie masculinity to leadership and consequently, weaken the connection between women and leadership.

Environment-leader congruency yields better adaptability manifested in better decision-making. The military combat environment offers advantages for leaders with ADHD; though they are expected to encounter difficulties due to executive dysfunction. This research aspired to increase the congruency effect for leaders with ADHD in a stressful military environment through interventions that improve executive decisions. We hypothesized that making decisions in isolation will improve decision quality overall; while face-to-face interventions that activate commitment and focused attention will promote decision-making particularly among respondents with ADHD. A large-scale controlled study explored candidates’ responses to combat dilemmas under four randomly assigned interventions: Isolation, Simple face-to-face, Withholding response face-to-face; and Control-peer-group classroom setting. The main effects of improved decision-making in isolation and simple face-to-face settings were shown across groups. Further, both face-to-face interventions interacted with ADHD, yielding stronger effects and better performance among participants with ADHD as compared to those without ADHD. Current findings highlight the importance of finding suitable conditions for enabling improved executive decisions among candidates with ADHD. Introducing economical and easy-to-operate face-to-face interventions enhances decision quality in a highly represented neurodiverse population. Current findings may generalize to an array of high-risk/high-stress working environments, providing ecologically relevant support for young leaders from neurodiverse populations.

Previous research has demonstrated that social stereotypes associated with women's gender can preclude them from leadership positions. It remains unclear whether these stereotypes affect how people perceive male and female leaders, however. To examine people's stereotypes, we extracted their mental representations of male and female leaders and typical men/women (referred to as nonleaders) using reverse correlation. We then asked perceivers to rate these prototypes’ apparent leadership ability and traits related to power and warmth across contexts that represented typically masculine, feminine, or neutral domains. Leaders in a feminine context appeared more leaderlike than nonleaders, but as equally leaderlike in neutral and masculine contexts. Moreover, female leader faces appeared more powerful than female nonleader faces but male leader and nonleader faces appeared equally powerful. Male leaders were perceived as warmer than male nonleaders, however, whereas female leaders and nonleaders were perceived as equally warm. Thus, people’s gender, social stereotypes, and the context in which leaders are judged influence how people conceive of male and female leaders, with counterstereotypical attributes distinguishing leaders within their gender.

The provision of feedback is fundamental for promoting employee performance in modern organisations; however, little is known about how the quality of feedback affects performance. We report an experiment where subjects perform a real-effort task repeatedly in a flat-wage environment which varies the quality of feedback across treatments. In the baseline treatment, subjects receive no feedback about their rank in their group. In the two main treatments, feedback quality varies in that subjects know (“High-Quality Feedback”) or do not know (“Low-Quality Feedback”) their exact rank in their group. We show that the quality of feedback is an important driver of productivity. Average performance is significantly higher for high-quality feedback than for low-quality or no feedback, where no significant overall performance differences are observed. Our results have significant implications for designing and implementing cost-effective policies within organisations.

The study of emotional intelligence (EI) in the field of leadership, and in the organizational sciences in general, has often been characterized by controversy and criticism. But the study of EI has nonetheless persisted by developing new measures and models to address these concerns. In a prior letter exchange by Antonakis, Ashkanasy, and Dasborough (2009), two author teams debated the role of EI in the leadership literature, but also set an agenda for research and reconciliation for the future. The present exchange revisits these arguments using evidence accumulated over the past decade. Specifically, the authors debate not only the evidence for the predictive power of EI for workplace outcomes, but also the validity of EI as a construct, the measurement of EI, and the appropriateness of analytical tests for establishing the value of EI. Although the author teams agree on the value of the study of emotions and the need for rigorous research in this area, they nonetheless propose alternative agendas and priorities for the future. Further, they conclude that the issues identified in this exchange are not unique to the study of EI; but should also serve to inform the study of other personality factors and leadership more broadly.

Attractive political candidates receive more votes on Election Day compared to their less attractive competitors. One well-cited theoretical account for this attractiveness effect (White et al., 2013) holds that it reflects an adaptive psychological response to disease threats. Voters are predicted to upregulate preferences for attractiveness because it constitutes a cue to health. The global COVID-19 pandemic constitutes an ecologically relevant and realistic setting for further testing this prediction. Here, we report the results from six tests of the prediction based on two large and nationally representative surveys conducted in Denmark (n = 3297) at the outbreak of the pandemic and one year later. Utilizing experimental techniques, validated individual difference measures of perceived disease threat and geographic data on COVID-19 severity, we do not find that disease threats like the COVID-19 pandemic upregulate preferences for attractive and healthy political or non-political leaders. Instead, respondents display heightened preferences for health in socially proximate relations (i.e. colleagues). Moreover, individuals who react aversively to situations involving risks of pathogen transmission (scoring high in Germ Aversion) report higher importance of a wide range of leadership traits, rather than for health and attractiveness in particular. Results are discussed in relation to evolutionary accounts of leadership and followership.

This paper provides experimental evidence on how monitoring intensity shapes the impact of leadership instruments like leading-by-example and punishment. The results show that, with low monitoring intensity, neither leading-by-example nor punishment increases cooperation if the leader can already send nonbinding signals about desired behavior. We identify two different reasons for this effect. Regarding leading-by-example, it is the cautiousness of the leader. Leaders are reluctant to recommend cooperative behavior and act accordingly, even though followers are particularly reciprocal in this context. Regarding punishment, it is the level of monitoring that matters. Monitoring of individual follower behavior increases the cooperation of leaders and followers across all treatments, but in particular, if the leader can punish uncooperative behavior. This result implies that monitoring in itself does not have a negative impact on the inclination to cooperate. It suggests that any motivational crowding out effect derives from a leader’s choice of monitoring, as it signals low trust in the followers. The paper concludes with a discussion of the implications.

Drawing upon signaling theory, charismatic leadership tactics (CLTs) have been identified as a trainable set of skills. Although organizations rely on technology-mediated communication, the effects of CLTs have not been examined in a virtual context. Preregistered experiments were conducted in face-to-face (Study 1; n = 121) and virtual settings (Study 2; n = 128) in the United States. In Study 3, we conducted virtual replications in Austria (n = 134), France (n = 137), India (n = 128), and Mexico (n = 124). Combined with past experiments, the meta-analytic effect of CLTs on performance (Cohen’s d = 0.52 in-person, k = 4; Cohen’s d = 0.21 overall, k = 10) and engagement in an extra-role task (Cohen’s d = 0.19 overall; k = 6) indicate large to moderate effects. Yet, for performance in a virtual context Cohen’s d ranged from −0.25 to 0.17 (Cohen’s d = 0.01 overall; k = 6). Study 4 (n = 129) provided mixed support for signaling theory in a virtual context, linking CLTs to some positive evaluations. We conclude with guidance for future research on charismatic leadership and signaling theory.

Understanding the traits that define a leader is a perennial quest. An ongoing debate surrounds the complexity required to unravel the leader trait paradigm. With the advancement of machine learning, scholars are now better equipped to model leadership as an outcome of complex patterns in traits. However, interpreting those models is often harder. In this paper, we guide researchers in the application of machine learning techniques to uncover complex relationships. Specifically, we demonstrate how applying machine learning can help to assess the complexity of a relationship and show techniques that help interpret the outcomes of “black box” machine learning algorithms. While demonstrating techniques to uncover complex relationships, we are using the Big Five Inventory and need for cognition to predict leadership role occupancy. Among our sample (n = 3385), we find that the leader trait paradigm can benefit from modeling complexity beyond linear effects and generate several interpretable results.

Machine Learning (ML) techniques offer exciting new avenues for leadership research. In this paper we discuss how ML techniques can be used to inform predictive and causal models of leadership effects and clarify why both types of model are important for leadership research. We propose combining ML and experimental designs to draw causal inferences by introducing a recently developed technique to isolate “heterogeneous treatment effects.” We provide a step-by-step guide on how to design studies that combine field experiments with the application of ML to establish causal relationships with maximal predictive power. Drawing on examples in the leadership literature, we illustrate how the suggested approach can be applied to examine the impact of, for example, leadership behavior on follower outcomes. We also discuss how ML can be used to advance leadership research from theoretical, methodological and practical perspectives and consider limitations.