Brian M. Doornenbal , Brian R. Spisak , Paul A. van der Laken
{"title":"Opening the black box: Uncovering the leader trait paradigm through machine learning","authors":"Brian M. Doornenbal , Brian R. Spisak , Paul A. van der Laken","doi":"10.1016/j.leaqua.2021.101515","DOIUrl":"10.1016/j.leaqua.2021.101515","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":48434,"journal":{"name":"Leadership Quarterly","volume":"33 5","pages":"Article 101515"},"PeriodicalIF":7.5,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.leaqua.2021.101515","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46491591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Allan Lee , Ilke Inceoglu , Oliver Hauser , Michael Greene
{"title":"Determining causal relationships in leadership research using Machine Learning: The powerful synergy of experiments and data science","authors":"Allan Lee , Ilke Inceoglu , Oliver Hauser , Michael Greene","doi":"10.1016/j.leaqua.2020.101426","DOIUrl":"10.1016/j.leaqua.2020.101426","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":48434,"journal":{"name":"Leadership Quarterly","volume":"33 5","pages":"Article 101426"},"PeriodicalIF":7.5,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.leaqua.2020.101426","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47152295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effect of charismatic signaling in social media settings: Evidence from TED and Twitter","authors":"Benjamin Tur , Jennifer Harstad , John Antonakis","doi":"10.1016/j.leaqua.2020.101476","DOIUrl":"10.1016/j.leaqua.2020.101476","url":null,"abstract":"<div><p>Informal leaders in social media currently characterize a large part of political and economic communication on various challenges societies face, whether localized or transborder (e.g., COVID-19 pandemic, global warming). Scholars have theorized that charismatic signaling is effective in informal leadership settings; yet empirical evidence remains scarce in understanding a ubiquitous phenomenon that marks our times and plays an important role in shaping public opinion. In this article, we used two unique data sets extracted from social media to investigate the success of charisma for informal leaders, leaders who signal their beliefs and preferences to others but having no formal authority over them. Social media offers us a standardized medium as well as a natural environment to test our predictions. Using a sample of TED talks and tweets, we coded for objective markers of charisma and found that using more verbal charismatic signals predicted (a) higher views for TED talks as well as higher ratings for the extent to which the talk was found to be inspiring—beyond attractiveness and nonverbal behavior—and (b) more retweets. We discuss the implications of such results for both theory and practice in the media age.</p></div>","PeriodicalId":48434,"journal":{"name":"Leadership Quarterly","volume":"33 5","pages":"Article 101476"},"PeriodicalIF":7.5,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.leaqua.2020.101476","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49356036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alina Lungeanu, Leslie A. DeChurch, Noshir S. Contractor
{"title":"Leading teams over time through space: Computational experiments on leadership network archetypes","authors":"Alina Lungeanu, Leslie A. DeChurch, Noshir S. Contractor","doi":"10.1016/j.leaqua.2021.101595","DOIUrl":"10.1016/j.leaqua.2021.101595","url":null,"abstract":"<div><p>A key function of team leadership is building and sustaining shared mental models. Topological approaches to leadership identify structural patterns, such as decentralized and shared leadership that empower members to collectively lead themselves toward important goals, but an open question is the particular form of leadership that best promotes team mental models. We explored 8 leadership archetypes using a computational model fit on data from a unique sample of NASA analog space crews. Data from 4, 4-member crews living and working together for 45-days were used to parameterize the model which then accurately predicted mental models for the next set of 4-member crews. The validated model was used to conduct virtual experiments exploring the effects of leadership structures on mental models. We found shared leadership has the largest effect on shared mental models, followed by hierarchical and coordinated leadership. These findings extend shared leadership theory leveraging computational methods to examine leadership archetypes and suggest propositions about how they shape team functioning over time.</p></div>","PeriodicalId":48434,"journal":{"name":"Leadership Quarterly","volume":"33 5","pages":"Article 101595"},"PeriodicalIF":7.5,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73084324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sudeep Bhatia , Christopher Y. Olivola , Nazlı Bhatia , Amnah Ameen
{"title":"Predicting leadership perception with large-scale natural language data","authors":"Sudeep Bhatia , Christopher Y. Olivola , Nazlı Bhatia , Amnah Ameen","doi":"10.1016/j.leaqua.2021.101535","DOIUrl":"10.1016/j.leaqua.2021.101535","url":null,"abstract":"<div><p>We present a computational method for predicting, and identifying the correlates of, leadership perceptions for prominent individuals. Our approach proxies knowledge representations for these individuals using high-dimensional semantic vectors derived from large-scale news media datasets. It then applies machine learning techniques to build a model that maps these vectors onto participant ratings of leadership effectiveness. This method greatly outperforms other approaches and achieves accuracy rates comparable to human participants in predicting leadership effectiveness judgments. Crucially, it relies on attributes and associations identified by established theories of leadership perception—notably implicit leadership theories—as guiding lay leadership perception. Thus, our model appears to have learnt the same implicit leadership cues as our human participants. In addition, we show that our approach can be used to not only predict leadership effectiveness judgments, but also to identify dimensions that people associate with effective leadership, as well as quantify the extent of this association for each dimension. We illustrate the broad applicability of our method by using it to predict leadership perceptions for over 6000 individuals in the public sphere, and to algorithmically uncover the particular traits, concepts, and attributes that people most strongly associate with effective leaders.</p></div>","PeriodicalId":48434,"journal":{"name":"Leadership Quarterly","volume":"33 5","pages":"Article 101535"},"PeriodicalIF":7.5,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.leaqua.2021.101535","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77500502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
George C. Banks , Shelley D. Dionne , Marianne Schmid Mast , Hiroki Sayama
{"title":"Leadership in the digital era: A review of who, what, when, where, and why","authors":"George C. Banks , Shelley D. Dionne , Marianne Schmid Mast , Hiroki Sayama","doi":"10.1016/j.leaqua.2022.101634","DOIUrl":"10.1016/j.leaqua.2022.101634","url":null,"abstract":"<div><p>Leadership as a social influence process has always involved a complex set of phenomena that demands an interdisciplinary lens. Leadership scholarship has now entered into a digital era. In a digital era, the overall phenomenon is changing, as are the tools through which we study it, demanding a new “lens” through which we view leadership. Yet, this raises the question, to what extent is leadership different in a digital era? In acknowledgement of this trend, a special issue was commissioned at The Leadership Quarterly that sought to stimulate the imagination of leadership scholars and practitioners. In the current work, we begin with a brief review of who, what, when, where and why of digital leadership. We cover leadership in informal contexts (e.g., social media), generalization from face-to-face to virtual contexts, computational modeling, the leveraging of technology (e.g., machine learning; Big Data), as well methodological how-to guides. We then plot a path forward for leadership scholars in the dawn of the digital era.</p></div>","PeriodicalId":48434,"journal":{"name":"Leadership Quarterly","volume":"33 5","pages":"Article 101634"},"PeriodicalIF":7.5,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1048984322000376/pdfft?md5=b794b741ecdf822c79558e8cbed40b80&pid=1-s2.0-S1048984322000376-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50166254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scott Tonidandel , Karoline M. Summerville , William A. Gentry , Stephen F. Young
{"title":"Using structural topic modeling to gain insight into challenges faced by leaders","authors":"Scott Tonidandel , Karoline M. Summerville , William A. Gentry , Stephen F. Young","doi":"10.1016/j.leaqua.2021.101576","DOIUrl":"10.1016/j.leaqua.2021.101576","url":null,"abstract":"<div><p>This paper leverages technological and methodological advances in natural language processing to advance our understanding and approaches to leadership research by introducing structural topic models (STM) to researchers wanting to inductively code massive amounts of unstructured texts. Specifically, we illustrate the application of STM applied to a large corpus (N ≈ 8000) of unstructured text responses from a diverse sample of leaders to inductively generate a classification system of leader challenges and simultaneously examine whether the challenges being experienced by leaders covary with leader characteristics. Overall, we identify nine central leader challenges. Results indicate that certain leader challenges are more prevalent depending on the leader’s characteristics (e.g., gender), and that two challenges, Daily Management Activities and Communication, were significantly related to boss’ ratings of performance. We also highlight additional applications of this technique to aid leadership researchers who wish to inductively derive meaning from large amounts of unstructured texts.</p></div>","PeriodicalId":48434,"journal":{"name":"Leadership Quarterly","volume":"33 5","pages":"Article 101576"},"PeriodicalIF":7.5,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77146654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nonhlanhla Khumalo , Kitty B. Dumont , Sven Waldzus
{"title":"Leaders’ influence on collective action: An identity leadership perspective","authors":"Nonhlanhla Khumalo , Kitty B. Dumont , Sven Waldzus","doi":"10.1016/j.leaqua.2022.101609","DOIUrl":"10.1016/j.leaqua.2022.101609","url":null,"abstract":"<div><p>What makes followers act collectively when called upon by their leaders? To answer this question, participants were randomly allocated to leader–follower relationships embedded either in a partisan group or a workgroup context; and the relationship between identity leadership and collective action through ingroup identification (Study 1: N = 293) or both ingroup identification and group-efficacy (Study 2: N = 338) were assessed. Based on the model of identity leadership, we predicted and found that identity leadership was positively related with intentions for collective action when called upon by the leader, both via ingroup identification and belief in group efficacy. As predicted, the social identity process for the effectiveness of identity leadership was more important in partisan groups than in workgroups. The efficacy related process was group context invariant. These results have implications for our understanding of group processes involved in the leadership in collective action.</p></div>","PeriodicalId":48434,"journal":{"name":"Leadership Quarterly","volume":"33 4","pages":"Article 101609"},"PeriodicalIF":7.5,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82340573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Valeria Amata Giannella , Stefano Pagliaro , Manuela Barreto
{"title":"Leader’s morality, prototypicality, and followers’ reactions","authors":"Valeria Amata Giannella , Stefano Pagliaro , Manuela Barreto","doi":"10.1016/j.leaqua.2021.101596","DOIUrl":"10.1016/j.leaqua.2021.101596","url":null,"abstract":"<div><p>We examine the effects of moral (vs. competent) leadership on followers' leader evaluations and endorsement. In Study 1 (N = 157), followers evaluated a leader more negatively and endorsed them less when they failed on morality than competence. An indirect effect from leader morality to leader evaluation, through perceived group prototypicality emerged, demonstrating the identity-basis of this evaluation. In Studies 2 (N = 150), 3 (N = 297), and 4 (N = 192) participants considered incongruous situations in which the leader failed on morality but succeed on competence, or vice-versa. Followers expressed more negative evaluations and less endorsement of an immoral but competent leader than of a moral but incompetent leader, through group prototypicality. In Study 4, we manipulated group prototypicality. A leader considered prototypical of the group received worse evaluations when they behaved immorally, irrespective of their competence. Results contribute to the understanding of leader-followers dynamics.</p></div>","PeriodicalId":48434,"journal":{"name":"Leadership Quarterly","volume":"33 4","pages":"Article 101596"},"PeriodicalIF":7.5,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76917468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Phillip M. Jolly , Ksenia O. Krylova , James S. Phillips
{"title":"Leader intention, misconduct and damaged relational follower identity: A moral decision making perspective","authors":"Phillip M. Jolly , Ksenia O. Krylova , James S. Phillips","doi":"10.1016/j.leaqua.2020.101425","DOIUrl":"10.1016/j.leaqua.2020.101425","url":null,"abstract":"<div><p>We demonstrate the value of a moral decision making paradigm for investigating the effects of intention and harm on followers' reactions to leaders' wrongdoing. We also introduce damaged relational identity as a mediator of these effects. Participants were assigned to one of four conditions in which intention to harm and harm were manipulated. The study was conducted using a stochastic, incentivized economic game that involved real monetary consequences for the followers. The results indicated that intention to harm was the primary determinant of followers' withdrawal behavior while actual harm had no effect on withdrawal. A desire to punish the offending leader was influenced by both intention and harm. Damaged relational identity mediated the effect of intention on withdrawal behavior and punishment. In contrast, harm's effect on punishment was direct. We hope that our study stimulates additional research on leader misconduct using intention and identification processes as linchpins.</p></div>","PeriodicalId":48434,"journal":{"name":"Leadership Quarterly","volume":"33 4","pages":"Article 101425"},"PeriodicalIF":7.5,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.leaqua.2020.101425","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87415883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}