Leadership in social groups is often a dynamic characteristic that emerges from interactions and opinion exchange. Empirical evidence suggests that individuals with strong opinions tend to gain influence, at the same time maintaining alignment with the social context is crucial for sustained leadership. Motivated by the social psychology literature that supports these empirical observations, we propose a novel dynamical system in which opinions and leadership co-evolve within a social network. Our model extends the Friedkin-Johnsen framework by making susceptibility to peer influence time-dependent, turning it into the leadership variable. Leadership strengthens when an agent holds strong yet socially aligned opinions, and declines when such alignment is lost, capturing the trade-off between conviction and social acceptance. After illustrating the emergent behavior of this complex system, we formally analyze the coupled dynamics, establishing sufficient conditions for convergence to a non-trivial equilibrium, and examining two time-scale separation regimes reflecting scenarios where opinion and leadership evolve at different speeds.
Leadership in social groups emerges dynamically through interaction and opinion exchange. Empirical evidence indicates that individuals expressing strong opinions tend to gain influence, while sustained leadership critically depends on maintaining alignment with the surrounding social context. Motivated by these observations, we introduce a coupled dynamical model describing the simultaneous evolution of opinions and leadership in a networked population. Extending the Friedkin-Johnsen framework, we represent leadership as a time-varying susceptibility to social influence, which evolves according to a game-theoretic mechanism, consistent with social psychology evidence. Within this setting, agents strengthen their leadership by expressing decisive yet socially coherent opinions, whereas misalignment with the collective state results in a loss of influence. We analyze the coupled dynamics and establish sufficient conditions to identify which agents necessarily emerge as leaders and which act as followers in the social network.
With the growing popularity of blockchains, modern chained BFT protocols combining chaining and leader rotation to obtain better efficiency and leadership democracy have received increasing interest. Although the efficiency provisions of chained BFT protocols have been thoroughly analyzed, the leadership democracy has received little attention in prior work. In this paper, we scrutinize the leadership democracy of four representative chained BFT protocols, especially under attack. To this end, we propose a unified framework with two evaluation metrics, i.e., chain quality and censorship resilience, and quantitatively analyze chosen protocols through the Markov Decision Process (MDP). With this framework, we further examine the impact of two key components, i.e., voting pattern and leader rotation on leadership democracy. Our results indicate that leader rotation is not enough to provide the leadership democracy guarantee; an adversary could utilize the design, e.g., voting pattern, to deteriorate the leadership democracy significantly. Based on the analysis results, we propose customized countermeasures for three evaluated protocols to improve their leadership democracy with only s
Context: Leadership has been extensively studied in management and agile software development; however, prior research predominantly focuses on formal roles and predefined leadership models, offering limited insight into how leadership is experienced and demonstrated by software practitioners in everyday practice. Objective: Our goal is to identify and categorize leadership practices as perceived and reported by software development practitioners based on their professional experiences. Method: We conducted a content analysis of 116 practitioner-authored articles published on the Dev.to online community. Articles were systematically collected, screened, and coded, resulting in the extraction, correlation analysis and categorization of leadership practices grounded in practitioners narratives. Results: We identified 103 practices for software project leaders, distinguished between recommended and discouraged ones. These practices were organized into five categories: People Management & Development, Processes & Execution, Professional & Personal Growth, Communication & Articulation and Strategic Vision. The most recurrent recommended practices include Cultivating &
Governing common-pool resources requires agents to develop enduring strategies through cooperation and self-governance to avoid collective failure. While foundation models have shown potential for cooperation in these settings, existing multi-agent research provides little insight into whether structured leadership and election mechanisms can improve collective decision making. The lack of such a critical organizational feature ubiquitous in human society presents a significant shortcoming of the current methods. In this work we aim to directly address whether leadership and elections can support improved social welfare and cooperation through multi-agent simulation with LLMs. We present our open-source framework that simulates leadership through elected personas and candidate-driven agendas and carry out an empirical study of LLMs under controlled governance conditions. Our experiments demonstrate that having elected leadership improves social welfare scores by 55.4% and survival time by 128.6% across a range of high performing LLMs. Through the construction of an agent social graph we compute centrality metrics to assess the social influence of leader personas and also analyze rh
Artificial Intelligence is currently and rapidly changing the way organizations and businesses operate. Ethical leadership has become significantly important since organizations and businesses across various sectors are evolving with AI. Organizations and businesses may be facing several challenges and potential opportunities when using AI. Ethical leadership plays a central role in guiding organizations in facing those challenges and maximizing on those opportunities. This article explores the essence of ethical leadership in the age of AI, starting with a simplified introduction of ethical leadership and AI, then dives into an understanding of ethical leadership, its characteristics and importance, the ethical challenges AI causes including bias in AI algorithms. The opportunities for ethical leadership in the age of AI answers the question: What actionable strategies can leaders employ to address the challenges and leverage opportunities? and describes the benefits for organizations through these opportunities. A proposed framework for ethical leadership is presented in this article, incorporating the core components: fairness, transparency, sustainability etc. Through the impor
This study investigates the significance of emotional intelligence (EI) as a fundamental component of effective leadership and its impact on building cohesive, motivated, and high-performing teams. Drawing on data from a survey of 100 professionals, the research examines how EI competencies including self-awareness, self-regulation, empathy, and social skills shape leadership effectiveness, team collaboration, conflict resolution, and workplace motivation. The results demonstrate strong correlations between EI and key leadership traits such as empathy, ethical conduct, social competence, and motivational effectiveness. Leaders with higher levels of EI are perceived as more empathetic, ethical, and capable of fostering trust, resolving conflicts, and inspiring commitment, thereby improving team dynamics and overall organizational performance. The study also highlights that ethical leadership significantly enhances motivation and that social competence is essential for engaging and aligning teams toward common goals. While the findings are exploratory due to the limited sample size, they provide valuable insights for leadership development programs, emphasizing the importance of inte
This paper introduces HyperSumm-RL, a hypertext-aware summarization and interaction analysis framework designed to investigate human perceptions of social robot leadership through long-form dialogue. The system utilizes a structured Natural Language Processing (NLP) workflow that combines transformer-based long dialogue summarization, leadership style modeling, and user response analysis, enabling scalable evaluation of social robots in complex human-robot interaction (HRI) settings. Unlike prior work that focuses on static or task-oriented HRI, HyperSumm-RL captures and hypertextually organizes dynamic conversational exchanges into navigable, semantically rich representations which allows researchers to trace interaction threads, identify influence cues, and analyze leadership framing over time. The contributions of this study are threefold: (1) we present a novel infrastructure for summarizing and linking long, multi-turn dialogues using leadership-style taxonomies; (2) we propose an interactive hypertext model that supports relational navigation across conversational themes, participant responses, and robot behavior modes; and (3) we demonstrate the utility of this system in int
Letters of recommendation (LORs) provide valuable insights into candidates' capabilities and experiences beyond standardized test scores. However, reviewing these text-heavy materials is time-consuming and labor-intensive. To address this challenge and support the admission committee in providing feedback for students' professional growth, our study introduces LORI: LOR Insights, a novel AI-based detection tool for assessing leadership skills in LORs submitted by online master's program applicants. By employing natural language processing and leveraging large language models using RoBERTa and LLAMA, we seek to identify leadership attributes such as teamwork, communication, and innovation. Our latest RoBERTa model achieves a weighted F1 score of 91.6%, a precision of 92.4%, and a recall of 91.6%, showing a strong level of consistency in our test data. With the growing importance of leadership skills in the STEM sector, integrating LORI into the graduate admissions process is crucial for accurately assessing applicants' leadership capabilities. This approach not only streamlines the admissions process but also automates and ensures a more comprehensive evaluation of candidates' capab
Orientation: The study explores the connections among servant leadership, burnout, and work ethic culture in organizations. It aims to provide a detailed understanding of how servant leadership influences work ethic culture, especially by considering the role of burnout. Research Purpose: This study aims to understand how servant leadership influences work ethic culture and explore the mediating role of burnout in this relationship. Motivation for the Study: This study wants to fill gaps in our understanding of how servant leadership, burnout, and work ethic culture are connected. It seeks to add useful insights to what we already know from previous research. Research Approach/Design and Method: The study, using surveys and statistics, examines the links between servant leadership, burnout, and work ethic culture in 113 hotels in Bandung, Indonesia, with 339 participants. A 183-sample, chosen with a 0.05 margin of error, underwent SEM-PLS analysis using SmartPLS 3.0. Main Findings: The key findings underscore that servant leadership exerts a positive influence on work ethic culture, and burnout plays a pivotal mediating role in this dynamic. The results shed light on the intricate
This study examines the influence of various leadership styles on project efficiency across diverse organizational contexts. Using a quantitative research design, data were collected through a survey of 100 project professionals representing multiple industries, and analyzed with statistical techniques, including Spearman correlation, to explore the relationship between leadership behaviors and project performance. The results show that leadership style significantly affects project outcomes, with constructive feedback, clear communication of goals, role clarity, and encouragement of team initiative emerging as the most impactful behaviors. These factors strongly correlate with project success indicators such as goal achievement, budget adherence, and stakeholder satisfaction. The findings also highlight areas needing improvement, including time management, conflict resolution, and involving team members in decision-making. Moreover, the study provides empirical evidence that leadership styles directly shape team dynamics, motivation, and collaboration, which in turn influence overall efficiency. While democratic and participative approaches enhance engagement, they do not always t
Delegation and leadership are critical components of software management, as they play a crucial role in determining the success of the software development process. This study examined the relationship between delegation and leadership in software management and the impact of these factors on project outcomes. Results showed that effective delegation and transformational leadership styles can improve workflow, enhance team motivation and productivity, and ultimately lead to successful software development projects. The findings of this study have important implications for software management practices, as they suggest that organizations and software managers should prioritize the development of effective delegation and leadership practices to ensure the success of their software development initiatives. Further research is needed to explore the complex interplay between delegation and leadership in software management and to identify best practices for improving these processes.
We show that the ability to lead groups of humans is predicted by leadership skill with Artificially Intelligent agents. In a large pre-registered lab experiment, human leaders worked with AI agents to solve problems. Their performance on this 'AI leadership test' was strongly correlated with their causal impact on human teams, which we estimate by repeatedly randomly assigning leaders to groups of human followers and measuring team performance. Successful leaders of both humans and AI agents ask more questions and engage in more conversational turn-taking; they score higher on measures of social intelligence, fluid intelligence, and decision-making skill, but do not differ in gender, age, ethnicity or education. Our findings indicate that AI agents can be effective proxies for human participants in social experiments, which greatly simplifies the measurement of leadership and teamwork skills.
This paper addresses the task of assessing PICU team's leadership skills by developing an automated analysis framework based on egocentric vision. We identify key behavioral cues, including fixation object, eye contact, and conversation patterns, as essential indicators of leadership assessment. In order to capture these multimodal signals, we employ Aria Glasses to record egocentric video, audio, gaze, and head movement data. We collect one-hour videos of four simulated sessions involving doctors with different roles and levels. To automate data processing, we propose a method leveraging REMoDNaV, SAM, YOLO, and ChatGPT for fixation object detection, eye contact detection, and conversation classification. In the experiments, significant correlations are observed between leadership skills and behavioral metrics, i.e., the output of our proposed methods, such as fixation time, transition patterns, and direct orders in speech. These results indicate that our proposed data collection and analysis framework can effectively solve skill assessment for training PICU teams.
Given that experience is a pivotal dimension of learning processes in the field of leadership, the ongoing and unresolved issue is how such experiential moments could be provided when developing leadership skills and competencies. Role-plays and business simulations are widely used in this context as they are said to teach relevant social leadership skills, like those required by everyday communication to followers, by decision-making on compensation, evaluating performance, dealing with conflicts, or terminating contracts. However, the effectiveness of simulations can highly vary depending on the counterpart's ability to act in the given scenarios. In our project, we deal with how immersive media could create experiential learning based on simulations for leadership development. In recent years different variations of extended reality got significant technological improvements. Head-mounted displays are an easy and cost-efficient way to present high-resolution virtual environments. For groups of people that are part of an immersive experience, cave automatic virtual environments offer an excellent trade-off between actual exchange with other humans and interaction with virtual con
Leadership in agile teams is a collective responsibility where team members share leadership work based on expertise and skills. However, the understanding of leadership in this context is limited. This study explores the under-researched area of prototypical leadership, aiming to understand if and how leaders who are perceived as more representative of the team are more effective leaders. Qualitative interviews were conducted with eleven members of six agile software teams in five Swedish companies from various industries and sizes. In this study, the effectiveness of leadership was perceived as higher when it emerged from within the team or when leaders aligned with the group. In addition, leaders in managerial roles that align with the team's shared values and traits were perceived as more effective, contributing to overall team success.
This paper develops a novel methodological framework for assessing leadership potential and productivity within organisational structure represented by directed graphs. In this setting, individuals are modeled as nodes and asymmetric supervisory or reporting relationships as directed edges. Leveraging the theory of transferable utility cooperative games, we introduce the Average Forest (AF) measure, a marginalist leadership measure grounded in the enumeration of maximal spanning forests, where teams are hierarchically structured as arborescences. The AF measure captures each agent`s expected contribution across all feasible team configurations under the assumption of superadditivity of the underlying game. We further define a measure of organisational productivity as the expected aggregate value derived from these configurations. The paper investigates key theoretical properties of the AF measure -- such as linearity, component feasibility, and monotonicity -- and analyzes its sensitivity to structural modifications in the underlying digraph. To address computational challenges in large networks, a Monte Carlo simulation algorithm is proposed for practical estimation. This framewor
Over the years, the concept of leadership has experienced a paradigm shift - from solitary leader (centralized leadership) to de-centralized leadership or distributed leadership. This paper explores the idea that centralized leadership, as earlier suggested, negatively impacts team performance. I applied the hypothesis to cricket, a sport in which leaders play an important role in team's success. I generated batting partnership network and evaluated the central-most player in the team, applying tools of social network analysis. Analyzing 3420 matches in one day international cricket and 1979 Test matches involving 10 teams, I examined the impact of centralized leadership in outcome of a contest. I observed that the odds for winning a one day international match under centralized leadership is 30% higher than the odds for winning under de-centralized leadership. In both forms of cricket (Test and one day international ), I failed to find evidence that distributed leadership is associated with higher team performance. These results suggest important implications for cricket administrators in development and management of working teams.
Leadership is evolving dynamically from an individual endeavor to shared efforts. This paper aims to advance our understanding of shared leadership in scientific teams. We define three kinds of leaders, junior (10-15), mid (15-20), and senior (20+) based on career age. By considering the combinations of any two leaders, we distinguish shared leadership as heterogeneous when leaders are in different age cohorts and homogeneous when leaders are in the same age cohort. Drawing on 1,845,351 CS, 254,039 Sociology, and 193,338 Business teams with two leaders in the OpenAlex dataset, we identify that heterogeneous shared leadership brings higher citation impact for teams than homogeneous shared leadership. Specifically, when junior leaders are paired with senior leaders, it significantly increases team citation ranking by 1-2%, in comparison with two leaders of similar age. We explore the patterns between homogeneous leaders and heterogeneous leaders from team scale, expertise composition, and knowledge recency perspectives. Compared with homogeneous leaders, heterogeneous leaders are more adaptive in large teams, have more diverse expertise, and trace both the newest and oldest reference
In this project, we describe a method of modeling semantic leadership across a set of communities associated with the #BlackLivesMatter movement, which has been informed by qualitative research on the structure of social media and Black Twitter in particular. We describe our bespoke approaches to time-binning, community clustering, and connecting communities over time, as well as our adaptation of state-of-the-art approaches to semantic change detection and semantic leadership induction. We find substantial evidence of the leadership role of BLM activists and progressives, as well as Black celebrities. We also find evidence of the sustained engagement of the conservative community with this discourse, suggesting an alternative explanation for how we arrived at the present moment, in which "anti-woke" and "anti-CRT" bills are being enacted nationwide.