Active Versus Avoidant Leadership in Information Technology: Contrasting Emotional-Intelligence Profiles of Transformational, Transactional, and Passive-Avoidant Leaders

1. Introduction

Leadership research often privileges positive styles and treats passive or laissez-faire leadership as a residual category. Yet avoidance, delayed intervention, and the failure to provide leadership are behaviors with organizational consequences, particularly during technology change. Information technology environments create frequent demands for timely decisions, coordination, problem resolution, and employee support. A passive leader can therefore shape outcomes through inaction as much as an active leader shapes them through action.

The dissertation dataset offers a useful contrast. Transformational leadership predicted all four emotional-intelligence components. Transactional leadership predicted three of four. Overall, EI predicted both transformational and transactional leadership. In contrast, EI did not significantly predict passive-avoidant leadership. Of the seven original null hypotheses, the first six were rejected and only the seventh - the EI/passive-avoidant relationship - was not rejected.

This article argues that the pattern is theoretically more useful when framed as a distinction between active and avoidant leadership. The purpose is not to elevate a null result into proof of no relationship in all settings. Rather, the non-significant finding defines a boundary in this sample and helps clarify that EI was selectively associated with leadership forms requiring active engagement.

2. Theoretical Background

2.1 Active leadership

Transformational and transactional leadership differ in their motivational mechanisms, but both require leaders to engage followers. Transformational leaders articulate vision, stimulate new thinking, model values, and develop followers. Transactional leaders clarify expectations, exchange rewards for performance, monitor standards, and intervene when deviations occur. Both styles therefore involve attention, communication, and behavioral response.

Emotional intelligence may support these activities by helping leaders perceive the affective context, regulate their own reactions, manage followers' emotions, and use emotional information in problem solving. Contemporary reviews indicate that leader EI is associated with a range of leadership behaviors and effectiveness outcomes (Gerhardt et al., 2026). In digital transformation, EI may also help leaders balance task, relation, change, and external-oriented behaviors (Orkamo et al., 2025).

2.2 Passive-avoidant leadership

Passive-avoidant leadership includes laissez-faire behavior and passive management-by-exception. It is characterized by delayed decisions, limited intervention, avoidance of responsibility, or action only after problems become serious. Although historically conceptualized as an absence of leadership, recent research treats laissez-faire leadership as an active research problem because it can influence employee experience and change readiness.

Groulx et al. (2024), for example, found that manager emotional exhaustion was associated with higher laissez-faire leadership, which in turn undermined team psychological safety and readiness for change. Zheng and Li (2024) describe laissez-faire leadership as potentially double-edged: the absence of guidance may be experienced as resource loss but can also be interpreted as autonomy under some conditions. These findings suggest that passive leadership is not psychologically empty; its antecedents and consequences deserve separate analysis.

2.3 Why emotional intelligence may differentiate active from avoidant leadership

EI is behaviorally relevant when a leader attends to followers, interprets emotional cues, communicates expectations, coaches employees, resolves conflict, or regulates personal reactions. These processes are integral to active leadership. Passive-avoidant leadership, by definition, reduces the frequency of such engagement. It is therefore plausible that self-reported EI will be more strongly associated with active than avoidant styles.

This proposition is especially relevant in technology settings. Digital transformation requires leaders to create acceptance, develop digital competence, and support innovation (Orkamo et al., 2025). Digital leadership reviews similarly emphasize vision, motivation, collaboration, and adaptation (Lin, 2025; Keisham & Lathabhavan, 2026). Avoidant leadership may be particularly poorly matched to these demands.

3. Method

The study used a quantitative, correlational design to examine relationships between self-reported leadership styles and emotional intelligence among information technology professional leaders. Participants were recruited through convenience and snowball sampling from the researcher's professional IT network. A total of 230 surveys were collected; 45 incomplete surveys were excluded, resulting in 185 usable cases.

Leadership style was measured with 36 items from the Multifactor Leadership Questionnaire (MLQ 5X), representing transformational, transactional, and passive-avoidant leadership. Emotional intelligence was measured with the Schutte Self-Report Emotional Intelligence Test (SSEIT), organized in the study into four components: perception of emotion, managing own emotions, managing others' emotions, and utilization of emotion. Demographic controls included gender, age, ethnicity, education, and tenure in leadership roles within information technology.

The original analyses used blockwise multiple regression at a significance level of p < .05. Demographic variables were entered before the focal leadership or emotional-intelligence variables so that relationships of primary interest could be evaluated after accounting for the controls. The design is cross-sectional and based on self-report; consequently, the word predictor refers to statistical prediction and should not be interpreted as proof of causality.

4. Results

Across the leadership-to-EI models, transformational leadership significantly predicted perception of emotion, managing own emotions, managing others' emotions, and utilization of emotion. Transactional leadership significantly predicted perception of emotion, managing others' emotions, and utilization of emotion, but did not predict managing own emotions. Passive-avoidant leadership did not emerge as a comparable significant predictor.

In the reverse-direction models, overall emotional intelligence significantly predicted transformational leadership (R² = .343, β = .585, p < .05) and transactional leadership (R² = .222, β = .471, p < .05). Overall emotional intelligence did not significantly predict passive-avoidant leadership.

At the hypothesis level, six of the seven original null hypotheses were rejected. The only hypothesis that was not rejected was the proposition of no relationship between overall emotional intelligence and passive-avoidant leadership. The convergence of results in both analytic directions supports an active-versus-avoidant interpretation.

5. Discussion

The study's most distinctive contribution is the pattern across results rather than any isolated coefficient. Emotional intelligence was consistently associated with transformational leadership and, to a somewhat narrower extent, transactional leadership. It was not significantly associated with passive-avoidant leadership. This suggests that EI may be tied to the interpersonal and self-regulatory processes involved in active leadership engagement.

The pattern also distinguishes transformational from transactional leadership. Transactional leadership did not predict managing own emotions, while transformational leadership did. Thus, active leadership is not a single psychological category. Transformational leadership appears to have the broadest emotional profile in this sample.

The passive-avoidant null result should be interpreted carefully. A non-significant relationship does not prove that EI is irrelevant to all forms of passive leadership. Contemporary research indicates that emotional exhaustion can contribute to laissez-faire behavior (Groulx et al., 2024), suggesting that other emotional variables may matter. The present result instead shows that overall self-reported EI did not statistically predict passive-avoidant leadership in this sample.

This distinction is valuable for digital transformation. Orkamo et al. (2025) show that successful transformation requires a balance of multiple leadership behaviors, while current digital-leadership research emphasizes adaptation, collaboration, talent development, and strategic action (Lin, 2025; Keisham & Lathabhavan, 2026). These demands are fundamentally active. The study's findings suggest that emotional competencies may be part of the human capability supporting such engagement.

6. Implications for Technology Organizations

Organizations should assess leadership readiness among technical professionals not only in terms of expertise but also in terms of behavioral engagement and emotional competence. Leadership development can focus on timely decision making, constructive intervention, communication, coaching, emotion regulation, and conflict management.

Passive-avoidant tendencies deserve explicit attention in leadership assessment. In technology projects, delayed decisions or limited support can contribute to unresolved issues, uncertainty, and loss of confidence. The original study did not measure project performance, cybersecurity outcomes, or implementation success, so those consequences should not be claimed from the data. They are testable implications for future research.

AI adoption raises an additional question: whether leaders become more or less passive when algorithmic systems provide recommendations or automate managerial tasks. Future studies should test whether reliance on AI can unintentionally encourage leadership withdrawal, or whether emotionally intelligent leaders use AI while maintaining human engagement and accountability.

7. Limitations and Future Research

The study is cross-sectional, self-reported, and based on a convenience sample, which limits causal inference and generalizability. The passive-avoidant score was relatively low on average, which may also constrain variance. The study did not distinguish the passive management-by-exception and laissez-faire subdimensions in the focal article-level analysis.

Future research should examine the passive components separately, use follower ratings, and include outcomes such as psychological safety, readiness for change, project performance, technostress (Ertiö et al., 2024), and employee retention. Longitudinal designs could test whether EI development reduces passive-avoidant behaviors or whether emotional exhaustion predicts movement toward leadership withdrawal. AI-enabled management environments offer an especially important context for examining whether technology augments active leadership or facilitates avoidance.

8. Conclusion

The dissertation results reveal a coherent boundary: emotional intelligence was associated with transformational and transactional leadership but not with passive-avoidant leadership. Reframing the findings as active versus avoidant leadership produces a distinct theoretical contribution and gives meaning to the one null hypothesis that was not rejected. The pattern is especially relevant to contemporary technology organizations, where digital transformation and AI require leaders to remain behaviorally and emotionally engaged even as technology assumes a larger role in decision support and work execution.

Data and Publication Note: This article was developed from the author's dissertation dataset and uses the same underlying sample and measures while addressing a distinct research question and theoretical contribution. Prior dissemination of the dissertation and related publications from the same dataset has been disclosed in accordance with the journal's publication policies.

Funding: This study received no funding.

Conflict of Interest: The authors declare no conflict of interest.

Informed Consent Statement/Ethics Approval: The original dissertation study was approved by the Our Lady of the Lake University Institutional Review Board (OLLU IRB) before data collection and was designated EXEMPT STATUS on February 15, 2016. Informed consent was presented to each respondent before the online survey. Participation was voluntary, respondents could discontinue at any time without penalty, and anonymity was maintained because names were not collected or linked to survey results.