When and How Leaders Withdraw Team Extra-Role Investment: The Role of Leaders’ Psychological Contract Breach

Abstract

This study investigates how team behavior shapes leaders’ supportive actions over time. Drawing on social exchange theory, we propose that leaders who initially invest extra-role efforts in their teams develop perceptions of reciprocal obligation on the part of the team. When teams fail to reciprocate through low levels of team organizational citizenship behavior toward the leader, leaders perceive a psychological contract breach by the team, particularly when their own prior extra-role investment has been high. These breach perceptions subsequently reduce leaders’ future extra-role investment. We test our model through three studies, including two scenario-based experiments and a multi-source, three-wave field study. Results consistently support our hypotheses, revealing that low team organizational citizenship behavior toward leaders in response to leaders’ extra-role investment predicts leaders’ psychological contract breach perceptions, and that this breach negatively predicts subsequent leader extra-role investment. These findings highlight the active role of teams in shaping leadership outcomes and offer a co-constructed perspective that demonstrates how leaders adjust their efforts in response to perceived team behavior.

Keywords

leader extra-role investment in the team team organizational citizenship behavior toward the leader psychological contract breach social exchange

Introduction

Leadership is increasingly viewed as a dynamic process co-constructed through ongoing interactions between leaders and followers (DeRue & Ashford, 2010; Hemshorn de Sanchez et al., 2022; Ribbat et al., 2024; Uhl-Bien et al., 2014). Recent reviews have expanded this perspective by highlighting how leadership emerges through contextually embedded, follower-driven processes (e.g., Kugler & Sims, 2025; Liden et al., 2025; Ribbat et al., 2024). Within this relational perspective, followers are not passive recipients but active agents who shape leadership outcomes through their behaviors (Coyle et al., 2023; Thommes et al., 2024). This co-productive view of leadership (Oc et al., 2023) builds on foundational arguments that leadership influence is mutually constituted (Hollander & Julian, 1969; Shamir, 2014).

Building on the growing recognition of followers’ influence, research has increasingly emphasized the positive contributions that subordinates make to leadership outcomes (Coyle et al., 2023; Javaid et al., 2023; Uhl-Bien et al., 2014). Yet, as Liden et al. (2025, p. 10) emphasize, the role of followers remains “underappreciated in leadership literature to date,” and they call for greater attention to how followers—particularly in team settings—contribute to the leadership process. This perspective underscores that limited attention has been given to how teams, as collective actors, co-construct leadership with their leaders. Given the interdependence of leader–team relationships, team members’ coordinated behaviors can both enable and constrain a leader’s supportive actions. Building on this relational view, our study examines how leaders adjust their extra-role investment in teams in response to the team’s collective reciprocation. In doing so, we extend prior work by offering a more nuanced understanding of how teams shape leadership through their shared, collective responses (J. Zhu et al., 2018; Y.-Q. Zhu et al., 2018).

To deepen our understanding of how followers’ behavior shapes leaders’ extra-role supportive actions over time, we draw on Social Exchange Theory (SET; Blau, 1964; Eisenberger et al., 2020). Consistent with the theory, we contend that leaders engage in extra-role investment behaviors toward teams (hereafter referred to as ERI), such as sacrificing their personal time or comfort, based on the belief that these efforts will be reciprocated (Halbesleben & Wheeler, 2015; Van Knippenberg & Van Knippenberg, 2005; Yaffe & Kark, 2011). However, when teams fail to reciprocate through team organizational citizenship behaviors towards the leader (hereafter referred to as team OCB-L), leaders may interpret this as a psychological contract breach (PCB, Knapp et al., 2020; Morrison & Robinson, 1997). Such breach perceptions are likely to prompt leaders to reduce further discretionary investment in their teams. Thus, we propose that leaders’ perceptions of PCB serve as a key cognitive mechanism that explains how the interaction between leaders’ ERI and the team OCB-L influences leaders’ future willingness to continue investing in the team. (See Figure 1 for the hypothesized model).

Our study makes several important contributions to the leadership and followership literature. First, while leadership research has traditionally emphasized a top-down, unidirectional influence—examining how leaders shape their own behavior (Liao et al., 2021; Lin et al., 2019) or team outcomes (Chen et al., 2020; Haeckl & Rege, 2025)—far less empirical attention has been devoted to how teams shape their leaders. Recent reviews consistently highlight this imbalance and call for stronger theorizing around followers as active agents in co-constructing leadership (Haslam et al., 2024; Knox et al., 2025; Kugler & Sims, 2025; Liden et al., 2025; Ribbat et al., 2024; Thommes et al., 2024; Uhl-Bien et al., 2014). Responding to these calls, our study models the interaction between leaders and teams’ behaviors. By theorizing and testing how leaders and teams mutually shape one another through ongoing interactions, we advance emerging perspectives that view leadership as a socially co-constructed process rather than a one-way cascade.

Second, our study offers a novel contribution to the psychological contract literature by examining a psychological contract that is distinct from the traditional employee–organization contract, namely, the psychological contract that leaders hold with their teams. Whereas most psychological contract research has traditionally examined obligations within the employer–employee relationship and has positioned leaders primarily as agents of the organization providing inducements such as compensation, development opportunities, or job security (Coyle-Shapiro et al., 2019; Kraak & Linde, 2019; Laulié et al., 2025), we shift the focus to the leader-team psychological contract that unfolds directly between leaders and their teams which entails a unique set of relational obligations grounded in leaders’ ERI and teams’ reciprocal behaviors. This reframing relocates the referent of the psychological contract from the organization to the leader–team relationship, emphasizing that leaders may hold perceptions of reciprocal obligations and breaches that are independent of organizational obligations. Despite growing scholarly attention to psychological contracts in team contexts—including work on team-level psychological contracts with external stakeholders (e.g., clients; Laulié & Escaffi-Schwarz, 2024) and repeated calls for further research (Akkermans et al., 2019; Laulié & Escaffi-Schwarz, 2024; Tekleab et al., 2020)—existing studies have not explicitly theorized the psychological contract that leaders hold with their teams. Responding to these calls, we conceptualize and empirically test a leader-centric psychological contract, defined as leaders’ cognitive appraisal of whether their team has fulfilled reciprocal obligations in response to leaders’ ERI. By doing so, we extend the multiple psychological contracts perspective by explicitly theorizing and testing the leader–team dyad as a distinct psychological contract domain.

Third, our research presents a cognitive, exchange-based explanation for leaders’ behavioral shifts, framing PCB as a mental assessment of unmet reciprocal obligations involving valued resources. Unlike prior studies that explain leaders’ withdrawal of ERI primarily through affective mechanisms, such as emotional exhaustion and burnout (Chen et al., 2020; Liao et al., 2021; Lin et al., 2019), we propose that leaders evaluate their ERI in terms of resource cost and the expected return within the exchange relationship (e.g., Garcia et al., 2018; Lambert, 2011). When leaders perceive insufficient reciprocal support from their teams, this imbalance may be interpreted as a breach of implicit obligations (Li et al., 2023), prompting them to reduce future discretionary efforts.

Theory and Hypothesis Development

Leaders’ ERI and Team OCB-L

ERI refers to discretionary efforts made by leaders that go beyond their formal job responsibilities. These efforts often involve the use of personal time and resources, such as mentoring, providing additional assistance, and engaging in self-sacrificial behaviors, to support their teams (Lundmark et al., 2023; Van Knippenberg & Van Knippenberg, 2005). Such behaviours demonstrate a leader’s commitment to the collective welfare of the group, often prioritizing the team’s goals and mission over personal interests (Choi & Mai-Dalton, 1999; Yang et al., 2023). A defining feature of ERI is the leader’s willingness to expend personal resources, such as time and energy, to enhance the functioning and cohesion of the team (Yaffe & Kark, 2011).

While organizational citizenship behaviour (OCB) was initially conceptualized at the individual level as voluntary behaviours not formally rewarded by the organization (Organ, 1988), recent research emphasizes the importance of examining extra-role behaviours as a team-level construct. Team OCB is defined as “the normative level of OCB performed within the unit” (Ehrhart, 2004, p. 64), shifting the focus from individual contributions to the collective behavior of the team as a whole. Studies suggest that the collective expression of OCB across team members has significant implications beyond isolated individual acts (Choi, 2009; Ehrhart, 2004; Ehrhart et al., 2006; Liu et al., 2014; Nohe & Michaelis, 2016). Prior research has linked team OCB to various desirable outcomes, including enhanced business unit performance (Liu et al., 2014; Sidorenkov et al., 2023) and improved firm financial performance (Chun et al., 2013).

Individual OCB is foundational in shaping team OCB through social and normative processes. In particular, when individual team members consistently demonstrate OCB, they set behavioural norms that influence others, ultimately leading to a shared understanding and expectation of engaging in such behaviours collectively (Ehrhart, 2004; Yaffe & Kark, 2011). Consistent with this conceptualization, we measure team OCB-L using leader ratings that assess the team’s overall behavior toward the leaders rather than evaluating individual team members’ behavior. This approach is well-established in prior research (Kim & Vandenberghe, 2020; Nohe & Michaelis, 2016; Zhang et al., 2024).

Beyond shaping team norms, team OCB-L also signals mutual obligations within the leader–team relationship. By engaging in discretionary actions that support the social and psychological work environment (Organ, 2014, p. 95), teams shape how leaders perceive the fulfillment of reciprocal obligations (Li et al., 2023). As integral components of the psychological contract, such contributions define mutual obligations (Chen et al., 2008; Tekleab & Taylor, 2003) and enable leaders to achieve goals (Decoster et al., 2014; Uhl-Bien, 2006). Consequently, leaders institutionalize these behaviors as workplace norms (Allen & Rush, 1998; Decoster et al., 2014), reinforcing the role of teams’ contributions in actively sustaining the leader–team exchange and shaping effective leadership dynamics.

Leaders’ ERI, Team OCB-L, and Leaders’ PCB: A SET Perspective

SET posits that interpersonal relationships evolve through reciprocal transactions that create mutual obligations over time (Blau, 2017; Eisenberger et al., 2020; Homans, 1958). These exchanges are guided by the norm of reciprocity, the moral expectation that benefits should be returned in kind (Gouldner, 1960). Through repeated exchanges, trust and interdependence emerge, transforming relationships from transactional to socioemotional (Cropanzano & Mitchell, 2005). Within this framework, each party’s behavior becomes both a response to and a signal for future exchanges, reinforcing or disrupting the relational balance. In leader–team relationships, leaders often initiate social exchange through extra-role investment; these acts communicate goodwill and trust, setting the tone for high-quality relationships. Followers, in turn, are expected to reciprocate through leader-directed supportive behaviors. When such reciprocation occurs, the relationship strengthens and becomes self-reinforcing.

However, when teams fail to reciprocate, leaders perceive this not as neutrality but as a violation of moral and relational norms central to social exchange (Cropanzano et al., 2017). This perceived violation reflects the symbolic nature of social exchange, where socioemotional resources such as respect, loyalty, and gratitude carry as much weight as tangible outcomes. The absence of reciprocation signals disregard for the leader’s goodwill and disrupts the psychological equilibrium of the relationship. SET scholars note that unreciprocated positive acts create negative hedonic value, as they imply rejection or devaluation of the initiator’s efforts (Cropanzano et al., 2017). In such cases, leaders experience PCB - a cognitive response to unmet obligations in the social exchange (Rousseau, 1995). Although PCB is traditionally examined from the employee’s perspective, leaders also form implicit psychological contracts with their teams, expecting reciprocity and support in return for their discretionary investment (Restubog et al., 2013; Rousseau et al., 2018).

From this perspective, followers are not passive recipients of leaders’ behavior but active participants whose actions sustain or disrupt the exchange relationship. Followership theory also highlights that effective followers engage in proactive, cooperative, and loyal behaviors that reciprocate leadership investment (Carsten et al., 2010; Ribbat et al., 2024; Uhl-Bien, 2006). Team OCB-L thus represents not only practical contributions but also moral acknowledgments of the leader’s benevolence. When such behaviors are withheld, leaders may interpret the lack of reciprocation as a breach of fairness and relational equity, eroding trust and prompting the withdrawal of further extra-role efforts toward followers (Halbesleben & Wheeler, 2015).

Moreover, SET highlights the asymmetry between positive and negative exchanges: specifically, violations of reciprocity norms have stronger, more enduring effects than positive interactions (Cropanzano et al., 2017). Once trust is broken, the exchange regresses from a socioemotional to an economic orientation—marked by self-protection and minimal engagement (Blau, 2017; Eisenberger et al., 2020; Griep et al., 2021). Consequently, leaders reduce their extra-role investment as a self-preserving response to perceived inequity and betrayal (Kiazad et al., 2014; Kim & Kim, 2024).

In sum, when leaders engage in ERI, they implicitly form perceptions of obligations on teams to reciprocate through team OCB-L, thereby reinforcing trust and mutual respect. Persistent low levels of team OCB-L disrupt this reciprocal balance, leading leaders to experience PCB. Hence, we propose the following hypothesis:

Hypothesis 1

Leaders’ ERI and team OCB-L interact to predict leaders’ perceptions of PCB, such that the relationship between leaders’ ERI and PCB is stronger when team OCB-L is low (compared to when team OCB-L is high).

Impact of the Leaders’ PCB on Subsequent Leaders’ ERI

So far, we have proposed that leaders’ experience of PCB involves negative cognitive evaluations. Specifically, it reflects the perception that the team has failed to fulfil implicit obligations of reciprocity, such as engaging in OCB-L in response to the leader’s initial ERI. This lack of reciprocity involves a sense of resource loss, in which leaders feel their investment of time, energy, or emotional support has not yielded the expected returns, leading to a PCB. In the following sections, we explain what happens in the aftermath of the leader’s PCB experience.

When leaders perceive a PCB, they are likely to adopt a “tit for tat” social exchange response (Coyle-Shapiro et al., 2019; Shaffakat et al., 2022). In such situations, leaders may deliberately withhold future ERI for three main reasons. First, these extra-role inducements (e.g., mentoring, personal support) are not formally required by the job and therefore are not included in formal performance evaluations. As a result, organizations typically cannot hold leaders accountable for withholding them. Second, the inherent power imbalance in leader-team relationships makes it easier for leaders to reduce such discretionary efforts without facing immediate consequences (Hobfoll et al., 2018; Liao et al., 2021). Third, the PCB signals to leaders that they have lost valuable social resources (e.g., team OCB-L). This disrupts the ongoing momentum of resource investment and accumulation, leading to the adoption of resource-conserving strategies (Hobfoll et al., 2018). Consequently, leaders no longer feel obligated to support the team and are likely to prefer withdrawal as a protective mechanism, often expressed through reduced leaders’ ERI (Chen et al., 2008; Lin et al., 2019).

Prior research demonstrated that PCB can deplete not only social resources but also psychological ones (Garcia et al., 2018; Kaya & Karatepe, 2020), leading to various negative outcomes, including reduced well-being (Costa & Neves, 2017; Gakovic & Tetrick, 2003), impaired creative thinking (Kiazad et al., 2014), and heightened anxiety (Asante et al., 2025; De Clercq et al., 2021). In light of this, we argue that when leaders perceive a PCB, they are likely to disengage from future team ERI to conserve their remaining resources (Hobfoll et al., 2018; Priesemuth & Taylor, 2016). Accordingly, we propose the following hypothesis:

Hypothesis 2

Leaders’ perception of PCB will be negatively related to their subsequent ERI in the teams.

Combining the arguments underlying Hypotheses 1 and 2, we propose a conditional indirect effect in which leaders’ initial ERI (Time 1) influences their subsequent ERI (Time 3) through perceptions of PCB when team OCB-L toward the leader is low. This hypothesis integrates the preceding relationships and reflects the overall logic of our conceptual model.

Hypothesis 3

Leaders’ PCB mediates the interactive effect of leaders’ ERI and team OCB-L on subsequent leaders’ ERI, such that the negative indirect effect is stronger when team OCB-L is low and is weaker when team OCB-L is high.

Overview of Methodology

We adopted methodological triangulation (Stone-Romero & Rosopa, 2004, 2008; Wellman et al., 2023) through three studies. Studies 1 and 2 employed scenario-based experiments to establish causal relationships for Hypotheses 1 and 2, while controlling for confounds (Greenberg & Folger, 2012). Study 3, a three-wave, multi-source field study, replicated our findings in a natural setting: team members rated leader extra-role investment (Time 1 and Time 3), while leaders rated team OCB-L across three lags, mitigating same-source bias (Podsakoff et al., 2003) and strengthening external validity (Greenberg & Tomlinson, 2004). This multi-method approach strikes a balance between experimental control and field realism (De Cremer & Van Knippenberg, 2002).

Study 1 Methods

Sample, Design, and Procedure

We conducted an experiment to test Hypothesis 1 (Leaders’ ERI and team OCB-L interact to predict leaders’ perceptions of PCB, such that the relationship between leaders’ ERI and PCB is stronger when team OCB-L is low than when it is high). Participants included MBA executives and students from the evening Master’s program at a private-sector university in Pakistan. Eligibility was limited to individuals with at least six months of experience in team leadership. The study employed a 2 (leaders’ ERI: Low vs. High) × 2 (Team OCB-L: Low vs. High) between-subjects design, randomly assigning participants to the corresponding conditions. A total of 163 individuals participated (47% females; M_age = 31.36 years, SD_age = 5.61; M _{work experience} = 5.33 years, SD _experience = 2.68). Participants received academic credit and were assured of confidentiality. They were blind to the study’s hypotheses.

Building on prior research on leadership (e.g., Decoster et al., 2014), we employed a scenario-based vignette to present a hypothetical situation involving the leader’s extra-role investment and the team’s reciprocal extra-role behaviors. Participants were welcomed into a laboratory setting and instructed to assume the role of a team leader in a tech company. After completing a demographic questionnaire, they read a vignette describing a situation in which the team failed to reciprocate the leader’s extra-role investment. They then responded to manipulation checks and questions assessing perceptions of psychological contract breach.

The leaders’ ERI manipulation was adapted from Tayyab et al. (2023) to reflect team-level leaders’ investment. In both conditions, participants read a scenario describing the same discretionary leader behaviors. These included exceeding formal job requirements to support the team, sacrificing personal time and comfort to assist with work-related or personal issues, championing teams’ interests above one’s own, and actively supporting teams’ career development, well-being, and personal goals. In the high ERI condition (n = 78), the leader was portrayed as consistently engaging in these behaviors, whereas in the low ERI condition (n = 85), the leader was shown as not engaging in such actions.

The team OCB-L was manipulated following Decoster et al. (2014). In all conditions, participants read a scenario describing the same discretionary team behaviors. These included going beyond formal duties to support the leader with tasks and challenges, sacrificing free time to assist with work issues, taking on extra responsibilities when the leader was unavailable or overburdened, and showing genuine concern and courtesy toward the leader, even under demanding circumstances. In the high team OCB-L condition (n = 85), teams engaged in these behaviors. In the low team OCB-L condition (n = 78), teams were reported not to engage in them. To ensure construct clarity and face validity at the team level, 12 subject matter experts and 15 managers reviewed and validated both scenarios. (See Appendix A in the supplementary material).

Measures

Responses for all scales were recorded on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Following previous research (e.g., Decoster et al., 2014; Wang et al., 2018), we conducted manipulation checks using two overall representative items for each construct.

Leaders’ ERI

To assess the effectiveness of the leaders’ ERI manipulation, participants as leaders responded to two items based on the scenario: “I willingly invest personal time to mentor, assist, or advocate for team members beyond my role,” and “I demonstrate genuine concern by advocating for team members beyond my formal duties.” The Spearman-Brown coefficient for these items is 0.95.

Team OCB-L

To assess the manipulation of team OCB-L, we adapted two items from Decoster et al. (2014). Based on the scenario, the leader rated the extent to which their team members: “willingly give their personal time to help you when you have a heavy workload or responsibilities” and “show genuine concern and courtesy by assisting you beyond their formal job responsibilities.” The Spearman-Brown coefficient for these two items was 0.84, representing good reliability. This approach to measuring the manipulation of extra-role support aligns with existing research (see Decoster et al., 2014 for a review).

Leaders’ Perceptions of PCB

We adapted a four-item scale from Bordia et al. (2017) to assess leaders’ perceptions of PCB. Our measure used the referent-shift composition model (Chan, 1998), a widely used approach in team research for assessing collective constructs by shifting the item referent to the group level. Consistent with this approach, we adapted the validated supervisor-perception items by replacing the individual-level referent (“employees”) with a collective referent (“team members”) to capture leaders’ perceptions of team-level obligation breach. This practice aligns with established team research employing referent-shift measures to assess shared constructs such as justice climate, helping norms, and collective psychological contracts (e.g., Laulié & Tekleab, 2016). A sample item included “The team members have not fulfilled their obligations to me”. The scale showed excellent reliability (α = .87). Additionally, the confirmatory factor analysis (CFA) supported unidimensionality with strong loadings (λ = 0.76–0.87, p < .001). The model demonstrated excellent fit: χ² (2) = 2.672, p = .263, CFI = 0.99, TLI = 0.994, SRMR = 0.015, and RMSEA = 0.045 (90% CI [0.00, 0.16]). The high factor loadings and model-fit indices confirm the scale’s validity for measuring leaders’ perceptions of psychological contract breaches by their teams.

Study 1 Results

Manipulation Check

A 2 (Leaders’ ERI: high vs. low) x 2 (Team OCB-L: high vs. low) analysis of variance (ANOVA) on perceived leaders’ ERI revealed a significant main effect of leaders’ ERI manipulation, F (1, 161) = 169.73, p < .001, η² = .51. The results showed that participants in the high leaders’ ERI condition reported higher ERI (M = 3.71, SD = 0.76) compared to those in the low leaders’ ERI condition (M = 2.15, SD = 0.77).

Similarly, results showed a significant main effect of team OCB-L, F (1, 161) = 257.5, p < .001, η² = .61. As anticipated, participants in the high team OCB-L condition reported a higher mean (M = 3.59, SD = 0.66) compared to participants in the low condition (M = 2.09, SD = 0.51). No significant interactions or other main effects were observed. Therefore, all manipulations were deemed successful.

Hypothesis Tests

We predicted that leaders would report perceptions of PCB only when their extra-role investment was followed by low, rather than high, levels of team OCB-L. To examine this, we conducted a 2 (leaders’ ERI: high vs. low) × 2 (team OCB-L: high vs. low) ANOVA. The analysis revealed that neither the main effect of leaders’ ERI, F (1,159) = 3.66, ηp² = .022, nor the main effect of team OCB-L, F (1,159) = 3.90, ηp² = .024, reached the conventional level of statistical significance (p < .05). However, there was a significant interaction between leaders’ ERI and team OCB-L, F (1,159) = 9.32, p < .01, ηp² = .055. Taken together, these findings indicate that leaders’ perceptions of breach emerge specifically when leaders’ ERI is followed by low levels of team OCB-L, as illustrated in Figure 2.

To further explore this interaction, we conducted simple effects analyses to examine the effect of team OCB-L on leaders’ perceptions of PCB separately at high versus low levels of leaders’ ERI. Specifically, when leaders’ ERI was high, the simple effect of team OCB-L was significant, F (1,76) = 12.34, p = .001. In contrast, when leaders’ ERI was low, the simple effect of team OCB-L was not significant, F (1,83) = 0.60, p = .44. Collectively, these results support Hypothesis 1. Although study 1 results indicate that low team OCB-L was related to leaders’ perceptions of PCB when leaders’ ERI was high, it did not examine the relationship between leaders’ perception of PCB and their subsequent ERI, which we explored in Study 2.

Study 2 Methods

Sample, Design, and Procedure

The purpose of this study was to test hypothesis 2 (Leaders’ perception of PCB will be negatively related to their subsequent ERI in the teams) using a scenario-based experimental design. Participants were Master’s evening program students from a private university in Pakistan, with eligibility restricted to individuals possessing at least six months of team leadership experience. The study employed a between-subjects design with two conditions (Leaders’ perceptions of PCB: Low vs. High) to which participants were randomly assigned.

A total of 108 individuals participated (37% female; M_age = 28.24 years, SD_age = 5.8; M_experience = 4.89 years, SD = 3.32). Participants received academic credit, were assured confidentiality, and were blind to the study’s hypotheses. Consistent with Study 1 and prior research on psychological contract breach (e.g., Atkinson et al., 2018), participants assumed the role of a team leader in a scenario-based vignette. The vignette manipulated leaders’ perceptions of PCB, after which participants evaluated their likelihood of ERI.

The PCB was manipulated by varying whether previously established team obligations were perceived as being upheld or violated. In both conditions, participants read a scenario describing the same reciprocal commitments and implicit team obligations—such as timely responsiveness, shared responsibility, follow-through on prior commitments, and reciprocal support following the leaders’ ERI. In the high PCB condition (n = 55), breach was conveyed by describing a pattern in which these obligations were no longer consistently fulfilled (e.g., delayed responses to urgent matters and unfulfilled prior commitments), signaling a violation of perceived obligations. In the low PCB condition (n = 53), the same obligations were described as being consistently honored, reinforcing the leader’s perception that the team upheld its side of the exchange relationship. To ensure construct validity at the team level, the scenario was reviewed and validated by 10 subject matter experts and 18 managers. (See Appendix A in the supplementary material).

Measures

Responses for all scales were recorded on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).

Leaders’ Perceptions of PCB

Similar to Study 1, we selected two representative items to assess the effectiveness of the leaders’ PCB manipulation. Participants were asked to rate the following statements based on the scenario: “Team members have done an excellent job fulfilling their obligations toward me” and “Team members have successfully delivered all the things committed at work.” Lower ratings on these items indicate a higher perception of leaders’ PCB. This approach aligns with previous research, demonstrating that low perceived fulfilment is associated with PCB (e.g., Jensen et al., 2010).

Leaders’ ERI

We adapted the 10-item scale by Tayyab et al. (2023) using referent-shift composition (Chan, 1998) to measure leaders’ likelihood of team-directed ERI. Example item included “How likely are you to advocate for your team members’ interests at personal cost?” The scale showed excellent reliability (α = .94). The CFA supported unidimensionality with strong loadings (λ = 0.67–0.91, all p < 0.001). Fit indices indicated excellent results: χ² (35) = 45.40 (p = .112), CFI = .98, TLI = .98, SRMR = .029, and RMSEA = .052 (90% CI [.01, .09]). These results demonstrated robust psychometric properties for assessing leaders’ ERI in the team.

Study 2 Results

Manipulation Check

We conducted ANOVA to evaluate the effectiveness of the leaders’ PCB manipulation using a two-item scale. The results indicated that participants in the low PCB scenario reported lower scores (M = 2.13, SD = 0.39) compared to those in the high PCB (M = 3.38, SD = 0.66), F (1, 106) = 141.60, p < .001, and a substantial effect size of η² = .57.

Hypothesis Tests

Leaders’ Extra-Role Investment

An ANOVA on leaders’ ERI showed a significant effect of PCB’s conditions, F (1, 106) = 15.60, p < .001, ηp² = .13. In line with our hypothesis, we observed a significant decrease in leaders’ ERI under the high PCB condition (M = 2.69, SD = 0.78) as compared to the low PCB condition (M = 3.22, SD = 0.56), t (106) = −3.95, p < .001. This finding supported Hypothesis 2.

The first two studies revealed distinct yet interconnected effects: Study 1 showed that the interaction between leaders’ ERI and the team OCB-L was associated with leaders’ perceptions of PCB. Study 2 demonstrated that leaders’ PCB was negatively related to subsequent leaders’ ERI. Building on these findings, we conducted Study 3 to test the complete conceptual model (Hypotheses 1–3) in a field setting.

Study 3 Methods

Participants and Procedure

The study drew data from 110 teams with a total of 475 employees representing a diverse range of organizational contexts from Pakistan. Of these, 40 teams (36%) belonged to the health sector, 29 teams (26%) came from manufacturing, 24 teams (22%) represented the finance sector, and 17 teams (16%) were drawn from telecommunication organizations. This distribution provides a balanced representation of industries, enabling meaningful comparisons across different work settings. Psychological contract breach is a widespread phenomenon occurring across a range of industries, employment types, and contexts where individuals or groups experience dependence, accountability, and trust (Bankins et al., 2020; Coyle-Shapiro et al., 2019; Knapp et al., 2020; Rousseau, 1995; Rousseau et al., 2018; Zhao et al., 2007). Following the methodological recommendations of Podsakoff et al. (2012), we employed a multi-source, lagged design to reduce common-method bias.

Before data collection, we obtained formal approval from the Human Resources departments of participating organizations to survey supervisory leaders and their teams. One hundred twenty team leaders and 650 team members were invited to participate voluntarily. Each team was assigned a unique code, and leaders were briefed to ensure they rated their team members consistently. Team members were also assigned unique identification codes to maintain confidentiality and enable accurate matching across waves. These identifiers allowed us to reliably link leader and team responses over the three time points while protecting respondent anonymity.

Data were collected at three separate time points. At Time 1, leaders and team members rated the leader’s extra-role investment. One month later, at Time 2, leaders assessed the team OCB-L. At Time 3—one month after the second survey—supervisory leaders reported their perceptions of psychological contract breach by the team, while team members once again rated the leaders’ ERI.

By the end of the third phase, we had collected 475 complete responses from employees across 110 teams, yielding an 86% response rate. The leader returned 110 complete surveys, yielding an 85% response rate. The high response rate was achieved through strong support from top management, which encouraged employees to participate in the study. Among the leaders, 40% were female, with an average age of 34.59 years (SD = 8.78) and an average work experience of 10.32 years (SD = 5.15). Among the team members, 29% were female. The average age of team members was 32.49 years (SD = 4.92), with an average work experience of 8.46 years (SD = 2.86). The dataset contains a maximum of 6 and a minimum of 3 team members, with an average of 4.32 team members per team.

Measures

For the study’s focal and control variables, participants were asked to rate each item on a 5-point Likert scale ranging from “1 = strongly disagree to 5 = strongly agree.”

Leaders’ ERI at Time 1 (ERI-T1)

We used the same scale as in Study 2 to measure leaders’ ERI toward their teams. At Time 1, team members rated their leaders’ ERI. A sample item included “My supervisor is willing to advocate for the team members’ interests, even at the expense of their own.” The scale reliability (α = .98 at the team level; α = .93 at the individual level). To justify aggregation to the team level, we assessed within-group agreement and between-group variance by calculating ICCs (Bliese, 2000) and r_{wg (j)} (James et al., 1984). A one-way random effects ANOVA revealed that team membership accounted for a significant proportion of the variance in ERI scores, F (109, 365) = 15.17, p < .001. The resulting ICC1 (0.77) and ICC2 (0.94), along with high within-team agreement (Median r_wg = 0.94; Mean r_wg = 0.96), provided strong support for aggregation. Therefore, we computed the within-team average ERI scores based on 110 teams to represent team-level leaders’ extra-role investment.

Team OCB-L

At Time 2, leaders completed a five-item OCB scale, which was initially developed by Williams and Anderson (1991) and later refined by Malatesta (1995). All five items were negatively worded (e.g., “Team members do not accept added responsibility when you are absent”) and were not reverse-coded; thus, higher scores reflect lower levels of team OCB-L. This scoring approach was retained to capture leaders’ negative perceptions directly. The scale has been widely used in organizational behavior research (see Rupp & Cropanzano, 2002, for a review). The scale demonstrated good internal consistency (α = .87).

Leaders’ Perceptions of PCB

We used the same four-item measure as in Study 1 (α = .93).

Leaders’ ERI at Time 3 (ERI-T3)

At Time 3, team members rated their leaders’ extra-role investment using the same scale as that of Time 1. The scale demonstrated excellent internal consistency (α = .96 at the team level and .92 at the individual level). To justify aggregating individual ratings to the team level, we conducted a one-way random-effects ANOVA to assess between-team variability. The results showed that team membership accounted for a significant proportion of the variance in ERI-T3 scores, F (109, 365) = 4.40, p < .001. This supported the presence of meaningful between-group differences. Further, the intra-class correlation coefficients (ICC1 = .44; ICC2 = .77) and within-group agreement indices (Median r_wg = .94; Mean r_wg = .87) indicated high reliability and agreement among team members. These values provided strong justification for aggregating individual scores to the team level. Accordingly, we computed the within-team average ERI-T3 score to represent team-level leader extra-role investment.

Control Variables

We included various control variables. At time 1, leaders assessed leader-member exchange (LMX) and perceived organizational support (POS). In high LMX relationships, leaders are generally more forgiving and support the team by making extra-role investment even when reciprocation is low. Measuring LMX allows us to partial out the buffering effect of relationship quality, isolating team-level reciprocity’s unique impact on leaders’ PCB and ERI trajectories. We used the four-item LMX scale by Scandura and Graen (1984). The sample item for the scale was “How well do you recognize this team’s potential?” (α = 0.84). Similarly, Leaders who feel valued and supported by their organization may interpret shortfalls in team reciprocity less personally. By including Rhoades and Eisenberger (2002) eight-item POS scale, we guard against the possibility that high organizational support alone could explain lower PCB perceptions and sustained ERI over time. The sample item for the POS was “My organization strongly considers my goals and values” (α = .75).

Next, at time 2, we controlled for PCB by the organization (PCBO), as leaders who perceive the organization as having failed to honor its commitments may be generally more sensitive to unmet obligations, including those of their team members. By accounting for PCBO, as measured with the three-item scale of Tekleab et al. (2005), we ensure that any increase in leaders’ perceptions of breach and the subsequent reduction in ERI reflect team-level factors rather than residual frustration with the organization. The sample item was “The organization has fulfilled the most important obligations to me” (α = .83).

At time 3, we controlled for team in-role performance to distinguish the effects of team OCB-L from basic task performance. Using Eisenberger et al. (2001) four-item in-role performance scale, we considered that teams who meet formal job requirements might elicit different perceptions of breach and levels of leaders’ ERI than those who do not. This control ensures that our findings pertain specifically to extra-role behaviors. The sample item for the scale was “Team members fulfill responsibilities specified in the job description” (α = .90).

Finally, we included the leaders’ age, gender, and experience, the team’s gender diversity, the team’s average age, and average experience as demographic controls, consistent with prior research on leadership (Bordia et al., 2017; Decoster et al., 2014). These characteristics can shape how leaders interpret team actions and allocate their resources over time.

Study 3 Results

Table 1 presents the descriptive statistics. All analyses were conducted at the team level using Mplus 8.3 (Muthén & Muthén, 2017).

Table 1.

Means, Standard Deviations, and Correlations (Study 3)

Variables	Mean	Within- team SD	Between- team SD	1	2	3	4	5	6	7	8	9	10	11	12	13	14
1- ERI-T1	3.42	.89	.81	-	−.03	−.01	.08	.22^**	−.20^**	.12^**	.16^**	.01	.15^**	−.12^**	.01	−.02	.02
2- PCB	3.17	-	.99	−.02	-	−.37^**
3- ERI-T3	2.58	.86	.65	−.02	−.47^**	-	−.08	.17^**	−.23^**	.01	.07	.01	.22^**	−.06	.01	.05	.08
4- OCB-L^a	3.08	-	.89	.11	.14	−.11	-
5- LMX	3.11	-	.86	.22^*	−.01	.21^*	−.21^*	-
6- PCBO	3.32	-	.97	−.21^*	.09	−.29^**	.03	−.20^*	-
7. TIP	3.06	-	.91	.13	−.08	.01	−.22^*	.16	−.07	-
8. POS	2.92	-	.70	.19	−.06	.08	−.10	.09	−.02	.14	-
9. L_gen	1.40	-	.49	−.01	.11	−.02	.02	.09	−.02	−.04	−.07	-
10. L_age	34.59	-	8.79	.16	−.22^*	.28^**	.08	.07	−.22^*	.10	−.03	−.07	-
11. L_exp	10.32	-	5.15	−.13	−.08	−.12	.02	−.03	.03	−.01	−.04	.09	.34^**	-
12. Tgen_d	0.36	-	.16	.01	−.03	−.04	.03	.09	.10	.05	−.08	.13	.05	.04	-
13. T_age	32.49	-	4.92	−.05	−.24^*	.24^*	−.06	−.03	.14	.08	−.08	.08	.05	−.09	−.04	-
14- T_exp	8.46	-	2.86	.05	−.26^**	.16	−.03	−.02	−.02	.03	−.08	.00	.13	−.09	.00	.77^**	-

Team-level correlations (N = 110) are below the diagonal; individual-level correlations (N = 475) are above the diagonal.

*P < 0.05, **P < 0.01 (Two tailed). The average team size was 4.32.

Abbreviations: ERI-T1 = Leaders’ Extra-Role Investment at time 1; PCB = Leaders’ Psychological Contract Breach by team, ERI-T3 = Leaders’ Extra-Role Investment at time 3; OCB-L = Team OCB towards leader; LMX = Leader Member Exchange; PCBO = Leaders’ Psychological Contract Breach by Organization; TIP = Team’s In-role Performance; POS = Perceived Organizational Support; L_gen = Leader gender; L_age = Leader age; L_exp = Leader experience; Tgen_d = Team gender diversity; T_age = Team average age; T_exp = Team average experience.

^aHigher scores represent lower levels of OCB.

Measurement Model

In the first step, we assessed the measurement structure of the model through a series of CFA. The CFA showed that the four-factor model (leaders’ ERI-T1, team OCB-L, leaders’ perception of PCB, and leaders’ ERI-T3) provided the best fit to the data, χ² (df = 371) = 498.45, p < 0.01, RMSEA = 0.05, CFI = 0.96, TLI = 0.96, SRMR = 0.05. All factor loadings were significant (p < 0.05) and exceeded 0.71. A comparison of the hypothesized four-factor model (Δχ² = 1.34, p < .001) with alternative models (three-, two-, and one-factor) confirmed that the four-factor model provided the best fit, offering strong evidence of construct distinctiveness (see Table 2, for details).We conducted Harman’s single-factor test to rule out the common method bias (Podsakoff et al., 2003). All survey items were subjected to an unrotated exploratory factor analysis. The first factor explained only 17.7% of the variance, far below the 50% threshold, indicating that common method bias is unlikely to confound our results (Fuller et al., 2016).

Table 2.

Measurement Model Results (Study 3)

Model	Δχ²/df	CFI	TLI	RMSEA	SRMR
4-Factor model (Leaders’ ERI-T1, team OCB-L, PCB, Leaders’ ERI-T3)	1.34	.96	.95	.05	.05
3-Factor model (Leaders’ ERI-T1 + PCB combined)	2.48	.83	.82	.11	.15
2-Factor model (Leaders’ ERI-T1 + team OCB-L & PCB + Leaders’ ERI-T3 combined)	2.83	79	78	.13	.12
1-Factor model (All factors loaded on a single factor)	6.07	.44	.43	.22	.29

Hypothesis Testing

Our hypothesized model was analyzed using structural equation modeling in MPlus. To examine the interaction between the leaders’ ERI-T1 and team OCB-L on the leaders’ perception of PCB (H1), we regressed ERI-T1, team OCB-L, and their interaction on the leaders’ PCB perceptions. The results in Table 3 indicate that the interaction of ERI-T1 and team OCB-L explains 34% of the variance in PCB (γ = 0.34, p < 0.001), supporting our first hypothesis. This interaction was further illustrated in Figure 3.

Table 3.

Direct Effects (Study 3)

Variables	Leaders’ PCB			Leaders’ ERI-T-3
Variables	γ	S.E	t	γ	S.E	t
Leaders’ ERI-T1	−.01	.11	−.10	−.22*	.08	−2.56
Team OCB-L	.17	.11	1.60
ERI-T1 × team OCB-L (negatively coded)	.34^***	.09	3.61
Leaders’ PCB				−.41^***	.08	−5.15
R²	.31^***			.53^***
Control Variables
Leader member exchange	.14	.10	1.28	.26^**	.09	2.88
Leaders’ PCB by organization	.13	.11	1.20	−.28^**	.09	−3.26
Team in-role performance	.01	.09	.04	−.13	.07	−1.75
Perceived organizational support	−.09	.11	−.92	.15	.09	1.73
Team gender diversity	−.03	.08	−.38	−.03	.07	−0.36
Team age	−.09	.14	−.63	.35^**	.12	2.95
Team experience	−.17	.14	−1.21	−.26^*	.12	−2.24
Leader’s gender	.15	.08	1.67	−.01	.07	−0.04
Leader’s age	−.15	.10	−1.53	.27**	.08	3.23
Leader’s experience	−.11	.09	−1.20	−.25**	.08	−3.24

N = 110, *P < 0.05, **P < 0.01, ***P < 0.001.

Note. Team OCB-L items were negatively coded; lower scores reflect higher team helping.

In the model excluding control variables, the interaction between leaders’ ERI-T1 and team OCB-L (negatively coded) significantly predicted leaders’ PCB (γ = .315, p = .002), indicating that the ERI–PCB relationship strengthened as team OCB-L decreased (i.e., when team OCB-L scores were higher). Neither the main effect of ERI-T1 nor team OCB-L was significant. Leaders’ PCB was negatively associated with leaders’ ERI-T3 (γ = −.479, p < .001), while the direct effects of ERI-T1 and team OCB-L on ERI-T3 remained non-significant. The Index of moderated mediation was significant (γ = −.098, p = .011), showing that the indirect effect of ERI-T1 on ERI-T3 via leaders’ PCB varied by team OCB-L. These results support a moderated mediation process in which leaders’ PCB and subsequent leaders’ ERI depend on the degree of team OCB-L.

We employed the Johnson–Neyman technique (Preacher et al., 2006) to identify regions of significance for the moderating effect of team OCB-L. Results indicated that when team OCB-L was relatively low (i.e., more deficient; values above 0.85 on the grand-mean–cantered scale), leaders’ ERI was positively associated with breach perceptions. Whereas, when team OCB-L was relatively high (values below −0.76), the relationship was significantly negative. These regions of significance further support Hypothesis 1, demonstrating that the consequences of leaders’ ERI depend critically on the level of team OCB-L. Consistent with these results, simple slopes analyses (Table 4) and the interaction plot (Figure 3) show that the relationship between leaders’ ERI-T1 and leaders’ PCB is significantly positive at lower levels of team OCB-L (+1 SD; γ = 0.39, p < .05, 95% CI [0.06, 0.72]). Moreover, we conducted a Necessary Condition Analysis (NCA) to determine whether the interaction between leaders’ ERI and team OCB-L constitutes a necessary condition for leaders’ perceptions of PCB. Results from the CE-FDH method revealed a significant necessity effect (d = 0.316, p = .008), with a ceiling line indicating that no cases violated the necessity condition, consistent with a strong necessary relationship. The bottleneck analysis further revealed that, for moderate levels of leaders’ PCB (≥1.625), the interaction must reach at least 31.8% of its potential range to account for 41.7% of PCB levels (≥4.625; Dul, 2016, 2024). Therefore, a sufficient level of interaction is necessary to reach moderate-to-high levels of leaders’ PCB. Thus, H1 was supported. The second hypothesis, indicating a negative relationship between the leaders’ perceptions of PCB and their ERI-T3 (Table 3, γ = −0.41, p < 0.001), was also supported.

Table 4.

Conditional Effects (Study 3)

Effects of ERI-T1 X Team OCB-L on Leaders’ PCB at SD ± 1
	γ	LLCI	ULCI
High team OCB-L (SD = −1)	−.41*	−.76	−.07
Mean team OCB-L (SD = 0)	−.01	−.26	.23
Low team OCB-L (SD = +1)	.39*	.06	.72
Moderated mediation Results
Index of moderated mediation	−.09^**	−.16	−.03

Conditional Indirect Effect of ERI (T1 → T3) via Leaders’ PCB at SD ± 1 of Team OCB-L
	γ	LLCI	ULCI
High team OCB-L (SD = −1)	.09*	.01	.18
Mean team OCB-L (SD = 0)	.01	−.05	.06
Low team OCB-L (SD = +1)	−.08^*	−.17	−.01

Note. Team OCB-L items were negatively coded; lower scores indicate greater team OCB-L. Accordingly, SD = −1 represents high Team OCB-L.

N = 110, *P < 0.05, **P < 0.01, 95% Confidence Interval, Abbreviations: ERI-T1 = Leaders’ Extra-Role Investment at time 1; PCB = Leaders’ Psychological Contract Breach; ERI-T3 = Leaders’ Extra-Role Investment at time 3.

For the moderated mediation hypothesis (H3), bootstrapped estimates (Table 4) showed that the indirect effect of the interaction (ERI-T1 × team OCB-L) on ERI-T3 via leaders’ PCB was significant (γ = −0.09, p < 0.01, 95% CI [−0.16, −0.03]). Conditional indirect effects further indicated that leader ERI-T1 was negatively related to ERI-T3 through leaders’ PCB at higher levels of team OCB-L (+1 SD, γ = −0.08, p < 0.05, 95% CI [−0.17, −0.01]). Thus, Hypothesis 3 was supported. We report the primary analyses excluding all control variables (demographics, LMX, POS, PCBO, Team in-role performance). The hypothesized relationships remained significant with and without controls (see Table 3).

Discussion

Our study represents one of the early investigations of PCB within leader–team dynamics. The findings reveal a clear temporal pattern: when leaders exhibit high ERI, they develop perceptions of reciprocal obligations on the part of the team. When these perceived obligations are not fulfilled—evidenced by low levels of team OCB-L — leaders experience heightened perceptions of PCB. In turn, these breach perceptions significantly reduce leaders’ subsequent ERI. We found consistent support for this hypothesized model across three studies.

Further, the NCA results indicated that the reciprocal leader–team relationship was grounded in implicit psychological contract obligations, underscoring the co-constructed nature of the leadership process. This finding aligns with the contemporary leadership co-production paradigms (e.g., Kugler & Sims, 2025; Liden et al., 2025; Ribbat et al., 2024).

Theoretical Implications

By applying the PCB perspective to leader–team dynamics, our study offers several contributions to theory. First, current findings reposition leaders within the framework of psychological contract theory. While prior work has established the centrality of psychological contracts in workplace relationships (Rousseau et al., 2018), prevailing frameworks typically confine leaders to the role of agents executing organizational inducements (e.g., Coyle-Shapiro et al., 2019; Li et al., 2023). Our findings offer a novel perspective by showing that leaders act as principals who establish unique reciprocal obligations with their teams. Importantly, the obligations embedded in the leader–team psychological contract differ from those associated with leaders’ organizational agent (Bankins et al., 2020; Knapp et al., 2020). Rather than centring on formal inducements such as pay, job security, or promotion opportunities—which are typically governed by the employee–organization psychological contract—the leader–team psychological contract is grounded in relational and discretionary obligations (e.g., Bordia et al., 2017; Li et al., 2023). These include teams’ obligations to reciprocate leaders’ ERI through support, responsiveness, initiative-taking, and OCB-L behaviors. Consistent with our measures, leaders’ breach perceptions reflect judgments about the non-fulfilment of these team-based reciprocal obligations, rather than failures to deliver organization-mandated duties. This distinction clarifies how leader–team psychological contracts constitute a conceptually distinct contract domain within the broader multiple psychological contracts’ framework.

Second, leader-as-principal perspective advances three theoretical insights: (a) It extends psychological contract research by drawing attention to the team as a meaningful locus of co-constructed obligations. While most prior work has focused on individual-level psychological contracts—often framing the supervisors as organizational representatives (e.g., Li et al., 2023)—our study shifts this lens to the leader–team level. In doing so, it aligns with broader calls for research on psychological contracts in team-based contexts (Akkermans et al., 2019; Laulié & Escaffi-Schwarz, 2024; Tekleab et al., 2020). (b) Our perspective reconceptualizes leaders’ agency by framing leaders as active architects of social exchange who invest discretionary resources with the expectation of reciprocation, yet become vulnerable to perceived breaches when teams do not respond with extra-role behaviors. (c). It demonstrates that leader–team relationships are co-constructed through mutual psychological contracts, extending psychological contract theory to account for team-induced leader PCB as a distinct and underexplored process (Lee et al., 2011; Tsui et al., 1997).

Third, the traditional leadership perspective frames leadership influence as a top-down causal chain (e.g., Khan et al., 2018; Lin et al., 2019) or reduces followership to passive receptivity (Ribbat et al., 2024; Uhl-Bien et al., 2014). We demonstrated leadership as a temporally dynamic, team-mediated co-construction. Our findings indicate that when teams fail to reciprocate, leaders experience PCB, resulting in reduced subsequent investment in the team. This reciprocal resource interdependence—where leader vulnerability transforms team actions into leadership outcomes—resolves the theoretical stalemate between leader-centric and follower-centric models (Uhl-Bien & Ospina, 2012). By revealing how team agency actively co-constructs leadership through psychological contracts, we demonstrate that leadership processes are bidirectional exchanges of socioemotional resources. Our theoretical development calls for further studies to adopt a leader-team reciprocity framework to explain the sustainability and effectiveness of leadership.

Fourth, we introduce leaders’ PCB as a cognitive mechanism that explains leaders’ behavioral change. While prior research largely attributes leaders’ withdrawal behaviors to emotional exhaustion or affective depletion (e.g., Chen et al., 2020; Liao et al., 2021), our temporal, team-level framing reveals that leaders engage in socio-cognitive resource appraisals. When teams fail to reciprocate leaders’ ERI, leaders perceive a violation of implicit obligations and a net loss of relational resources, triggering leaders’ PCB. Leaders strategically withdraw investment as a rational effort to conserve remaining resources (Garcia et al., 2018; Griep et al., 2025; Halbesleben & Wheeler, 2015). Thus, we position leaders’ PCB as the linchpin mechanism that translates team-level support failures into calculated leader disengagement.

Lastly, the NCA findings extend our theoretical understanding of leader–team reciprocity by showing that leaders’ perceptions of PCB are shaped by collective leader-team behaviours. This highlights the importance of considering team norms and interactions in leader–team exchanges and underscores that breach perceptions emerge from the broader pattern of reciprocal co-construction of leadership process, offering a nuanced perspective on how leadership is co-constructive process and respond to team contributions.

Managerial Implications

Our findings offer several practical implications. First, organizations may reconfigure leadership development programs to focus on co-creating explicit team charters that document mutual obligations for personalized inducements (such as mentoring and advocacy) and collective reciprocation. Similarly, the team breaches may be framed as organizational systemic issues to prevent leaders’ disengagement. Second, organizations can support sustained leader extra-role investment by embedding reciprocity-focused indicators into performance dashboards and team-based incentives. In addition to core task metrics, organizations may track leader-evaluated indicators of team reciprocity - such as responsiveness to leader support or willingness to assume additional responsibilities - and incorporate these into periodic performance reviews. Consistent with compensation design principles, a limited proportion (e.g., 20–35%) of variable team-based rewards can be tied to such non-core relational metrics to avoid distorting primary performance objectives (Milkovich et al., 2014). Used in this way, reciprocity metrics can help organizations identify teams at risk of leader disengagement and sustain leaders’ discretionary efforts over time.

Third, organizations should implement systems for early detection and repair of breaches. This can be achieved by deploying monthly leader pulse surveys, configuring automated HR analytics to flag leaders who report elevated breach risk, and institutionalizing standardized repair protocols to transform breaches into opportunities for relationship realignment (Rousseau et al., 2018). Fourth, organizations may replace burnout-centric interventions with cognitive resource management tools for leaders. This can be achieved by implementing decision-support algorithms that flag low-reciprocity teams when leaders propose discretionary efforts, coaching leaders to redirect their energy toward high-return team investment, and training that simulates investment trade-offs. Such interventions leverage leaders’ innate socio-cognitive calculus, converting disengagement from a personal failure into a strategic resource optimization challenge.

Limitations and Future Research Directions

Despite the theoretical and practical contributions, we acknowledge several limitations that deserve future attention. First, leaders may sometimes focus on salient individual members when rating the team. To mitigate this, we framed items at the collective level (‘team members’), provided explicit instructions for leaders to evaluate the team as a whole, and employed a validated team-level supervisor-as-principal measure. Multiple robustness checks—including CFA, internal consistency, correlations with aggregated team behaviors, sensitivity analyses, controls for team size, and NCA—further support the measure’s validity. Nevertheless, we cannot fully rule out subtle individual-level biases in individual’s interpretation. Future research could strengthen team-level measurement by incorporating additional data sources, such as peer assessments or behavioral observations.

Second, scenario-based experiments present inherent limitations in terms of external validity due to their controlled nature and short-term focus. Future research may further bolster ecological validity by considering a similar framework in the field or quasi-experiments in more naturally occurring workplace settings.

Third, our study employed a relatively short time lag (e.g., one month) to capture dynamic leader-team exchanges. While this was suitable for detecting perceptions of leaders’ PCB, longer-term studies may offer deeper insights into the evolving nature of leader-team obligations, including outcomes such as promotability (Li et al., 2023) and career advancement (Bordia et al., 2017). Fourth, individual differences, such as employee conscientiousness and competence (Lin et al., 2019), may influence the leaders’ PCB experience and warrant future examination as moderating conditions.

Finally, this research was conducted in a high power-distance cultural context (i.e., Pakistan, and China), where hierarchical norms may influence how psychological contracts are perceived and acted upon. To enhance generalizability, future studies should replicate and extend this work in other cultural contexts with varying levels of power distance and social exchange norms.

Conclusion

Our research offers a new perspective on leaders’ reduction of ERI in their teams, revealing that such investment heightens leaders’ perception of PCB when team OCB-L is lacking. The PCB perceptions, motivate leaders to conserve investment and reciprocate similarly. Consequently, our study shifts the scholarly focus from traditional employer-employee psychological contracts to a leader-team perspective, offering an important theoretical viewpoint for future research to study leader-team dynamics.

Supplemental Material

Supplemental Material - When and How Leaders Withdraw Team Extra-Role Investment: The Role of Leaders’ Psychological Contract Breach

Supplemental Material for When and How Leaders Withdraw Team Extra-Role Investment: The Role of Leaders’ Psychological Contract Breach by Hafiz Habib Tayyab, Qingxiong Weng, Abdul Karim Khan, Ahmed Ali, Gulfam Murtaza, Basharat Javed in Group & Organization Management

Footnotes

ORCID iD

Hafiz Habib Tayyab

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China; 72472146.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental Material

Supplemental material for this article is available online

Author Biographies

Hafiz Habib Tayyab is a PhD candidate at the University of Science and Technology of China, China. His research focuses on dynamic psychological contracts, leadership processes, role enrichment, well-being, intrapreneurship and innovative work behavior.

Qingxiong (Derek) Weng is a professor at the University of Science and Technology of China, China. His research interests include vocational psychology, personnel selection, organizational behavior, and entrepreneurship.

Abdul Karim Khan is a professor at United Arab Emirates University, United Arab Emirates. His research focuses on leadership, workplace emotions, and knowledge management.

Ahmed Ali is an assistant professor at King Fahd University of Petroleum & Minerals, Saudi Arabia. His research interests include leadership and organizational behavior.

Gulfam Murtaza is an assistant professor at Al Ghazali University, Pakistan. His research interests include ambivalent leadership and organizational behavior.

Basharat Javed is an associate professor at Al Ghazali University, Pakistan. His research focuses on design thinking, innovative behavior, inclusive leadership, and Islamic work ethics.

References

Akkermans

De Jong

Bal

P. M.

(2019). Me and my team: The role of social context in psychological contract breach and fulfilment. In Handbook of research on the psychological contract at work (pp. 164–185). Edward Elgar Publishing.

Allen

T. D.

Rush

M. C.

(1998). The effects of organizational citizenship behavior on performance judgments: A field study and a laboratory experiment. Journal of Applied Psychology, 83(2), 247–260. https://doi.org/10.1037/0021-9010.83.2.247

Asante

E. A.

Gyensare

M. A.

El Bouzidi

Twumasi

(2025). An employee–employer relationship gone bad? Examining the double‐edged effect of psychological contract violation on employees' helping behaviors. Industrial Relations: A Journal of Economy and Society, 64(1), 103–124. https://doi.org/10.1111/irel.12358

Atkinson

T. P.

Matthews

R. A.

Henderson

A. A.

Spitzmueller

(2018). Reactions to psychological contract breaches and organizational citizenship behaviours: An experimental manipulation of severity. Stress and Health, 34(3), 391–402. https://doi.org/10.1002/smi.2798

Bankins

Griep

Hansen

S. D.

(2020). Charting directions for a new research era: Addressing gaps and advancing scholarship in the study of psychological contracts (Vol. 29, pp. 159–163). Taylor & Francis.

Blau

(1964). Exchange and power in social life. Wiley.

Blau

(2017). Exchange and power in social life. Routledge.

Bliese

(2000). Within-group agreement, non-independence, and reliability: Implications for data aggregation and analysis. In Multilevel theory, research, and methods in organizations. Jossey-Bass.

Bordia

Restubog

S. L. D.

Bordia

Tang

R. L.

(2017). Effects of resource availability on social exchange relationships: The case of employee psychological contract obligations. Journal of Management, 43(5), 1447–1471. https://doi.org/10.1177/0149206314556317

10.

Carsten

M. K.

Uhl-Bien

West

B. J.

Patera

J. L.

McGregor

(2010). Exploring social constructions of followership: A qualitative study. The Leadership Quarterly, 21(3), 543–562. https://doi.org/10.1016/j.leaqua.2010.03.015

11.

Chan

(1998). Functional relations among constructs in the same content domain at different levels of analysis: A typology of composition models. Journal of Applied Psychology, 83(2), 234–246. https://doi.org/10.1037/0021-9010.83.2.234

12.

Chen

Yuan

Liu

Zhu

(2020). Social bonding or depleting? A team‐level investigation of leader self‐sacrifice on team and leader work engagement. Journal of Occupational and Organizational Psychology, 93(4), 912–941. https://doi.org/10.1111/joop.12315

13.

Chen

Z. X.

Tsui

A. S.

Zhong

(2008). Reactions to psychological contract breach: A dual perspective. Journal of Organizational Behavior: The International Journal of Industrial, Occupational and Organizational Psychology and Behavior, 29(5), 527–548. https://doi.org/10.1002/job.481

14.

Choi

J. N.

(2009). Collective dynamics of citizenship behaviour: What group characteristics promote group‐level helping? Journal of Management Studies, 46(8), 1396–1420. https://doi.org/10.1111/j.1467-6486.2009.00851.x

15.

Choi

Mai-Dalton

R. R.

(1999). The model of followers' responses to self-sacrificial leadership: An empirical test. The Leadership Quarterly, 10(3), 397–421. https://doi.org/10.1016/s1048-9843(99)00025-9

16.

Chun

J. S.

Shin

Choi

J. N.

Kim

M. S.

(2013). How does corporate ethics contribute to firm financial performance? The mediating role of collective organizational commitment and organizational citizenship behavior. Journal of management, 39(4), 853–877. https://doi.org/10.1177/0149206311419662

17.

Costa

S. P.

Neves

(2017). Forgiving is good for health and performance: How forgiveness helps individuals cope with the psychological contract breach. Journal of Vocational Behavior, 100, 124–136. https://doi.org/10.1016/j.jvb.2017.03.005

18.

Coyle

P. T.

Goswami

Foti

R. J.

(2023). Using a role-based approach to develop a comprehensive typology of follower characteristics and behaviors. Group & Organization Management, 48(2), 468–506. https://doi.org/10.1177/10596011231162725

19.

Coyle-Shapiro

J. A.-M.

Pereira Costa

Doden

Chang

(2019). Psychological contracts: Past, present, and future. Annual Review of Organizational Psychology and Organizational Behavior, 6(1), 145–169. https://doi.org/10.1146/annurev-orgpsych-012218-015212

20.

Cropanzano

Anthony

E. L.

Daniels

S. R.

Hall

A. V.

(2017). Social exchange theory: A critical review with theoretical remedies. The Academy of Management Annals, 11(1), 479–516. https://doi.org/10.5465/annals.2015.0099

21.

Cropanzano

Mitchell

M. S.

(2005). Social exchange theory: An interdisciplinary review. Journal of Management, 31(6), 874–900. https://doi.org/10.1177/0149206305279602

22.

De Cremer

Van Knippenberg

(2002). How do leaders promote cooperation? The effects of charisma and procedural fairness. Journal of Applied Psychology, 87(5), 858–866. https://doi.org/10.1037/0021-9010.87.5.858

23.

De Clercq

Azeem

M. U.

Haq

I. U.

(2021). But they promised! how psychological contracts influence the impact of felt violations on job-related anxiety and performance. Personnel Review, 50(2), 648–666. https://doi.org/10.1108/pr-07-2019-0388

24.

Decoster

Stouten

Camps

Tripp

T. M.

(2014). The role of employees' OCB and leaders' hindrance stress in the emergence of self-serving leadership. The Leadership Quarterly, 25(4), 647–659. https://doi.org/10.1016/j.leaqua.2014.02.005

25.

DeRue

D. S.

Ashford

S. J.

(2010). Who will lead and who will follow? A social process of leadership identity construction in organizations. Academy of Management Review, 35(4), 627–647. https://doi.org/10.5465/amr.2010.53503267

26.

Dul

(2016). Identifying single necessary conditions with NCA and fsQCA. Journal of Business Research, 69(4), 1516–1523. https://doi.org/10.1016/j.jbusres.2015.10.134

27.

Dul

(2024). Necessary condition analysis (NCA) with R (version 4.0. 0): A quick start guide.

28.

Ehrhart

M. G.

Bliese

P. D.

Thomas

J. L.

(2006). Unit-level OCB and unit effectiveness: Examining the incremental effect of helping behavior. Human Performance, 19(2), 159–173. https://doi.org/10.1207/s15327043hup1902_4

29.

Ehrhart

M. G.

(2004). Leadership and procedural justice climate as antecedents of unit‐level organizational citizenship behavior. Personnel Psychology, 57(1), 61–94. https://doi.org/10.1111/j.1744-6570.2004.tb02484.x

30.

Eisenberger

Rhoades Shanock

Wen

(2020). Perceived organizational support: Why caring about employees counts. Annual Review of Organizational Psychology and Organizational Behavior, 7(1), 101–124.

31.

Eisenberger

Armeli

Rexwinkel

Lynch

P. D.

Rhoades

(2001). Reciprocation of perceived organizational support. Journal of Applied Psychology, 86(1), 42–51. https://doi.org/10.1037/0021-9010.86.1.42

32.

Fuller

C. M.

Simmering

M. J.

Atinc

Babin

B. J.

(2016). Common methods variance detection in business research. Journal of Business Research, 69(8), 3192–3198. https://doi.org/10.1016/j.jbusres.2015.12.008

33.

Gakovic

Tetrick

L. E.

(2003). Psychological contract breach as a source of strain for employees. Journal of Business and Psychology, 18(2), 235–246. https://doi.org/10.1023/a:1027301232116

34.

Garcia

P. R. J. M.

Bordia

Restubog

S. L. D.

Caines

(2018). Sleeping with a broken promise: The moderating role of generativity concerns in the relationship between psychological contract breach and insomnia among older workers. Journal of Organizational Behavior, 39(3), 326–338. https://doi.org/10.1002/job.2222

35.

Gouldner

A. W.

(1960). The norm of reciprocity: A preliminary statement. American Sociological Review, 25(2), 161–178. https://doi.org/10.2307/2092623

36.

Greenberg

Folger

(2012). Controversial issues in social research methods. Springer Science & Business Media.

37.

Greenberg

Tomlinson

E. C.

(2004). Situated experiments in organizations: Transplanting the lab to the field. Journal of management, 30(5), 703–724. https://doi.org/10.1016/j.jm.2003.11.001

38.

Griep

Germeys

Kraak

J. M.

(2021). Unpacking the relationship between organizational citizenship behavior and counterproductive work behavior: Moral licensing and temporal focus. Group & Organization Management, 46(5), 819–856. https://doi.org/10.1177/1059601121995366

39.

Griep

Kraak

J. M.

Knol

W. M.

Dolislager

Beekman

E. M.

(2025). The ripple effect of abusive supervision: A longitudinal examination of psychological contract breach, turnover intentions, and resilience among third parties. Journal of Business Research, 189, Article 115141. https://doi.org/10.1016/j.jbusres.2024.115141

40.

Haeckl

Rege

(2025). Effects of supportive leadership behaviors on employee satisfaction, engagement, and performance: An experimental field investigation. Management Science, 71(1), 347–365.

41.

Halbesleben

J. R.

Wheeler

A. R.

(2015). To invest or not? The role of coworker support and trust in daily reciprocal gain spirals of helping behavior. Journal of management, 41(6), 1628–1650. https://doi.org/10.1177/0149206312455246

42.

Haslam

S. A.

Alvesson

Reicher

S. D.

(2024). Zombie leadership: Dead ideas that still walk among us. The Leadership Quarterly, 35(3), Article 101770. https://doi.org/10.1016/j.leaqua.2023.101770

43.

Hemshorn de Sanchez

C. S.

Gerpott

F. H.

Lehmann‐Willenbrock

(2022). A review and future agenda for behavioral research on leader–follower interactions at different temporal scopes. Journal of Organizational Behavior, 43(2), 342–368. https://doi.org/10.1002/job.2583

44.

Hobfoll

S. E.

Halbesleben

Neveu

J.-P.

Westman

(2018). Conservation of resources in the organizational context: The reality of resources and their consequences. Annual Review of Organizational Psychology and Organizational Behavior, 5(1), 103–128. https://doi.org/10.1146/annurev-orgpsych-032117-104640

45.

Hollander

E. P.

Julian

J. W.

(1969). Contemporary trends in the analysis of leadership processes. Psychological Bulletin, 71(5), 387–397. https://doi.org/10.1037/h0027347

46.

Homans

G. C.

(1958). Social behavior as exchange. American Journal of Sociology, 63(6), 597–606. https://doi.org/10.1086/222355

47.

James

L. R.

Demaree

R. G.

Wolf

(1984). Estimating within-group interrater reliability with and without response bias. Journal of Applied Psychology, 69(1), 85–98. https://doi.org/10.1037/0021-9010.69.1.85

48.

Javaid

Kumari

Khan

S. N.

Jaaron

A. A.

Shaikh

(2023). Leader green behavior as an outcome of followers' critical thinking and active engagement: The moderating role of pro-environmental behavior. The Leadership & Organization Development Journal, 44(2), 218–239. https://doi.org/10.1108/lodj-07-2021-0361

49.

Jensen

J. M.

Opland

R. A.

Ryan

A. M.

(2010). Psychological contracts and counterproductive work behaviors: Employee responses to transactional and relational breach. Journal of Business and Psychology, 25(4), 555–568. https://doi.org/10.1007/s10869-009-9148-7

50.

Kaya

Karatepe

O. M.

(2020). Attitudinal and behavioral outcomes of work-life balance among hotel employees: The mediating role of psychological contract breach. Journal of Hospitality and Tourism Management, 42, 199–209. https://doi.org/10.1016/j.jhtm.2020.01.003

51.

Khan

A. K.

Moss

Quratulain

Hameed

(2018). When and how subordinate performance leads to abusive supervision: A social dominance perspective. Journal of Management, 44(7), 2801–2826. https://doi.org/10.1177/0149206316653930

52.

Kiazad

Seibert

S. E.

Kraimer

M. L.

(2014). Psychological contract breach and employee innovation: A conservation of resources perspective. Journal of Occupational and Organizational Psychology, 87(3), 535–556. https://doi.org/10.1111/joop.12062

53.

Kim

B.-J.

Kim

M.-J.

(2024). The influence of work overload on cybersecurity behavior: A moderated mediation model of psychological contract breach, burnout, and self-efficacy in AI learning such as ChatGPT. Technology in Society, 77, Article 102543. https://doi.org/10.1016/j.techsoc.2024.102543

54.

Kim

Vandenberghe

(2020). Ethical leadership and team ethical voice and citizenship behavior in the military: The roles of team moral efficacy and ethical climate. Group & Organization Management, 45(4), 514–555.

55.

Knapp

J. R.

Diehl

M.-R.

Dougan

(2020). Towards a social-cognitive theory of multiple psychological contracts. European Journal of Work & Organizational Psychology, 29(2), 200–214. https://doi.org/10.1080/1359432x.2019.1709538

56.

Knox

Way

K. A.

Haslam

S. A.

(2025). Whatever your job is, we are all about doing that thing super well’: High‐reliability followership as a key component of operational success in elite air force teams. British Journal of Social Psychology, 64(2), Article e12882. https://doi.org/10.1111/bjso.12882

57.

Kraak

J. M.

Linde

B. J.

(2019). The usefulness of the psychological contract in the 21st century. In Handbook of research on the psychological contract at work (pp. 101–121). Edward Elgar Publishing.

58.

Kugler

Sims

(2025). Following the beaten paths: A systematic literature review of followership behavior. The Journal of Management Development.

59.

Lambert

L. S.

(2011). Promised and delivered inducements and contributions: An integrated view of psychological contract appraisal. Journal of Applied Psychology, 96(4), 695–712. https://doi.org/10.1037/a0021692

60.

Laulié

Escaffi-Schwarz

(2024). Emergence in context: How team-client psychological contract fulfillment is associated with the emergence of team identification or team-member exchange. Journal of Applied Psychology.

61.

Laulié

Tekleab

A. G.

(2016). A multi-level theory of psychological contract fulfillment in teams. Group & Organization Management, 41(5), 658–698. https://doi.org/10.1177/1059601116668972

62.

Laulié

Tekleab

A. G.

Rousseau

D. M.

(2025). Psychological contracts at different levels: The cross-level and comparative multilevel effects of team psychological contract fulfillment. Group & Organization Management, 50(3), 1020–1060. https://doi.org/10.1177/10596011231203365

63.

Lee

Liu

Rousseau

D. M.

Hui

Chen

Z. X.

(2011). Inducements, contributions, and fulfillment in new employee psychological contracts. Human Resource Management, 50(2), 201–226. https://doi.org/10.1002/hrm.20415

64.

C. H.

Dong

Weisman

Sun

L. Y.

(2023). A psychological contract perspective on how and when employees' promotive voice enhances promotability. Human Resource Management Journal.

65.

Liao

Lee

H. W.

Johnson

R. E.

Lin

S.-H.

(2021). Serving you depletes me? A leader-centric examination of servant leadership behaviors. Journal of Management, 47(5), 1185–1218. https://doi.org/10.1177/0149206320906883

66.

Liden

R. C.

Wang

(2025). The evolution of leadership: Past insights, present trends, and future directions. Journal of Business Research, 186, Article 115036. https://doi.org/10.1016/j.jbusres.2024.115036

67.

Lin

S.-H.

Scott

B. A.

Matta

F. K.

(2019). The dark side of transformational leader behaviors for leaders themselves: A conservation of resources perspective. Academy of Management Journal, 62(5), 1556–1582. https://doi.org/10.5465/amj.2016.1255

68.

Liu

Gong

Liu

(2014). When do business units benefit more from collective citizenship behavior of management teams? An upper echelons perspective. Journal of Applied Psychology, 99(3), 523–534. https://doi.org/10.1037/a0035538

69.

Lundmark

Tafvelin

Stenling

(2023). Depleting pathways of self-sacrificial and laissez-faire leadership: The roles of leader gender and perceived organizational support. International Journal of Stress Management.

70.

Malatesta

R. M.

(1995). Understanding the dynamics of organizational and supervisory commitment using a social exchange framework. Wayne State University.

71.

Milkovich

G. T.

Newman

J. M.

Gerhart

(2014). Compensation. McGraw-Hill.

72.

Morrison

E. W.

Robinson

S. L.

(1997). When employees feel betrayed: A model of how psychological contract violation develops. Academy of Management Review, 22(1), 226–256. https://doi.org/10.2307/259230

73.

Muthén

(2017). Mplus. In Handbook of item response theory (pp. 507–518). Chapman and Hall/CRC.

74.

Nohe

Michaelis

(2016). Team OCB, leader charisma, and organizational change: A multilevel study. The Leadership Quarterly, 27(6), 883–895. https://doi.org/10.1016/j.leaqua.2016.05.006

75.

Chintakananda

Bashshur

M. R.

Day

D. V.

(2023). The study of followers in leadership research: A systematic and critical review. The Leadership Quarterly, 34(1), Article 101674. https://doi.org/10.1016/j.leaqua.2022.101674

76.

Organ

D. W.

(1988). OCB: The good soldier syndrome. Lexington Books.

77.

Organ

D. W.

(2014). Organizational citizenship behavior: It's construct clean-up time. In Organizational citizenship behavior and contextual performance (pp. 85–97). Psychology Press.

78.

Podsakoff

P. M.

MacKenzie

S. B.

Lee

J.-Y.

Podsakoff

N. P.

(2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

79.

Podsakoff

P. M.

MacKenzie

S. B.

Podsakoff

N. P.

(2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63(1), 539–569. https://doi.org/10.1146/annurev-psych-120710-100452

80.

Preacher

K. J.

Curran

P. J.

Bauer

D. J.

(2006). Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics, 31(4), 437–448. https://doi.org/10.3102/10769986031004437

81.

Priesemuth

Taylor

R. M.

(2016). The more I want, the less I have left to give: The moderating role of psychological entitlement on the relationship between psychological contract violation, depressive mood states, and citizenship behavior. Journal of Organizational Behavior, 37(7), 967–982. https://doi.org/10.1002/job.2080

82.

Restubog

S. L. D.

Zagenczyk

T. J.

Bordia

Tang

R. L.

(2013). When employees behave badly: The roles of contract importance and workplace familism in predicting negative reactions to psychological contract breach. Journal of Applied Social Psychology, 43(3), 673–686. https://doi.org/10.1111/j.1559-1816.2013.01046.x

83.

Rhoades

Eisenberger

(2002). Perceived organizational support: A review of the literature. Journal of Applied Psychology, 87(4), 698–714. https://doi.org/10.1037/0021-9010.87.4.698

84.

Ribbat

Klasmeier

K. N.

Hüffmeier

(2024). Empirical Followership Research Since the Publication of the Formal Theory of Followership by Uhl-Bien et al.(2014)—A Systematic Review. Collabra: Psychology, 10(1), 92804. https://doi.org/10.1525/collabra.92804

85.

Rousseau

(1995). Psychological contracts in organizations: Understanding written and unwritten agreements. Sage publications.

86.

Rousseau

D. M.

Hansen

S. D.

Tomprou

(2018). A dynamic phase model of psychological contract processes. Journal of Organizational Behavior, 39(9), 1081–1098. https://doi.org/10.1002/job.2284

87.

Rupp

D. E.

Cropanzano

(2002). The mediating effects of social exchange relationships in predicting workplace outcomes from multifoci organizational justice. Organizational Behavior and Human Decision Processes, 89(1), 925–946. https://doi.org/10.1016/s0749-5978(02)00036-5

88.

Scandura

T. A.

Graen

G. B.

(1984). Moderating effects of initial leader–member exchange status on the effects of a leadership intervention. Journal of Applied Psychology, 69(3), 428–436. https://doi.org/10.1037/0021-9010.69.3.428

89.

Shaffakat

Otaye-Ebede

Reb

Chandwani

Vongswasdi

(2022). Mindfulness attenuates both emotional and behavioral reactions following psychological contract breach: A two-stage moderated mediation model. Journal of Applied Psychology, 107(3), 425–443. https://doi.org/10.1037/apl0000878

90.

Shamir

(2014). From passive recipients to active co-producers: Followers’ roles in the leadership process.

91.

Sidorenkov

A. V.

Borokhovski

E. F.

Vorontsov

D. V.

(2023). Associations of employees’ identification and citizenship behavior in organization: A systematic review and a meta-analysis. Management Review Quarterly, 73(2), 695–729. https://doi.org/10.1007/s11301-022-00258-9

92.

Stone-Romero

E. F.

Rosopa

P. J.

(2004). Inference problems with hierarchical multiple regression-based tests of mediating effects. In Research in personnel and human resources management (23, pp. 249–290). Emerald Group Publishing Limited.

93.

Stone-Romero

E. F.

Rosopa

P. J.

(2008). The relative validity of inferences about mediation as a function of research design characteristics. Organizational Research Methods, 11(2), 326–352. https://doi.org/10.1177/1094428107300342

94.

Tayyab

Weng

Popelnukha

Jisuvei Sungu

Tetteh

A. N.

(2023). Supervisor perception of psychological contract breach and abusive supervision. Academy of management proceedings.

95.

Tekleab

A. G.

Laulié

De Vos

De Jong

J. P.

Coyle-Shapiro

J. A.

(2020). Contextualizing psychological contracts research: A multi-sample study of shared individual psychological contract fulfilment. European Journal of Work & Organizational Psychology, 29(2), 279–293. https://doi.org/10.1080/1359432x.2019.1608294

96.

Tekleab

A. G.

Takeuchi

Taylor

M. S.

(2005). Extending the chain of relationships among organizational justice, social exchange, and employee reactions: The role of contract violations. Academy of Management Journal, 48(1), 146–157. https://doi.org/10.5465/amj.2005.15993162

97.

Tekleab

A. G.

Taylor

M. S.

(2003). Aren’t there two parties in an employment relationship? Antecedents and consequences of organization–employee agreement on contract obligations and violations. Journal of Organizational Behavior, 24(5), 585–608.

98.

Thommes

M. S.

Uitdewilligen

Rico

Waller

M. J.

(2024). Switching gears: How teams co-construct adaptive leadership style transitions in dynamic contexts. Organizational Psychology Review, 14(4), 542–570. https://doi.org/10.1177/20413866231214238

99.

Tsui

A. S.

Pearce

J. L.

Porter

L. W.

Tripoli

A. M.

(1997). Alternative approaches to the employee-organization relationship: Does investment in employees pay off? Academy of Management Journal, 40(5), 1089–1121. https://doi.org/10.2307/256928

100.

Uhl-Bien

(2006). Relational leadership theory: Exploring the social processes of leadership and organizing. The Leadership Quarterly, 17(6), 654–676. https://doi.org/10.1016/j.leaqua.2006.10.007

101.

Uhl-Bien

Ospina

S. M.

(2012). Advancing relational leadership research: A dialogue among perspectives. IAP.

102.

Uhl-Bien

Riggio

R. E.

Lowe

K. B.

Carsten

M. K.

(2014). Followership theory: A review and research agenda. The Leadership Quarterly, 25(1), 83–104. https://doi.org/10.1016/j.leaqua.2013.11.007

103.

Van Knippenberg

(2005). Leader self-sacrifice and leadership effectiveness: The moderating role of leader prototypicality. Journal of Applied Psychology, 90(1), 25–37. https://doi.org/10.1037/0021-9010.90.1.25

104.

Wang

Restubog

Shao

Van Kleef

G. A.

(2018). Does anger expression help or harm leader effectiveness? The role of competence-based versus integrity-based violations and abusive supervision. Academy of Management Journal, 61(3), 1050–1072. https://doi.org/10.5465/amj.2015.0460

105.

Wellman

Tröster

Grimes

Roberson

Rink

Gruber

(2023). Publishing multimethod research in AMJ: A review and best-practice recommendations. Academy of Management Journal, 66(4), 1007–1015. https://doi.org/10.5465/amj.2023.4004

106.

Williams

L. J.

Anderson

S. E.

(1991). Job satisfaction and organizational commitment as predictors of organizational citizenship and in-role behaviors. Journal of management, 17(3), 601–617. https://doi.org/10.1177/014920639101700305

107.

Yaffe

Kark

(2011). Leading by example: The case of leader OCB. Journal of Applied Psychology, 96(4), 806–826. https://doi.org/10.1037/a0022464

108.

Yang

Senewiratne

Newman

Sendjaya

Chen

(2023). Leader self‐sacrifice: A systematic review of two decades of research and an agenda for future research. Applied Psychology, 72(2), 797–831. https://doi.org/10.1111/apps.12407

109.

Zhang

Liu

(2024). Anger for good? Unethical‐behavior‐targeted leader anger expression and its consequences on team outcomes. Journal of Organizational Behavior, 45(1), 57–80. https://doi.org/10.1002/job.2756

110.

Zhao

Wayne

S. J.

Glibkowski

B. C.

Bravo

(2007). The impact of psychological contract breach on work‐related outcomes: A meta‐analysis. Personnel Psychology, 60(3), 647–680. https://doi.org/10.1111/j.1744-6570.2007.00087.x

111.

Zhu

Liao

Yam

K. C.

Johnson

R. E.

(2018). Shared leadership: A state‐of‐the‐art review and future research agenda. Journal of Organizational Behavior, 39(7), 834–852. https://doi.org/10.1002/job.2296

112.

Zhu

Y.-Q.

Gardner

D. G.

Chen

H.-G.

(2018). Relationships between work team climate, individual motivation, and creativity. Journal of Management, 44(5), 2094–2115. https://doi.org/10.1177/0149206316638161