Abstract
Purpose
Leaders are role models and through social influence processes, they shape the behaviour of their followers. We build on social learning, social identity and person-environment (P-E) fit theories of leadership to explore the association between leaders’ and followers’ resilient behaviours.
Design/methodology/approach
In a three-wave, multisource study amongst 269 Dutch leaders and their followers, we investigate the mediating role of coaching in the relationship between leaders’ resilient behaviour and followers’ resilient behaviour and the moderating role of regulatory focus in this mediation path.
Findings
Our results show that coaching is a key relational vehicle through which leaders’ resilient behaviours shape employees’ resilient behaviours, and this indirect association is stronger for employees scoring low on promotion focus. In addition, our results show that resilient employees attract more coaching from their leaders, which further strengthens their resilient behaviours.
Originality/value
Existing studies have shown the occurrence of trickle-down effects of various leader behaviours, moods and work states on those of their followers. However, it remained obscure whether leaders’ resilient behaviour could trickle down to followers’ as well. Our study shows that such a link indeed exists and that coaching is a relational vehicle that embodies two key mechanisms to (1) foster social learning through behavioural entrainment and contagion and (2) facilitate support provision through which leaders promote resilient behaviour in their followers.
Keywords
Citation
Caniëls, M.C.J. and Curseu, P. (2024), "Contagious resilience – how leaders’ resilient behaviour promotes followers’ resilient behaviour", Leadership & Organization Development Journal, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/LODJ-09-2023-0474
Publisher
:Emerald Publishing Limited
Copyright © 2024, Marjolein C.J. Caniëls and Petru Curseu
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
In modern, fast changing organisational contexts, employees have to be capable of recovering quickly from adverse events and such resilient behaviour (Bonanno, 2004; Sutcliffe and Vogus, 2003) fosters employees’ individual well-being and overall organisational performance (Hartmann et al., 2020; Lengnick-Hall et al., 2011; Van der Vegt et al., 2015). Programs designed to build workplace resilience typically focus on the individual employee and target the development of individual or person-centred resources (e.g. self-efficacy, mindfulness and optimism) as a way to protect against the expected negative impact of work-related stressors (e.g. Li and Tong, 2021; Rees et al., 2015; Vanhove et al., 2016; Luthans, 2012). Resilient behaviour can be developed through social influence processes (Eliot, 2020; Liu and Xiang, 2020), yet to date, the role of leaders as role models in promoting followers’ resilience has received much less empirical consideration (Richard, 2020; Franken et al., 2020, 2023; Nguyen et al., 2016). Building on the key tenets of social learning (Bandura, 1962), we argue that leaders model the resilient behaviours of their followers through coaching; therefore, we set out to explore how leaders’ own resilient behaviours inspire followers’ resilient behaviour. We build on the person-environment fit (P-E fit) theory of leadership (Lambert et al., 2012; Tepper et al., 2018) that conceptualises leadership as a pool of relational resources that followers use to satisfy their work-related and psychological needs and we argue that leaders help their followers to develop resilience through coaching. Coaching behaviours are defined as behaviours of leaders that entail “providing one-on-one feedback and insights aimed at guiding and inspiring improvements in an employee’s work performance” (Heslin et al., 2006, p. 874). We build on social and observational learning processes, to argue that leaders who display resilient behaviour themselves will promote resilient behaviour in their followers directly, as well as indirectly, i.e. via their coaching behaviour.
The P-E fit theory of leadership states that employees benefit most from the relational resources provided by their leaders when these resources fit precisely the followers’ needs (Tepper et al., 2018). Leaders’ coaching behaviours are proactive attempts to help employees and we argue that the relational resources supplied through coaching are needed more for employees who score low on security and nurturance need satisfaction and needed less for employees who inherently strive for advancement and accomplishment. We therefore introduce regulatory focus as framework to explore the boundary conditions for the coaching-based mediation mechanism that explains the association between leader and employee resilience. Regulatory focus theory (Higgins, 1997), identifies two different regulatory foci in self-regulation: (1) promotion focus is a motivational orientation towards the satisfaction of nurturance needs and aims at fulfilling the ideal self, seeking possibilities for growth and development; and (2) prevention focus is a motivational orientation towards the satisfaction of security needs aimed at fulfilling the ‘ought’ self, fulfilling obligations, responsibilities and seeking ways to obtain security (Higgins, 1997; Lanaj et al., 2012). Counterintuitively, and contrasting to their expectations, Brenninkmeijer et al. (2010) found that “the effect of job resources on motivational outcomes was more pronounced for individuals with a weak promotion focus” (Brenninkmeijer et al., 2010, p. 708). Building on the P-E fit theory of leadership (Tepper et al., 2018) and using a need satisfaction perspective, we argue that coaching followers for resilience and helping them recover after setbacks fits the satisfaction of security and nurturance needs of those scoring low on prevention and promotion focus. Therefore, we expect that leadership coaching will be more effective in generating follower resilience for people scoring low in promotion as well as prevention focus. For this reason, in line with the theorising about “relational needs fit” (Ehrhardt and Ragins, 2019) and the “social support paradox” (Shinn et al., 1984), we argue – similarly to what was found by Brenninkmeijer et al. (2010) – that the effect of coaching leadership (Heslin et al., 2006) on followers’ resilient behaviour will be more pronounced for followers with a weak promotion focus (as opposed to a strong promotion focus). Additionally, we explore the role of prevention focus in the coaching-resilience relationship and expect that followers scoring low on prevention focus would benefit more from leadership coaching than followers scoring high on prevention focus.
To summarise, the aim of our study is to examine the mediating role of coaching in the relationship between leaders’ resilient behaviour and followers’ resilient behaviour and the moderating role of regulatory focus in this mediation mechanism (Figure 1). Specifically, we focus on the possible crossover effects of leaders’ resilience, which reflects the extent to which leaders display resilient behaviour in their daily activities. Our study design uses time-lagged multisource data and corrects for auto regressions in our dependent variable.
This study envisions several theoretical contributions. First, we show that leaders serve as resilience role models as leader resilience trickles down to influence employees’ resilience. Second, we contribute to the P-E theory of leadership (Tepper et al., 2018) by showing that leaders’ coaching behaviours are the vehicle that transfers the relational resources related to resilience from leaders to their followers. Third, our study adds to the conceptualisation of leadership in terms of relational exchanges and builds on the P-E fit perspective to argue that leadership coaching works best when prevention and promotion focus are low rather than high. By exploring the moderating role of regulatory focus in the relationship between leaders’ coaching behaviours and followers’ resilient behaviours, our study contributes to the research on complementary fit (Ehrhardt and Ragins, 2019) and the “social support paradox” (Shinn et al., 1984). In this way, we identify the boundary conditions that qualify the relationship between leaders’ coaching behaviours and followers’ resilient behaviours.
Theoretical background and Hypotheses
Linking leaders’ resilient behaviour to followers’ resilient behaviour
Workplace resilience captures the capacity to bounce back and thrive despite experiencing adversity and setbacks at work (Smith et al., 2008; Kuntz et al., 2017). The interest in resilience at the workplace has been booming over the past years (Hartmann et al., 2020). Studies find that resilience of employees is associated with positive work outcomes, including organisational commitment and job performance (Meneghel et al., 2016a, 2016b; Wang et al., 2017; see Hartmann et al., 2020 for an overview) and personal outcomes, such as job satisfaction and happiness at work (e.g. Youssef and Luthans, 2007). With resilience increasingly being recognised as a capacity or a malleable state, i.e. an ability that may be developed over time (Bonanno, 2004; Xanthopoulou et al., 2009; Dello Russo and Stoykova, 2015; Tonkin et al., 2018), a fascinating idea (inspired from social learning, Bandura, 1962) presents itself that leaders’ resilience may spill over and could be passed on to followers and therefore promotes followers’ resilience though observational learning. Despite growing research interest in antecedents of employee resilience (e.g. Caniëls and Hatak, 2022; Hartmann et al., 2020), there is still limited understanding on how resilience can be fostered through social influence and in particular there is little empirical exploration of the link between supportive leadership and resilience of their followers (Cooke et al., 2019; Richard, 2020; Franken et al., 2020, 2023).
When followers experience and observe positive attitudes and behaviours of credible role models in leadership positions they are likely to mimic these attitudes and behaviours (Bandura, 1962). In light of the social identity approach to leadership, leaders are prototypical representations of the organisation (Hogg et al., 2012), therefore employees typically perceive their resilient leaders as demonstrating desirable and acceptable behaviours (Dietz et al., 2020). With their behaviours, resilient leaders showcase what they expect of their followers (Hogg et al., 2012) and followers will typically emulate the behaviour observed in their role models through behavioural entrainment and contagion (Hogg et al., 2012). We therefore argue that resilient leaders are prototypical organisational members (Hogg et al., 2012) who showcase exemplary resilience.
With respect to resilient behaviours, we expect that mostly a trickle-down mechanism (Masterson, 2001; Wo et al., 2019) is at play, as resilience is more typified as a behavioural capacity and less as a temporary mood or affective state (Kuntz et al., 2017). In light of the social identity view on leadership (Hogg et al., 2012), we argue that followers are likely to look to their resilient leader to emulate the appropriate way to react to and deal with a setback at work. In their reaction to adversity at work, leaders may send behavioural cues to followers about how to cope with setbacks, i.e. how to behave resiliently. When leaders expose highly resilient behaviour, they are signalling to their followers that resilient behaviour is desirable and encouraged by them.
Leaders’ resilient behaviour is positively related to followers’ resilient behaviour
Coaching as a mediator
Resilience can be conceived of as a behavioural capability (Kuntz et al., 2017) and as a personal resource that allows employees to cope with adversity. An important question is whether and how resilience can be exchanged in leader-follower dyads. We build on two streams of research to present coaching as one of the relevant vehicles through which resilience-related resources are transferred in leader-follower dyads. Based on correlates of resilience, we first argue that resilience generates a pro-social orientation focused on helping others to overcome setbacks; and, second, based on P-E fit theory of leadership (Tepper et al., 2018; Lambert et al., 2012), we argue that resilient leaders actively transfer personal resources to help their followers thrive and perform.
Resilience as positive psychological capital is developed over time by successfully overcoming adversity (Robertson et al., 2015), therefore resilient leaders are expected to have successfully coped with past adversities and possess personal resources that can be transferred to their followers. Literature on post-traumatic growth shows that resilient individuals who experience traumatic events undergo psychological changes that underscore the importance of their personal coping resources for themselves and others (Jayawickreme and Blackie, 2014). In line with such results, we expect that resilient leaders consider their personal resources relevant for others and use coaching to provide support and express exemplary behaviours that followers can mimic and increase their own resilience (i.e. social learning, Bandura, 1962). Think of modern influential speakers or writers that experienced post-traumatic growth and engage in public action to share their insights and support others to become more resilient. Meta-analytic evidence on trait resilience shows that resilient individuals display high levels of social confidence tend to experience more emotional stability and engage in social activities to support the achievement of their goals (Oshio et al., 2018). Moreover, in a meta-theory of resiliency and resilient behaviour, Richardson (2002) argues that resilience promotes altruism and pro-social behaviours as social mechanisms in service of self-actualisation. Based on such results, we expect resilient leaders to actively engage in social influence through coaching to increase their resilience and effectiveness of their employees.
The P-E fit theory of leadership (Tepper et al., 2018; Lambert et al., 2012) also focuses on such a transfer of relational resources from the leaders to their followers and posits that leadership effectiveness reflects the extent to which leaders supply the relational resources that their followers need. Coaching behaviours are directed towards identifying followers’ challenges and needs, so as to maximise their potential for facing adversity at work (Kim, 2014). In particular, Tepper et al. (2018) show that employees report more positive work attitudes and engage more in organisational citizenship behaviour when transformational leadership fits their daily needs. Resilient leaders attend to the emotional needs of their followers and engage in coaching behaviours to help them successfully overcome setbacks at work. We thus argue that leaders’ coaching behaviours are the relational vehicle through which personal resources supporting resilient behaviours are transferred between leaders and their followers. Resilient leaders have a wealth of experience in strategies that help to deal with the various types of setbacks that work (and life) throws at employees and they can transfer these resources though coaching.
Overall, studies on external factors that promote individual resilience often point to social support as a critical factor in overcoming setbacks (e.g. Kearns and McArdle, 2012; Wang et al., 2014; Zunz, 1998). Adversity at work may manifest itself as an isolated high-intensity event (e.g. crisis), or it may consist of long-during low-intensity circumstances (e.g. work stress) (Fisher et al., 2019). In both situations, trustful and authentic social relationships at work allow employees to share feelings and to improve coping experiences (Wilson and Ferch, 2005; McLarnon and Rothstein, 2013). Coaching behaviours of leaders can fulfil an important role in providing support to followers as it can be focused on followers’ specific workplace challenges (Hall et al., 1999; Heslin et al., 2006). Coaching also reflects a set of social influence behaviours through which relational and personal resources are transferred in leader-follower dyads, in that leaders who engage in coaching behaviours are role models that provide inspiration, guidance and facilitation to followers (Heslin et al., 2006).
We therefore argue that coaching is a relational vehicle that embodies two key mechanisms to (1) foster social learning through behavioural entrainment and contagion; and (2) facilitate support provision though which leaders promote resilient behaviour in their followers.
Coaching mediates the association between leaders’ and followers’ resilient behaviours.
The moderating role of regulatory focus
In line with the P-E fit theory of leadership (Tepper et al., 2018; Lambert et al., 2012) the resources supplied through coaching behaviours by leaders are not equally needed or relevant for all employees. In other words, the relational resources transferred through coaching behaviours impact differently on followers’ resilient behaviours depending on their motivational needs. Regulatory focus theory (Higgins, 1997) poses that individuals are motivated by two independent self-regulatory orientations: promotion and prevention. Individuals with a promotion focus are motivated to go from the current state to the desired state by the gains that are associated with the desired state. Promotion-focused individuals aim for advancement, growth and attainment of aspirations and ideals. At work, promotion-focused individuals are motivated by the desirable growth outcomes that result from their work activities (Johnson and Chang, 2008). Relating the promotion focus to resilient behaviours, we argue that employees scoring high on promotion focus have the strategies to search for and acquire sufficient personal resources to cope with adversity on their own. In contrast, prevention-focused individuals emphasise avoiding losses. They strive for safety, security and the fulfilment of duties and obligations. At work, they are motivated to engage in work activities by a sense of obligation, fear of letting others down and avoiding mistakes (Johnson and Chang, 2008). In relation to resilience, employees scoring high on prevention focus are likely to avoid setbacks as they continuously assess the environment in terms of risks and use protective strategies to avoid setbacks and disadvantageous situations at work.
According to the P-E fit theory of leadership (Tepper et al., 2018) and in line with regulatory focus theory (Higgins, 1997) we believe followers will perceive leaders’ coaching behaviours as a resource that fulfils their motivational needs and provides them with opportunities to develop and grow. From a resource accumulation perspective on the relationship between leaders’ coaching behaviours and followers’ resilience, one would expect followers with a strong promotion focus to be particularly responsive to the beneficial effects of leaders’ coaching behaviours. Yet, a few studies show contrasting results (Brenninkmeijer et al., 2010; Liu and Xiang, 2020) and point towards a complementary fit perspective, such that relational resources provided by leaders are best used when employees are lacking such resources. In these studies, positive effects of job resources were more beneficial to followers with a weak promotion focus compared to followers with a strong promotion focus. Notably, Brenninkmeijer et al. (2010) showed that employees with a strong promotion focus had high levels of positive work outcomes, irrespective of the amount of perceived job resources. Similarly, Liu and Xiang (2020) found that the association between leaders’ coaching behaviours and followers’ work outcomes was non-significant in the high promotion focus group, whilst being positive and significant for followers with weak promotion focus. Moreover, Kuntz et al. (2017) showed in a sample of 162 white collar employees that job feedback was positively related to employee resilience only for those scoring low rather than high on promotion focus, whilst supervisory feedback was positively related to employee resilience only for those scoring low rather than high on prevention focus. The strongest association between both job as well as supervisory feedback with employee resilience was observed when both prevention and promotion focus were low.
These counterintuitive findings are perfectly in line with the P-E fit theory of leadership as coaching resources fit best motivational profiles in which both the prevention as well as the promotion focus is low, as these employees need more guidance, support and attention from their leaders. They are also in line the Conservation of Resources Theory (Hobfoll, 1989): followers with a strong promotion focus are capable of accumulating resources in so-called “resource caravans”, as having one resource is usually associated with having others as well, whilst followers with a weak promotion focus may depend to a larger extent on resources that are provided to them in the work environment, i.e. followers with a weak promotion focus may be more susceptible to the beneficial effects of available resources at work, including leaders’ coaching behaviours.
Similarly, prevention-focused followers may perceive leaders’ coaching behaviours as providing information about which expectations need to be fulfilled (Johnson and Chang, 2008). Leaders’ coaching behaviours may provide safety and security to followers who have a strong prevention focus. Drawing on this line of reasoning, we pose:
Regulatory focus moderates the positive association between leaders’ coaching behaviour and followers’ resilient behaviour, such that these effects will be stronger for those who have a weak promotion focus (3a), or have a weak prevention focus (3b).
The moderated mediation
Hypotheses 2 and 3 suggest a conditional indirect effect of leaders’ coaching in the relationship between leaders’ own resilient behaviours and that of their followers. This conditional indirect effect exists when the strength of a mediated relationship varies across the levels of regulatory focus. This reasoning follows the notion of “relational needs fit” (e.g. Kausel and Slaughter, 2011; Ehrhardt and Ragins, 2019), which reflects followers’ perceptions about the extent in which their needs are met in their work relationships. Followers may differ in what they want and need in terms of coaching and support from their work relationships (Ehrhardt and Ragins, 2019). In fact, receiving too much support, was found to be experienced as intrusive and controlling and led to followers pulling back from their work relationships (Ehrhardt and Ragins, 2019). For example, Liu and Xiang (2020) found that above a certain level, guidance from leaders served to undermine followers’ learning willingness rather than to promote it. Literature about social support and personal relationships have acknowledged this effect and labelled it as the “social support paradox” (see Shinn et al., 1984; Shumaker and Brownell, 1984). Surprisingly, with the exception of Ehrhardt and Ragins (2019), management studies largely overlooked this effect a priori and only theorised about it after it occurred in findings (Brenninkmeijer et al., 2010; Liu and Xiang, 2020). Such an effect is however specified in the P-E fit theory of leadership, as the excess in resources supply may lead to negative outcomes, especially when the resources have antagonistic properties (Tepper et al., 2018; Lambert et al., 2012). Coaching for resilience could be antagonistic for followers scoring high on prevention focus, as they are motivated to avoid risky and disadvantageous situations. Emphasising the need to recover after setbacks may generate the expectation that they do have to take risks and could potentially fail.
In brief, we hypothesise that promotion focus buffers the indirect relationship of leaders’ resilience with followers’ resilience via leaders’ coaching. In other words, because they have substantial resources to cope with setbacks followers who score high on promotion focus (or low on prevention focus) will not benefit from coaching, whilst employees low on promotion focus (or high on prevention focus) need the resilient and coaching leader to enact resilient behaviour themselves. We also expect that employees scoring high on prevention focus tend to avoid risky situations involving possible setbacks and as such coaching for resilience is an antagonistic relational resource for them, whilst leaders’ coaching behaviour serves as a vehicle for fostering resilient behaviour in followers scoring low on prevention focus.
Regulatory focus moderates the positive indirect association between leaders’ coaching behaviour and followers’ resilient behaviour in a way that the indirect path is stronger for individuals who score low on promotion focus (4a) or low on prevention focus (4b).
Methods
Sample and procedure
Dyadic data were collected from various Dutch leaders and their followers using a cross-lagged design. Our sample covered employees in various sectors, including financial and business services, health care and manufacturing. The data consisted of leader-follower dyads, with each leader having one unique follower. Leaders and followers completed two online questionnaires each. Due to practical reasons (holidays of respondents, availability of respondents and access to the survey tool) the following timeline was adopted: leaders’ first questionnaire (T1); followers’ first questionnaire (T2, 10 days after T1); leaders’ second questionnaire (T3, 4 weeks after T2); followers’ second questionnaire (T4, 7 weeks after T3). Prior to collecting the data, the characteristics of the study design were assessed and approved by the institutional Ethics Committee of the Open Universiteit. A cover letter explained the objective of the study and underlined the privacy of participants. Respondents provided informed consent and all usual remedies to curb common method bias were undertaken (use of pseudonyms, ability to stop anytime, etc.). In total 420 leaders were invited of which 384 completed the questionnaire on T1 (response rate: 91.4%). The first follower questionnaire (T2) generated 345 unique leader-follower pairs. The second data collection wave amongst followers (T4) generated 269 responses that could be matched to the earlier observations. Of the final sample (269 unique matched leader-follower pairs), 56% of leaders and 48% of followers were male; 43% of leaders and 22% of followers had a university degree. The average age of leaders was 46.4 years old and of followers it was 41.6 years old.
Measures
Our core constructs were assessed by using multiple-item scales of which the psychometric properties were validated in previous studies.
Resilient behaviour, i.e. the capacity to adapt positively to adverse conditions was measured using the nine-item scale developed by Näswall et al. (2019) assessing resilient work behaviours, anchored by 1 (strongly disagree) and 5 (strongly agree). We evaluated resilient behaviours of leaders at T1 and of followers at T2 and T4 (αT1 = 0.74, αT2 = 0.76, αT4 = 0.81). An example item is: “I use change at work as an opportunity for growth”.
Coaching. To assess the employee perception of leaders’ coaching behaviours at T2 we used the 10-item scale by Heslin et al. (2006), which covers guiding, facilitating and inspirational behaviours of leaders (αT2 = 0.90) and ranged from 1 (strongly disagree) to 5 (strongly agree). An example item is: “To what extent does your supervisor provide guidance regarding performance expectations?” We conducted a three-factor confirmatory factor analysis (CFA) to examine the distinctiveness of the three-factor model. The three-factor fitted the data better (χ2 = 133.82; df = 32; p = 0.00; comparative fit index (CFI) = 0.93; Tucker–Lewis index (TLI) = 0.91 and root mean square error approximation (RMSEA) = 0.11) than the one-factor model (χ2 = 484.15; df = 35; p = 0.00; CFI = 0.71; TLI = 0.62 and RMSEA = 0.22), indicating that a composite variable should be formed by first calculating the average of each lower-order coaching behaviour, before averaging over the three behaviours.
Regulatory focus was assessed amongst employees at T2, using the shortened form of the General Regulatory Focus Measure (GFRM) of Lockwood et al. (2002), which contain two subscales measuring promotion and prevention goals. The GRFM is one of the most popular measures of dispositional regulatory focus (Gorman et al., 2012). The four-item promotion scale (e.g. “I frequently imagine how I will achieve my hopes and aspirations”) as well as the four-item prevention scale (e.g. “I am anxious that I will fall short of my responsibilities and obligations”) were reliable (αT2 = 0.87 and αT2 = 0.77, respectively). A meta-analysis of 30 studies using the GRFM reported an average Cronbach’s alpha of α = 0.82 for both subscales (Gorman et al., 2012). Items were rated on a seven-point scale, ranging from 1 (totally disagree) to 7 (totally agree). We conducted a two-factor CFA to examine the distinctiveness of the two-factor model. The two-factor fitted the data better (χ2 = 55.392; df = 19; p = 0.00; CFI = 0.96; TLI = 0.94; RMSEA = 0.084) than the one-factor model (χ2 = 323.368; df = 20; p = 0.00; CFI = 0.66; TLI = 0.52; RMSEA = 0.24).
Controls. Several control variables were assessed, because studies have suggested that the demographic background of employees may account for some of the variance in their resilience (Meneghel et al., 2016b). We included age in years, gender (0 = male; 1 = female) and education level (1 = basic education; 2 = high school; 3 = applied; 4 = higher applied; 5 = university; 6 = PhD). Furthermore, we corrected for the level of follower resilient behaviour at T2. In this way we controlled for the autoregressive effect of follower resilient behaviour in the time period prior to our final measurement.
Analytic approach
To examine the hypothesised moderated mediation effects (Figure 1), we used a bootstrapping approach (n = 10,000) to assess the significance of the indirect effects at different levels of the moderator (Hayes, 2013). PROCESS for R (Hayes, 2022), template number 14, was used to test the significance of the indirect (i.e. mediated) effects moderated by regulatory focus, i.e. conditional indirect effects. Measures were grand mean-centred before the analyses. Followers’ resilient behaviour at T2 was included as a covariate in the moderated mediation analyses.
Confirmatory factor analysis (CFA) results
We followed the recommendations of Farrell (2010) and conducted a CFA including all measures to examine the distinctiveness of the scales. The CFA assumed a seven-factor structure to have a better fit than all other model specifications (Table 1).
Results
Table 2 presents means, standard deviations and correlations for all variables in our study. All correlations are below the threshold of 0.70 (Tabachnick and Fidell, 1996), indicating that the likelihood of multicollinearity is low. Table 1 indicates that correlations of gender and education level with all our main variables are below 0.3. The age of the employee showed a significant negative correlation of −0.31 with promotion focus. Furthermore, as expected, the resilience of employees at T4 was highly correlated to their resilience at T2. Given these correlations and conform the recommendations of Bernerth and Aguinis (2016) and Becker (2005) for parsimonious research designs, we decided to remove control variables that were uncorrelated to our core variables and only include follower’s age as a control variable to our regression analyses. Furthermore, we controlled for autocorrelation with respect to followers’ resilient behaviour.
The proposed moderated mediation model fits the data well (χ2 = 622.70; df = 367 χ2/df = 1.69; CFI = 0.89; TLI = 0.87; RMSEA = 0.51) (Kline, 2011). Figure 2 displays the results for the partial relationships in our hypothesised model. We find that all partial relationships (a-path as well as b-path) were significant. The paths towards and from leaders’ coaching behaviour had positive coefficients that were in accordance with what was expected.
Table 3 presents the results of our moderated mediation model (derived from 10,000 bootstrap samples). The total effect indicates that leaders’ resilient behaviour was positively associated with followers’ resilient behaviour (b = 0.23, confidence interval (CI) = [0.10; 0.37]), therefore Hypothesis 1 was supported.
Hypothesis 2 poses that leaders’ coaching behaviour mediates the relationship between leaders’ resilient behaviour and follower resilient behaviour. The estimate of the a-path (Table 2) showed that leaders’ resilient behaviour was positively associated with leaders’ coaching behaviour (b = 0.21, CI = [0.06; 0.36]). The estimate of the b-path shows that leaders’ coaching behaviour was positively associated with followers’ resilient behaviour (b = 0.10, CI = [0.10; 0.19] for the model that included promotion focus; and b = 0.11, CI = [0.030.20] for the model that included prevention focus). The direct effect was statistically significant for that model that included promotion focus (b = 0.12, CI = [0.010.23]) and also for the model that included prevention focus (b = 0.11, CI = [0.001; 0.23]). These findings suggest a partial mediation, indicating that leaders who score high on resilient behaviour have more resilient followers than leaders who score relatively low on resilient behaviour, given leaders’ coaching behaviours and the promotion focus (or prevention focus) of employees. Taken together, these findings are supportive of Hypothesis 2.
Hypothesis 3 stated that follower promotion (prevention) focus positively (negatively) moderates the relationship between leaders’ resilient behaviour and followers’ resilient behaviour. The interaction term (coaching x regulatory focus) was significant and negative (b = −0.07, CI = [−0.13; −0.01]) for promotion focus that is in line with our expectation and supports Hypothesis 3a. Yet, the interaction term was not significant for prevention focus (b = −0.05, CI = [−0.11; 0.00]). Hence, Hypothesis 3b was not supported in our sample.
The addition of the moderator, promotion (prevention) focus, on the b-path provides information about the conditions under which a positive relationship between leaders’ coaching behaviour and followers’ resilient behaviour occurs. The index of moderated mediation (IMM) (Hayes, 2015) is depicted in Figure 3 and shows the slope (and intercept) of the line that relates the independent with the dependent variable as a function of the moderator (Verboon and Peters, 2019). It shows how the relation between leaders’ coaching behaviour and followers’ resilient behaviour changed proportionally with changes in the promotion focus of the employee (IMM = −0.014, CI = [−0.039; −0.001]). The steeper the line, the stronger the moderated mediation effect. The downward sloping line in Figure 3 implies that the mediation by coaching is smaller for individuals who perceive more promotion focus compared to individuals who perceive less promotion focus, thereby supporting Hypothesis 4a.
The indirect effect of leaders’ resilient behaviour on followers’ resilient behaviour through leaders’ coaching was positive amongst followers with relatively weak promotion focus (b = 0.04, CI = [0.01; 0.10]) and relatively moderate promotion focus (b = 0.02, CI = [0.00; 0.05] but not different from zero amongst those with strong promotion focus (b = 0.00, CI = [−0.03; 0.03]). Figure 4 shows the mediated simple slopes plot. It depicts the indirect effect of leaders’ resilience on followers’ resilience through coaching for a low value of promotion focus (−SD) and a high value of promotion focus (+SD), as recommended by Hayes (2018). Parallel lines would indicate the absence of moderation, whilst the differently sloped lines in Figure 4 demonstrate the presence of moderation.
Additional analyses
Two additional analyses were carried out to add more clarity to the results and check the robustness of our findings: (1) first we needed to address a possible interplay of promotion and prevention focus as different motivational profiles benefit differently from leadership coaching behaviours and (2) second we needed to account for the relational interdependence between leaders and followers.
First, as previous studies looked at the interaction effect between the two motivational foci (Kuntz et al., 2017; Caniëls and Assen, 2019), treating the two motivational orientations as orthogonal constructs, we have explored the mediation role of leadership coaching for the four motivational profiles created by dichotomising promotion and prevention focus based on the sample average. For employees scoring low both on prevention and promotion focus, the indirect association was significant (b = 0.17, standardized error (SE) = 0.08, CI = [0.04; 0.49]), for employees scoring high on prevention and low on promotion the indirect association was not significant (b = 0.01, SE = 0.06, CI = [−0.11; 0.13]), for employees scoring low on prevention and high promotion focus the indirect association was significant (b = 0.08, SE = 0.04, CI = [0.004; 0.17]) and finally for the employees scoring high on both prevention and promotion focus the indirect association was not significant (b = 0.01, SE = 0.03, CI = [−0.05; 0.07]).
Second, given that data on resilient behaviours was collected from leaders and followers, one needs to account for the actor-partner interdependence. In order to check the robustness of our mediation results, we have supplemented the mediation analyses with an actor-partner modelling in which we have used leaders’ and followers’ resilience at their first measurement (T1 for leaders and T2 for followers) to predict leader and follower resilience at their second measurement (T3 for leaders and T4 for followers) using coaching as a mediator. In order to analyse the mediation and account for the actor-partner interdependence we have used the medyad function written for R (Coutts et al., 2019) that allows the test of mediation models in which independent and dependent variables are evaluated from dyads as it was the case in our design. The results of these analyses are summarised in Figure 5.
As illustrated in Figure 5, two indirect effects were significant. One of the indirect effects was the one identified in the initial analyses using PROCESS, namely leaders’ coaching behaviours significantly mediated the association between leaders’ resilient behaviour at time 1 and employees’ resilient behaviour at time 2 (a partner to actor indirect effect of 0.02, SE = 0.02, 95% CI[0.0001; 0.06]). Moreover, the MEDYAD analyses revealed another significant indirect effect, in which leaders’ coaching behaviours mediated the association between the employees’ resilient behaviour at time 1 and their resilient behaviours at time 2 (an actor to actor indirect effect 0.06, SE = 0.03, 95%CI [0.01; 0.12]). These additional analyses support the mediating role of coaching behaviours and shed more light on an additional mechanism that explains employees’ resilient behaviour. Employees that reported higher scores on resilient behaviours at time 1 reported they have received more coaching from their leaders’ that in turn enhanced their resilience at time 2. In other words, this mediation reflects a resilience capitalisation effect, in the sense that resilient employees seem to strengthen their initial resilience by attracting more coaching behaviours from their leaders.
Discussion
In this three-wave, multisource study, we showed that leaders are resilience role models as their resilient behaviour trickles down to influence their followers’ resilient behaviour. Moreover, we show that coaching is the vehicle that partially explains the association between leaders’ and followers’ resilient behaviours. Additionally, we explored the boundary conditions defined by the regulatory focus, under which this mediating role of coaching is effective and we found that followers’ promotion focus weakened the positive indirect relationship between leaders’ resilient behaviour and followers’ resilient behaviour via leaders’ coaching behaviour.
Theoretical implications
This study makes several important theoretical contributions. First, we advance the existing literature about leader-follower influences as well as the literature about the promotion of employee resilience by providing evidence for the link between leaders’ resilient behaviour and followers’ resilient behaviour. Our study shows that leader resilience is an antecedent of follower resilience and that coaching is a relational vehicle through which leaders offer support and signal exemplary behaviours that their followers can use as relational resources to enhance their resilience. Such insights contribute to the literature on coaching behaviours (e.g. Heslin et al., 2006) and show that coaching is the relational path through which employees draw on the relational resources provided by their leaders. Given that current insights in the relational mechanisms that explain the link between leadership resilience and the resilience of followers is limited (Cooke et al., 2019; Franken et al., 2020, 2023; Richard, 2020), we show that social influence processes between leaders and followers play a key role in resilience at work. The conservation of resources perspective (Hobfoll, 1989) through the “resource caravan” analogy, could also explain why followers scoring high on resilience attract more coaching behaviours from their leaders, one of the emergent findings of our paper. Building on a resource accumulation perspective we argue that resilient followers can use their personal resources (resilience) to attract more relational resources and motivate their leaders to engage in more coaching behaviours. In other words, employees use their personal resources (personal resilience) as well as relational resources (coaching and social support) to maintain and further increase their resilience. This resource accumulation perspective on the leader-member relations opens important venues for future research. On the one hand, future studies could further disentangle the actor-partner influences that explain such a transfer and accumulation of resources. We put forward two plausible explanations for such mediating effects of coaching. On the one hand we argued that through coaching followers attract more social support from their leaders and on the other hand we argued that coaching is the relational vehicle that makes exemplary resilient behaviour contagious. Future studies could disentangle these mechanisms and explore whether both mechanisms are equally at work for various categories of followers. It is not unreasonable to argue that followers scoring initially low on resilience could benefit more from social support provision, whilst followers scoring initially high on resilience could both seek support and engage in behavioural entrainment, thus capitalising more fully from the coaching leadership behaviours. Future studies could further explore other vehicles (next to coaching behaviours) through which these resources are transferred between leaders and their followers. Such studies could focus on a more fine grained evaluation of additional social influence mechanisms that could serve as potential explanations of how leaders influence the resilience of their followers. We have argued that resilient leaders are prototypical images of the organisation and they are more likely to emerge as role models to shape the resilient behaviours of their followers, therefore future research could test the extent to which identification with the leader and the organisation are likely mechanisms to explain the association between leader and follower resilient behaviours.
Second, our research advances current understanding of the boundary conditions under which such a mediating role of leaders’ coaching is prominent. Our results are aligned with a complementary fit perspective on P-E fit, namely that leadership relational resources are best used where promotion focus is lacking. Followers with relatively weak or moderate promotion focus benefit from leaders’ coaching behaviours, whereas followers with a strong promotion focus do not. This counterintuitive finding is in line with results reported by Brenninkmeijer et al. (2010) and Liu and Xiang (2020). Whilst previous studies have tried to find ad hoc explanations for this finding, we have a priori theorised the effect by building on the P-E fit theory of leadership (Lambert et al., 2012) and relying on the notion of “relational needs fit” (e.g. Kausel and Slaughter, 2011; Ehrhardt and Ragins, 2019) as well as on the “social support paradox” (Shinn et al., 1984; Shumaker and Brownell, 1984). These theoretical arguments also explain the non-significant association between supervisor support and the resilience of low-promotion-focused employees reported in the study of Kuntz et al. (2017). Our results show that low-promotion-focused and high-prevention-focused employees report less resilient behaviours and such a pattern of results could reflect that low-promotion-focused individuals and high-prevention individuals may avoid setbacks by pre-emptively mitigating risks in their work-related actions. As such, these employees do not report engaging in resilient behaviours because they do not have to cope with setbacks associated with taking substantial risks in their work life. Future research could explore this interpretation, because it is the cornerstone of our complimentary fit interpretation of leader – member interactions (coaching for resilience is required for those followers who do experience setbacks in their work).
Our supplemental analyses explored whether promotion and prevention focus interact such that different motivational profiles benefit differently from leadership coaching behaviours. A high promotion-high prevention profile has been shown to be positively associated with high levels of employee resilience (Kuntz et al., 2017), a motivational profile that is less likely to require leadership coaching as a source for developing resilient behaviours. Our data supported this notion, as the mediating effect of coaching was not significant for followers with a high promotion-high prevention profile. In contrast, coaching as a mediator did work for followers with either a low promotion-low prevention profile, or a high promotion-low prevention profile. These findings suggest that coaching by resilient leaders works best for followers who seek security and confirmation from their leaders. Our resilience measure focused on resilient behaviours as we explored the malleable and relational nature of resilience, yet future research could focus on resilience as a trait. When the congruence between leader and follower trait resilience is high, leadership coaching could be more effective than in situations of low leader-follower congruence in resilience. The motivational profiles shape the way in which employees engage with work-related issues. For example, the risk avoidance tendencies of employees scoring high on prevention may lead to fewer setbacks at work that ultimately require resilience, whilst a promotion focus may involve more risky choices that generate setbacks and require resilient responses.
Practical implications
Several practical implications can be derived from this study. First, our study has implications for training and development trajectories of employees, including employees in leadership positions as well as their followers. Human resource managers may develop resilience-increasing practices that – instead of a sole focus on developing employees’ personal resources – also pay attention to developing supporting structures in the form of leaders’ behaviours (resilient behaviours as well as coaching behaviours). Although leadership development occupies centre stage in human resource development (Yoo et al., 2019), the realisation of its impact on resilient behaviours of employees has not yet reached human resource practices.
Second, our study shows that followers’ promotion focus attenuates the extent to which leaders’ resilient behaviour, strengthening followers' resilience via coaching behaviours. Therefore, we suggest that leaders adapt their coaching approach to the regulatory focus of their followers. As our results show, resilient leaders may be naturally inclined to offer coaching to the ones that could use it best (resilient followers), nevertheless leaders should also be aware of the fact that the employees that benefit most from coaching are the ones that have a weak promotion focus.
Limitations
No study is without limitations that may harbour avenues for future research. First, our sample consisted of leaders and their followers from organisations in various sectors. Whilst this is advantageous with respect to the generalisability of our findings, our final sample of 269 observations does not allow us to tease out differences between sectors. It may be so that resilient behaviour is more needed in particular sectors than in others. For example, it may be so that employees in sectors that involve high emotional labour require more resilient behaviours than employees working in other sectors. Future studies are advised to replicate our results, using other samples in specific sectors to further validate our study.
Second, although our study used time-lagged, multisource data, we measured followers’ regulatory focus at one moment in time. Yet, regulatory focus may vary over time (Johnson et al., 2015; Wallace et al., 2016). Followers may fluctuate in their regulatory profile depending, for example, on the stage in their career (Wallace et al., 2016). Future studies could explore whether and how fluctuations in regulatory foci impact fluctuations in resilient behaviour.
Future studies could more evaluate more directly the behavioural aspects tied to the promotion and prevention motivational tendencies as well as provide more direct insights into the unmet security and nurturance needs. We have used a generic scale to evaluate leadership coaching and did not explicitly evaluate coaching resilient behaviours. Our coaching scale included aspects related to guiding, facilitating and inspiring employee performance that are aligned with the two theorised mediation mechanisms namely coaching as a vehicle for modelling exemplary behaviour and providing social support, yet future studies could evaluate more directly the leader-employee relational aspects responsible for the crossover of resilience at work. Moreover, in order to further clarify the relation between leadership coaching and employee resilience, future research could explore the extent to which employee relational needs impact on the extent to which coaching behaviours are translated in employee resilience.
Figures
Confirmatory factor analyses and fit indices
| Model | Factors | χ2 | df | χ2/df | p value | CFI | TLI | AIC | BIC | RMSEA | SRMR | Chisq diff | diff | Pr(>Chisq) | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 7-factor | 948.31 | 573 | 1.65 | 0.00 | 0.90 | 0.89 | 21,809 | 22,143 | 0.05 | 0.06 | ||||
| 2 | 6-factor | 1263.12 | 579 | 2.18 | 0.00 | 0.81 | 0.79 | 22,112 | 22,424 | 0.07 | 0.09 | 314.81 | 6 | <2.2e−16 | *** |
| 3 | 5-factor | 1315.35 | 584 | 2.25 | 0.00 | 0.80 | 0.78 | 22,154 | 22,449 | 0.07 | 0.07 | 367.04 | 11 | <2.2e−16 | *** |
| 4 | 4-factor | 1625.56 | 588 | 2.76 | 0.00 | 0.71 | 0.69 | 22,456 | 22,736 | 0.08 | 0.09 | 677.25 | 15 | <2.2e−16 | *** |
| 5 | 1-factor | 2855.38 | 594 | 4.81 | 0.00 | 0.37 | 0.33 | 23,674 | 23,933 | 0.12 | 0.13 | 1907.1 | 21 | <2.2e−16 | *** |
Note(s): ***p < 0.001. Model 1 is our measurement model in which items were loaded onto their respective factors (i.e. leader resilience, follower resilience, promotion focus, prevention focus, guidance, facilitation, inspiration). Model 2 is a 6-factor model in which promotion focus and prevention focus were loaded onto one factor and all other measures were loaded onto their respective factors. Model 3 is a 5-factor model in which guidance, facilitation and inspiration items were loaded onto one factor and all other measures were loaded onto their respective factors. Models 4 is a 4-factor model in which promotion focus and prevention focus items were loaded onto one factor and guidance, facilitation and inspiration items were loaded onto one factor; and all other measures were loaded onto their respective factors. Model 5 is a 1-factor model in which all measure items were loaded onto one factor
Source(s): Authors' work
Means, standard deviations and correlations with confidence intervals
| Variable | M | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1. Followers’ resilient behaviour T4 | 4.10 | 0.46 | |||||||||||
| 2. Followers’ resilient behaviour T2 | 4.15 | 0.43 | 0.56** | ||||||||||
| 3. Leaders’ resilient behaviour T1 | 4.19 | 0.40 | 0.21** | 0.15* | |||||||||
| 4. Leaders’ coaching behaviour (follower-rated) T2 | 4.26 | 0.55 | 0.35** | 0.41** | 0.21** | ||||||||
| 5. Followers’ promotion focus T2 | 4.67 | 1.38 | 0.15* | 0.07 | 0.06 | 0.06 | |||||||
| 6. Followers’ prevention focus T2 | 2.65 | 1.30 | −0.33** | −0.36** | −0.00 | −0.14* | 0.19** | ||||||
| 7. Age leader | 46.40 | 9.54 | −0.05 | −0.08 | −0.18** | −0.11 | −0.14* | −0.06 | |||||
| 8. Age follower | 40.88 | 10.91 | −0.04 | 0.02 | −0.08 | 0.05 | −0.31** | −0.18** | 0.27** | ||||
| 9. Gender leader (0 = male) | 0.44 | 0.50 | 0.05 | 0.03 | 0.02 | 0.02 | 0.03 | 0.04 | −0.05 | 0.05 | |||
| 10. Gender follower (0 = male) | 0.52 | 0.50 | 0.08 | 0.04 | −0.05 | −0.03 | −0.05 | 0.00 | 0.13 | 0.08 | 0.36** | ||
| 11. Education level leader | 4.34 | 0.76 | −0.09 | −0.03 | 0.05 | 0.06 | −0.03 | 0.12* | 0.00 | 0.01 | −0.02 | −0.00 | |
| 12. Education level follower | 3.91 | 0.85 | −0.10 | −0.05 | 0.07 | −0.02 | 0.23** | 0.15* | 0.05 | −0.14* | −0.09 | −0.05 | 0.24** |
Note(s): M and SD are used to represent mean and standard deviation, respectively. * indicates p < 0.05. ** indicates p < 0.01
Source(s): Authors' work
Regression summary for the mediating role of leaders’ coaching behaviour in the relationship between leaders’ resilient behaviour and followers’ resilient behaviour (n = 269)
| Mediation through leaders’ coaching behaviour, moderated by promotion focus [95% bias-corrected CI] | Mediation through leaders’ coaching behaviour, moderated by prevention focus [95% bias-corrected CI] | |
|---|---|---|
| Direct effects (c’-path) | ||
| Leaders’ resilience T1 → Followers’ resilience T4 | 0.12* [0.01; 0.23] | 0.11* [0.001; 0.23] |
| Followers’ resilience T2 | 0.51*** [0.40; 0.62] | 0.49*** [0.36; 0.64] |
| Followers’ age | −0.00 [−0.00; 0.00] | −0.00 [−0.00; 0.01] |
| Constant | 1.50*** [0.82; 2.17] | 1.88*** [1.19; 2.57] |
| Partial effect toward the mediator (a-path) | ||
| Leaders’ resilience T1 → Leaders’ coaching T2 | 0.21** [0.06; 0.36] | 0.21** [0.060.36] |
| Followers’ resilience T2 | 0.50*** [0.36; 0.64] | 0.50*** [0.36; 0.64] |
| Partial effects from mediator to outcome (b-path) | ||
| Leaders’ coaching T2 → Followers’ resilience T4 | 0.10* [0.10; 0.19] | 0.11* [0.030.20] |
| Promotion focus → Followers’ resilience T4 | 0.04 [0.01; 0.08] | |
| Leaders’ coaching x Promotion focus → Followers’ resilience T4 | −0.07* [−0.13; −0.01] | |
| Prevention focus → Followers’ resilience T4 | −0.06** [−0.10; −0.02] | |
| Leaders’ coaching x Prevention focus → Followers’ resilience T4 | −0.05† [−0.11; 0.00] | |
| Total effect | ||
| Constant | 3.12*** [2.56; 3.69] | 3.12*** [2.56; 3.69] |
| Leaders’ resilience T1 → Followers’ resilience T4 | 0.23*** [0.10; 0.37] | 0.23*** [0.10; 0.37] |
Note(s): Unstandardized coefficients are reported, independent variables were centred. ***p < 0.001, **p < 0.01 and *p < 0.05, †p < 0.01. Indirect effects are conditional on the moderator and are displayed in Figure 4
Source(s): Authors' work
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Acknowledgements
The authors thank the students of the Open Universiteit for their support in gathering respondents for the survey on which this study is based.