Literature review

Foundations of servant leadership

From its inception in Robert K. Greenleaf’s 1970 essay ‘The Servant as Leader’ to its fuller treatment in Servant Leadership: A Journey into the Nature of Legitimate Power and Greatness (Reference Greenleaf2013), servant leadership has been shaped by Greenleaf’s foundational writings. In his view, leadership derives its legitimacy not from formal authority or control but from moral responsibility, stewardship, and the primacy of follower growth and community well-being, such that the true test of leadership lies in whether ‘the least privileged in society’ are helped to grow (Greenleaf, 1977/Reference Greenleaf2013). Leadership is thus understood as a moral, relationship-based endeavor grounded in service first, the ethical use of power, and the cultivation of trust and community. These principles were subsequently institutionalized and extended by the Greenleaf Center for Servant Leadership, which articulated service, trust, listening, and stewardship as the normative foundations of effective leadership in complex social systems and advanced their application through education, practice, and research across organizational contexts.

This orientation challenged power-centric paradigms and, through the influence of the Greenleaf Center and subsequent scholarly development, was translated into systematic operationalizations of servant leadership as a multidimensional construct reflecting empowerment, humility, ethical stewardship, and developmental support (Eva, Robin, Sendjaya, Van Dierendonck & Liden, Reference Eva, Robin, Sendjaya, Van Dierendonck and Liden2019; Liden et al., Reference Liden, Wayne, Zhao and Henderson2008; van Dierendonck, Reference van Dierendonck2011). Researchers have found that servant-minded actions (e.g., actively listening, providing effective stewardship, demonstrating empathy, and offering personalized support) are predictors of elevated engagement, workplace thriving, commitment to the organization, and discretionary citizenship actions (Usman et al., Reference Usman, Liu, Li, Zhang, Ghani and Gul2021). It nurtures constructive voice (Duan, Kwan & Ling, Reference Duan, Kwan and Ling2014). Servant leadership can positively enhance subordinate attitudes and behaviors, as well as the psychological climate, encouraging trust, fairness, and affective commitment that leads to citizenship behaviors and satisfaction (Ozyilmaz & Cicek, Reference Ozyilmaz and Cicek2015).

While early investigations portrayed servant leadership as a consistent approach, contemporary scholarship emphasizes its emergent, situationally adaptive qualities. Viewed through Complexity Leadership Theory, servant leadership functions as a generative phenomenon that is activated by fluctuations in job demands and the availability of resources (Lichtenstein & Plowman, Reference Lichtenstein and Plowman2009; Uhl-Bien et al., Reference Uhl-Bien, Marion and McKelvey2007). Osborn, Hunt, and Jauch (Reference Osborn, Hunt and Jauch2002) posited that effective leadership requires leaders’ behaviors be congruent with the situational contingencies. This aligns with the CLT idea that servant leaders must continually adjust their own supportive, empowering, and stewardship behaviors by being attentive to the feedback they are receiving from their subordinates. In practice, servant leadership does not involve a static set of one-size-fits-all actions. Rather, leaders dynamically adjust their responses to align with the continually changing demands of their subordinates while working within the constraints imposed by available resources.

Gardner et al. (Reference Gardner, Karam, Noghani, Cogliser, Gullifor, Mhatre and Dahunsi2024) found that contextual factors are important for authentic leadership and argued for a greater contextual focus in leadership research, a point that can be extended to servant leadership as well. Previous studies support servant leadership as an inherently adaptive approach. Chiniara and Bentein (Reference Chiniara and Bentein2016) found that a servant leader’s actions will change dynamically in reaction to the fluctuating needs of their subordinates as well as the demands placed upon them. Chaudhry, Cao, Liden, Point, and Vidyarthi (Reference Chaudhry, Cao, Liden, Point and Vidyarthi2021) corroborated this dynamic pattern, showing within their study that the enhancement of well-being through servant leadership is stronger under substantial job demands, indicating that it is likely a responsive amplification. Studies by Lemoine, Hartnell, and Leroy (Reference Lemoine, Hartnell and Leroy2019), as well as Owens and Hekman (Reference Owens and Hekman2016), provide support for the argument that servant leaders fine-tune the degree to which they serve or empower, adapting their personal approach based on task complexity and their subordinates’ level of maturity. Servant leadership positively impacts team safety and resource availability by way of open channels of communication, personalized feedback, and proactive acquisition of material or social resources (Haq, Raja, Alam, De Clercq & Saleem, Reference Haq, Raja, Alam, De Clercq and Saleem2022; Lord, Brown & Freiberg, Reference Lord, Brown and Freiberg1999). This can be conceptualized as a self-reinforcing cycle in which leaders use subordinates’ responses as real-time feedback to determine when and how to bolster support or resources. This serves as an adaptive loop, which embodies the co-creative dynamics central to CLT (Uhl-Bien et al., Reference Uhl-Bien, Marion and McKelvey2007). Thus, servant leadership can be framed as an adaptive, feedback-based phenomenon.

Although servant leadership theory explains how leaders provide ethical, relational, and developmental support to followers, it does not by itself specify the contextual conditions that give rise to these behaviors or the motivational processes through which they shape effort, vigilance, initiative, and responsibility. The JD–R model supplies this missing contextual structure by identifying the energetic strains and developmental opportunities that create the need for buffering, empowerment, and the mobilization of resources. RFT, in turn, specifies the self-regulatory mechanisms through which these leadership and contextual cues are internalized by employees as promotion- or prevention-oriented motivational states. Together, JD–R and RFT provide the contextual and motivational micro-foundations required to model servant leadership as an emergent, feedback-driven process within a complex adaptive system.

Job demands–resources model

To explain why and when servant leadership emerges within complex adaptive systems, the JD–R model specifies the energetic and developmental conditions that create the need for buffering, empowerment, and adaptive resource mobilization. Job resources and demands shape both promotion and prevention regulatory foci from a distance (Kauppila et al., Reference Kauppila, Ehrnrooth, Mäkelä, Smale, Sumelius and Vuorenmaa2022). According to Demerouti et al. (Reference Demerouti, Bakker, Nachreiner and Schaufeli2001), the JD-R model asserts that job demands encompass physical, psychological, social, and organizational work aspects that require sustained effort. Central to the JD-R model is the idea that job demands, defined as the physical, psychological, social, or organizational facets of work that require prolonged effort, may exhaust an employee’s energy and eventually cause strain or burnout when they become too great (Bakker & Demerouti, Reference Bakker and Demerouti2017; Bakker, Demerouti & Sanz-Vergel, Reference Bakker, Demerouti and Sanz-Vergel2023; Demerouti et al., Reference Demerouti, Bakker, Nachreiner and Schaufeli2001). This can potentially extend to physical stress in dealing with those demands (Petrou & Demerouti, Reference Petrou and Demerouti2010; Yin, Huang & Lv, Reference Yin, Huang and Lv2018). Job demands encompass quantitative overload, the challenges of emotional labor, unclear roles, and contradictory expectations. In contrast, job resources – such as autonomy, social support, feedback, and task significance – support goal attainment, mitigate demand-related strain and stimulate personal development (Bakker & Demerouti, Reference Bakker and Demerouti2017). Job resources can foster motivation and personal growth in the workplace (Lu, Siu, Chen & Wang, Reference Lu, Siu, Chen and Wang2011). The model thus outlines two linked processes. The dual-pathway model comprises a health impairment route – where excessive demands result in burnout – and a motivational route – where sufficient resources bolster engagement and initiative (Bakker, Demerouti & Sanz-Vergel, Reference Bakker, Demerouti and Sanz‐Vergel2014; Christian, Garza & Slaughter, Reference Christian, Garza and Slaughter2011; Halbesleben, Reference Halbesleben2010; Maslach, Schaufeli & Leiter, Reference Maslach, Schaufeli and Leiter2001). Equally important, resources cushion the strain induced by high demands, underscoring their indispensable role in preserving well-being.

Recent JD-R developments reveal how the framework adjusts to dynamic work settings. They also draw attention to employees’ agency in configuring their own work environments. In their 2023 work, Demerouti and Bakker recommend adjustments for contexts marked by crisis and uncertainty. They argue that the usual challenge versus hindrance dichotomy might transform, and new resources such as digital readiness gain importance during swift change. Job crafting research, which examines how employees actively reshape tasks, relationships or mindsets, finds a clear division: promotion-oriented individuals engage in approach crafting by seeking new challenges and developmental resources, whereas prevention-oriented individuals rely on avoidance crafting to minimize hindrances and uncertainties (Nong, Ye & Hong, Reference Nong, Ye and Hong2022; Petrou, Demerouti & Schaufeli, Reference Petrou, Demerouti and Schaufeli2015). At the same time, virtual social support has become essential for buffering and coping (Molino et al., Reference Molino, Ingusci, Signore, Manuti, Giancaspro, Russo and Cortese2020; Salanova, Llorens & Schaufeli, Reference Salanova, Llorens and Schaufeli2011). By introducing novel demands and resources, these changes validate JD-R’s dynamic nature and its resonance with CLT. Demands and resources signal when servant leadership should emerge. Employees’ proactive crafting and their promotion versus prevention focus then inform how leadership adjusts. However, excessive job demands may impede a leader’s ability to support and develop subordinates (Li, Fu, Chadwick & Harney, Reference Li, Fu, Chadwick and Harney2024). On the basis of this framework, we next consider RFT. It supplies the motivational perspective employees employ to decode and respond to the contextual conditions identified by JD-R.

Regulatory Focus Theory

To explain how employees translate servant leadership and contextual conditions into patterns of effort, vigilance, initiative, and responsibility, RFT specifies the motivational self-regulatory mechanisms through which these contextual cues are internalized. Having shown that demands and resources act as contextual cues in the JD–R framework, our attention shifts to RFT. This framework shows how employees’ motivational orientations both shape and are shaped by those contextual elements. Higgins (Reference Higgins1997, Reference Higgins1998) first proposed RFT. It differentiates a promotion focus – steering individuals toward gains, aspirations, and personal growth – from a prevention focus, which directs attention to safety, duty, and loss avoidance (Johnson, Smith, Wallace, Hill, & Baron, Reference Johnson, Smith, Wallace, Hill and Baron2015). These foci significantly influence how people interpret information, regulate emotions, make decisions, and pursue goals (Brockner & Higgins, Reference Brockner and Higgins2001; Gamache, McNamara, Mannor & Johnson, Reference Gamache, McNamara, Mannor and Johnson2014).

Traditional frameworks view promotion and prevention as enduring personality traits. In contrast, CLT sees these orientations as fluid, emerging and adapting alongside changing leadership actions, and resource distributions, much like servant leadership itself. This approach holds that employees’ promotion versus prevention orientations come into being through dynamic feedback loops. Leaders’ adaptive support and decisions about resource allocation guide subordinates toward either seeking gains or avoiding losses.

Conceptual model

From CLT’s holistic lens, this framework integrates the JD–R model, RFT, and servant leadership into a unified process in which job demands (energy draining factors) and job resources (growth-supporting factors) trigger servant leadership behaviors. These behaviors then influence whether employees adopt a promotion or a prevention focus. The result is improved fit, satisfaction, motivation, initiative, and responsibility (Demerouti et al., Reference Demerouti, Bakker, Nachreiner and Schaufeli2001; Higgins, Reference Higgins1997; Uhl-Bien et al., Reference Uhl-Bien, Marion and McKelvey2007). Three CLT principles serve as the theoretical glue: emergence (servant leadership arises unpredictably from leader–follower–context interactions); nonlinear feedback (small leadership or resource shifts cascade through mediation chains), and adaptive co-creation (subordinates’ evolving regulatory foci inform subsequent leadership adjustments) (Lichtenstein & Plowman, Reference Lichtenstein and Plowman2009; Uhl-Bien et al., Reference Uhl-Bien, Marion and McKelvey2007).

Empirical findings show that by furnishing support, sharing information, and creating development opportunities, servant leaders reduce strain, enhance engagement, and may foster prevention orientation in high-stress environments (Haq et al., Reference Haq, Raja, Alam, De Clercq and Saleem2022). When servant leaders help cushion their subordinates’ stress by providing the right support, this heightened prevention focus predicts greater experienced responsibility (Chaudhry et al., Reference Chaudhry, Cao, Liden, Point and Vidyarthi2021). Servant leaders build trust, grant autonomy, and provide social support, which may amplify subordinates’ promotion focus. These leaders provide information, a psychologically safe environment, and other resources (Haq et al., Reference Haq, Raja, Alam, De Clercq and Saleem2022; Lord et al., Reference Lord, Brown and Freiberg1999; Marinan & Brown, Reference Marinan and Brown2019). By serving ethically, they establish an environment founded on trust, fairness, prosocial actions, service, and organizational commitment (Newman, Schwarz, Cooper & Sendjaya, Reference Newman, Schwarz, Cooper and Sendjaya2017; Walumbwa, Hartnell & Oke, Reference Walumbwa, Hartnell and Oke2010). This strengthened focus manifests in the subordinates’ own approach in crafting their roles. This causes them to actively seek out challenges and learning opportunities, as well as improve their person–job fit and boost their intrinsic motivation (Petrou et al., Reference Petrou, Demerouti and Schaufeli2015; Tims, Bakker, Derks & van Rhenen, Reference Tims, Bakker, Derks and van Rhenen2013). Leaders model self-regulation by framing tasks in promotion- or prevention-oriented terms, shaping subordinates’ mindsets and reducing the impact of job demands (Kark & Shamir, Reference Kark and Shamir2002; Lockwood, Jordan & Kunda, Reference Lockwood, Jordan and Kunda2002; Yang, Ming, Ma & Huo, Reference Yang, Ming, Ma and Huo2017).

These dynamics form a four-path process model: (1) Job Demands → Servant Leadership → Promotion Focus → Positive Outcomes; (2) Job Demands → Servant Leadership → Prevention Focus → Responsibility; (3) Job Resources → Servant Leadership → Promotion Focus → Positive Outcomes; and (4) Job Resources → Servant Leadership → Lower Prevention Focus → Lower Vigilance-Based Responsibility. In the next section, we translate this integrative framework into testable hypotheses via SEM, followed by a CLPM hypothesis to capture the feedback-driven emergence at the heart of CLT.

Synthesis and theoretical integration

Having reviewed the JD–R model, RFT, and servant leadership, we integrate them under CLT, which frames job demands (e.g., workload, ambiguity) and job resources (e.g., autonomy, social support) as triggers for servant leadership that shape followers’ regulatory orientations and drive outcomes.

Empirical data reveal that context activates servant leadership behaviors, which shifts subordinates’ regulatory foci and predicts outcomes in a sequential chain (X → M₁ → M₂ → Y). Supporting and defending subordinates in high-demand situations converts prevention orientation into greater experienced responsibility (Chaudhry et al., Reference Chaudhry, Cao, Liden, Point and Vidyarthi2021). Bolstered job resources ignite promotion focus, prompting approach-oriented role crafting, resulting in gains in fit, satisfaction, motivation, and initiative (Petrou et al., Reference Petrou, Demerouti and Schaufeli2015; Tims et al., Reference Tims, Bakker, Derks and van Rhenen2013). Within adaptive co-creation, dynamic sensemaking by servant leaders encourages promotion or prevention mindsets. Resulting subordinate adaptation in their regulatory focus orientations provides feedback to the leaders helping them decide how to behave next (Kark & Shamir, Reference Kark and Shamir2002). Improved PJ-fit and satisfaction bolster retention and morale, while motivation and initiative drive innovation.

Figure 1 illustrates these four intertwined pathways as CLT’s feedback-driven emergence. The signs included in the figure indicate whether prior research suggests a positive or negative association for each path. They do not represent the formal hypotheses.

Figure 1. Hypothesized process model.

We next test these pathways via SEM. Separately, we review the direct and conditional effects of JD–R, RFT, and servant leadership on the same outcomes.

Finally, we employ a CLPM to capture the temporal feedback loops at the heart of CLT. This is displayed in Figure 2, in which we can see the impact of servant leadership on regulatory foci, feedback loop that occurs through feedback from subordinates to their servant leaders, and the changes in the reality or perceptions of demands and resources as a result of subordinates’ regulatory foci-related activities.

Note. Each feedback loop controls for Time 1 outcomes.

Figure 2. Feedback-driven, co-creative process model.

Direct and conditional effects on outcomes

To establish the baseline for our four-path process model, we review how job demands, resources, regulatory focus, and servant leadership directly and conditionally influence key outcomes through CLT’s emergence and feedback principles. Figure 1 presents the model.

Hypotheses

Having examined the dynamic process model within the CLT framework, we now present the hypotheses.

Demand-driven adaptive servant leadership and promotion focus (H1)

When job demands become particularly intense, employees are subjected to significant time pressure, pronounced cognitive load, and the erosion of available resources, which the JD–R model regards as activation of the health-impairment pathway that threatens both well-being and goal accomplishment. From a Complexity Leadership Theory perspective, such strain conditions are expected to elicit adaptive leadership responses aimed at stabilizing the system by restoring meaning, support, and access to resources. Servant leadership represents an enabling and generative pattern of response that can arise in demanding environments by restoring resources and psychological safety, thereby alleviating strain and orienting attention toward future possibilities. These leader behaviors are theorized to buffer threat and, after first stabilizing the system and reducing perceived loss, reframe high demands as manageable challenges, thereby activating a promotion regulatory focus in followers, defined by growth, advancement, and sensitivity to gains (Brockner & Higgins, Reference Brockner and Higgins2001; Higgins, Reference Higgins1997). A promotion focus subsequently promotes engagement, proactive behavior, and positive alignment between the self and work, thereby strengthening person–job fit, person–role fit, satisfaction with supervisors, satisfaction with growth, intrinsic motivation, and personal initiative. Accordingly, job demands are expected to influence positive outcomes primarily through an adaptive leadership–motivation pathway linking servant leadership and promotion focus, rather than primarily exerting direct positive effects.

H1 (Demand-Driven Positive Outcomes Pathway). In high-demand contexts, servant leadership will emerge as an adaptive, enabling response that fosters employees’ promotion regulatory focus, which will in turn enhance positive work outcomes, such that servant leadership and promotion focus serially transmit the effects of job demands on person–job fit, person–role fit, supervisor satisfaction, growth satisfaction, intrinsic motivation, and personal initiative.

Demand-driven adaptive servant leadership and prevention focus (H2)

When job demands are elevated, employees face increased risks of error, role overload, and potential loss. The JD–R health-impairment pathway indicates that such environments elevate strain while also making issues of safety, obligation, and error avoidance more prominent. Within the CLT framework, these conditions are expected to elicit adaptive servant leadership behaviors aimed at buffering demands, safeguarding employees, and clarifying roles and expectations. These leader behaviors are theorized to elicit a prevention regulatory focus in followers, characterized by vigilance, a strong sense of duty, and sensitivity to possible negative outcomes (Brockner & Higgins, Reference Brockner and Higgins2001; Higgins, Reference Higgins1997). This motivational state should heighten perceived responsibility as employees become increasingly attentive to their obligations and more strongly motivated to avoid mistakes and failures.

H2 (Demand-Driven Responsibility Pathway). In high-demand contexts, servant leadership will emerge as an adaptive buffering response that fosters employees’ prevention regulatory focus, which will, in turn, increase their experienced responsibility, such that servant leadership and prevention focus serially transmit the effects of job demands on responsibility.

Resource-driven generative servant leadership and promotion focus (H3)

In resource-rich work settings, employees experience higher levels of autonomy, support, feedback, and opportunities for development, which the JD–R motivational pathway associates with energy, learning, and sustained goal striving. From a CLT perspective, such abundance creates fertile ground for generative leadership to emerge as leaders and followers co-construct meaning, experiment with new ways of working, and orient themselves toward growth rather than protection. Servant leadership in these contexts acts as an enabling and amplifying influence that activates available resources, empowers employees, and reinforces a forward-looking orientation. These leader behaviors are theorized to activate a promotion regulatory focus in followers, characterized by aspirations for growth, advancement, and the pursuit of gains (Brockner & Higgins, Reference Brockner and Higgins2001; Higgins, Reference Higgins1997). These conditions are expected to stimulate exploration, intrinsic motivation, and proactive involvement. Through this motivational mechanism, resource-rich contexts should enhance perceptions of fit, satisfaction, and personal initiative.

H3 (Resource-Driven Positive Outcomes Pathway). In resource-rich contexts, servant leadership will emerge as a generative, enabling response that fosters employees’ promotion regulatory focus, which will in turn enhance positive work outcomes, such that servant leadership and promotion focus serially transmit the effects of job resources on person–job fit, person–role fit, supervisor satisfaction, growth satisfaction, intrinsic motivation, and personal initiative.

Resource-driven adaptive regulation and prevention focus (h4)

Although the availability of job resources typically supports engagement and growth, it can also reduce perceptions of threat, uncertainty, and potential loss, thereby weakening activation of the prevention regulatory system, which is oriented toward vigilance and obligation-based self-regulation. RFT holds that prevention focus is most strongly activated in situations characterized by threat, obligation, and the possibility of loss rather than in resource-abundant conditions (Brockner & Higgins, Reference Brockner and Higgins2001; Higgins, Reference Higgins1997). From the standpoint of CLT, servant leadership operating in contexts of low strain and high resources may thus signal environmental safety and stability, orienting followers away from protective self-regulation and toward learning- and growth-oriented modes of functioning. Accordingly, prevention focus and the associated vigilance-based, loss-avoidance form of responsibility may be reduced when resources are plentiful and servant leadership highlights empowerment rather than safeguarding.

H4 (Resource-Driven Responsibility Pathway). In resource-rich contexts, servant leadership will be associated with lower activation of employees’ prevention regulatory focus and, consequently, lower experienced responsibility in the sense of vigilance- and obligation-based monitoring, reflecting reduced vigilance- and duty-based self-regulation in low-threat conditions, such that servant leadership and prevention focus serially transmit the effects of job resources on responsibility in a negative direction.

Feedback-driven emergence and co-evolution (H5)

CLT asserts that leadership, motivation, and context mutually develop through nonlinear feedback processes instead of through simple unidirectional causation. Job demands and resources influence the emergence of leadership behavior, leadership behavior shapes followers’ regulatory orientations, and these motivational states then feed back to modify how work characteristics are experienced, organized, and enacted over time. This cycle of reciprocal influence represents adaptive co-creation and system-level emergence, in which micro-level interactions generate macro-level patterns that later constrain and enable further interaction. Accordingly, leadership, regulatory focus, and job characteristics should exhibit bidirectional and temporally ordered effects that reflect feedback-driven adaptation.

H5 (Feedback-Driven Emergence). Job demands and resources, servant leadership, and employees’ promotion and prevention regulatory focus will exhibit reciprocal cross-lagged relationships over time, such that servant leadership and regulatory focus not only emerge from job demands and resources but also feed back to shape subsequent levels of those same demands and resources, demonstrating feedback-driven co-evolution consistent with CLT.

Method

Measures

All items were measured on a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree). Cronbach’s α coefficients are reported in Table 1.

Table 1. Measurement scales, sources, and reliabilities

Note. All items were measured on a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree). Growth Satisfaction items were subjected to exploratory factor analysis (principal axis factoring with varimax rotation), yielding loadings of 0.92, 0.89, 0.86, and 0.88.

Data screening

Data were examined for missing cases and for participants whose responses were missing less than 5% of the data, missing values were imputed using the MCMC method with twenty imputed data sets (Rubin, Reference Rubin1987). Box plots were examined for outliers and no kurtosis values greater than ±2.00 were found, and no items were removed from the model.

Confirmatory factor analysis

A confirmatory factor analysis (CFA) was performed in Amos 29.0. Multiple disturbance terms for items were covaried. Goodness-of-fit indices showed good model fit (χ2 = 4089.43; df = 2982; χ2/df = 1.37; CFI = 0.96; TLI = 0.96; RMSEA = 0.03; NFI = 0.87, and SRMR = 0.04) based on accepted thresholds (Hair, Black, Babin & Anderson, Reference Hair, Black, Babin and Anderson2010). The hypothesized model demonstrated significant improvement in fit compared to the independence model, evidenced by a lower chi-square value (CMIN = 4089.43, df = 2982, χ ²/df = 1.37) relative to the independence model (CMIN = 32,190.82, df = 3321, χ ²/df = 9.69), indicating a better representation of the observed data. The hypothesized 20-factor model was compared with five alternative models, each one examining variations of latent variables. The alternative models offered greater parsimony but the hypothesized model best fit the data as shown in Table 1.

Means, standard deviations, AVE, MSV, and MaxR(H), and correlations are included in Table 2.

Table 2. CFA model comparison

Note. N = 423.

Common method bias. Common method bias was assessed using Harman’s single-factor test (Podsakoff, MacKenzie, Lee & Podsakoff, Reference Podsakoff, MacKenzie, Lee and Podsakoff2003; Podsakoff & Organ, Reference Podsakoff and Organ1986) with results indicating that the single-factor solution accounted for 23.56% of variance explained, below the 25.00% cutoff (Williams, Cote & Buckley, Reference Williams, Cote and Buckley1989). This suggested that common method bias did not present major concerns. For assurance, common latent factor (CLF) analysis recommended by Podsakoff et al. (Reference Podsakoff, MacKenzie, Lee and Podsakoff2003) was also performed with results suggesting minimal common method bias given standardized regression weights ranging from 0.084 to 0.369, with over 90% below 0.30.

Analytical strategy

Justification of cross-lagged panel modeling

To examine the reciprocal and feedback-driven processes proposed by CLT, we utilized a CLPM. CLPMs estimate both autoregressive stability and cross-lagged directional effects, which makes it possible to determine whether earlier levels of one construct predict changes in another construct over time, while also testing whether the second construct subsequently feeds back to influence the first (Selig & Little, Reference Selig, Little, Laursen, Little and Card2012). This modeling structure corresponds directly to CLT assumptions regarding interdependence, nonlinear feedback, and co-evolution among leaders, followers, and contextual conditions (Hazy & Uhl-Bien, Reference Hazy and Uhl-Bien2015; Uhl-Bien et al., Reference Uhl-Bien, Marion and McKelvey2007).

We also evaluated other longitudinal modeling options. The Random Intercept Cross-Lagged Panel Model, referred to as the RI-CLPM, separates enduring between-person differences from short-term within-person fluctuations. However, CLT views leadership emergence and regulatory focus as system-level states that arise from relatively stable relational and structural configurations, not simply from transient intra-individual changes. Removing between-person variance would thus eliminate substantively meaningful system-level structure that CLT treats as theoretically central to emergence and adaptive coordination, making RI-CLPM less well aligned with the present research aims.

Dynamic SEM, or DSEM, is especially well-suited for intensive longitudinal designs that involve many measurement occasions and capture micro-temporal dynamics (e.g., day-to-day or moment-to-moment adaptation). In contrast, the present two-wave panel design is intended to examine meso-level organizational feedback loops that unfold across longer adaptive cycles, for which the cross-lagged panel model is the established analytic framework for testing such meso-level reciprocal dynamics.

Cross-lagged analytical approaches have a well established history of use in examining reciprocal patterns of influence between leaders and followers (e.g., Kark, Van Dijk, & Vashdi, Reference Kark, Van Dijk and Vashdi2018), in modeling motivational feedback processes within adaptive and relational systems (Chen, Ployhart, Thomas, Anderson, & Bliese, Reference Chen, Ployhart, Thomas, Anderson and Bliese2011), and in capturing adaptive dynamics within organizational systems (Lichtenstein & Plowman, Reference Lichtenstein and Plowman2009), thereby offering strong methodological precedent for applying these techniques to models grounded in Complexity Leadership Theory.

Theoretical implications

The first theoretical implication of this study is that servant leadership should be reconceptualized as an emergent, context-sensitive process rather than a stable individual style, as demonstrated by the serial mediation and reciprocal effects linking job demands, job resources, regulatory focus, and leadership behavior. Across three theoretical fronts, these results enrich leadership research by illustrating how servant leadership moves beyond a static label to become an evolving process that both springs from and redefines its organizational setting.

First, the observed cross-lagged and mediation patterns provide direct empirical support for applying CLT to servant leadership. Instead of exhibiting unchanging trait-based actions, leaders shift support and resources in line with changing demands, which stimulates followers’ motivation. Our emergent model directly challenges traditional trait and behavior approaches (Liden et al., Reference Liden, Wayne, Zhao and Henderson2008; van Dierendonck, Reference van Dierendonck2011) and draws attention to the critical role of local engagement and feedback cycles in fostering leadership effectiveness (Uhl-Bien & Arena, Reference Uhl-Bien and Arena2018; Uhl-Bien et al., Reference Uhl-Bien, Marion and McKelvey2007). In day-to-day operations, servant leaders become aware of either increased pressures or plentiful resources and then adapt their behavior – sometimes empowering, sometimes stewarding, sometimes reallocating – to match the situation, illustrating CLT’s core proposition that leadership emerges from ongoing interaction rather than from fixed role prescriptions.

Second, the findings extend RFT by demonstrating that promotion and prevention orientations operate as contextually activated, leadership-shaped motivational states rather than fixed individual differences. Promotion focus emerged as the critical conduit linking both high resources and buffered demands to enhanced person–job fit, satisfaction, intrinsic motivation, and initiative. Conversely, prevention focus – activated primarily under elevated demands – served to heighten employees’ sense of responsibility rather than merely reflecting risk aversion. This bifurcation extends RFT’s application in organizational settings by showing that promotion and prevention foci are not interchangeable but are differentially mobilized by leadership and context to yield distinct downstream effects (Higgins, Reference Higgins1997; Petrou & Demerouti, Reference Petrou and Demerouti2010), providing direct theoretical grounding for the differential mediation pathways tested in the SEM and CLPM models rather than treating regulatory focus as a static individual trait.

Third, embedding the JD–R model within a complexity lens clarifies how demands and resources act not only as predictors of strain and motivation but also as dynamic contextual triggers that shape the emergence and evolution of servant leadership itself. Our cross-sectional SEM and longitudinal CLPM evidence shows that servant leaders buffer the deleterious effects of demands and amplify the motivational power of resources, driving nonlinear feedback cycles that conventional JD–R applications often model as primarily unidirectional (Bakker & Demerouti, Reference Bakker and Demerouti2017; Demerouti et al., Reference Demerouti, Bakker, Nachreiner and Schaufeli2001). In doing so, we demonstrate how demands can paradoxically foster responsibility when mediated through adaptive leadership and prevention focus, and how resources translate into growth-oriented outcomes via promotion focus, thereby empirically substantiating the dual-pathway logic of JD–R (health impairment versus motivational gain) as part of a feedback-driven leadership process rather than as parallel, static causal chains.

Fourth, the identification of serial mediation chains and reciprocal cross-lagged effects provides direct empirical support for CLT’s core propositions of nonlinear feedback, interdependence, and adaptive co-creation. When leaders modulate their approach, they enhance followers’ regulatory focus, which then circles back to shape the design of demands, the distribution of resources, and the leaders’ subsequent actions. Emergence, interdependence, nonlinear feedback, and adaptive co-creation together embody core principles of complexity theory (Hazy & Uhl-Bien, Reference Hazy and Uhl-Bien2015; Lichtenstein & Plowman, Reference Lichtenstein and Plowman2009). By empirically modeling these bidirectional, time-ordered effects, the present study moves beyond static or one-way leadership models and demonstrates that servant leadership, motivational regulation, and work characteristics co-evolve as mutually conditioning system elements rather than as isolated causal variables, thereby answering recent calls to operationalize CLT with longitudinal process evidence rather than cross-sectional trait-based proxies.

Altogether, this work recasts servant leadership as central to a dynamic systems view of organizations. It reveals that context, leadership, and follower mindsets co-develop over time in ways that support enduring positive performance, as evidenced by the serial mediation of job demands and resources through servant leadership and regulatory focus, and by the reciprocal cross-lagged effects observed in the CLPM analyses, thereby positioning servant leadership as a core adaptive mechanism within complex work systems rather than a stable behavioral style.

Practical implications

Building directly on the four-path process model and the SEM and CLPM findings, we now outline four practical implications that follow from the observed mediation and feedback dynamics.

Practical Implication 1. Servant leadership should be developed and managed as a dynamic, context-responsive process rather than as a stable individual style.

These findings demonstrate that viewing servant leadership purely as an individual attribute or discrete style is insufficient, as the SEM and CLPM results show that servant leadership both emerges from and reshapes job demands, job resources, and regulatory focus over time. Organizations should therefore embed servant leadership as a continuous, adaptive process across work design, resource flows, and talent system infrastructures, rather than treating it solely as a set of trainable interpersonal behaviors. According to Conservation of Resources (COR) theory (Hobfoll, Reference Hobfoll2011), servant leaders spark upward spirals of resources. Capitalizing on this dynamic demands that front-line managers have decision rights and practical tools to reassign time, data, and social backing swiftly (Hutchison-Krupat & Kavadias, Reference Hutchison-Krupat and Kavadias2015; Maritan & Lee, Reference Maritan and Lee2017). The creation of formal processes – such as short resource sprints or hubs for peer networks that allow swift workload and expertise redistribution – helps uphold a promotion-oriented environment marked by strong engagement and growth, even under intense pressure (Demerouti & Bakker, Reference Demerouti and Bakker2023; Kluger & Itzchakov, Reference Kluger and Itzchakov2022), thereby operationalizing the promotion-focus mediation pathway observed in the SEM and CLPM analyses.

Practical Implication 2. In high-risk and compliance-intensive contexts, servant leadership can be deliberately leveraged to cultivate prevention focus and experienced responsibility rather than merely suppressing risk.

In industries governed by strict safety or compliance requirements, servant leadership can shift prevention focus – from its usual alignment with risk aversion – to a robust commitment to quality and safety standards. Consistent with the demand → servant leadership → prevention focus → responsibility pathway identified in the SEM and CLPM analyses, leaders who buffer strain and clarify obligations can channel vigilance into heightened ownership rather than disengagement. Static leadership workshops are less effective; programs can shift to focusing on meeting new demands. It is standard for generic workshops to focus on consistent leadership behavior while bypassing the subtle contextual factors that are highlighted within our model. A better strategy involves investing in hands-on learning rotations, teams drawn from different departments, and immediate feedback loops. A servant leadership approach, which emphasizes leader humility, can help encourage this feedback from subordinates and positively impact their adaptation (Li, Zhang, Xia, & Liu, Reference Li, Zhang, Xia and Liu2019). Such investments allow leaders to sense evolving demands and resource availability and to modify their support as needed (Jackson, Reference Jackson2000; McCauley & van Velsor, Reference McCauley and Van Velsor2004). Curriculum design for leadership coaching should combine promotion-oriented skills – including framing a compelling vision and identifying opportunities – with prevention-oriented competencies, such as assessing risks and establishing guardrails, so that leaders can intentionally activate the dual regulatory pathways identified in the four-path model and thereby sustain growth while reinforcing responsibility in safety-critical conditions.

Practical Implication 3. Servant leadership can be used to intentionally activate promotion focus and proactive job crafting in resource-rich and growth-oriented contexts.

It is also important that leaders support personnel in reshaping their own positions to align with whether they adopt a promotion or a prevention focus (Bakker et al., Reference Bakker, Demerouti and Sanz-Vergel2023; Wrzesniewski & Dutton, Reference Wrzesniewski and Dutton2001). Consistent with the resource → servant leadership → promotion focus → positive outcomes pathway, servant leaders who emphasize autonomy, development, and psychological safety can stimulate approach-oriented self-regulation and proactive role expansion. To accelerate job crafting, servant leaders could introduce brief micro-innovation workshops for incremental role redesigns and set up peer-mentoring forums that bring individual strengths and group-level resource needs to light. By focusing on better employee fit and intrinsic motivation, these leadership programs could ensure that when demands intensify, employees are more likely to perceive them as opportunities rather than stressors, mirroring the serial mediation pattern in which promotion regulatory focus transmits the effects of job resources and buffered demands on fit, satisfaction, motivation, and personal initiative observed in both the SEM and longitudinal analyses.

Practical Implication 4. Organizations should institutionalize feedback infrastructures that allow servant leadership, regulatory focus, and work design to co-evolve over time.

Lastly, organizations need policy frameworks that nurture, rather than constrain, the feedback loops driving complex processes. Embedding brief pulse surveys within performance conversations equips servant leaders with immediate alerts about changing demands or resource gaps (Salanova et al., Reference Salanova, Llorens and Schaufeli2011). Rotating leadership posts across departments simultaneously breaks down silos and strengthens group sense-making (Rosenhead et al., Reference Rosenhead, Franco, Grint and Friedland2019). As part of their recruitment and onboarding, organizations can use situational judgment tests that evaluate candidates’ decisions regarding models of variable demands to evaluate empathy and adaptability. Offering peer-nominated accolades like ‘resource champion’ can also help with the development of promotion focus while signaling what is important, thereby reinforcing the reciprocal, feedback-driven cycles identified in the CLPM analyses between leadership behavior, regulatory focus, and subsequent contextual conditions.

By reframing servant leadership as a co-creative and continuous feedback process, servant leaders in organizations can shield employees from the strains of high demands while maximizing the advantages of resource abundance. Through promotion regulatory focus, employees may not only engage in positive proactive behaviors, but those proactive behaviors can further enhance the leader–member exchange with their supervisors, thereby serving as a relational resource (Shih & Nguyen, Reference Shih and Nguyen2025). Consistent with the observed reciprocal cross-lagged effects, these employee regulatory states and proactive behaviors also feed back to shape subsequent leadership responses and the configuration of job demands and resources over time, demonstrating in practice the feedback-driven emergence proposed by CLT. By adopting this systemic approach, organizations can improve immediate results and employee well-being and simultaneously build the resilient adaptability essential for future challenges.

Future research

From our combined CLT–JD–R–RFT perspective, one can pursue a variety of promising research trajectories. A first implication for future research, grounded in the observed reciprocal CLPM effects and serial mediation pathways, is the need to examine these adaptive processes at finer temporal resolutions. As a starting point, one could conduct diary-based or experience-sampling research to capture the immediate effects of shifting resource allocation on followers’ regulatory states. Such work would also uncover the tipping point at which a prevention focus becomes authentic stewardship instead of simple risk avoidance (van Knippenberg, van Knippenberg, De Cremer & Hogg, Reference van Knippenberg, van Knippenberg, De Cremer and Hogg2004). In a second line of inquiry, scholars might use experimental or multi-sample designs – comparing contexts such as healthcare and creative industries – to identify moderators. Acute crisis conditions versus enduring overload and the contrast of financial to social resources may either bolster or weaken the servant leadership-regulatory focus linkage.

Daily or weekly longitudinal designs offer the temporal precision needed to spot nonlinear tipping points in feedback loops. Such designs would directly extend the present two-wave CLPM by allowing scholars to model the emergence, strengthening, and decay of regulatory focus and servant leadership responses across multiple time scales, consistent with CLT’s emphasis on dynamic co-evolution. Identifying these moments allows practitioners to intervene effectively, for example by deploying extra resources or scheduling coaching sessions. An inquiry into digital and blended work formats will show whether virtual servant leadership and algorithmic resource signals can successfully launch emergent dynamics, or whether personal, on-site engagement is required.

The third research path is to conduct action research that instructs leaders in complexity-informed, regulatory‐focus‐responsive techniques, for instance rapid sense making paired with reflective coaching. Such interventions would allow direct testing of the causal mechanisms implied by the serial mediation and cross-lagged paths observed in the present study, linking adaptive servant leadership behaviors to shifts in promotion and prevention focus and subsequent changes in fit, motivation, and responsibility. These trials would examine whether such adaptive routines intensify feedback loops and generate sustained gains across both motivational orientations. In combination, these extensions will hone the model’s applicability, expand its temporal dimensions, and transform complexity theory into validated organizational and leadership development practices.

Study limitations

There are certain limitations that should be addressed. First and foremost, every variable in our study – demands, resources, leadership behavior, regulatory focus, and outcomes – depended on self-report measures. Such reliance could lead to common method bias, social-desirability distortion, and flawed recall, even with our CFA checks and time-lagged controls. This limitation is particularly relevant given the serial mediation and reciprocal paths tested in the SEM and CLPM, as shared method variance may inflate associations among leadership, regulatory focus, and perceived job characteristics. Future studies ought to gather data from multiple sources – such as subordinate, peer, and supervisor ratings – and include objective metrics like performance records to triangulate self-reported perceptions.

The second limitation concerns attrition: the CLPM analysis at Time 2 retained only 232 of the original 423 participants, necessitating composite indicators rather than complete scales; this reduction may undermine the robustness and external validity of our longitudinal findings. Because the feedback-driven hypotheses rely on detecting reciprocal change over time, sample loss may have reduced statistical power to capture weaker cross-lagged effects and nonlinear dynamics predicted by CLT. Future replications that employ expanded, diverse panels and shorter data‐collection intervals (for example daily diaries) could pinpoint the onset and speed of feedback cycles.

Our third limitation is that our sample exclusively involved organizations based in the southeastern United States. Consequently, differences in cultural practices, sector characteristics, or national resource arrangements might alter the pathways we observed. Because regulatory focus activation and servant leadership enactment are known to vary across cultural value systems and institutional regimes, the generalizability of the CLT–JD–R–RFT feedback model may be bounded by national context. Cross‐cultural and multi‐industry investigations would help establish boundary conditions for the CLT–JD–R–RFT process model.

Lastly, while our emphasis on positive results and personal responsibility addresses critical aspects of fit and well-being, we did not explore variables like innovation behaviors, retention patterns, or group performance. These outcomes are central in both JD–R and complexity-based leadership research, where adaptive cycles are expected to scale from individual motivation to collective learning, coordination, and sustained performance. Broadening which outcomes we measure, along with testing moderators such as personal regulatory orientation or climate, will allow us to refine and scale up this dynamic approach to leadership.