2.1 Spiritual leadership and service performance

In today’s globally competitive aviation industry, airlines have shifted from being mere transporters to service providers. Delivering high-quality service and retaining loyal passengers are critical for success [6,7,50,51]. However, flight attendants play a vital role in this process [10,8,14,52]. As the airline employees who have more frequent interactions with passengers than any other staff [50], they not only project an image of elegant professionalism and gracious service [50], but also convey the airline’s brand identity and commitments [9,49,52]—even when confronted with internal and external challenges, such as physical and mental stress, emotional labor, burnout, fatigue, irregular work schedules, long night shifts, and disruptive passengers [13,14,50,53–55]. Their complex role means failure to perform duties leads directly to service failures and customer loss [56]. Creating a motivating work environment is thus essential for effective airline management [10].

There is a growing call to examine different styles of leadership—such as transformational leadership [57,58], empowering leadership [36], and safety leadership [59]—in relation to job performance (e.g., pilots’ safety performance). This line of inquiry aims to deepen and refine understanding of how leadership can address employee performance challenges [27].

This represents a notable oversight: as an indispensable component of the flight crew, flight attendants’ job performance (e.g., service performance)—and particularly its association with leadership—has received limited scholarly attention. The present study addresses this research gap by examining the relationship between spiritual leadership and flight attendants’ service performance.

Spiritual leadership theory, built upon Giacalone and Jurkiewicz’s [60] concept of workplace spirituality and extended by Fry [22], is defined as the values, attitudes, and behaviors that intrinsically motivate oneself and others through a vision, hope/faith, altruistic love, and a sense of calling and membership, fostering spiritual well-being [22].

Spiritual leadership is chosen as an antecedent because it motivates workers through a transcendent vision and culture, satisfying leaders’ and followers’ needs for spiritual well-being [34]. This leadership style fosters higher employee well-being, commitment, productivity, and performance [26,60–63], aligning with airline management needs. It also instills trust, intrinsic motivation, and commitment essential for optimizing organizational performance. Strong organizational outputs—such as high service quality and on-time performance—contribute to customer satisfaction, which, in turn, ultimately affects airlines’ financial performance [64]. Crossman [65] views spiritual leadership as a powerful management paradigm for enhancing human well-being and performance excellence.

Empirically, spiritual leadership effectively promotes pilots’ safety performance [27], encourages organizational citizenship behaviors in finance and retail [61], enhances task performance, knowledge sharing, and innovation in the energy industry [26], and improves job performance in the hotel industry [66]. This occurs as employees reciprocate the sense of membership provided by spiritual leaders [35,66]. Therefore, the following hypothesis were proposed:

Hypothesis 1. Spiritual leadership is positively related with flight attendants’ service performance

2.2 Mediating role of meaningful work

While spiritual leadership is linked to enhanced employee and organizational performance, the specific mechanisms, particularly for flight attendants’ service performance (interpersonal behaviors directed at serving customers that contribute to positive work outcomes) [16,67–69], remain less understood. Distinctively, spiritual leadership comprises three core elements expressed as leader values, attitudes, and behaviors: vision (a meaningful future providing direction and purpose), hope/faith (belief in achieving the vision), and altruistic love (fostering commitment and engagement) [22,26,66,70–73]. These elements manifest through a sense of calling and membership [74], intrinsically motivating employees towards better performance by enhancing work meaningfulness [35,61].

Individuals seek competence, social value, and meaningful work [75]. Meaningful work signifies the positive value and significance individuals attribute to their tasks [76]. Rooted in Job Characteristics Theory [29,77], meaningful work arises from core job dimensions (e.g., significance, identity) and acts as a key psychological state driving motivation, leading to improved satisfaction, performance, and commitment [31,78]. Kahn [41] extended this, viewing meaningfulness as employees connecting their work to self-expression and values. Alignment between job characteristics/tasks and personal values/identity heightens meaningful work perceptions, resulting in better outcomes like performance and commitment [31,33,47,79].

Empirically, employees who perceive leader-fostered meaningful work (beyond extrinsic rewards) reciprocally demonstrate improved performance [35,80,81]. A leader who leverages work meaningfulness is more capable of clarifying where an organization needs to go and how to get there [33]. Clear vision communication (e.g., via transformational or charismatic leadership) positively influences performance, partly through meaningful work [82-84]. Moreover, meaningful work is central to work unit spirituality, suggesting a link to performance [74]. However, empirical evidence for meaningful work mediating spiritual leadership’s effect on flight attendants’ service performance is lacking. Guided by this research gap in the existing literature, drawing on the critical dimensions of spiritual leadership, and grounded in Job Characteristics Theory, this study first seeks to propose the following propositions:

Hypothesis 2: Spiritual leadership can positively predict meaningful work.

Hypothesis 3: Meaningful work can positively predict service performance.

Hypothesis 4: Meaningful work mediates the relationship between spiritual leadership and service performance.

2.3 Mediating role of work engagement

Research on work engagement has grown significantly due to its strong links to employee well-being and performance [85–88]. While much is known about its nature, causes, and outcomes, the evolving workplace necessitates continued study [89,90]. Kahn [41] pioneered the concept, defining engagement as employees’ physical, cognitive, and emotional connection to their work roles. Schaufeli et al.’s [38] widely cited definition describes it as a positive, fulfilling state characterized by vigor (high energy/resilience), dedication (involvement, significance, enthusiasm), and absorption (concentration, immersion). This integration of pleasure, motivation, cognition, and attraction makes engagement an excellent predictor of performance [85,91].

While existing empirical research has provided sufficient evidence to support that work engagement has a positive association with work outcomes—such as pursers’ service recovery performance [19], flight attendants’ job performance [11], their service performance [49], and their service behavior [18]—empirical research on the factors influencing work engagement remains sparse. Notably, among these limited studies exploring factors influencing work engagement (and its link to job performance), most have focused on individual-level antecedents (e.g., psychological capital [18,92], job crafting [48,93], psychological contract [49]), while few have examined organizational management-level factors—thus lacking practical applicability. Yet, translating accumulated knowledge about work engagement into practical applications—such as enhancing individual, team, and organizational performance—is of great significance [94,95]. Meanwhile, Bakker and Albrecht [89] argue that future research on employee engagement could focus on fully uncovering the factors affecting engagement across specific demographic groups (e.g., millennials; older workers; people with disabilities), specific industry sectors (public, private, nonprofit), and specific occupations (nurses, teachers, flight attendants).

Furthermore, while leadership theories are diverse, the role of leadership in fostering work engagement has garnered limited empirical attention [96]. For instance, to our knowledge, Karatepe and Talebzadeh [19] are among the few scholars who have examined the positive relationship between servant leadership and work engagement among airline pursers; a similar association between transformational leadership and work engagement has been documented in hospital and industrial consultancy settings [97–99]. This study not only refines and extends existing knowledge on work engagement by investigating the relationship between spiritual leadership, work engagement, and flight attendants’ service performance, but also discusses the implications of these findings from the perspectives of organizational psychology and airline management practice. This approach aligns with current research trends and practical needs in the field of work engagement. Therefore, we hypothesize that:

Hypothesis 5: Work engagement positively relates to flight attendants’ service performance.

According to the Job Demands-Resources (JD–R) Theory [100], job resources refer to the physical, social, or organizational aspects of a job that may mitigate job demands—specifically, demands that require sustained physical and mental effort. Examples of such resources include social support, autonomy, and skill variety, all of which facilitate the achievement of work goals and stimulate individual growth and development [48,101–103]. The Job Demands-Resources (JD–R) Theory posits that job resources become salient and acquire motivational potential when employees are confronted with high job demands [104], and can further affect work engagement directly or indirectly via personal resources [28,44]. Within this framework, a resource-rich and visionary work environment shaped by spiritual leadership is expected to enhance flight attendants’ sense of vision, hope/faith, and altruistic love, thereby increasing their work engagement. In addition to job resources, personal resources—such as confidence in one’s ability to succeed, optimism about the future, perseverance toward goals, resilience, and organization-based self-esteem—are important predictors of engagement [91,105,106].

Under spiritual leadership, airline employees tend to experience greater care, concern, understanding, support, and appreciation from self, colleagues, and supervisors. This fosters an optimistic belief that the organization’s vision, goals, and mission can be realized and that their work is meaningful. Consequently, intrinsic motivation, organizational loyalty, career sustainability, and organization-based self-esteem are strengthened [22,28].

In summary, spiritual leadership enhances both employees’ job and personal resources, which in turn promote positive mood and work engagement [44,100,104], consistent with JD–R theory. Hence, such engaged employees exhibit high levels of energy and self-efficacy [47,106,107], enabling them to achieve desirable work outcomes such as successfully managing challenging problems and demanding service encounters faced by flight attendants [44,106,108]. Therefore, based on theoretical and empirical evidence, the following hypotheses are proposed:

Hypothesis 6: Spiritual leadership positively relates to flight attendants’ work engagement.

Hypothesis 7: Work engagement mediates the relationship between spiritual leadership and service performance.

2.4 Spiritual leadership, meaningful work, work engagement and service performance

As noted earlier, Job Demands–Resources (JD–R) theory posits that job resources and personal resources satisfy psychological needs—such as the need for meaningfulness, belongingness, and competence—which in turn foster positive mental states and work engagement [44,100,104]. Albrecht & Su [109] found, in a study of Chinese telecommunication workers, that performance feedback (a job resource) was related to work engagement through the fulfillment of employees’ need for meaningful work. As Steger and Dik [43] observe, people prosper when engaged in meaningful work, and organizations prosper when their employees are similarly engaged.

Numerous studies have examined the consequences of meaningful work both theoretically and empirically. Kahn [41] initially argued that work meaningfulness is a necessary prerequisite for work engagement, and subsequent empirical research by May et al. [46] and Ghadi et al. [45] confirmed these qualitative findings. Stairs and Galpin [110] further clarified the conceptual link, showing that individuals who experience their jobs as personally meaningful are more engaged than those who do not.

From the perspective of proximal outcomes, meaningful work exhibits stronger relationships with certain variables—such as work engagement, job satisfaction, and commitment—than with others [31,40,43,111]. Allan et al. [31] noted that meaningful work relates to job performance, organizational citizenship behaviors, and turnover intention through work engagement, commitment, and job satisfaction. Van Wingerden and Van der Stoep [112] corroborated these findings in a study of 459 professionals at a global health technology organization. Van Wingerden and Poell [47] proposed a chain-mediation model using data from Dutch teachers, revealing that meaningful work is positively linked to resilience sequentially through teachers’ work engagement and job crafting. Johnson and Jiang [113], in a study of 194 respondents, found that a sense of meaningfulness facilitates work engagement, which in turn enriches employees’ lives beyond the workplace. Consistent with these findings, we hypothesize:

Hypothesis 8: Meaningful work is positively related to flight attendants’ work engagement.

In fact, individuals’ real-life work environments are often complex and dynamic, shaped by multiple factors that influence behavior [114], and this is particularly true for flight attendants. Although Job Demands–Resources (JD–R) theory provides a framework for hypothesizing relationships among spiritual leadership, meaningful work, work engagement, and service performance, no study to date has integrated these constructs into a single framework. To systematically examine the mediating effects among these variables, gain a deeper and more comprehensive understanding of the psychological mechanisms linking spiritual leadership to service performance, and enhance the ecological validity of the research, we propose the following hypothesis:

Hypothesis 9: Spiritual leadership is positively related to service performance via Meaningful work and work engagement.

3.1 Research design

This study adopts a cross-sectional design, which involves collecting data from flight attendants via a single-time-point psychological questionnaire survey. Consistent with prior aviation research on leadership and service performance [10,19], this design is specifically tailored to our core research objective—exploring the correlational relationships and mediating mechanisms among spiritual leadership (SL), meaningful work (MW), work engagement (WE), and service performance (SP)—rather than verifying temporal causality between variables. The cross-sectional approach effectively addresses the logistical challenges of accessing flight attendants (a population with irregular work schedules) and allows for initial validation of the proposed theoretical model.

This cross-sectional study employed a psychological questionnaire survey methodology, utilizing established measurement scales: Fry et al.‘s [22] spiritual leadership scale, Steger et al.’s [43] Work as Meaning Inventory (WAMI), Schaufeli et al.’s [115] 9-item Utrecht Work Engagement Scale (UWES-9), and Liao and Chuang’s [16] service performance scale.

Data were collected between September–December 2021 (post-COVID-19 recovery period). Questionnaires were administered electronically via the professional data collection platform Wenjuanxing (https://www.wjx.cn/) and distributed through WeChat, China’s most popular social networking application. With assistance from our research partners at Tibet Airlines, survey instruments and information statements were sent to randomly selected flight attendants from company personnel lists.

Notably, WeChat and Wenjuanxing served solely as platforms to facilitate paperless data collection. This approach addressed the logistical challenge of gathering large numbers of airline employees simultaneously for on-site data collection. Given flight attendants’ work characteristics, the electronic format enabled participants to complete self-report measures anytime and anywhere by scanning the questionnaire QR code via WeChat, thereby enhancing both response rates and data quality.

All collected data were downloaded from the Wenjuanxing database using secure credentials for subsequent analysis.

3.2 Participants

A total 320 in-service Chinese flight attendants were randomly selected as initial participants from Tibet Airlines via the company’s internal collaborative channels across its operational branches. The sample size was determined based on the statistical requirements of mediation effect analysis and confirmatory factor analysis, with the initial 320 participants meeting the generally recommended minimum sample size threshold (≥200) for such analyses, thus ensuring adequate statistical test power [116,117].

After retrieving all questionnaires, the completeness and validity of the collected data were systematically assessed, with 7 invalid questionnaires excluded in accordance with pre-determined criteria [118]. The specific exclusion criteria for questionnaires were as follows: (1) Missing responses to ≥3 items in any single scale (e.g., more than 3 missing items in the Spiritual Leadership Scale); (2) Identical responses to all items (e.g., selecting ‘4’ for every 5-point Likert item, indicating inattentive responding); (3) Obvious logical contradictions in response information (e.g., reporting ‘0 years of service’ but ‘1000+ flight hours’). Regarding sample flow and attrition, the above criteria yielded a total of 313 valid questionnaires, corresponding to an effective response rate of 97.8%. Before data cleaning, the pattern of missing values was evaluated: 2.2% of the questionnaires (7 out of 320) contained missing data, with no single item having a missing rate exceeding 1%. Little’s Missing Completely at Random (MCAR) test was further conducted to assess the missing data mechanism, with the results (χ² = 38.72, df = 42, p = 0.601) indicating that the missing data were completely random (MCAR). This statistical evidence justified the use of listwise deletion for handling invalid questionnaires [119].

Among the 313 valid participants, 75 participants were male and 238 participants were female, including 3 cabin managers, 62 pursers, 81 business/first class flight attendants, 156 economy class flight attendants and 11 flight attendants trainee. The flight attendants’ age ranged from 21 to 50 years old (M = 27.66, SD = 4.85), total flight hours ranged from 110 to 26,000 h (M = 4502.90, SD = 4249.39) and their years of service for the cooperation from 1 year to 29 years (M = 5.96, SD = 4.87). All participants were given detailed information about the academic purpose of this study, and were assured their response would be confidential. Also, they were guaranteed that their individual response would not be identified in the results, and would not have any influence on their future career. They all voluntarily participated in this study and answered the questionnaires truthfully.

3.3 Measures

Referring to Brislin’s [120] back-translation procedure, the original survey items were translated into Chinese and then back-translated into English. Furthermore, the reliability and validity of each measure were examined via confirmatory factor analysis (CFA) and internal consistency test. Detail for each measure is present below.

3.4 Statistics analysis

SPSS 22.0 with PROCESS 3.3 and Amos 24.0 were used in analysis. First, the Cronbach’s α coefficient of each measure was calculated by SPSS for evaluating internal consistency. Then the confirmatory factor analysis (CFA) was excuted by Amos to varify the validity of each measure and to exclude the influence of common-method bias, referring to the fit indices of the model to the data recommended by Hu and Bentler [116]. Next, the descriptive statistics calculation and Pearson’s correlations were completed by SPSS (See Section 4.2 for the relevant results). Last, PROCESS Model 6 was selected for testing the sequential chain mediation effect of meaningful work and work engagement, as this model is specifically designed for analyzing multiple mediators and serial mediation pathways [117]; Model 6 of the PROCESS with SPSS was employed to verify the mediating effect of meaningful work, and work engagement. The bias-corrected percentile bootstrap method [121,122] was used in this study to assess the mediation effect, a method recommended for mediation testing due to its robustness to non-normal data distributions [122], which is that a significant mediating effect was indicated if bootstrap confidence interval (CI) does not include zero based on 5000 random samples [117,123].

Specifically, Pearson correlation and regression analyses were used to test the direct relationships in Hypotheses 1,2,3,5,6,8, while the bootstrap method in PROCESS Model 6 was adopted to verify the independent mediation effects (Hypotheses 4,7) and sequential mediation effect (Hypothesis 9). All regression analyses were pre-validated for compliance with basic statistical assumptions (residual normality and homoscedasticity) via SPSS diagnostic tools; no assumption violations were observed. Key model diagnostic indices (including R², F-value, and 95% CI) were reported for all analyses to verify model validity.

4.1 Common-method bias test

To address potential common method bias (CMB)—a critical concern in questionnaire-based research—our study employed a two-pronged approach: procedural controls during data collection and post-hoc statistical validation, as detailed below:

First, our research team established a close strategic partnership with Tibet Airlines Co., Ltd. For this collaboration, we jointly developed a dedicated database on flight attendants’ leadership, aviation psychology, and service performance. This partnership ensured the standardization and rigor of the sampling process, laying a robust foundation for data quality.

Second, under the framework of our joint research project with Tibet Airlines, 320 flight attendants were randomly sampled from the airline’s official roster. Random sampling was used to ensure the sample was highly representative of the target population (i.e., Tibet Airlines flight attendants) and provided sufficient statistical power for subsequent analyses.

Third, all participants received a detailed information sheet outlining the study’s academic context, specific research objectives, and data usage protocols. They also received clear, actionable instructions: to “complete the questionnaire carefully,” avoid non-standard responses (with clarifying examples provided), and follow submission guidelines. These measures minimized response ambiguity and inattention.

Fourth, participants were explicitly assured that their questionnaire responses would be treated with strict confidentiality, with no adverse effects on their professional careers. All individuals participated voluntarily and completed the questionnaire anonymously and truthfully during work breaks—further reducing response bias.

To confirm that missing data did not introduce systematic bias, we conducted a sensitivity analysis. Results revealed no significant differences between valid and excluded cases in key demographic variables (age: t = 1.23, p = 0.220, 95% CI = [−0.12, 0.50], Cohen’s d = 0.09; years of service: t = 0.98, p = 0.330, 95% CI = [−0.08, 0.46], Cohen’s d = 0.07) or core variables (spiritual leadership [SL]: t = 0.76, p = 0.450, 95% CI = [−0.10, 0.42], Cohen’s d = 0.05; service performance [SP]: t = 0.52, p = 0.600, 95% CI = [−0.15, 0.37], Cohen’s d = 0.04).

For statistical validation of CMB mitigation, we first conducted a post-hoc Harman’s single-factor test using Amos 24.0. This test—retained for transparency as a widely used initial screening tool [118]—extracted 32.7% of total variance from the unrotated factor solution, well below the 40% threshold indicating severe CMB [124]. However, we emphasize that multi-factor confirmatory factor analysis (CFA) and the marker variable approach are more rigorous, providing stronger evidence against CMB [125].

To supplement Harman’s test, we performed multi-factor CFA in Amos 24.0. The theoretical four-factor model (spiritual leadership [SL], meaningful work [MW], work engagement [WE], service performance [SP]) exhibited excellent data fit: χ²/df = 1.87, goodness-of-fit index (GFI) = 0.92, normed fit index (NFI) = 0.95, comparative fit index (CFI) = 0.97, root mean square error of approximation (RMSEA) = 0.052, and root mean square residual (RMR) = 0.031. By contrast, the single-factor model (all 40 items loading onto one factor) showed poor fit: χ²/df = 8.49, GFI = 0.36, NFI = 0.61, CFI = 0.63, RMSEA = 0.155. Additionally, the four-factor model’s CFI was 0.34 higher than the single-factor model—a difference > 0.10, indicating CMB is not a significant concern [126].

We further employed a marker variable (a theoretically unrelated construct) to quantify and control for potential CMB, following Lindell & Whitney [127]. The marker variable—“frequency of using public transportation”—was assessed on a 5-point Likert scale (1 = Never, 5 = Daily) and has no theoretical link to SL, MW, WE, or SP. The average correlation between the marker variable and core variables was r = 0.08 (p > 0.05), indicating minimal shared variance attributable to CMB. We then adjusted correlations among core variables using the marker variable’s maximum correlation (r = 0.11 with MW); adjusted correlations remained significant (e.g., SL-SP: r = 0.61 → 0.59, p < 0.001), confirming CMB did not distort observed relationships between core variables.

4.2 Correlation analysis

Descriptive statistics analysis and correlations analysis for all variables are shown in Table 1, and the correlation coefficients of the main variables were statistically significant. For example, Spiritual leadership has positive relationship with meaningful work, work engagement and service performance. Meaningful work is positively related with work engagement and service performance. Work engagement is positively correlated with service performance. Thus, according to Baron and Kenny [128] and Mackinnon [129], above significant correlations confirm the relationships between the variables discussed in the hypothesis, and meet the requirements to conduct the mediation effect test.

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Table 1. Descriptive statistics and correlations of the main variables (N = 313).

https://doi.org/10.1371/journal.pone.0324405.t001

4.3 Mediation effects analysis

Based on the analytical strategies mapped to each hypothesis, we tested the direct and mediating effects after controlling for four types of covariates. After introducing four types of control variables mentioned above, a test for mediating effects was performed by using PROCESS 3.3. All regression models report key diagnostic indices (R² for goodness of fit, F-value for overall model significance, 95% CI for coefficient reliability), with all models showing significant overall fit (all R² > 0.395, F > 34.556, p < .001) and good explanatory power for outcome variables. The analysis results are present in Table 2 and Fig 2, and Table 2 is designed and categorized based on the same outcome variable. As model 1 shows, spiritual leadership is positively related with meaningful work (b = 0.699, 95% CI = [0.642, 0.756], p < 0.001), supporting Hypothesis 2. In model 2, spiritual leadership is positively associated with flight attendants’ work engagement (b = 0.649, 95% CI = [0.457, 0.842], p < 0.001), which supports Hypothesis 6, and meaningful work positively affect flight attendant’s work engagement (b = 0.486, 95% CI = [0.263, 0.709], p < 0.001), supporting Hypothesis 8. In model 3, spiritual leadership (b = 0.227, 95% CI = [0.087, 0.367], p < 0.01), meaningful work (b = 0.317, 95% CI = [0.161, 0.473], p < 0.001) and work engagement (b = 0.081, 95% CI = [0.005, 0.157], p < 0.05) all have positively influence on flight attendants’ service performance, which supports Hypothesis 1, Hypothesis 3 and Hypothesis 5 respectively. Up to now, Hypothesis 1, Hypothesis 2, Hypothesis 3, Hypothesis 5, Hypothesis 6 and Hypothesis 8 are proved to be true. It should be noted that, in model 3, the calculated effect of spiritual leadership on service performance is direct effect, while in model 4, the calculated effect of spiritual leadership on service performance is total effect (b = 0.529, 95% CI = [0.450, 0.609], p < 0.001).

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Table 2. Regression results of the chain mediating effects model (N = 313).

https://doi.org/10.1371/journal.pone.0324405.t002

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Fig 2. The chain mediating effect of meaningful work and work engagement.

Note: *p < 0.05, **p < 0.01 and ***p < 0.001.

https://doi.org/10.1371/journal.pone.0324405.g002

As present in Table 3. Bootstrap Results of Chain Mediating Effects, the results of the bootstrap analysis (a bootstrap sample of 5000 was specified) for meaningful work and work engagement separately of spiritual leadership on service performance, which are path 1 and path 3 in Table 3, do not include zero.

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Table 3. Bootstrap results of chain mediating effects (N = 313).

https://doi.org/10.1371/journal.pone.0324405.t003

1. Path 1 (SL → MW → SP): The indirect effect was estimated as b = 0.222, 95% CI = [0.140, 0.316], p < 0.001, supporting Hypothesis 4.
2. Path 2 (SL → MW → WE → SP): The chain mediation effect was estimated as b = 0.028, 95% CI = [0.006, 0.062], p < 0.05, supporting Hypothesis 9.
3. Path 3 (SL → WE → SP): The indirect effect was estimated as b = 0.053, 95% CI = [0.012, 0.100], p < 0.01, supporting Hypothesis 7.

Additionally, the total indirect effect (SL → Mediators → SP) was b = 0.302, SE = 0.048, t = 6.292, 95% CI = [0.212, 0.398], p < 0.001, and the total effect (SL → SP) was b = 0.529, SE = 0.040, t = 13.076, 95% CI = [0.450, 0.609], p < 0.001, further confirming the robust overall impact of spiritual leadership on service performance.

5.1 Filling gaps in spiritual leadership-service performance research among flight attendants

5.2 Uncovering multi-path mechanisms linking spiritual leadership to service performance among flight attendants

5.3 Extending positive psychology and validating specific pathways in civil aviation

5.4 Limitations and future research directions

While this study makes the aforementioned theoretical and practical contributions, it is not without limitations—these, however, offer meaningful avenues for future research.