© 2026 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
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Employee retention has become a persistent concern in the hotel sector, where labour instability not only disrupts service delivery but also undermines the long-term social sustainability of the industry. This study examines how individual and organizational factors jointly shape employees’ decisions to remain, with particular attention to the roles of grit, perceived fairness, and service-oriented organizational citizenship behaviour (SOCB). A survey was conducted among 225 employees working in three- to five-star hotels in Jakarta. The data were analysed using partial least squares structural equation modelling. The results indicate that fairness exerts a consistent and substantial influence on both SOCB and retention. In contrast, grit does not directly affect employees’ intention to stay, but operates indirectly through its contribution to discretionary service behaviours. SOCB, in turn, emerges as an important behavioural mechanism linking workplace conditions to retention outcomes. These findings suggest that employee retention in hospitality cannot be explained solely by individual resilience or motivation. Instead, it reflects a broader organizational environment in which fairness and everyday service practices play a central role. From a sustainability perspective, strengthening fair management systems and fostering service-oriented behaviours can contribute to more stable and committed workforces. This, in turn, supports the continuity and resilience of service systems in the hospitality sector.
social sustainability, employee retention, perceived fairness, service-oriented behavior, hospitality sector
The emergence of Industry 4.0, the hallmark of the Fourth Industrial Revolution, has transformed the operational landscape of modern businesses, including tourism and hospitality. Two key challenges dominate this transformation: human resources and technology [1]. Technology has become a critical enabler of customer service. During the COVID-19 pandemic, when physical interactions were restricted, hotels increasingly relied on digital platforms to facilitate customer feedback and engagement. Technology not only supports efficiency, but also shapes the reputation of hospitality firms. However, technology alone cannot replace human interaction. Service excellence in hospitality remains dependent on skilled human resources because social interaction and emotional connections are intrinsic to service experience. As Arief Yahya, former Indonesian Minister of Tourism, stated, the digitalization of consumer behavior must be accompanied by personalization; digital tools should enable businesses to reach customers individually [2].
Beyond Industry 4.0, the emergence of Society 5.0, first articulated by the Japanese government in January 2019, has further redefined the balance between technology and humanity. Conceived as a human-centered, technology-driven society, Society 5.0 envisions people transforming big data into new wisdom that advances human capability and social well-being [3]. The concept was introduced to counter fears that automation under Industry 4.0 would marginalize human roles. In this paradigm, humans remain at the core of civilization, suggesting that technological advancement should augment rather than replace human contributions [4]. This principle is particularly relevant in the hospitality sector, in which the essence of service rests on human empathy, responsiveness, and adaptability. As a fast-growing service industry, hospitality exemplifies the global shift from product-based to service-based business models, in pursuit of greater interactivity and value creation [5].
Tourism and hospitality occupy strategic positions in Indonesia’s national economy. The sector consistently generated substantial foreign exchange, ranking third in 2016 and rising to second in 2017 [1]. This trend is reflected in the rising hotel occupancy rate, which increased from 54.16% in 2018 to 58.42% in 2019. However, the COVID-19 pandemic caused a sharp decline, and many hotels were forced to close. In July 2020, the average occupancy rate of star-rated hotels fell to 28.07%, down 28.66 points from the previous year’s 56.73%. Despite this contraction, a modest rebound began in mid-2020, led by hotels in Jakarta with an occupancy of 41.03% [1].
The sector’s resilience is further evidenced by the macroeconomic data. According to the Indonesian Central Bureau of Statistics, the accommodation and food service subsector grew by 5.45% in the first quarter of 2018 (year-on-year), driven by increased foreign tourist arrivals and domestic consumption. Growth accelerated to 5.75% in the second quarter, with cumulative gains of 5.60% [6]. Hotel investments have also increased. Colliers International Indonesia [7] reported an increase of 50 new star-rated hotels in Jakarta by 2019, primarily within the Central Business District, including luxury brands such as Alila, St Regis, Waldorf Astoria, Regent, and The Langham [7].
Hospitality is inherently a people-intensive industry that operates “by humans and for humans.” Unlike manufacturing, it relies on intangible, inseparable, heterogeneous, and perishable services [8]. However, hospitality employees often face demanding work conditions, such as low wages, long hours, repetitive tasks, and high pressure, while being expected to deliver consistently excellent services [9]. Frontline staff must display warmth, courtesy, and sincerity; adapt services to individual needs; and resolve complaints swiftly to ensure customer satisfaction. Such requirements demand employees to be emotionally, psychologically, and spiritually resilient [9].
Maintaining a consistent service quality across all hotel units remains a major challenge [10]. Service quality reflects employees’ reliability, willingness to assist guests, responsiveness, courtesy, and capacity to build trust [11]. As hospitality competition extends beyond pricing to include experience and service differentiation, service quality becomes the central source of competitive advantage [12]. Nevertheless, industry forums have highlighted persistent structural challenges such as talent shortages, intense competition, absence of licensing moratoria, inadequate managerial expertise, weak certification systems, declining room rates, and insufficient service quality orientation [13].
Human capital issues are particularly concerning. According to Alexander Nayoan, Chair of the Jakarta Hotel Association, many hotels struggle to retain skilled workers amid talent wars and high turnovers [14]. The average employee turnover rate in 2019 reached 17%, which is significantly above the normal range of 5–10% [15]. A high turnover imposes recruitment and training costs, disrupts team cohesion, and erodes morale. Therefore, sustaining a stable and committed workforce has become one of the most pressing priorities in the industry.
To address this issue, scholars have begun to examine the psychological and behavioral factors that influence employee retention. Literature and field observations suggest that grit, fairness, and service-oriented organizational citizenship behavior (SOCB) are pivotal variables affecting employees’ willingness to remain in hospitality organizations [16-19]. These constructs offer a promising framework for understanding why some employees persist and excel despite adverse working conditions. Therefore, this study seeks to analyze the role of grit and fairness in predicting employee retention within Indonesia’s hospitality industry, with SOCB as a mediating variable. By integrating psychological endurance, perceptions of organizational justice, and prosocial service behavior, this study aimed to contribute a novel explanatory model for enhancing long-term workforce stability in the Indonesian hotel sector.
2.1 Grand theory
The grand theoretical anchor for this study is the Resource-Based View (RBV), which explains heterogeneity in firm performance through the heterogeneity and relative immobility of firm resources [20, 21]. The RBV assumes that firms within an industry differ in their bundles of resources and capabilities and that these resources do not move freely across firms. Therefore, competitive advantage rests on deploying resources that are valuable, rare, inimitable, and non-substitutable, yielding sustained competitive advantage when rivals cannot replicate the underlying resource configuration or decipher the causal mechanisms linking resources to superior returns [20, 21]. Early RBV work conceptualized resources broadly to include tangible and intangible assets such as brand names, proprietary technologies, contracts, and efficient routines, as well as the knowledge, skills, and abilities of employees [22]. Subsequent elaborations emphasize that rivalry is best understood as competition over resource endowments and capability development rather than over static market positions or collusive behaviors and that firms must manage causal ambiguity and information constraints when assembling resource portfolios [23, 24].
In hospitality, the RBV offers a precise lens: human resources are both the most consequential and the hardest to imitate. Hotels operate through continuous, high-contact service encounters, where employee judgment, emotional labor, and tacit coordination directly determine quality. Heterogeneity is pronounced because labor forces draw from diverse cultural and experiential backgrounds, whereas immobility emerges when firms retain key employees long enough to embed firm-specific knowledge and team routines. Under these conditions, HR systems that attract, develop, and retain employees with distinctive psychological strengths become core strategic assets, rather than support functions. The RBV thus predicts that the capacity to cultivate and retain human capital that is valuable, rare, inimitable, and non-substitutable will separate hotels that sustain advantage from those that compete on price alone [25]. In short, employee attributes and organizational practices that stabilize them are not peripheral inputs, but the principal levers through which hospitality firms translate resources into durable performance.
2.2 Middle-range theory
Bridging RBV with testable mechanisms requires mid-range theories that specify how organizations mobilize human resources and how individuals convert attitudes into behavior. Human Resource Management (HRM) provides the first bridge. As a managerial philosophy, HRM aligns people’s policies with business strategy, builds high-performance cultures, ensures access to skilled and engaged talent, and fosters trust-based employment relations under an ethical frame [26]. Canonical HRM models underscore strategic fit, long-term orientation, stakeholder salience, and the complementarity between “hard” calculative controls and “soft” practices that elevate communication, motivation, and leadership [26]. Contemporary agendas extend to human capital and talent management, competency-based HR, reward systems, and employee engagement as drivers of strategic outcomes [26]. A comprehensive systematic review maps HRM scholarship into five clusters, notably “experiencing HRM” which encompasses retention, employee perceptions, psychological contracts, and engagement, the exact zone where hospitality’s people challenges concentrate [27]. This mid-range view reframes retention not as an administrative by-product, but as a strategic capability through which firms preserve and compound returns to their human capital.
A second mid-range pillar is the Theory of Planned Behavior (TPB), which explains how attitudes, subjective norms, and perceived behavioral control shape intentions and, in turn, behavior [28-30]. TPB accommodates the reality that employees may intend to enact pro-organizational behavior, yet face constraints in knowledge, time, or coordination that blunt enactment [31]. Robust evidence links intentions to behavior while identifying moderators that strengthen intention–action conversion, including temporal stability, need satisfaction, implementation intentions, personality, and age [32, 33]. In hotel settings, the TPB clarifies how workplace norms and perceived control activate or suppress pro-service intentions. HR policies, supervisory climates, and peer expectations instantiate subjective norms; access to training, information, and tools constitutes perceived control. Together, they explain the variance in whether employees actually display discretionary, customer-facing behaviors that drive service quality.
Organizational Behavior (OB) and industrial-organizational psychology add a complementary lens by connecting enduring personality differences with work outcomes in teams and service systems [34]. The Big Five model captures relatively stable traits linked to performance, OCB, creativity, counterproductive work behaviors, and burnout across occupations, with clear implications for high-strain, high-contact hospitality roles, where emotional stability, conscientiousness, and agreeableness are repeatedly taxed [35]. OB research thereby rationalizes selection, socialization, and climate-building as levers that translate individual dispositions into collective service capability, tightening the conceptual link between the RBV’s human capital thesis and the observable micro-behaviors that constitute service excellence [36].
Finally, retention literature frames the dependent construct of interest. Turnover is persistently costly and salient, with direct replacement costs and indirect customer impacts that can erode performance [37]. Retention can be viewed from the employee’s perspective as a movement from consideration to commitment, which reduces exit intentions, and from the firm’s side as a deliberate system of practices that encourages employees to say positive things, stay with the organization, and strive beyond role expectations [38]. Mapping employees into enthusiastic or reluctant stayers and leavers further nuances the retention challenge and points to targeted interventions [37]. As a mid-range construct, retention becomes the behavioral end-state through which hotels conserve and scale their VRIN human resources.
2.3 Applied theory
At the applied level, this study focuses on three psychologically grounded antecedents—grit, fairness, and SOCB—and their relationships with retention in hospitality. Grit captures the perseverance of effort and consistency of interest directed toward long-term goals [18, 39]. Evidence links grit to sustained goal pursuit and retention beyond intelligence and the Big Five, including in demanding contexts such as the military and sales [18, 19]. Emerging work also associates grit with OCB and job attitudes, positioning it as a personal resource that sustains high performance under the pressure and monotony typical of hotel operations [17]. In the hospitality milieu, where 24/7 operations, emotional labor, and peak-period volatility are the norm, grit functions as a micro-foundation of resilience that the RBV deems strategically consequential.
Fairness, often discussed interchangeably with justice, encapsulates employees’ evaluations of distributive outcomes, procedural systems, and interactional treatment [40, 41]. Distributive fairness concerns the proportionality of rewards to contributions; procedural fairness concerns transparency and consistency in decision processes and timing; and interactional fairness concerns dignity, respect, and adequacy of explanations in interpersonal exchanges. Empirical research across services, retail banking, travel, restaurants, and repairs links fairness to OCB, organizational identification, and loyalty, whereas hotel-specific work remains sparse relative to its practical salience [42]. In frontline service systems, fairness signals that the organization values employees, thereby strengthening engagement and discouraging withdrawal cognitions that feed turnover.
OCB represents discretionary extra-role behaviors that support organizational functioning without being formally prescribed [43]. In hospitality, generic OCB is necessary but insufficient. SOCB specifies the customer-facing contours of extra-role behavior in three dimensions: loyalty, service delivery, and participation [16]. Loyalty concerns proactively promoting the organization’s services and images to customers. Service delivery focuses on acting as a communication bridge between external and internal environments, handling requests, and adapting to offerings. Participation emphasizes voluntarily proposing improvements to align services with evolving customer needs. Prior studies associate SOCB with service quality, competitive advantage, and financial performance, and suggest that HR systems, training, and leader–member exchange can induce these behaviors, although hospitality-specific evidence remains limited [12].
Positioning SOCB as a mediator aligns with both the TPB and RBV. At the micro level, grit and fairness shape attitudes, norms, and perceived control that foster intentions to go beyond role, which then materializes as SOCB. At the strategic level, these discretionary behaviors are proximate mechanisms through which VRIN human resources create value at the moment of truth with customers. Empirical hints support each link: grit relates to OCB and persistence; fairness predicts OCB with distributive fairness, often the strongest component; and OCB relates to turnover intentions and retention, although the findings are not uniform across settings [38, 43-45]. The mixed evidence underscores both the need and opportunity to test a fuller causal chain in a high-pressure, service-intensive context such as Indonesian hotels, where average turnover has been reported above benchmark levels and where sustained service quality is strategically decisive.
The applied model derived from this study is as follows. The RBV motivates a focus on human resources as strategic assets for hospitality. HRM and OB specify organizational levels and individual dispositions that nurture these assets and anchor behavioral expectations. The TPB clarifies how personal resources and fairness perceptions translate into intentions and realize extra-role service behaviors. SOCB then operates as a behavioral engine that links psychological antecedents to retention, an outcome that preserves and compounds human capital advantages. Using this logic, this study investigates whether grit and fairness directly enhance SOCB and whether SOCB reduces the propensity to leave, thereby improving retention. It also tested whether SOCB mediates the effects of grit and fairness on retention. This specification directly addresses documented gaps: prior studies have validated grit scales and tied grit to outcomes, linked justice to OCB, and connected OCB to turnover intentions, but have not jointly examined grit, fairness, SOCB, and retention within the hospitality context in Indonesia [17, 19, 44, 45].
2.4 Conceptual framework
Indonesia’s rapid expansion of hotels has intensified competition for high-quality talent and, in turn, raised employee turnover, making long-term retention a central managerial challenge. This study proposes that retention can be strengthened by identifying and developing employees with grit, ensuring perceptions of fairness in the employment relationship, and cultivating SOCB. Grit denotes perseverance toward long-term goals, reflected in the perseverance of effort and consistency of interest [46]. In practice, hotels should audit current staff and align future recruitment with these grit dimensions so that employees possess the stamina to perform under the 24/7 operational cadence of hospitality. Retention is also shaped by whether employees perceive the organization as fair. Fairness is experienced through distributive, procedural, and interactional dimensions; optimizing these signals is expected to foster both service OCB and willingness to remain with the firm. Engagement, which is observable by saying positive things about the organization, choosing to stay, and striving beyond role requirements, offers an actionable lens for monitoring the retention propensity [47].
Service OCB captures the extra-role and customer-facing behaviors that sustain service quality. Its core facets, that is, loyalty, service delivery, and participation, provide a concrete template for shaping frontline conduct and for designing training, evaluation, and recognition systems that encourage employees to promote the hotel, bridge customers’ need for internal processes, and proactively suggest service improvements [16]. Conceptually, hotels should also segment their workforce into enthusiastic stayers, enthusiastic leavers, reluctant stayers, and reluctant leavers to target retention efforts toward employees most likely to remain and intervene early with those at risk of exit.
Synthesizing these elements, the model in Figure 1 posits that grit and fairness each enhance service OCB, grit, fairness, and service OCB directly influence retention, and service OCB functions as the behavioral conduit through which grit and fairness translate into lower turnover intentions. Prior findings linking OCB to retention provide an empirical rationale for this pathway in service settings [38]. The framework is tested via a survey design with hypothesis testing to validate these relationships in Indonesia’s hospitality context.
The hypotheses articulate how the constructs derived from the literature are expected to relate within the hospitality context. Grit is conceptualized as a forward-looking source of motivation that imbues long-term goals with meaning, and reflects steadfast pursuit when those goals align with inner values [48]. Unlike conscientiousness, a relatively stable Big Five trait [49], grit is treated as a malleable motivational resource that is amenable to intervention and behavioral choices. Given its two facets, perseverance of effort and consistency of interest [46], employees with higher grit should be more inclined to enact extra-role and customer-facing behaviors. Accordingly, we hypothesized that grit would positively influence SOCB (H1). Because gritty individuals sustain effort, experience more positive work affect, and exhibit stronger self-control across domains [19, 50], we further posit a positive effect of grit on employee retention (H2).
Figure 1. Research design
Fairness is expected to foster prosocial service behavior and attachment. Prior studies link justice perceptions to ethical conduct, affective and cognitive mechanisms, leader–member dynamics, firm sustainability, and OCB, with salient predictors of distributive, procedural, and interactional justice [44, 51]. Therefore, we hypothesize that fairness positively influences SOCB (H3) and retention (H4), consistent with the evidence that justice strengthens loyalty and satisfaction [40]. As low OCB is associated with higher quit tendencies [38], we expect SOCB to positively influence retention (H5). Finally, integrating these pathways, we propose that SOCB mediates the effects of grit on retention (H6) and fairness on retention (H7), in line with research linking grit to OCB and retention [19, 45, 46], and justice to OCB and withdrawal cognitions [44].
3.1 Research approach
This study employs a quantitative approach that integrates descriptive and verificative statistics to analyze the relationships between key variables. The descriptive analysis aims to portray the characteristics of the observed data, providing an overview of each construct: grit, fairness, SOCB, and employee retention. The verificative approach tests the proposed hypotheses statistically, verifying whether the empirical data support or refute the relationships established in the conceptual framework [52].
The unit of analysis and observation comprised employees of three-, four-, and five-star hotels located in Jakarta. This research adopts a cross-sectional time horizon, meaning that all data were collected empirically at a single point in time to capture current perceptions and behavioral tendencies among hotel employees.
3.2 Operationalization of variables
The research model consisted of two exogenous variables (grit and fairness), one mediating variable (service OCB), and one endogenous variable (employee retention). Retention refers to employees’ willingness to remain in the organization, expressed through engagement (say, stay, strive), and classified into four behavioral categories: enthusiastic or reluctant stayers and leavers [37].
Service OCB represents employees’ discretionary behavior that goes beyond formal job requirements to enhance service quality. It comprises three dimensions: loyalty (promoting the product, service, and brand image), service delivery (bridging communication and responding to customer requests), and participation (suggesting improvements, contributing to decisions, and supporting organizational initiatives) [16].
Grit is defined as sustained effort and consistency of interest toward long-term goals, even under challenging or monotonous conditions [17, 39]. Its two dimensions, that is perseverance of effort and consistency of interest, capture resilience, goal orientation, and enduring motivation. Fairness refers to employees’ perceptions of being treated equitably by the organization [44], encompassing interactional, procedural, and distributive fairness, which collectively influence employees’ prosocial behaviors and organizational attachment.
3.3 Data sources and collection
Primary and secondary data were used. Primary data were collected via an online questionnaire employing a six-point Likert scale ranging from “strongly disagree” to “strongly agree.” The survey targeted hotel employees directly, supplemented by follow-up phone calls and email reminders to maximize response rates. Secondary data were obtained from relevant government and industry sources, including statistical reports from the Ministry of Tourism, Central Bureau of Statistics, and Indonesian Hotel and Restaurant Association (PHRI), covering sector profiles, workforce data, and regulatory frameworks.
Additional qualitative insights were obtained through interviews with key informants, such as the Chair of the Jakarta Hotel General Manager Association, the Chair of the Frontliner Association, and the Chair of the Human Resources Manager Association. Observations of hotel operations and document reviews provided contextual validation of the constructs.
3.4 Sampling technique
The population comprises employees of three-, four-, and five-star hotels in Jakarta. Sampling followed a stratified random technique, with strata defined by hotel classification, to ensure proportional representation. According to the 2018 Central Bureau of Statistics, there were 276 classified hotels in Jakarta: 213 three-star, 16 four-star, and 48 five-star. The total employee population before the pandemic was approximately 25,920, declining by approximately 50 percent by 2020 due to workforce reductions [53].
Using Bartlett’s formula for categorical data, 225 valid samples were targeted and distributed proportionally across hotel categories: 62 from three-star hotels, 77 from four-star hotels, and 86 from five-star hotels. The sampling error was set at 5 percent with a 95 percent confidence level to ensure sufficient statistical power to test hypothesized relationships.
This methodological design integrates rigorous quantitative analysis with contextual insights from industry practitioners, enhancing both the empirical validity and practical relevance of the findings to Indonesia’s hospitality sector.
3.5 Design of the analysis and tests
This study applied variance-based structural equation Modeling using SmartPLS version 3.2.6. PLS-SEM is appropriate because it imposes minimal distributional assumptions, accommodates ordinal measurements, and performs well with modest sample sizes [54]. The estimation follows two-step procedure: first, evaluation of the measurement model (outer model) to establish that indicators validly and reliably reflect the latent constructs; second, evaluation of the structural model (inner model) to test the hypothesized relationships among constructs [52, 54]. The path diagrams in the attached figures depict the causal structure estimated in the analysis, with grit and fairness as exogenous variables, SOCB as the mediator, and retention as the endogenous outcome.
The measurement model assesses the extent to which the manifest indicators represent each latent variable. The constructs in this study were modeled using reflective indicators, unless otherwise specified. Convergent validity was examined via standardized outer loadings and Average Variance Extracted (AVE). Indicators with loadings above 0.70 are retained, and an AVE exceeding 0.50 indicates that a construct explains more than half of the variance in its indicators. Reliability is evaluated using composite reliability, with values typically expected to meet or exceed the conventional thresholds for internal consistency. Discriminant validity is verified by comparing the square root of each construct’s AVE with its inter-construct correlations and inspecting cross-loadings to ensure that indicators load higher on their intended construct than on others [54]. These procedures determine the dominant indicators in forming each latent variable and confirm the adequacy of the measurement specifications.
The structural model examines the magnitude and direction of the relationships among the latent variables. The significance of the path coefficients was tested using nonparametric bootstrapping, which generates t-statistics for each estimated path. Two-tailed tests (α = 0.05) were applied, with a critical value of 1.96 as the decision threshold for the acceptance or rejection of each hypothesis. Model explanatory power was assessed using the coefficient of determination (R²) of endogenous constructs. Following Chin’s rule of thumb, R² values of approximately 0.67, 0.33, and 0.19 indicate substantial, moderate, and weak explanatory power, respectively. Changes in R² across competing specifications indicate the substantive contribution of the exogenous variables to the outcome. Where relevant, effect sizes were calculated to gauge the practical importance of each predictor.
Hypothesis testing was conducted on the full PLS path model, which simultaneously estimated the outer, inner, and casewise latent variable scores through the algorithm’s weighting scheme. The testing sequence proceeds from the confirmation of the measurement properties to the evaluation of the direct and mediated effects among grit, fairness, SOCB, and retention. This design provides a clear and rigorous basis for determining whether the proposed causal mechanisms are supported in the context of Indonesian hospitality.
4.1 Respondent characteristics
This section presents the respondents’ demographic and professional characteristics, emphasizing their hotel classification, job position, department, gender, age, education, tenure, total work experience, and managerial experience. The total sample consisted of 225 employees from three-, four-, and five-star hotels in Jakarta.
The sample comprised 225 employees drawn mainly from five-star hotels (43.6%), with additional representation from four-star (33.8%) and three-star properties (22.7%). Most participants held managerial roles; managers/supervisors accounted for 40%, followed by line staff (27.1%), senior managers (20.4%), general managers (8.9%), and directors (3.6%). The front office was the dominant department (35.6%), with smaller shares in human resources (15.1%), food and beverage production (9.3%), and housekeeping (8.9%). Men and women constituted 60.4% and 39.6% of the respondents, respectively. The age profile was concentrated in the prime working years: 26–35 years (35.6%) and 36–45 years (28%), with smaller groups aged 17–25 (20%), 46–55 (15.1%), and 56–65 (1.3%) (Table 1).
Table 1. Respondent characteristics
|
Characteristic |
Category |
n (%) |
|
Hotel category |
Three-star |
51 (22.7) |
|
|
Four-star |
76 (33.8) |
|
|
Five-star |
98 (43.6) |
|
Position |
Director |
8 (3.6) |
|
|
General Manager |
20 (8.9) |
|
|
Senior Manager |
46 (20.4) |
|
|
Manager/Supervisor |
90 (40.0) |
|
|
Line Staff |
61 (27.1) |
|
Department |
Front Office |
76 (35.6) |
|
|
Human Resources |
34 (15.1) |
|
|
F&B Production |
21 (9.3) |
|
|
Housekeeping |
20 (8.9) |
|
Gender |
Male |
136 (60.4) |
|
|
Female |
89 (39.6) |
|
Age group |
17–25 (late adolescence) |
45 (20.0) |
|
|
26–35 (early adulthood) |
80 (35.6) |
|
|
36–45 (late adulthood) |
63 (28.0) |
|
|
46–55 (early senior) |
34 (15.1) |
|
|
56–65 (late senior) |
3 (1.3) |
|
Education |
High school |
33 (14.7) |
|
|
Diploma |
77 (34.2) |
|
|
Bachelor’s |
85 (37.8) |
|
|
Master’s |
30 (13.3) |
|
Tenure (current company) |
< 2 years |
111 (49.3) |
|
|
2–5 years |
69 (30.7) |
|
|
6–10 years |
21 (9.3) |
|
|
> 10 years |
24 (10.7) |
|
Total work experience |
< 2 years |
32 (14.2) |
|
|
2–5 years |
48 (21.3) |
|
|
6–10 years |
49 (21.8) |
|
|
> 10 years |
96 (42.7) |
|
Managerial experience |
None |
53 (23.6) |
|
|
< 2 years |
30 (13.3) |
|
|
2–5 years |
67 (29.8) |
|
|
6–10 years |
31 (13.8) |
|
|
> 10 years |
44 (19.6) |
Educational attainment was relatively high for a vocationally oriented sector: 37.8% held a bachelor’s degree, 34.2% held a diploma, 14.7% held a high school certificate, and 13.3% held a master’s degree. Nearly half of the respondents had been in their current organization for less than two years (49.3%), signaling notable mobility; the remainder reported two to five years (30.7%), six to ten years (9.3%), and more than ten years (10.7%). The total industry experience is deeper, with 42.7% exceeding ten years and only 14.2% under two years. Managerial experience was most commonly two–five years (29.8%), while 23.6% reported none, and the rest were distributed across more than ten years (19.6%), six to ten years (13.8%), and under two years (13.3%).
4.2 Descriptive statistics of the variables
All constructs were measured on a six-point Likert scale and exhibited generally high central tendencies around the “agree” anchor. Grit showed the strongest average endorsement (item mean = 5.22), with particularly high scores for hard work and persistence. Fairness averages 4.91, with somewhat lower means for procedural and distributive aspects relative to interactional treatment. SOCB averages 5.09; loyalty and service-delivery items score higher than participation in decision-making. Retention recorded the lowest average (4.76), driven by weaker intentions to remain compared with positive word-of-mouth and striving. Dispersion was modest across constructs, with average item standard deviations ranging from 0.71 (grit) to 1.01 (retention), indicating acceptable variability for structural analysis (Table 2).
Table 2. Descriptive statistics of the variables
|
Variable |
Items (k) |
Item Mean Range |
Average Item Mean |
Average SD |
Total Mean Score |
|
Grit |
7 |
4.933–5.373 |
5.221 |
0.707 |
36.547 |
|
Fairness |
10 |
4.702–5.267 |
4.908 |
0.895 |
49.077 |
|
Service OCB |
7 |
4.867–5.320 |
5.087 |
0.873 |
35.606 |
|
Retention |
5 |
4.538–4.911 |
4.763 |
1.009 |
23.814 |
4.3 Cross-tabulation analysis
We conducted a cross-tabulation of the descriptive data to profile retention across the respondent strata. Because retention was measured with five Likert items, total scores ranged from 5 to 30; scores of 18–30 denoted high retention and 5–17 denoted low retention.
The overall retention rate is high. Of 225 employees, 211 (93.8%) were in the high-retention category. By hotel class, high retention was most pronounced in five-star properties (94.9%), followed by four-star (88.2%) and three-star hotels (100%). By position, the share of high-retention respondents was consistently elevated: directors 100%, general managers 95.0%, senior managers 93.5%, managers/supervisors 95.6%, and line staff 90.2%. The departmental results were similar, with the highest proportions in food and beverage production (100%) and human resources (97.3%), followed by “other” departments (95.7%), front office (92.9%), housekeeping (90.5%), and food and beverage services (81.3%).
Gender differences were small; 92.6% of men and 95.5% of women exhibited high retention. Retention was highest at ages 26–35 (97.5%) and 46–55 (97.1%), remained high at 17–25 (91.5%) and 36–45 (88.9%), and was universally high in the small 56–65 age group. In terms of education, diploma holders showed the highest high-retention share (98.7%), followed by master’s (96.7%), bachelor’s (90.6%), and high school (87.9%). With respect to organizational tenure, high retention was observed for less than two years (94.6%), two to five years (91.3%), six to ten years (95.2%), and more than ten years (95.8%). The total industry experience shows a similar pattern, peaking at two–five years and six–ten years (both 100%), with strong proportions above ten years (90.6%). Finally, managerial experience aligns positively with retention: less than two years 100%, more than ten years 97.7%, six to ten years 93.5%, and two to five years 92.5%, compared with 88.7% among those without such experience. Collectively, the cross-tabulations indicate consistently high retention across strata, with modest variation favoring higher-tier hotels, HR and production functions, mid-career age groups, and respondents with managerial exposure.
4.4 Validity and reliability testing result
Construct validity was assessed using indicator loadings, AVE, communality, and composite reliability. Consistent with the recommended thresholds, AVE values should exceed 0.50, indicating that at least half of the variance in the indicators is captured by the latent construct, whereas reflective indicators are expected to load at or above 0.70, with T-statistics of at least 1.96. The initial estimation identified several indicators with suboptimal loadings: G1 = 0.206, G7 = 0.469, S5 = 0.478, S6 = 0.691, R6 = 0.573, R7 = 0.338, R8 = 0.202, and R9 = 0.149. Therefore, the measurement model was verified by removing the eight indicators. The revised model shows that all retained indicators load substantially on their intended constructs, with loadings meeting or approaching the 0.70 criterion across Grit, Fairness, SOCB, and Retention, as summarized in Table 3.
Table 3. Measurement model: standardized loadings for retained indicators (after respecification)
|
Construct |
Indicator (abbrev.) |
λ |
|
Grit |
Work setbacks do not weaken effort (G2) |
0.769 |
|
|
Sets work targets (G3) |
0.758 |
|
|
Works hard (G4) |
0.761 |
|
|
Focus on work (G5) |
0.663 |
|
|
Finishes what is started (G6) |
0.729 |
|
|
Perseveres in challenging work (G8) |
0.757 |
|
|
Diligent (G9) |
0.791 |
|
Fairness |
Polite treatment (F1) |
0.742 |
|
|
Respectful treatment (F2) |
0.768 |
|
|
Given time to voice views (F3) |
0.783 |
|
|
Listened to (F4) |
0.807 |
|
|
Procedural consistency (F5) |
0.847 |
|
|
Procedural appropriateness (F6) |
0.81 |
|
|
Procedural fit (F7) |
0.798 |
|
|
Outcomes match contribution (F8) |
0.796 |
|
|
Earnings are proportional (F9) |
0.828 |
|
|
Provision is proportional (F10) |
0.772 |
|
Service-oriented organizational citizenship behaviour (SOCB) |
Promotes products (S1) |
0.791 |
|
|
Promotes services (S2) |
0.841 |
|
|
Promotes image (S3) |
0.786 |
|
|
Communication intermediary (S4) |
0.717 |
|
|
Improves service (S7) |
0.765 |
|
|
Makes decisions (S8) |
0.738 |
|
|
Participates in decisions (S9) |
0.729 |
|
Retention |
Speaks positively (R1) |
0.861 |
|
|
Feels part of the organization (R2) |
0.784 |
|
|
Contributes beyond expectations (R3) |
0.781 |
|
|
Intends to stay (R4) |
0.807 |
|
|
Able to stay (R5) |
0.815 |
Note: The conventional rule of thumb is λ ≥ 0.70; items with λ in the high-0.60s were retained given satisfactory AVE and reliability at the construct level.
Figure 2. Model loading factor
Figure 2 illustrates the model loading factor.
Reliability was evaluated using Cronbach’s alpha, composite reliability, and the average variance. The results indicated strong internal consistency and convergent validity for all constructs. Grit achieves α = 0.872, composite reliability = 0.901, and AVE = 0.566; Fairness achieves α = 0.934, composite reliability = 0.944, and AVE = 0.627; SOCB achieves α = 0.889, composite reliability = 0.914, and AVE = 0.603; Retention achieves α = 0.885, composite reliability = 0.916, and AVE = 0.684. All values surpass the conventional reliability thresholds of 0.70 for alpha and composite reliability, and 0.50 for AVE, confirming that the final indicators provide precise and stable measurements and that each construct explains more than half of the variance in its indicators (Table 4).
Table 4. Scale reliability and convergent validity (after respecification)
|
Construct |
Cronbach’s α |
Composite Reliability |
AVE |
|
Grit |
0.872 |
0.901 |
0.566 |
|
Fairness |
0.934 |
0.944 |
0.627 |
|
SOCB |
0.889 |
0.914 |
0.603 |
|
Retention |
0.885 |
0.916 |
0.684 |
Benchmarks: α > 0.70; CR > 0.70; AVE > 0.50. All the constructs met or exceeded the thresholds, indicating good internal consistency and convergent validity.
Thus, the outer model satisfied the standard criteria for indicator validity and construct reliability (Figure 3).
Figure 3. Outer model loading factor
Table 5. Items removed during model respesification
|
Construct |
Dropped Indicator |
λ |
|
Grit |
G1 (attention not diverted) |
0.206 |
|
|
G7 (stable interest) |
0.469 |
|
SOCB |
S5 (meets customer requests) |
0.478 |
|
|
S6 (anticipates changing needs) |
0.691 |
|
Retention |
R6 (must stay) |
0.573 |
|
|
R7 (intends to leave) |
0.338 |
|
|
R8 (able to leave) |
0.202 |
|
|
R9 (must leave) |
0.149 |
Validity criteria: Indicators were dropped when λ < 0.70 and did not contribute to acceptable convergent validity at the construct level; retained items collectively yield AVE ≥ 0.50 for all constructs.
Subsequent analyses proceeded using the refined measurement model estimated in PLS-SEM, with the indicator set and outer loadings, and the reliability summary (Table 5).
4.5 Hypothesis testing result
We estimated PLS-SEM with bootstrapped standard errors (N = 225; two-tailed, α = 0.05). The results are clear. Grit is a strong predictor of SOCB (SOCB; β = 0.482, t = 8.641, p < 0.001), supporting H1. In contrast, grit showed no direct association with retention (β = −0.054, t = 0.666, p = 0.506); therefore, H2 was not supported. Fairness matters on both fronts: it is positively related to SOCB (β = 0.304, t = 4.416, p < 0.001) and directly related to retention (β = 0.487, t = 5.254, p < 0.001), supporting H3 and H4. SOCB itself predicts retention (β = 0.290, t = 3.137, p = 0.002), which is in line with H5 (Table 6).
Table 6. Direct effects and indirect effects (path coefficients)
|
Direct Path |
β (Original) |
t |
p |
|
Grit → SOCB |
0.482 |
8.641 |
0 |
|
Grit → Retention |
−0.054 |
0.666 |
0.506 |
|
Fairness → SOCB |
0.304 |
4.416 |
0 |
|
Fairness → Retention |
0.487 |
5.254 |
0 |
|
SOCB → Retention |
0.29 |
3.137 |
0.002 |
|
Indirect path |
β (Original) |
t |
p |
|
Fairness → SOCB → Retention |
0.088 |
2.18 |
0.03 |
|
Grit → SOCB → Retention |
0.14 |
3.025 |
0.003 |
Mediation tests sharpen the pictures. Grit influenced retention indirectly through SOCB (β = 0.140, t = 3.025, p = 0.003), supporting H6. Fairness also exerted an indirect effect on retention via SOCB (β = 0.088, t = 2.180, p = 0.030), thus supporting H7. Taken together, these findings indicate full mediation for grit; its contribution to retention operates through the behaviors captured by SOCB, while fairness exhibits partial mediation, combining a sizable direct link to retention with a smaller, complementary pathway through SOCB.
The two practical takeaways are as follows. First, the magnitude of the grit → SOCB path is the largest among the predictors of SOCB, implying that hiring and development practices that cultivate perseverance and sustained interest are likely to translate into observable service citizenship behavior. Second, fairness is the most potent direct driver of retention in this model, and it nudges SOCB upward. Policies that strengthen interactional, procedural, and distributive fairness should, therefore, raise retention both directly and by encouraging pro-service discretionary behaviors. The results are shown in Figure 4.
The model is internally consistent and theoretically aligned: grit fuels how people go the extra mile for guests, and fairness keeps them in the organization. SOCB is a bridge between individual disposition and staying decisions. H1, H3, H4, H5, H6, and H7 were supported, whereas H2 was not (Figure 5).
Figure 4. Calculation results of variables’ relationships
Figure 5. Results of hypothesis testing
4.6 Discussion
The first set of findings concerns the role of grit in shaping SOCB. Using PLS-SEM, we found that grit significantly predicts SOCB in the hotel context, consistent with the notion that perseverance of effort and consistency of interest equip employees to sustain effortful, guest-facing behaviors. Operationally, gritty employees are those who are not discouraged by setbacks, set clear work targets, work hard, stay focused, complete what they start, persist under pressure, and display diligence during routine tasks. These attributes align closely with the elements of SOCB observed in hotels: consistently promoting products, services, and brand image; acting as communication bridges between the firm and guests; proactively improving service; and taking and participating in service decisions. Such dispositions are especially consequential in a business that operates continuously throughout the year and where high service standards are inseparable from the product itself. The positive grit–SOCB link echoes prior work that frames grit as a future-oriented motivation that gives meaning to sustained effort, a steadfast pursuit of goals aligned with one’s values [48], and a target for behavioral development rather than a fixed personality trait. Anchoring grit in Duckworth’s dimensions of perseverance and consistency [46], our evidence suggests that these qualities translate into extra-role service-enhancing actions that define SOCB in hospitality. This result is also compatible with research showing that grit reduces emotional exhaustion and bolsters willingness to go beyond formal role requirements [55] and with the broader characterization of gritty individuals as those who persist through challenges [56].
The second finding was counterintuitive. Grit does not exhibit a significant direct association with retention. Theory suggests that perseverance and long-term consistency should help employees withstand pressure, stay engaged, and remain with their employers. Prior studies linked grit to retention across multiple settings, positive affect at work, and stronger self-control [19, 50]. However, our data were collected in a sector deeply affected by the pandemic, and interviews with ten hotel leaders indicated that job insecurity and exogenous shocks overrode personal dispositions in shaping staying decisions. This aligns with evidence that job insecurity lowers retention intentions, even among otherwise resilient employees [57]. In other words, grit may allow employees to persist in their roles, yet macro shocks and structural constraints can have a direct effect on staying behavior in hospitality.
Fairness has emerged as a robust driver of SOCB. Employees’ perceptions that they are treated with courtesy and respect, are listened to, and are given time to voice concerns, alongside consistent, appropriate, and fitting procedures and reward allocations proportional to contribution, all foster the willingness to go beyond the call of duty in service. Interactional, procedural, and distributive fairness appears to reinforce the social and cognitive mechanisms that underpin discretionary and pro-service actions. This pattern is consistent with prior work linking justice perceptions to ethical conduct, justice climates, leader–member relations, and OCB [51]. It also matches the evidence that the three fairness forms are central predictors of OCB in organizational settings [44]. In hotels where codified procedures and interpersonal interactions with both managers and guests are frequent and visible, fairness seems to be a particularly salient antecedent of service-enhancing citizenship.
Fairness also has a direct positive effect on retention. In a sector characterized by long hours, atypical shifts, limited public holidays, and intense guest demands, fairness acts as a stabilizing force. Interactional, procedural, and distributive justice not only reduces the impulse to search for alternatives but also strengthens felt loyalty to the organization. Prior studies support this logic: interactional, procedural, and distributive fairness increase organizational loyalty, a core component of retention, and guest interactions perceived as fair by frontline employees elevate employee satisfaction [40]. The present results extend the evidence to Jakarta’s hotel workforce by underscoring fairness as an actionable lever for curbing turnover.
SOCB itself was positively associated with retention. Employees who willingly promote the hotel’s offerings and image, mediate communication with guests, propose improvements, and participate in decisions are more likely to speak positively about the organization, feel part of it, contribute beyond expectations, and intend to stay. This is compatible with prior research mapping different staying and leaving profiles, and showing that lower OCB is associated with higher quit intentions [37, 38]. In hospitality, where customer contact is continuous and reputational stakes are high, SOCB appears to anchor a virtuous cycle in which extra-role service behavior fosters attachment and strengthens staying decisions.
Mediation analyses clarified these relationships. Grit affects retention indirectly through SOCB. The absence of a direct grit–retention path coupled with a strong grit–SOCB link and a positive SOCB retention path indicates that grit operates by channeling perseverance and consistency into visible service citizenship, which then fortifies employees’ inclination to remain. This pattern reconciles the non-significant direct effect with the theory and prior findings that connect grit to job-relevant outcomes and OCB [19, 45, 46]. In practical terms, cultivating grit may not immediately reduce turnover unless organizations scaffold and recognize the service behaviors through which grit manifests.
Fairness exhibits both direct and indirect links to retention, the latter through SOCB. Procedural consistency is especially salient in hotels where standard operating procedures govern most tasks. When similar issues are handled inconsistently across employees, perceptions of unfairness quickly degrade the motivation to invest in discretionary effort and stay. Conversely, fair procedures and respectful interactions encourage SOCB, supporting retention. This dovetails with the literature indicating that fair treatment elicits OCB, while perceived injustice leads employees to withdraw citizenship and narrow efforts to minimize contractual obligations [44]. It also aligns with the evidence that justice perceptions shape performance, engagement, and counterproductive behaviors [58].
Click or tap here to enter the text. Dispositional perseverance and long-term consistency are valuable, but their impact on staying emerges through behaviors that managers and guests can see and reward. Organizational fairness works on two fronts: it directly anchors staying by signaling respect, transparency, and proportionality, and it indirectly strengthens staying by eliciting the very service citizenship behaviors that bind employees to the organization. The implications for hotel leaders are clear. Recruiting and developing grit can raise SOCB, particularly when paired with systems that channel persistence into guest-facing improvement. Building and enforcing interactional, procedural, and distributive fairness should be treated as foundational retention strategies, not only to reduce inequities but also to catalyze a service citizenship culture that makes it attractive.
In short, the hospitality workforce remains, above all, both human and relational. Grit helps employees sustain the extra effort that guests make. Fairness signals that an organization notices in return. SOCB sits between the two, translating personal resolve and fair contexts into an enduring attachment to the hotel.
Amid intensifying talent competition and pandemic-driven shocks that have depressed employee retention in Jakarta’s hotel sector, this study demonstrates that organizational justice and service-oriented citizenship are the most actionable levers for strengthening employees’ intentions to stay. Using survey data from 225 employees across three- to five-star hotels and PLS-SEM, we find that perceived fairness—interactional, procedural, and distributive—significantly increases both SOCB and retention, while SOCB itself positively predicts retention. Grit, conceptualized as perseverance of effort and consistency of interest, meaningfully enhances SOCB but does not directly influence retention; its effect operates indirectly through SOCB, suggesting that persistence translates into staying only when it manifests as visible, discretionary service behaviors that organizations value and reward. These results underscore the primacy of fair treatment and consistent procedures in a high-pressure, guest-facing industry and posit that SOCB is a critical behavioral conduit between individual dispositions and retention outcomes. Although conducted during an extraordinary period of environmental volatility, the findings offer clear guidance: hotels that invest in justice systems and cultivate a culture of service citizenship—while selecting and developing grit—are better positioned to retain talent in a persistently competitive labor market.
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