Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6, 989-1001 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i6.8006 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 24 March 2025; Revised: 22 May 2025; Accepted: 26 May 2025; Published: 12 June 2025 * Correspondence: jiafure.wan@dpu.ac.th The impact of social face consciousness on taking-charge behavior of employees: The mediating effect of thriving at work, and the moderating effect of ethical leadership and general self-efficacy Yuqi Li1, Jia-Fure Wang2* 1,2Chinese International College, Dhurakij Pundit University, Bangkok, Thailand; lyqvicky_DPU@163.com (Y.L.) jiafure.wan@dpu.ac.th (J.F.W.) Abstract: Under the dual impacts of digital transformation and the post-pandemic era, organizational sustainability increasingly relies on employees' proactive taking charge behavior. Against this backdrop, this study constructs a moderated mediation model based on proactive motivation theory within Chinese organizational contexts, aiming to uncover the influence mechanism of social face consciousness on employee taking charge behavior and its boundary conditions. Through purposive sampling of employees from multiple enterprises and institutions, 631 valid questionnaires were collected. Data were analyzed using structural equation modeling (SEM) and hierarchical regression analysis. The findings reveal that both face-gaining consciousness and face-losing consciousness positively influence thriving at work. Thriving at work significantly enhances taking charge behavior; face-gaining consciousness and face-losing consciousness directly and positively affect taking charge behavior; thriving at work mediates the positive relationships between face-gaining/face-losing consciousness and taking charge behavior; general self-efficacy positively moderates the effect of thriving at work on taking charge behavior. Keywords: Consciousness of social face, Employee taking charge behavior, Ethical leadership, General self-efficacy, thriving at work. 1. Introduction In digital transformation and the post-pandemic era, organizational sustainability increasingly depends on employees' proactive, responsible behaviours, known as Taking Charge Behavior (TCB) voluntary actions to improve processes and drive change [1]. In China’s Confucian-influenced culture, Consciousness of Social Face (CSF), the desire to gain face (DGF) or fear of losing face (FLF) is a critical but underexplored factor influencing such behaviours [2, 3]. While past studies have linked face consciousness to avoidance or unethical behaviour, few have examined its dual impact on positive behaviours like TCB. This study applies the Proactive Motivation Theory Parker, et al. [4] to propose that CSF drives TCB through different motivational paths: DGF promotes proactive responsibility for social recognition, while FLF may lead to defensive responsibility to avoid negative evaluation. Thriving at Work is a state of vitality, and learning may mediate this relationship by providing psychological resources [5]. Furthermore, Ethical Leadership (promotion- vs. prevention-focused) and General Self-Efficacy [6] are proposed as moderators that either strengthen or weaken the impact of CSF on TCB. By integrating cultural, psychological, and organizational factors, this study investigates how the dual dimensions of face consciousness affect responsible behaviour, the mediating role of thriving, and the moderating effects of ethical leadership and self-efficacy. Zhang, et al. [3] link face consciousness to positive organizational behaviours, they do not account for the potentially opposing effects of DGF and https://orcid.org/0009-0003-3075-2860 https://orcid.org/0009-0006-4112-6453 990 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 989-1001, 2025 DOI: 10.55214/25768484.v9i6.8006 © 2025 by the authors; licensee Learning Gate FLF. Moreover, although face consciousness is known to inhibit risk-taking, its potential to drive proactive behaviours like Taking Charge Behavior (TCB) remains underexplored. This study adopts a dual-dimensional lens to clarify these motivational dynamics. Furthermore, existing research tends to generalize ethical leadership benefits without considering its sub-dimensions differential impact. Promotion-focused leadership encourages proactivity, whereas prevention-focused leadership may suppress autonomy [7]. Although General Self-Efficacy (GSE) promotes proactive behaviour [6] its moderating effect on FLF-induced anxiety is unclear [8]. This study investigates how social face consciousness influences employees' taking charge behaviour, focusing on the mediating role of Work flourishing and the moderating effects of ethical leadership and general self-efficacy. The research addresses the following questions: 1. How does social face consciousness impact work flourishing? 2. How does Work flourishing affect taking charge behaviour? 3. Does Work flourishing mediate the link between social face consciousness and taking charge behaviour? 4. How does social face consciousness directly influence taking charge behaviour? 5. Does ethical leadership moderate the relationship between social face consciousness and work flourishing? 6. Does ethical leadership moderate the relationship between social face consciousness and taking charge behaviour? 7. Does general self-efficacy moderate the relationship between Work flourishing and taking charge behaviour? This study investigates how social face consciousness, specifically the desire to gain face (DGF) and fear of losing face (FLF), influences employees' taking charge behaviour (TCB), with Work flourishing as a mediator and ethical leadership and general self-efficacy (GSE) as moderators. The key objectives are: (1) to test the direct effects of DGF and FLF on both Work flourishing and TCB; (2) to assess whether Work flourishing mediates the relationship between face-related motivations and TCB; (3) to examine how promotive and prohibitive ethical leadership, along with GSE, moderate the effects of DGF and FLF on both Work flourishing and TCB; and (4) to provide practical strategies for fostering TCB by managing face-related motivations, enhancing flourishing, and leveraging leadership styles and GSE. This study introduces three key innovations: First, it differentiates between the desire to gain face (intrinsic motivation) and fear of losing face (extrinsic motivation), providing a clearer understanding of proactive behaviours. Second, it examines the dual impact of promotive and prohibitive ethical leadership on taking charge behaviour, highlighting its motivating and inhibiting effects. Third, it applies Proactive Motivation Theory, offering a new theoretical perspective that enhances understanding of the mechanisms driving taking charge behaviour beyond traditional frameworks. This study deepens theoretical understanding by distinguishing between the desire to gain face and the fear of losing face as "want-to-do" and "have-to-do" motivations behind taking charge behaviour, addressing the dual nature of face consciousness [3]. It also explores the contrasting effects of promotive and prohibitive ethical leadership on this behavior [7]. It introduces the Proactive Motivation Theory to explain how cultural pressure can drive proactive responsibility [9]. Practically, the findings guide organizations to harness face culture through recognition-based incentives, develop ethical leadership to steer image-driven behaviour positively and enhance general self-efficacy via training and challenging tasks to transform pressure into initiative. 991 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 989-1001, 2025 DOI: 10.55214/25768484.v9i6.8006 © 2025 by the authors; licensee Learning Gate 2. Literature Review 2.1. Proactive Motivation Theory Proactive Motivation Theory, proposed by Parker, et al. [4] explains proactive behaviour as a deliberate, goal-oriented choice driven by intrinsic motivation. It identifies three key conditions: "can do" (belief in capabilities like self-efficacy), "reason to" (perceived value of goals), and "energized to" (positive emotions and vitality) [10]. This theory offers a comprehensive framework beyond the traditional stimulus-response model, explaining complex behaviours like innovation and proactive actions in the workplace. Research on the theory spans five areas: personal factors, job-related factors, leadership, organizational environment, and cross-cultural studies. Self-efficacy, a core variable in the "can do" pathway, positively influences proactive behaviour [11]. Extraversion and openness promote proactivity, while neuroticism suppresses it [12]. Proactive personalities seek environmental change [13]. A learning goal orientation enhances "reason to" motivation, fostering innovation [14] and strong moral values drive proactive actions [15]. 2.2. Social Face Consciousness Social face consciousness refers to how individuals perceive their self-image through social interactions, encompassing self-esteem and dignity. It comprises two dimensions: the desire to gain face (enhancing social reputation) and the fear of losing face (avoiding negative evaluation) [3]. This two- dimensional model is widely validated [16] and reflects social and psychological constructs. Initially treated as unidimensional, face consciousness is now measured by scales distinguishing proactive face- gaining and defensive face-protection motives and adopted an 11-item, 5-point Likert scale [3]. Antecedents include cultural collectivism, which increases fear of losing face [17] and individual traits like self-esteem and neuroticism [18]. Organizational competitive evaluation also intensifies face- conscious behaviour [19]. Consequences involve luxury consumption to gain face [20] conflict avoidance due to fear of losing face [21] workplace silence and help avoidance [22] and strict conformity to norms to maintain image [23]. 2.3. Work Thriving Work thriving is a sustained positive psychological state at Work, marked by a sense of learning and vitality [5]. It reflects ongoing self-development through in-role and extra-role behaviours [24] and is influenced by cognitive, emotional, and behavioural engagement [25]. This study defines Work thriving as a state where individuals maintain vitality while actively learning and engaging in Work [24]. It is commonly measured using a two-dimensional scale of learning and vitality developed by [5] and later refined by Porath, et al. [24] into a 10-item scale with high reliability (α = 0.87). Antecedents include psychological capital, proactive personality, supportive leadership, and job resources such as autonomy and task variety [26]. Empowering and inclusive leadership also enhance thriving through trust and fairness [27]. Organizational factors like flexible work arrangements and developmental HR practices further support thriving. However, resource overuse can be detrimental and leads to higher task performance, innovation, and citizenship behaviours while reducing burnout and turnover intention [28-30]. It also mediates relationships between psychological safety and engagement and between support and engagement [31] with proactive personality strengthening its link to career adaptability [26]. 2.4. Employee Responsibility Behavior Employee responsibility behaviour is a proactive form of work behaviour where employees voluntarily initiate actions to improve processes and organizational effectiveness [1]. Grounded in role theory and self-determination theory Deci and Ryan [32] it goes beyond formal roles to drive 992 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 989-1001, 2025 DOI: 10.55214/25768484.v9i6.8006 © 2025 by the authors; licensee Learning Gate constructive change, distinct from organizational citizenship behaviour, which focuses on interpersonal support [4]. This study adopts [1] definition, measuring it using Li, et al. [33] 10-item scale (α = 0.93), with items like “I often suggest constructive recommendations to improve internal operations” on a five- point scale. Antecedents include individual factors such as self-efficacy [34] sense of responsibility [1] psychological collectivism [35] and role efficacy [36] as well as contextual factors like organizational support, fairness, team exchange quality, and leader support [37, 38]. Positive outcomes include higher job satisfaction [39] innovation, leadership expression [40] work-family enrichment and performance gains [41, 42]. However, under low autonomy, responsible behaviour may cause energy depletion and adverse peer reactions such as jealousy, especially in less proactive teams [40, 43]. 2.5. Ethical Leadership Ethical leadership is a leadership style rooted in social learning theory Bandura and Wessels [6] and moral identity theory Aquino and Reed II [44] where leaders model ethical behaviour, reinforce norms, and promote values to foster an ethical climate within the organization [45]. Defined as the leader's display of norm-compliant behaviour and encouraging such behaviour among subordinates through communication, reinforcement, and decision-making, ethical leadership has evolved into a two- dimensional model: promotive and prohibitive. Promotive ethical leadership involves encouraging and rewarding ethical conduct (e.g., setting moral examples), while prohibitive ethical leadership focuses on deterring unethical behaviour through monitoring and disciplinary actions. The Ethical Leadership Scale by Baron and Kenny [45] initially measured ethical leadership with 10 items (α = 0.92), while Bush, et al. [46] refined it into 12 items divided across promotive and prohibitive dimensions (α = 0.94).Antecedents of ethical leadership include personal traits like integrity, responsibility, and communication ability [47]. Its outcomes are diverse and largely positive, enhancing followers' moral identity [48] job satisfaction, affective commitment; organizational citizenship behaviour [49] employee voice and performance [50] and reducing misconduct and deviance [51, 52]. 2.6. General Self-Efficacy General self-efficacy refers to an individual’s broad belief in their ability to handle diverse tasks and challenges across situations [53]. Rooted in social cognitive theory, it influences behaviour through cognitive, motivational, emotional, and selective mechanisms [6]. Unlike task-specific self-efficacy, it reflects stable cross-situational confidence and adaptability, functioning as a meta-competence that supports resource integration and resilience [54, 55]. This study adopts Chen, et al. [54] definition and 8-item scale, featuring statements like “When facing difficult tasks, I am confident in completing them,” measured on a five-point Likert scale (Cronbach’s α = 0.85). General self-efficacy is positively associated with personality traits such as extraversion, conscientiousness, and openness and can be enhanced through creativity training, leadership, autonomy, and social support [56, 57]. It significantly predicts creativity, work performance, persistence, and adaptability in complex environments [11]. 2.7. Research Hypotheses General self-efficacy refers to an individual’s broad belief in their ability to handle diverse tasks and challenges across situations [6]. Rooted in social cognitive theory, it influences behaviour through cognitive, motivational, emotional, and selective mechanisms [6]. Unlike task-specific self-efficacy, it reflects stable cross-situational confidence and adaptability, functioning as a meta-competence that supports resource integration and resilience [55]. This study adopts Chen, et al. [54] definition and 8- item scale, featuring statements like “When facing difficult tasks, I am confident in completing them,” measured on a five-point Likert scale (Cronbach’s α = 0.85). General self-efficacy is positively associated with personality traits such as extraversion, conscientiousness, and openness and can be enhanced 993 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 989-1001, 2025 DOI: 10.55214/25768484.v9i6.8006 © 2025 by the authors; licensee Learning Gate through creativity training, leadership, autonomy, and social support [56]. It significantly predicts creativity, work performance, persistence, and adaptability in complex environments [6]. 2.8. Research Framework This study examines social face consciousness as the independent variable and employee responsibility behaviour as the dependent variable, with Work flourishing as a mediator and ethical leadership and general self-efficacy as moderators. Based on relevant literature and proactive motivation theory, the research framework is illustrated in Figure 1. Figure 1. Research Framework. 3. Research Methodology 3.1. Research Population and Sampling Method This study focuses on enterprises and institutions in Shaanxi Province, China, selected for its leading role in the region's economy, ranking first in GDP among the five Northwestern provinces in 2023, and its emphasis on high-tech industries, modern services, and innovation. An online questionnaire will be created on the Wenjuanxing platform and distributed via WeChat, QQ, DingTalk, and other channels to minimize costs, save time, and streamline data collection. Wenjuanxing simplifies the survey process for participants and enables real-time monitoring of responses. Purposive sampling will target a specific sample population based on relevant characteristics, suitable for cases where the population's boundaries are unclear, or resources are limited. Although purposive sampling does not follow a strict principle and results cannot be generalized, it offers valuable insights. The sample size is determined based on Wu [58] recommendation, using a 1:10 ratio of survey items to the pretest sample size, with the questionnaire including 55 items. Therefore, the study aims to collect at least 631 valid responses by distributing 650 questionnaires to account for invalid replies. 3.2. Research Design This study employs a quantitative research approach using a questionnaire survey to gather data from organizational employees. The aim is to use statistical analysis to infer insights about the broader population by measuring a large sample of employees and identifying patterns in their responses. Based on established scales, the questionnaire uses a 5-point Likert scale to measure variables such as social face consciousness, work flourishing, responsibility-taking behaviour, ethical leadership, and general 994 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 989-1001, 2025 DOI: 10.55214/25768484.v9i6.8006 © 2025 by the authors; licensee Learning Gate self-efficacy. Data will be collected through the Wenjuanxing platform, ensuring efficient distribution and screening for invalid responses. Statistical analysis will be conducted using SPSS 25.0 and AMOS 24.0 to perform descriptive statistics, reliability, validity, and regression analyses. The study will examine the relationships between the five key variables, determine their correlation coefficients, and explore the direction and strength of these relationships. The findings will inform the research questions and offer actionable insights to address practical issues businesses and organizations face. 3.3. Research Tools This study uses established scales on a 5-point Likert scale (1–5). Social face consciousness Zhang, et al. [3] includes 11 items across two dimensions: desire to gain face (e.g., “I want others to think I do better than most people") and fear of losing face (e.g., "I try to avoid letting others think I do not understand"). Thriving at Work [24] measures learning and vitality with items like "I often find myself learning new things." An employee taking charge behaviour [1] assesses proactive efforts to improve the organization. Ethical leadership [46] covers promotive and preventive dimensions, e.g., "My leader encourages ethical behaviour." General self-efficacy [54] evaluates confidence in handling tasks, e.g., “I am confident I can accomplish difficult tasks.” All variables are measured using these validated scales on a 5-point Likert scale. 3.4. Data Analysis Method The questionnaire was distributed to employees, who then shared it with colleagues and friends. Invalid responses were removed based on identical answers, unrealistic completion times (established via a 20-person pretest), contradictory reverse-coded items, and participants under 18 or holding "Senior Executive" positions. Valid data were analyzed using SPSS 25.0 and AMOS 24.0. SPSS handled common method bias (via Harman's single-factor test, with a 40% variance threshold), descriptive statistics, reliability (Cronbach’s alpha >0.8 excellent, >0.5 acceptable), correlation, and regression analyses. AMOS was used for confirmatory factor analysis to test model validity, with AVE >0.5 indicating good validity. Regression assessed variable impacts, with R² showing explained variance, significance set at p < 0.05, and VIF <10 confirming no multicollinearity. 4. Results and Analysis 4.1. Descriptive Statistical Analysis Table 1 presents the mean, standard deviation, skewness, and kurtosis for each variable in the study. The mean scores for all variables desire to gain face (M = 3.309), fear of losing face (M = 3.490), Work flourishing (M = 3.495), employee taking charge behaviour (M = 3.582), promotive ethical leadership (M = 3.602), prohibitive ethical leadership (M = 3.365), and general self-efficacy (M = 3.697) are above 3, indicating generally high levels across all measured constructs among respondents. Table 1. Descriptive Analysis. Variable Mean Standard Deviation Skewness Kurtosis Desire to Gain Face 3.309 0.756 -0.173 -0.147 Fear of Losing Face 3.490 0.632 -0.772 1.473 Work Flourishing 3.495 0.421 -0.731 0.831 Employee Taking Charge Behavior 3.582 0.621 -0.403 0.729 Promotive Ethical Leadership 3.602 0.655 -0.436 0.653 Prohibitive Ethical Leadership 3.365 0.703 -0.234 0.295 General Self-Efficacy 3.697 0.592 -0.652 1.522 4.2. Socio-Economic Factor Analysis As shown in Table 2, the sample consisted of 55.47% females and 44.53% males. Most respondents 995 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 989-1001, 2025 DOI: 10.55214/25768484.v9i6.8006 © 2025 by the authors; licensee Learning Gate were aged 18–35 years (64.03%), held a bachelor’s degree or higher (90.17%), and were primarily general staff (61.01%), followed by junior and middle management. This demographic distribution reflects a relatively young, well-educated workforce suitable for examining workplace behaviour and psychological constructs. Table 2. Socio-Economic Factor Analysis. Variable Option Frequency Percentage (%) Gender Male 281 44.53 Female 350 55.47 Age 18–25 years 174 27.58 26–35 years 230 36.45 36–45 years 135 21.39 46 years and above 92 14.58 Education Level High school or below 18 2.85 Associate degree 44 6.97 Bachelor's degree 394 62.44 Master's or above 175 27.73 Position General staff 385 61.01 Junior management 122 19.33 Middle management 124 19.65 4.3. Common Method Bias Test Harman's single-factor test was conducted to assess the presence of standard method bias due to the concentration of participants primarily in Shaanxi Province, China. An exploratory factor analysis (EFA) was applied to all items in the study's constructs. As presented in Table 3, the unrotated factor analysis extracted seven factors with eigenvalues greater than 1. The first factor accounted for 29.614% of the total variance, below the critical threshold of 40%. This indicates that no single factor dominates the variance, suggesting the absence of significant standard method bias in the dataset and supporting the validity of the data for further analysis. Table 3. Harman’s Single-Factor Test. Component Initial Eigenvalue (Total) Extracted Load Square Sum (Variance %) 1 15.103 29.614 2 4.469 8.763 3 4.307 8.445 4 2.814 5.518 5 2.669 5.234 6 2.242 4.395 7 1.492 2.925 8 0.933 1.829 9 0.872 1.710 10 0.853 1.673 11 0.731 1.434 12 0.713 1.399 13 0.691 1.356 14 0.650 1.274 15 0.601 1.179 16 0.573 1.123 17 0.545 1.069 18 0.519 1.017 19 0.515 1.009 20 0.492 0.966 996 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 989-1001, 2025 DOI: 10.55214/25768484.v9i6.8006 © 2025 by the authors; licensee Learning Gate 21 0.477 0.935 22 0.460 0.902 23 0.439 0.861 24 0.421 0.825 25 0.411 0.807 26 0.402 0.788 27 0.399 0.783 28 0.384 0.752 29 0.366 0.718 30 0.352 0.690 31 0.347 0.681 32 0.336 0.658 33 0.325 0.638 34 0.304 0.596 35 0.297 0.582 36 0.293 0.575 37 0.275 0.540 38 0.262 0.514 39 0.254 0.498 40 0.245 0.480 41 0.241 0.472 42 0.229 0.449 43 0.224 0.439 44 0.221 0.433 45 0.209 0.409 46 0.200 0.393 47 0.192 0.377 48 0.185 0.363 49 0.177 0.348 50 0.155 0.305 51 0.131 0.257 Note: This table presents the results of the Harman single-factor analysis. Compiled by this study. 4.4. Reliability Analysis Reliability refers to the consistency of a measurement. This study used Cronbach's α to assess the internal consistency of variables such as the desire to gain face, fear of losing face, work prosperity, employee responsibility behaviour, promotive ethical leadership, prohibitive ethical leadership, and general self-efficacy. According to [59]. Cronbach's α above 0.8 indicates good reliability. The 5-point Likert scale was used for measurement. As shown in Table 4, all variables had Cronbach's α values greater than 0.75, indicating high reliability and strong internal consistency, supporting further analysis. Table 4. Reliability Analysis. Variable Number of Items Cronbach’s α Desire to Gain Face 6 0.892 Fear of Losing Face 5 0.872 Work Prosperity 10 0.785 Employee Responsibility Behavior 10 0.927 Promotive Ethical Leadership 6 0.900 Prohibitive Ethical Leadership 6 0.890 General Self-Efficacy 8 0.917 997 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 989-1001, 2025 DOI: 10.55214/25768484.v9i6.8006 © 2025 by the authors; licensee Learning Gate 4.5. Confirmatory Factor Analysis (CFA) Confirmatory Factor Analysis (CFA) tests hypotheses based on established factor models using actual data. If the model fits the data well, the hypothesis is considered valid. This study employs CFA to assess the degree of fit between the data and the scale model using mature, widely recognized, widely-recognized measurement scales. The model fit is evaluated against the criteria in Table 5, as proposed by Wu [60]: Table 5. Fit Indices for Confirmatory Factor Analysis (CFA). Measurement Index Fit Criteria c²/df Chi-Square/df Ratio 1-5 RMSEA Root Mean Square Error of Approximation <0.05 (Good fit), <0.08 (Reasonable fit) SRMR Standardized Root Mean Square Residual <0.05 (Good fit), <0.08 (Reasonable fit) GFI Goodness of Fit Index >0.9 AGFI Adjusted Goodness of Fit Index >0.9 NFI Normed Fit Index >0.9 CFI Comparative Fit Index >0.9 The questionnaire data were analyzed using structural equation modelling, with the fit results shown in Table 6. The chi-square/df ratio is 2.900 (<5), RMSEA is 0.055 (<0.08), and SRMR is 0.044 (<0.05), all indicating acceptable model fit. The incremental fit indices, NFI (0.846), RFI (0.836), CFI (0.893), IFI (0.893), and TLI (0.886) are close to or exceed acceptable thresholds. These results confirm that the model fits the data reasonably well and explains the observed relationships appropriately. Table 6. Overall Model Fit Results. Fit Index χ²/df RMSEA SUMMER NFI RFI CFI IFI TLI Model 2.900 0.055 0.044 0.846 0.836 0.893 0.893 0.886 4.6. Convergent Validity Convergent validity assesses how well items of the exact construct correlate. It is evaluated using standardized factor loadings (≥0.5), Average Variance Extracted (AVE ≥ 0.5), and Composite Reliability (CR ≥ 0.6). As shown in Table 7, all constructs such as Desire to Gain Face, Fear of Losing Face, Thriving at Work, Employee Responsible Behavior, Promotive and Preventive Ethical Leadership, and General Self-Efficacy that exhibit AVE values above 0.5 and CR values above 0.6, confirming good convergent validity and internal consistency. All standardized factor loadings are acceptable, indicating strong item-construct relationships. 998 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 989-1001, 2025 DOI: 10.55214/25768484.v9i6.8006 © 2025 by the authors; licensee Learning Gate Table 7. Convergent Validity. Variable Item Code Estimate AVE CR Desire to Gain Face GF1 0.873 0.595 0.897 GF2 0.866 GF3 0.718 GF4 0.708 GF5 0.725 GF6 0.716 Fear of Losing Face LF1 0.834 0.585 0.875 LF2 0.683 LF3 0.811 LF4 0.762 LF5 0.723 Thriving at Work TW1 0.837 0.563 0.855 TW2 0.843 TW3 0.696 TW4 -0.602 TW5 0.710 TW6 0.828 TW7 0.726 TW8 -0.577 TW9 0.807 TW10 0.818 Employee Responsible Behavior TC1 0.818 0.573 0.930 TC2 0.853 TC3 0.673 TC4 0.790 TC5 0.748 TC6 0.759 TC7 0.724 TC8 0.676 TC9 0.719 TC10 0.787 Promotive Ethical Leadership PM1 0.677 0.604 0.901 PM2 0.763 PM3 0.764 PM4 0.859 PM5 0.794 PM6 0.795 Preventive Ethical Leadership PV1 0.749 0.576 0.891 PV2 0.710 PV3 0.814 PV4 0.724 PV5 0.793 PV6 0.761 General Self-Efficacy SE1 0.814 0.586 0.919 SE2 0.735 SE3 0.755 SE4 0.714 SE5 0.827 SE6 0.796 SE7 0.725 SE8 0.749 999 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 989-1001, 2025 DOI: 10.55214/25768484.v9i6.8006 © 2025 by the authors; licensee Learning Gate 5. Conclusion This study explored the influence of face consciousness, specifically, the desire to gain face and the fear of losing face on employee responsible behaviour, with general self-efficacy as a potential moderating variable. The results revealed that both the desire to gain face and the fear of losing face significantly influence responsible behaviour among employees. However, while general self-efficacy positively impacted employee responsibility, its moderating role in the relationship between face concerns and responsible behaviour was not supported. The findings indicate that employees motivated by face concerns are more likely to engage in responsible behaviour, regardless of their level of self- efficacy. These results contribute to a deeper understanding of culturally rooted psychological motivations in the workplace and underscore the importance of recognizing face dynamics in organizational behaviour research. 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