Next Article in Journal
Blockchain Effects and Investment Strategies in the Maritime Supply Chain Under Perishable Goods Loss
Previous Article in Journal
Estimation of CO2 Emissions in Transportation Systems Using Artificial Neural Networks, Machine Learning, and Deep Learning: A Comprehensive Approach
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Systems
Volume 13
Issue 3
10.3390/systems13030195
systems-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Integrating Cultural and Emotional Intelligence to Examine Newcomers’ Performance and Error Reduction: A Moderation–Mediation Analysis

by
Tesfaye Agafari Bafa
,
Mingyu Zhang
* and
Chong Chen
School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
*
Author to whom correspondence should be addressed.
Systems 2025, 13(3), 195; https://doi.org/10.3390/systems13030195
Submission received: 17 January 2025 / Revised: 23 February 2025 / Accepted: 7 March 2025 / Published: 11 March 2025
(This article belongs to the Section Systems Practice in Social Science)
Browse Figures
Versions Notes

Abstract

:
Built on the Conservation of Resources (COR), Multiple Intelligence (MI), and Social Exchange (SET) theories, this study investigates how cultural intelligence, emotional intelligence, and perceived organizational support influence newcomers’ task performance and error reduction. The research also explores the mediating effects of emotional exhaustion and the moderating effects of cognitive diversity. Data were collected from 476 participants in organizations employing newcomers, using census, stratified, and simple random sampling techniques. Structural Equation Modeling (SEM) was employed to test the research hypotheses. The results reveal that higher levels of cultural and emotional intelligence are negatively associated with emotional exhaustion, while an increase in perceived organizational support reduces emotional exhaustion. Emotional exhaustion was found to be linked to higher error rates and lower task performance. The mediation analyses showed that emotional exhaustion mediated the relationship between cultural intelligence, emotional intelligence, and perceived organizational support and both task performance and error reduction. Furthermore, cognitive diversity moderated the relationships between cultural intelligence and emotional exhaustion, as well as between emotional intelligence and emotional exhaustion. These findings underscore the critical roles of cultural and emotional intelligence, along with organizational support, in mitigating emotional exhaustion, reducing errors, and enhancing task performance, while emphasizing the importance of cognitive diversity in shaping organizational outcomes.

1. Introduction

The hospitality industry is currently grappling with the challenge of attracting and retaining skilled, creative, and customer-centric employees [1,2]. This issue is particularly pronounced in developing countries, where employees are often vulnerable to physical and emotional harm, workplace hazing, moral disengagement, humiliation, and perceived low social status [3,4,5,6]. Despite these challenges, the value of newcomers in the hospitality sector is widely acknowledged, as they bring valuable skills and unique experiences [7,8]. To maintain high service standards and deliver exceptional customer-centric service, it is critical for hospitality organizations to effectively integrate and support newcomers in adjusting to their new work environment. Successfully navigating steep learning curves and thriving in their roles is crucial for both individual and organizational success [9,10].
A broad range of research has explored various factors that influence newcomers’ task performance and error rates, such as socialization [11,12], job role-related stress, conflict, work attitudes [13], hazing, moral disengagement, knowledge sharing [14], job clarity, and supervisor support [15,16]. Studies have also examined job satisfaction, as well as psychological and emotional factors [17]. Additionally, the dynamics of leadership and organizational climate, particularly in leader–member exchanges and co-worker interactions, have been shown to influence task performance and reduce errors [18]. However, these studies often fail to adequately address the complexity of transitioning newcomers from outsiders to well-adjusted insiders, particularly within the hospitality industry context.
Despite the growing body of research on international businesses and expatriate workers, the application of Multiple Intelligences (MIs) within the hospitality sector remains relatively underexplored. While existing studies primarily investigate the effects of cultural intelligence (CQ) and emotional intelligence (EI) on expatriates’ effectiveness in terms of behavioral and attitudinal outcomes in international business [19], there remains a significant gap in examining how these intelligences specifically affect hospitality newcomers’ performance. The unique challenges that newcomers face in culturally diverse environments in the hospitality industry present a compelling reason for further investigation [20].
As an illustration, Karroub, Hadineja, and Mahmoudzadeh [21] explored the impact of a service provider’s cultural intelligence on consumer satisfaction, as well as its role in the cross-cultural adjustment of tour operators. However, there exists a notable gap in research addressing how culturally intelligent hospitality newcomers perform their tasks with minimal errors. Similarly, although hospitality employees are frequently characterized as engaging in “emotional labor”, the influence of emotional intelligence on task performance and error reduction remains underrepresented in the hospitality research domain [22]. Early studies by Prentice [23] and Sigala and Chalkiti [24] are among the few attempts to investigate the relationship between emotional intelligence, organizational creativity, and performance. Nevertheless, these authors argue that research specifically focusing on newcomers and their application of emotional intelligence in the hospitality industry remains scarce and warrants further attention [25,26,27,28].
Methodologically, the study employed scientometrics to systematically gather relevant literature on newcomers’ Learning Change Engagement (LCE) and identify the key emerging trends and research hotspots. Through techniques such as reference network analysis and keyword mutation, several significant hotspots and trends were identified, addressing a gap in systematic research on LCE-related findings through academic visualization. These findings not only contribute to the theoretical development of LCE but also provide new insights into its evolution [29].
From both theoretical and methodological perspectives, the authors conclude that there is a need to extend and develop a robust theoretical and conceptual model that can address the inconsistencies, conflicting findings, and conceptual ambiguities across different geographic and organizational contexts. Furthermore, there has been a quandary of employing moderators, mediators’ predictors, and predicted variables interchangeably. This serves as another rationale for the need for further research to develop a comprehensive theoretical and conceptual model that can robustly explain newcomers’ task performance and error reduction in hospitality research [30]. Hence, this article aims to examine how cultural intelligence, emotional intelligence, and perceived organizational support influence newcomers’ task performance and error reduction by extending the Conservation of Resources, Multiple Intelligence, and Social Exchange theories. Additionally, it explores the mediating roles of emotional exhaustion and employee empowerment, along with the moderating effects of cognitive diversity and social support.

2. Theoretical Foundation and Hypothesis Development

2.1. Theoretical Foundations

This study integrates three prominent theoretical frameworks, Social Exchange Theory (SET), Gardner’s Theory of Multiple Intelligences (MI), and Conservation of Resources (COR) theory, to explore the effects of cultural intelligence, emotional intelligence, and perceived organizational support on hospitality newcomers’ task performance and error reduction [31]. Additionally, it investigates the moderating effects of cognitive diversity and the mediating role of emotional exhaustion. Among these frameworks, SET serves as the primary foundation, positing that the interactions and exchanges between individuals, groups, and organizations are central to understanding the dynamics of power, influence, and mutual benefit [32]. SET has been extensively applied to examine employees’ perceptions and reactions toward their organizations [33,34], the benefits they receive, and the support provided by supervisors [35]. In hospitality research, SET has been particularly instrumental in exploring the relationship between employees and their organizations, providing valuable insights into how social exchanges influence both individual and organizational outcomes [36].
Building on this foundational framework, Gardner’s Theory of Multiple Intelligences (MI) enhances our understanding of how cultural and emotional intelligence contribute to newcomers’ emotional exhaustion [37]. According to MI theory, individuals possess a range of intelligences that allow them to adapt to various work-related challenges [22]. Newcomers who exhibit cultural and emotional intelligence are better equipped to navigate the complexities of their work environments, particularly in managing interpersonal interactions, which helps reduce emotional exhaustion. By developing these intelligences, newcomers are more likely to engage in behaviors that foster empowerment, leading to improved task performance and reduced workplace stress.
Finally, COR theory emphasizes the role of resource management in coping with stress and burnout. COR theory suggests that individuals are motivated to conserve, protect, and acquire resources, as both actual and potential losses of resources can lead to stress [38]. This framework is particularly pertinent for newcomers, who often face resource scarcity during the adjustment period in a new role. Due to their limited tenure in the organization, newcomers may not yet have access to resources such as recognition or support that enable them to fulfill their responsibilities effectively. This lack of resources can increase stress levels and hinder performance. COR theory also introduces the concept of the resource gain paradox, which posits that rapid replenishment of resources is essential for preventing burnout and maintaining optimal performance [39]. In this regard, COR theory offers critical insights into how newcomers manage available resources, with implications for error reduction and performance enhancement [37].

2.1.1. Cultural Intelligence (CQ) and Emotional Exhaustion (EEX)

Cultural intelligence (CQ) denotes an individual’s ability to recognize, adapt to, and leverage diversity through the collection and processing of information and the implementation of effective measures [40]. Initially derived from Multiple Intelligence {MI}, Earley and Stanford [31] conceptualized cultural intelligence (CQ) as a four-factor construct, consisting of knowledge, metacognition, motivation, and behavior. However, this four-factor model has faced criticism due to conflicting findings regarding the relationship between each dimension of the construct and its predicted variables [41]. While earlier studies have investigated each dimension independently, many have emphasized the importance of considering CQ as an integral construct. As evidenced by Thomas et al. [42], CQ was proposed as a unified construct that serves as an antecedent to task performance, emotional exhaustion, and error reduction. For this study, we adopt CQ as a singular construct, as robust meta-analytic evidence supports its conceptualization in this manner [38].
The interplay between cultural intelligence (CQ) and emotional exhaustion (EEX) suggests that individuals with high cultural intelligence are adept at engaging in gap-bridging behaviors, enabling them to proactively integrate into groups and support fellow members [43]. According to Richter et al. [44], individuals with high cultural intelligence (CQ) can easily navigate to access information, connect to co-workers, and take part in decision-making processes. Stoermer, Davies, and Froese [45] further assert that elevated CQ enhances individuals’ sense of fit within their environment and strengthens their cultural competencies [46]. Moreover, individuals with higher CQ tend to be more active and engaged in knowledge sharing and socialization within culturally diverse work climates, which facilitates their ability to understand and effectively navigate diverse settings [47,48,49].
Furthermore, Ang et al. [41] assert that higher cultural intelligence (CQ) assists individuals to overcome feelings of confusion, frustration, and stress. Mustafa et al. [50] argued that culturally adaptable employees experience lower levels of emotional exhaustion and are better equipped to navigate complex interpersonal dynamics. This adaptability fosters a sense of belonging and reduces feelings of isolation, which are central to the newcomers’ well-being [50]. In addition, individuals with higher cultural intelligence (CQ) are better prepared to confront uncertainty in complex work environments, such as those found in the hospitality industry [51]. Accordingly,
H1. 
Higher cultural intelligence (CQ) is significantly associated with lower emotional exhaustion (EEX).

2.1.2. Emotional Intelligence (EI) and Emotional Exhaustion (EEX)

Emotional intelligence (EI) refers to the ability to recognize, understand, and regulate one’s own emotions, as well as those of others, to guide thinking and behavior [52]. In the context of hospitality, EI enables employees to manage their emotions and navigate the emotional dynamics of others, particularly in high-pressure work environments [22].
Research has established that emotional intelligence (EI) significantly impacts various outcomes, including candidness, stress coping, emotional self-concept, empathy, and mood regulation [53]. These studies affirm the positive relationship between EI and workplace success, job satisfaction, performance [54], organizational commitment [55], and organizational citizenship behaviors [56]. Moreover, employees with higher EI tend to respond proactively and perform better than their lower-EI counterparts in stressful situations [57]. Empirical evidence focusing on newcomers suggests that the emotional resources of employees are often depleted during the transition into a new organization, leading to reduced performance and difficulty adapting to new roles. However, newcomers with higher EI are better equipped to cope with the stressors of role adjustment and can effectively employ adaptive strategies to manage emotional exhaustion [58]. Accordingly,
H2. 
Higher emotional intelligence (EI) is significantly associated with a reduction in emotional exhaustion (EEX).

2.1.3. Perceived Organizational Support (POS) and Emotional Exhaustion (EEX)

Grounded in SET, POS is defined as employees’ perceptions of the degree to which their organization values their contributions and cares about their well-being. This perception suggests that when employees feel their efforts are adequately rewarded, they are less likely to experience emotional exhaustion [59]. Management literature recognizes that POS extends to encompass all forms of support employees expect to receive from their organization to facilitate their job performance and socio-economic well-being [60].
Additionally, research highlights that POS plays a crucial role in mitigating the negative effects on the emotional well-being of hospitality employees [61]. Specifically, POS reduces feelings of isolation and unfriendliness, thereby contributing to lower emotional exhaustion. In other words, when employees perceive that their efforts are rewarded and they are treated fairly, they are less likely to experience emotional exhaustion (EEX) [62]. Accordingly,
H3. 
Perceived organizational support (POS) is negatively correlated with newcomers’ emotional exhaustion (EEX).

2.1.4. Emotional Exhaustion (EEX), Task Performance (TP), and Error Reduction (ER)

Existing empirical evidence indicates that employees experiencing higher levels of emotional exhaustion (EEX) often struggle to perform their job responsibilities, leading to decreased performance and negative job outcomes [63,64]. According to COR theory, exhaustion depletes valuable personal resources, leaving employees with insufficient capacity to effectively manage the stressors they face [65]. Employees who become disillusioned with their interactions and experience frustration are less likely to perform tasks effectively, which can increase errors and hinder job performance [66].
In the context of this research, consistent with the tenets of COR theory, emotional exhaustion (EEX) arises when newcomers encounter a depletion of personal resources, leaving them with insufficient capacity to effectively manage the stressors they encounter [67]. As a result, these employees become scared and perturbed by their relationship with their organizations. Consequently, they are more likely to commit errors and lose a sense of self-control [67,68]. Accordingly,
H4. 
High emotional exhaustion (EEX) is negatively correlated with task performance (TP).
H5. 
High emotional exhaustion is negatively associated with error reduction (ER).

2.1.5. The Moderating Role of Cognitive Diversity (KD)

Cognitive diversity describes the organizational workforce variation in employees’ proficiency, experiences, talents, knowledge, beliefs, values, and ways of thinking [2,69]. It is considered as the idiosyncratic patterns of one’s information processing, beliefs, context-specific knowledge, and localized values and beliefs. Despite scant empirical evidence, some studies have highlighted the buffering role of cognitive diversity in mitigating the negative effects of cultural misunderstandings or conflicts that often arise in diverse teams [70]. The results affirmed that when team members possess varied cognitive styles, they are better equipped to navigate cultural differences, which results in improved communication and collaboration. Moreover, teams characterized by high cognitive diversity may develop stronger cultural intelligence, as members learn from one another’s experiences and perspectives [45]. This collective learning enhances their ability to manage intercultural interactions effectively, thereby mitigating the stressors typically associated with these encounters [58,71]. Accordingly,
H6. 
Cognitive diversity (KD) moderates the relationship between cultural intelligence (CQ) and emotional exhaustion (EEX).
Similarly, cognitive diversity plays a significant moderating role between emotional intelligence and emotional exhaustion. The presumption indicates that teams with high cognitive diversity are better equipped to resolve conflicts, reducing emotional strain on individuals and helping to mitigate stressors that lead to exhaustion [72]. The prevalence of diverse cognitive perspectives is assumed to enhance emotional support within teams, whereby newcomers with high emotional intelligence can better understand and respond to their colleagues’ emotional needs, fostering a supportive environment that alleviates feelings of exhaustion [73]. Furthermore, cognitive diversity is believed to facilitate collective learning among team members, allowing them to share emotional responses and coping strategies. Hence, by leveraging cognitive diversity, organizations can build a more resilient workforce capable of managing emotional demands in the workplace [74]. Accordingly,
H7. 
Cognitive diversity (KD) moderates the relationship between emotional intelligence (EI) and emotional exhaustion (EEX).

2.1.6. The Mediating Role of Emotional Exhaustion (EEX)

According to Zhao and Jiang [75] and Aljaier et al. [76], emotional exhaustion (EEX) refers to the depletion of emotional resources caused by prolonged stressors such as role overload, ambiguity, and a lack of autonomy. This depletion impairs employees’ ability to meet job demands and manage relationships, often leading to negative behaviors like absenteeism, conflicts, and deviance, particularly in high-stress environments like hospitality [64]. The Conservation of Resources (COR) theory suggests that emotional resource loss increases vulnerability to negative outcomes, such as turnover and decreased job satisfaction, and mediates the effects of stressors, such as bullying, on these outcomes [65,74]. Moreover, employees may cope with emotional exhaustion by seeking social exchanges to restore self-esteem and belonging, but this can reduce their investment in both interpersonal and organizational relationships [8,77]. Thus, emotional exhaustion also mediates the relationship between workplace stressors such as bullying, incivility, and abusive supervision and negative work outcomes, including interpersonal deviance, knowledge sharing, turnover intentions, and job satisfaction [78,79].
Cultural intelligence (CQ) plays a key role in managing emotional exhaustion by helping employees navigate cross-cultural challenges. High CQ enables employees to conserve emotional resources, reduce stress, and prevent burnout, which enhances task performance and minimizes errors [31,39]. The COR theory supports this, suggesting that emotional resource depletion, whether from stress or cultural misunderstandings, impairs employees’ ability to manage work demands [38,65]. Consequently, CQ reduces emotional exhaustion, improving performance and reducing errors. Empirical evidence supports that emotional exhaustion mediates the relationship between CQ and work outcomes, such as task performance and error reduction [16,80]. Accordingly,
H8a. 
Emotional exhaustion (EEX) mediates the relationship between cultural intelligence (CQ) and error reduction (ER).
H8b. 
Emotional exhaustion (EEX) mediates the relationship between cultural intelligence (CQ) and task performance (TP).
Similarly, emotional intelligence (EI) is crucial for managing stress and preventing emotional exhaustion. Employees with high EI regulate their emotions effectively, reducing stress and conserving emotional resources, which, in turn, improves task performance and error reduction [71,73,74]. These employees are better equipped to handle interpersonal challenges and prevent burnout, ultimately enhancing productivity. Research shows that high EI increases resilience to emotional exhaustion, leading to better job performance [16,74,80]. Accordingly,
H9a. 
Emotional exhaustion (EEX) mediates the relationship between emotional intelligence (EI) and error reduction (ER).
H9b. 
Emotional exhaustion (EEX) mediates the relationship between emotional intelligence (EI) and task performance (TP).
Perceived organizational support (POS) refers to employees’ belief that their organization values their contributions and cares for their well-being. High POS is associated with lower emotional exhaustion, as it helps employees cope with stress, reduce burnout, and improve performance [17,59]. Research shows that POS buffers the negative impact of stressors, promoting a positive work environment and alleviating burnout, especially in high-stress settings like hospitality [60,63]. Accordingly,
H10a. 
Emotional exhaustion (EEX) significantly mediates the relationship between perceived organizational support (POS) and error reduction (ER).
H10b. 
Emotional exhaustion (EEX) significantly mediates the relationship between perceived organizational support (POS) and task performance (TP).
Drawing upon the theoretical models and empirical evidence presented in the theoretical foundations and hypothesis development, we integrate Multiple Intelligence (MI), Social Exchange Theory (SET), and Conservation of Resources (COR) Theory to examine newcomers’ performance and error reduction. Cultural Intelligence (CQ) and Emotional Intelligence (EI) are central components of MI, which facilitate effective collaboration across diverse workgroups and enhance interpersonal relationships while managing emotions to reduce conflict [35,36,37,38]. COR theory emphasizes that when employees feel supported, they are more likely to engage positively, resulting in improved performance and reduced emotional exhaustion (EEX). SET, on the other hand, emphasizes the balance of costs and benefits in interpersonal relationships. Moreover, Cognitive Diversity (KD), characterized by the variety of perspectives within a team, enhances creativity and innovation, which in turn improves task performance [73].
Our extended model proposes that Cognitive Diversity (KD) moderates the relationships between Cultural Intelligence (CQ) and Emotional Exhaustion (EEX), as well as between Emotional Intelligence (EI) and Emotional Exhaustion (EEX), fostering better problem-solving and enhancing task performance (TP) [74]. We argue that higher levels of CQ and EI contribute to an inclusive environment, while strong Perceived Organizational Support (POS) can mitigate emotional exhaustion (EEX) by providing essential resources. In contrast, emotional exhaustion (EEX) can diminish task performance due to burnout. Furthermore, increased EI and CQ can lead to fewer errors in collaborative settings by enhancing understanding and interpersonal skills, ultimately boosting overall task performance [79,80], as shown in Figure 1.

3. Materials and Methods

3.1. Research Methodology, Procedures and Samples

This study employed a positivist research paradigm with a quantitative approach, utilizing descriptive and explanatory research designs to validate the research model. Data were collected through a survey strategy conducted in five-star-rated hotels. The target population consisted of 2000 individuals, including both newcomers and supervisors. Sampling was carried out using a combination of census, stratified, and simple random sampling techniques to ensure representativeness. To determine the sample size, the study followed Aaker and Day’s [81] sample determination approach, which is commonly used in social science research. This method accounts for factors such as the desired confidence level, confidence interval, sampling error, and population characteristics. The sample size formula used was S = z√((P(1 − P))/n) √((N − n)/(N − 1)). Here, Z = confidence interval = 1.96, S = sample error (5%) = 0.05, P = ratio of population characteristics (50% in social sciences) = 0.5, N = total population, and n = sample size. As a result, a total of 476 samples were selected: 449 from newcomers and 27 from supervisors and managers. With a response rate of 95.5%, all 476 samples were used for further analysis. This sample size is considered adequate, as recommended by Kline [82] and Sarstedt et al. [83], who suggest a sample size of 200–300 for models with fewer constructs. Since the sample in this study exceeds this threshold, it is deemed appropriate. The study used Structural Equation Modeling (SEM) to test the hypothesized relationships, independencies, and causalities among the research variables. Data analysis was performed using SPSS 23, StatTools pack 20, and AMOS 23.

3.2. Measurement Instruments

All constructs included in this study were measured using well-established and validated scales. A 5-point Likert scale, with a range from 1 (“strongly disagree”) to 5 (“strongly agree”), was used.
As shown in Table 1, cultural intelligence (CQ) was assessed using 10 items representing three dimensions: cultural knowledge, skills, and motivation [31,41]. Emotional exhaustion was assessed using four items from the German version of the Maslach Burnout Inventory, originally developed by Maslach and Jackson [58,84]. The error reduction (ER) scale was adapted from the Error Orientation Questionnaire (EOQ) to better suit the context of this study [80]. Task performance (TP) was measured using a five-point scale adapted from K.-J. Chen et al. [18]. Likewise, the measures of emotional intelligence (EI) were adapted from Darvishmotevali et al. [1]. The perceived organizational support (POS) scale was adapted from Kurtessis et al. [59], and the cognitive diversity (KD) scale was adapted from Mathuki, E., Zhang, J. [69].

4. Results and Discussions

4.1. Descriptive Statistics and Correlation of the Study Constructs

As shown in Table 2, the survey participants consisted of 276 males (58%) and 200 females (42%). Upon examining the mean, standard deviation, and correlation analysis results of each construct, the mean values ranged from 3.8479 for EEX to 3.9279 for ER, signifying positive views from the respondents. To assess the relationships and associations among the variables, a correlation analysis was performed. The results confirmed that CQ had a significant positive correlation with EI (0.245), POS (0.349), KD (0.493), EEX (0.526), ER (0.315), and TP (0.351). POS also exhibited moderate correlations with KD (0.474) and EEX (0.538), implying that changes in POS lead to significant changes in KD and EEX. Finally, ER revealed significant correlations with all variables, particularly with EI (0.448) and EEX (0.482). These findings reinforce the idea that error reduction is significantly associated with all variables.

4.2. Evaluation of the Measurement Model

Normality was visually assessed using histograms and normal probability plots. The results revealed that the histogram was symmetrical and approximately bell-shaped, confirming the presence of normality in the data distribution. To further assess univariate normality, the researchers examined the distribution of each observed variable for skewness and kurtosis. The absolute values of the Z-scores for skewness and kurtosis were compared against critical values: >1.96 (significant at p < 0.05), >2.58 (significant at p < 0.01), and >3.29 (significant at p < 0.001). The data appeared to conform to a normal distribution. These findings are consistent with the recommendations of Hu and Bentler [85], Hoyle [86], Byrne [87], and Field [88].
Moreover, the deviation of each observation from the mean in the multidimensional space was assessed. The values of D2/df were found to fall within the acceptable range (3–4), indicating that only a few observations deviated from the general distribution in the multidimensional space. These results align with the recommendations of Hair et al. [89], confirmatory factor analysis (CFA) was performed using AMOS 23.0. All measurement scales underwent a CFA to evaluate their psychometric properties and ensure both validity and reliability.
SEM was used to assess the measurement model. The assumptions of multivariate analysis were evaluated to ensure validity. The independence of the research constructs was examined using Pearson’s bivariate correlation. The results show that the correlation coefficients were below 0.80, indicating that multicollinearity and singularity were not issues in the data.
As shown in Table 3, the composite reliability (CR) and average variance extracted (AVE) were computed for all constructs. The CR and AVE for cultural intelligence (CQ) were 0.860 and 0.57, respectively. The values for emotional intelligence (EI) were CR = 0.860 and AVE = 0.541; for perceived organizational support (POS), CR = 0.818 and AVE = 0.553; for cognitive diversity (KD), CR = 0.861 and AVE = 0.572; for emotional exhaustion (EEX), CR = 0.852 and AVE = 0.560; for error reduction (ER), CR = 0.802 and AVE = 0.535; and for task performance (TP), CR = 0.902 and AVE = 0.651. These results indicate that the constructs meet the cut-off points for reliability, convergent validity, and discriminant validity, with no identified issues [90].

4.3. Confirmatory Factor Analysis (CFA)

Since the research is grounded in a strong theoretical foundation underpinning the measurement model, a confirmatory factor analysis (CFA) was employed to assess the psychometric properties and validate the measurement scales.
To ensure sufficient model fit, cut-off points were applied to assess whether the data adequately aligned with the hypothesized model [90]. The test results, shown in Table 4, reveal that with goodness-of-fit indices such as GFI (0.901), AGFI (0.925), TLI (0.950), CFI (0.960), and RMSEA (0.052), the data adequately fit the hypothesized model, providing a solid basis for further analysis.

4.4. Hypothesis Testing

The hypothesized model was proposed based on SET, the theory of MI, and COR theory. By using path analysis, the hypothesized causal relationships and interdependences were tested. Thus, Figure 2 illustrates the coefficients for each linear model.

4.4.1. The Main Effect Analysis

Based on the path analysis, as shown in Figure 2, the hypothesized causal relationships and interdependencies were tested. The path model revealed that higher cultural intelligence (CQ) was significantly associated with lower emotional exhaustion (EEX) (ß = −0.320, p < 0.001), indicating that an increase in CQ leads to a decrease in EEX. This finding supports Hypothesis 1. Similarly, higher emotional intelligence (EI) was significantly associated with lower EEX (ß = −0.345, p < 0.001), confirming that an increase in EI results in lower EEX, thereby supporting Hypothesis 2. Likewise, an increase in perceived organizational support (POS) led to a significant negative change in EEX (ß = −0.425, p < 0.001), indicating that newcomers who perceive more support from their organizations are less likely to experience emotional depletion, supporting Hypothesis 3.
The result for Hypothesis 4 showed that EEX was negatively associated with task performance (TP) (ß = −0.315, p < 0.001), indicating that higher EEX is linked to lower task performance, which provides strong evidence that EEX adversely affects employees’ ability to perform tasks effectively. The hypothesis test for H5 also found strong support, with results showing that increased EEX is significantly associated with a lower likelihood of error reduction (ß = −0.560, p < 0.001). This confirms that higher emotional exhaustion is linked to an increased occurrence of errors, offering robust evidence that EEX contributes to error rates, rather than error reduction.

4.4.2. The Mediation Effect Analysis

The mediating effects of emotional exhaustion (EEX) on specific indirect relationships were tested using bootstrapping (N = 5000), in accordance with the recommendations of Hayes [91].
The specific indirect effects were estimated with bootstrapping procedures, as shown in Table 5. The test results of the specific indirect effect reveal that the indirect effects of CQ on ER through EEX were significantly different from 0 at the 0.05 significance level, with a 95% confidence interval ranging from 0.0278 to 0.1714. EEX significantly carries the influence of CQ on TP at CI (0.0790–0.2201). EEX significantly mediates the relationship between EI and ER with the CI (0.0044–0.0642), EI and TP with the CI (0.0573–0.0008), POS and ER with CI (0.0487–0.0096), and POS and TP with the CI (0.0778–0.0053). The results confirmed that EEX significantly mediates the relationship between CQ and ER, CQ and TP, EI and ER, EI and TP, POS and TP, POS and ER.

4.4.3. The Moderation Analysis

The moderating effects of cognitive diversity (KD) were tested as shown in Figure 3 and Figure 4 below. The findings revealed KD strengthens the positive relationship between CQ and EEX and EI and EEX. These results highlight the significant moderating role of KD in enhancing both the relationships between the respective variables.

5. Discussion

It is widely recognized that joining a new organization often involves encountering a reality shock. Newcomers face challenges such as unfamiliar co-workers, supervisors, guests, rules, information, objectives, and regulations. One of the primary challenges they face during the initial stage is learning the “ropes” of the new organization [6]. In the hospitality industry, where emotional and cultural intelligence play a critical role, and face-to-face interactions are a daily norm, newcomers’ ability to function effectively and make informed decisions in response to a new cultural and emotional context is essential [30].

5.1. The Effects of Cultural Intelligence, Emotional Intelligence, and Perceived Organizational Support on Emotional Exhaustion

Drawing from the Conservation of Resources (COR), Multiple Intelligence (MI), and Social Exchange (SET) theories, this study developed a moderation–mediation model to explore the effects of cultural intelligence (CQ), emotional intelligence (EI), and perceived organizational support (POS) on newcomers’ task performance and error reduction.
First, we examined the main effect of CQ on emotional exhaustion (EEX) and extended previous research by investigating this relationship within the hospitality context. The findings support existing empirical evidence, demonstrating that newcomers with high CQ are better equipped to navigate information, connect with the workforce [41], adapt to new environments, and develop cultural competence [50,51]. As hypothesized, higher CQ helps reduce emotional exhaustion by enabling newcomers to manage the stressors of adapting to new cultural settings [52,53]. Additionally, because CQ fosters proactive adaptation, it allows newcomers to clarify their values, characteristics, and behaviors [31,40], thus minimizing misunderstandings and conflicts [43].
Second, in line with the propositions of COR theory, this study found that, as newcomers’ emotional intelligence (EI) increases, they are less likely to be exposed to stressors or experience depletion of emotional resources. This result extends previous literature [56,57], as higher EI enables newcomers to better develop coping mechanisms when facing personal resource depletion and the stressors associated with adjusting to new roles, particularly those that require a high degree of human interaction and attention, such as in hospitality [25,49]. These findings further suggest that higher EI enhances emotional resilience and adaptability in high-stress, people-centered environments like hospitality.
Third, in line with the Conservation of Resources (COR) and Social Exchange theories, the study highlights that perceived organizational support (POS) is negatively associated with emotional exhaustion (EEX). This finding suggests that newcomers who perceive less organizational support are more likely to experience higher levels of emotional exhaustion [67]. Extending previous literature, the study shows that POS significantly reduces feelings of isolation and unfriendliness, while positively contributing to a decrease in emotional exhaustion [59].

5.2. The Effect of Emotional Exhaustion on Error Reduction and Task Performance

We applied the Conservation of Resources (COR) theory and argued that newcomers experiencing emotional exhaustion (EEX) often struggle to fulfill their job responsibilities, resulting in poor performance and negative job outcomes [55,58]. Building on previous studies, our findings show that EEX significantly contributes to the depletion of valued personal resources and the lack of sufficient resources to effectively manage encountered stressors [77]. Similarly, consistent with earlier research, the results indicate that newcomers who become suspicious about their interactions with others and experience frustration often struggle to perform their tasks effectively [38,76].

5.3. The Mediating Roles of Emotional Exhaustion

As proposed in the conceptual model, the findings confirmed that emotional exhaustion (EEX) significantly mediates the effects of cultural intelligence (CQ) on error reduction (ER) and task performance (TP); emotional intelligence (EI) on ER and TP; and perceived organizational support (POS) on ER and TP. This finding contributes to the existing literature, suggesting that overextended and drained emotional resources among newcomers undermine their ability to cope with the challenges they face in their new work environment [47,49,78]. Moreover, the results indicate that EEX negatively impacts task performance and increases error rates [7]. In line with this, Chou, Fang, and Yeh [78] demonstrated that newcomers’ emotional exhaustion during the integration process significantly affects their task performance and error reduction. The Conservation of Resources (COR) theory further supports this by positing that newcomers experiencing emotional exhaustion often adopt defensive strategies or withdraw to conserve their remaining resources [78].

5.4. The Moderating Effects of Cognitive Diversity

This study’s results indicate that cognitive diversity (KD) strengthens the positive relationships between cultural intelligence (CQ) and emotional exhaustion (EEX), as well as between emotional intelligence (EI) and EEX. These findings are strongly supported by previous empirical studies. Gong et al. [73] argued that newcomers with high KD are better equipped to resolve conflicts, reducing emotional strain and mitigating stressors that lead to exhaustion. This suggests that KD enhances emotional support within teams, where newcomers with high EI are better able to understand and respond to their colleagues’ emotional needs, fostering a supportive environment that alleviates feelings of exhaustion [69]. Therefore, by leveraging cognitive diversity, organizations can build a more resilient workforce capable of managing emotional demands in the workplace [70].

5.5. Theoretical and Practical Significances

5.5.1. Theoretical Significances

This study extends the COR theory, Social Exchange Theory, and Multiple Intelligence frameworks to explore newcomers’ task performance and error reduction in the hospitality sector. By integrating these theories into a new model, the research illustrates how factors such as cultural intelligence, emotional intelligence, perceived organizational support, cognitive diversity, and emotional exhaustion influence task performance and error reduction. This novel approach deepens the understanding of these constructs within the hospitality context.
Adopting a positivist research philosophy, the study examines the antecedents and interrelationships of these factors in shaping newcomer adaptation and performance. The findings highlight the importance of evidence-based methodologies in addressing the challenges faced by newcomers, offering valuable insights for improving organizational practices in the hospitality industry.

5.5.2. Practical Implications

The study provides valuable insights into policy and managerial practices within the hospitality sector, highlighting the importance of integrating cultural and emotional intelligence into organizational strategies. By focusing on these factors, organizations can more effectively support newcomers in adapting to the workplace, enhancing task performance, and minimizing operational errors. The findings provide government bodies, industry practitioners, and managers with a deeper understanding of the key influences on newcomers’ engagement and performance, thus informing the development of policies and strategies aimed at improving outcomes and reducing errors.

5.5.3. Limitations and Future Research Directions

This study is grounded in three theoretical imperatives. However, given the multidisciplinary nature of hospitality research, incorporating more well-established, discipline-specific frameworks could have further strengthened the theoretical foundation. Additionally, while perceived organizational support is often used as a moderator in prior studies, this research treats it as an exogenous variable. This adaptation may yield distinct outcomes compared to those of previous work, underscoring the need for further validation. Regarding the sample size, although it is adequate for advanced multivariate analyses such as SEM, the study was limited to five-star hotels in Addis Ababa, which may restrict the generalizability of the findings to other hotel categories. Finally, the study adopts a positivist approach, suggesting that future research could examine this area from a post-positivist perspective to provide a more comprehensive understanding.

Author Contributions

Conceptualization, T.A.B., M.Z. and C.C.; Methodology, T.A.B., M.Z. and C.C.; Software, T.A.B., M.Z. and C.C.; Validation, T.A.B., M.Z. and C.C.; Formal analysis, T.A.B., M.Z. and C.C.; Investigation, T.A.B., M.Z. and C.C.; Resources, T.A.B., M.Z. and C.C.; Data curation, T.A.B., M.Z. and C.C.; Writing original draft, T.A.B., M.Z. and C.C.; Writing review & editing, T.A.B., M.Z. and C.C.; Visualization, M.Z. and C.C.; Supervision, M.Z. and C.C.; Project administration, M.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Beijing Propaganda and Culture High-Level Talent Training Grant Project “Zhang Mingyu’s Studio” and Fundamental Research Funds for central university (2021JBWZD001).

Informed Consent Statement

All respondents participated voluntarily and provided oral consent to their participation.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Darvishmotevali, M.; Altinay, L.; De Vita, G. Emotional intelligence and creative performance: Looking through the lens of environmental uncertainty and cultural intelligence. Int. J. Hosp. Manag. 2018, 73, 44–54. [Google Scholar] [CrossRef]
  2. Ma, Z.; Song, L.; Huang, J. How maladjustment and workplace bullying affect newcomers’ turnover intentions: Roles of cognitive diversity and perceived inclusive practices. Int. J. Contemp. Hosp. Manag. 2024, 36, 1066–1086. [Google Scholar] [CrossRef]
  3. Raza, A.; Ishaq, M.I.; Jamali, D.R.; Zia, H.; Haj-Salem, N. Testing workplace hazing, moral disengagement and deviant behaviors in the hospitality industry. Int. J. Contemp. Hosp. Manag. 2024, 36, 743–768. [Google Scholar] [CrossRef]
  4. Quratulain, S.; Al-Hawari, M.A. Interactive effects of supervisor support, diversity climate, and employee cynicism on work adjustment and performance. Int. J. Hosp. Manag. 2021, 93, 102803. [Google Scholar] [CrossRef]
  5. Cudjoe, J.; Agyapong, D.; Light, O.; Frimpong, S.E.; Opoku, R.K. Psychological empowerment and job performance of star-rated hotels: The mediating role of emotional intelligence. Cogent Bus. Manag. 2023, 10, 2266131. [Google Scholar] [CrossRef]
  6. Raub, S.; Borzillo, S.; Perretten, G.; Schmitt, A. New employee orientation, role-related stressors and conflict at work: Consequences for work attitudes and performance of hospitality employees. Int. J. Hosp. Manag. 2021, 94, 102857. [Google Scholar] [CrossRef]
  7. Chen, J.; Cooper-Thomas, H.D. Finding one’s own way: How newcomers who differ stay well. Evid. Based HRM A Glob. Forum Empir. Scholarsh. 2023, 11, 143–157. [Google Scholar] [CrossRef]
  8. Lan, J.; Wong, C.S.; Wong, I.A. The role of knowledge sharing in hotel newcomer socialization: A formal intervention program. Int. J. Contemp. Hosp. Manag. 2022, 34, 2250–2271. [Google Scholar] [CrossRef]
  9. Chen, Y.; Yang, Z.; Liu, B.; Wang, D.; Xiao, Y.; Wang, A. How cultural intelligence affects expatriate effectiveness in international construction projects. Eng. Constr. Archit. Manag. 2024, 31, 1696–1714. [Google Scholar] [CrossRef]
  10. Bauer, T.N.; Erdogan, B. Organizational socialization: The effective onboarding of new employees. In APA Handbook of Industrial and Organizational Psychology; Maintaining, Expanding, and Contracting the Organization; American Psychological Association: Washington, DC, USA, 2011; Volume 3, pp. 51–64. [Google Scholar]
  11. Liu, J.; Lee, A.; Li, X.; Li, C.R. The role of change in the relationships between leader-member exchange/coworker exchange and newcomer performance: A latent growth modeling approach. Front. Psychol. 2021, 12, 600712. [Google Scholar] [CrossRef]
  12. Smith, D.L. Effects of Leader-Member Exchange Quality and Perceived Support on Leader and Employee Engagement: A Quantitative Correlational Study. Ph.D. Thesis, Northcentral University, Minneapolis, MN, USA, 2022. [Google Scholar]
  13. Mazzei, A.; Ravazzani, S.; Butera, A.; Conti, S.; Fisichella, C. The affective commitment of newcomers in hybrid work contexts: A study on enhancing and inhibiting factors and the mediating role of newcomer adjustment. Front. Psychol. 2023, 13, 987976. [Google Scholar] [CrossRef] [PubMed]
  14. Jha, S.; Bhattacharyya, S.S. Learning Orientation and Performance Orientation: Scale Development and Its Relationship with Performance. Global Bus. Rev. 2013, 14, 43–54. [Google Scholar] [CrossRef]
  15. Kammeyer-Mueller, J.; Wanberg, C.; Rubenstein, A.; Song, Z. Support, Undermining, and Newcomer Socialization: Fitting in During the First 90 Days. Acad. Manag. J. 2013, 56, 1104–1124. [Google Scholar] [CrossRef]
  16. Spitzer, M.W.H.; Musslick, S.; Janz, J.; Kiesel, A.; Dignath, D. Task Performance Errors and Rewards Affect Voluntary Task Choices. Psychol. Res. 2024, 88, 892–909. [Google Scholar] [CrossRef]
  17. Rhoades, L.; Eisenberger, R. Perceived Organizational Support: A Review of the Literature. J. Appl. Psychol. 2002, 87, 698–714. [Google Scholar] [CrossRef]
  18. Chen, T.J.; Wu, C.M. Can Newcomers Perform Better at Hotels? Examining the Roles of Transformational Leadership, Supervisor-Triggered Positive Affect, and Perceived Supervisor Support. Tour. Manag. Perspect. 2020, 33, 100587. [Google Scholar] [CrossRef]
  19. Yuan, L.; Kim, H.J.; Min, H. How Cultural Intelligence Facilitates Employee Voice in the Hospitality Industry. Sustainability 2023, 15, 8851. [Google Scholar] [CrossRef]
  20. Chen, K.J.; Lin, C.P.; Chen, P.C. Multiple Intelligences and Job Performance: The Moderating Role of Learning Goal Oriented Training. Total Qual. Manag. Bus. Excell. 2024, 35, 46–63. [Google Scholar] [CrossRef]
  21. Karroubi, M.; Hadinejad, A.; Mahmoudzadeh, S.M. A Study on Relationship Between Cultural Intelligence and Cross-Cultural Adjustment in Tour Management. Manag. Sci. Lett. 2014, 4, 1233–1244. [Google Scholar] [CrossRef]
  22. Miao, C.; Humphrey, R.H.; Qian, S. Emotional Intelligence and Job Performance in the Hospitality Industry: A Meta-Analytic Review. Int. J. Contemp. Hosp. Manag. 2021, 33, 2632–2652. [Google Scholar] [CrossRef]
  23. Prentice, C. Emotional Labour and Its Consequences: The Moderating Effect of Emotional Intelligence. In Proceedings of the 2013 International Conference on Business and Management, Lahore, Pakistan, 27–28 February 2013; pp. 187–201. [Google Scholar]
  24. Sigala, M.; Chalkiti, K. Knowledge management, social media and employee creativity. Int. J. Hosp. Manag. 2015, 45, 44–58. [Google Scholar] [CrossRef]
  25. Baum, T.; Kralj, A.; Robinson, R.N.S.; Solnet, D.J. Tourism workforce research: A review, taxonomy and agenda. Ann. Tour. Res. 2016, 60, 1–22. [Google Scholar] [CrossRef]
  26. Wei, J.; Lin, X.; Jiang, Y.; Zhou, X. The influence of emotional intelligence and relationship quality on the service recovery effect of online platform ecosystem. Curr. Psychol. 2022, 41, 7898–7910. [Google Scholar] [CrossRef]
  27. Stoyanova-Bozhkova, S.; Paskova, T.; Buhalis, D. Emotional intelligence: A competitive advantage for tourism and hospitality managers. Tour. Recreat. Res. 2022, 47, 359–371. [Google Scholar] [CrossRef]
  28. Caldwell, C.; Hayes, L.A. Self-efficacy and self-awareness: Moral insights to increased leader effectiveness. J. Manag. Dev. 2016, 35, 1163–1173. [Google Scholar] [CrossRef]
  29. Koc, E.; Bozkurt, G.A. Hospitality Employees’ Future Expectations: Dissatisfaction, Stress, and Burnout. Int. J. Hosp. Tour. Adm. 2017, 18, 459–473. [Google Scholar] [CrossRef]
  30. Zeb, A.; Goh, G.G.G.; Javaid, M.; Khan, M.N.; Khan, A.U.; Gul, S. The interplay between supervisor support and job performance: Implications of social exchange and social learning theories. J. Appl. Res. High. Educ. 2023, 15, 429–448. [Google Scholar] [CrossRef]
  31. Earley, P.C.; Stanford, S.A. Cultural intelligence: Individual interactions across cultures intelligence in recent public literature. Stud. Intell. 2005, 49, 1–4. [Google Scholar]
  32. Zhang, Y.C.; Zemke, D.M.V.; Belarmino, A.; Shum, C. Comparing the antecedents of manager’s and employee’s job satisfaction in the housekeeping department. Int. Hosp. Rev. 2024, 8, 376–396. [Google Scholar] [CrossRef]
  33. Jones, D.A. Does serving the community also serve the company? Using organizational identification and social exchange theories to understand employee responses to a volunteerism programme. J. Occup. Organ. Psychol. 2010, 83, 857–878. [Google Scholar] [CrossRef]
  34. Bakker, A.B.; de Vries, J.D. Job Demands–Resources theory and self-regulation: New explanations and remedies for job burnout. Anxiety Stress Coping 2021, 34, 1–21. [Google Scholar] [CrossRef] [PubMed]
  35. Ko, J.; Hur, S. The impacts of employee benefits, procedural justice, and managerial trustworthiness on work attitudes: Integrated understanding based on social exchange theory. Public Adm. Rev. 2014, 74, 176–187. [Google Scholar] [CrossRef]
  36. Meira, J.V.d.S.; Hancer, M. Using the social exchange theory to explore the employee-organization relationship in the hospitality industry. Int. J. Contemp. Hosp. Manag. 2021, 33, 670–692. [Google Scholar] [CrossRef]
  37. Hobfoll, S.E. Conservation of resources: A new attempt at conceptualizing stress. Am. Psychol. 1989, 44, 513–524. [Google Scholar] [CrossRef]
  38. Hobfoll, S.E.; Freedy, J. Conservation of resources: A general stress theory applied to burnout. In Professional Burnout; Schaufeli, W.B., Maslach, C., Marek, T., Eds.; Taylor & Francis: London, UK, 2018; pp. 115–129. [Google Scholar]
  39. Aldhaheri, A. Cultural intelligence and leadership style in the education sector. Int. J. Educ. Manag. 2017, 31, 718–735. [Google Scholar] [CrossRef]
  40. Alexandra, V.; Ehrhart, K.H.; Randel, A.E. Cultural intelligence, perceived inclusion, and cultural diversity in workgroups. Pers. Individ. Dif. 2021, 168, 110285. [Google Scholar] [CrossRef]
  41. Ang, S.; Van Dyne, L.; Koh, C.; Ng, K.Y.; Templer, K.J.; Tay, C.; Chandrasekar, N.A. Cultural intelligence: Its measurement and effects on cultural judgment and decision making, cultural adaptation, and task performance. Manag. Organ. Rev. 2007, 3, 335–371. [Google Scholar] [CrossRef]
  42. Thomas, D.C.; Liao, Y.; Aycan, Z.; Cerdin, J.L.; Pekerti, A.A.; Ravlin, E.C.; Stahl, G.K.; Lazarova, M.B.; Fock, H.; Arli, D.; et al. Cultural intelligence: A theory-based, short form measure. J. Int. Bus. Stud. 2015, 46, 1099–1118. [Google Scholar] [CrossRef]
  43. Amissah, E.F.; Blankson-Stiles-Ocran, S.; Mensah, I. Emotional labour, emotional exhaustion, and job satisfaction in the hospitality industry. J. Hosp. Tour. Insights 2022, 5, 805–821. [Google Scholar] [CrossRef]
  44. Richter, N.F.; Martin, J.; Hansen, S.V.; Taras, V.; Alon, I. Motivational configurations of cultural intelligence, social integration, and performance in global virtual teams. J. Bus. Res. 2021, 129, 351–367. [Google Scholar] [CrossRef]
  45. Stoermer, S.; Davies, S.; Froese, F.J. The influence of expatriate cultural intelligence on organizational embeddedness and knowledge sharing: The moderating effects of host country context. J. Int. Bus. Stud. 2021, 52, 3. [Google Scholar] [CrossRef]
  46. Fernández-Martín, F.D.; Flores-Carmona, L.; Arco-Tirado, J.L. Coping strategies among undergraduates: Spanish adaptation and validation of the Brief-COPE inventory. Psychol. Res. Behav. Manag. 2022, 15, 991–1003. [Google Scholar] [CrossRef] [PubMed]
  47. Koon, V.Y.; Pun, P.Y. The mediating role of emotional exhaustion and job satisfaction on the relationship between job demands and instigated workplace incivility. J. Appl. Behav. Sci. 2018, 54, 187–207. [Google Scholar] [CrossRef]
  48. Kim, H.; Qu, H. Employees’ burnout and emotional intelligence as mediator and moderator in the negative spiral of incivility. Int. J. Contemp. Hosp. Manag. 2019, 31, 1412–1431. [Google Scholar] [CrossRef]
  49. Kim, N.; Kang, Y.J.; Choi, J.; Sohn, Y.W. The crossover effects of supervisors’ workaholism on subordinates’ turnover intention: The mediating role of two types of job demands and emotional exhaustion. Int. J. Environ. Res. Public Health 2020, 17, 7742. [Google Scholar] [CrossRef]
  50. Mustafa, M.J.; Hallak, R.; Lee, C.; Manshor, S.S.B.S. Leaders’ coaching behaviors and the emotional exhaustion of hotel frontline supervisors: Examining the serial mediating effects of taking charge and work engagement. J. Hum. Resour. Hosp. Tour. 2024, 23, 386–412. [Google Scholar] [CrossRef]
  51. Wang, X.; Dong, B. Emotional intelligence and knowledge hiding behaviors: The mediating role of job stress. Front. Psychol. 2022, 13, 845782. [Google Scholar] [CrossRef]
  52. Sternberg, R.J.; Co, C.; Siriner, I.; Soleimani-Dashtaki, A.; Wong, C.H. Cultural intelligence deployed in one’s own vs. in a different culture: The same or different? J. Intell. 2023, 11, 212. [Google Scholar] [CrossRef]
  53. Ain, N.U.; Azeem, M.U.; Haq, I.U.; Mehmood, I. When does knowledge hiding hinder employees’ job performance? The roles of emotional exhaustion and emotional intelligence. Knowl. Manag. Res. Pract. 2024, 22, 210–222. [Google Scholar] [CrossRef]
  54. Desai, D.; Srivastava, M. Emotional Intelligence—The Moderator of Leadership Styles and Performance. NMIMS Manag. Rev. 2017, 33, 35–56. [Google Scholar]
  55. Liu, H.; Boyatzis, R.E. Focusing on resilience and renewal from stress: The role of emotional and social intelligence competencies. Front. Psychol. 2021, 12, 749079. [Google Scholar] [CrossRef] [PubMed]
  56. De Geofroy, Z.; Evans, M.M. Are emotionally intelligent employees less likely to hide their knowledge? Knowl. Process Manag. 2017, 24, 81–90. [Google Scholar] [CrossRef]
  57. Jung, H.S.; Yoon, H.H. Why is employees’ emotional intelligence important? The effects of EI on stress-coping styles and job satisfaction in the hospitality industry. Int. J. Contemp. Hosp. Manag. 2016, 28, 1649–1675. [Google Scholar] [CrossRef]
  58. Maslach, C.; Jackson, S.E. The Measurement of Experienced Burnout. J. Organ. Behav. 1981, 2, 99–113. [Google Scholar] [CrossRef]
  59. Kurtessis, J.N.; Eisenberger, R.; Ford, M.T.; Buffardi, L.C.; Stewart, K.A.; Adis, C.S. Perceived organizational support: A meta-analytic evaluation of organizational support theory. J. Manag. 2017, 43, 1854–1884. [Google Scholar] [CrossRef]
  60. Sahibzada, Y.A.; Ali, M.; Toru, N.; Farooq Jan, M.; Ellahi, A. Exploitative leadership and green innovative behavior of hospitality employees: Mediation of emotional exhaustion and moderation of perceived organizational support. J. Hosp. Tour. Insights 2024. [Google Scholar] [CrossRef]
  61. De Clercq, D.; Haq, I.U.; Azeem, M.U. Ignoring leaders who break promises or following God: How depersonalization and religious faith inform employees’ timely work efforts. Br. J. Manag. 2023, 34, 16–36. [Google Scholar] [CrossRef]
  62. Reb, M.; Atkins, P.W.B. Mindfulness in Organizations: Foundations, Research, and Applications; Cambridge University Press: Cambridge, UK, 2015. [Google Scholar]
  63. Pimenta, S.; Duarte, A.P.; Simões, E. How socially responsible human resource management fosters work engagement: The role of perceived organizational support and affective organizational commitment. Soc. Responsib. J. 2024, 20, 326–343. [Google Scholar] [CrossRef]
  64. Leiter, M.P.; Maslach, C. Latent burnout profiles: A new approach to understanding the burnout experience. Burn. Res. 2016, 3, 89–100. [Google Scholar] [CrossRef]
  65. Extremera, N.; Mérida-López, S.; Sánchez-Álvarez, N.; Quintana-Orts, C. How Does Emotional Intelligence Make One Feel Better at Work? The Mediational Role of Work Engagement. Int. J. Environ. Res. Public Health 2018, 15, 1909. [Google Scholar] [CrossRef]
  66. Choi, H.M.; Mohammad, A.A.A.; Kim, W.G. Understanding Hotel Frontline Employees’ Emotional Intelligence, Emotional Labor, Job Stress, Coping Strategies, and Burnout. Int. J. Hosp. Manag. 2019, 82, 102399. [Google Scholar] [CrossRef]
  67. Saks, A.M.; Gruman, J.A. Making Organizations More Effective through Organizational Socialization. J. Organ. Eff. People Perform. 2014, 1, 261–280. [Google Scholar] [CrossRef]
  68. Lee, L.; Madera, J.M. A Systematic Literature Review of Emotional Labor Research from the Hospitality and Tourism Literature. Int. J. Contemp. Hosp. Manag. 2019, 31, 1868–1903. [Google Scholar] [CrossRef]
  69. Mathuki, E.; Zhang, J. Cognitive Diversity, Creativity, and Team Effectiveness: The Mediations of Inclusion and Knowledge Sharing. VINE J. Inf. Knowl. Manag. Syst. 2024, 54, 1379–1403. [Google Scholar] [CrossRef]
  70. Thou, M.; Jeffrie-El, M.; Holly, J., Jr.; Martin, A.; Blair, P.Q. Cognitive Diversity for Creativity and Inclusive Growth. Angew. Chem. Int. 2025, 64, e202415695. [Google Scholar] [CrossRef]
  71. Carmeli, A. The Relationship between Emotional Intelligence and Work Attitudes, Behavior, and Outcomes. J. Manag. Psychol. 2003, 18, 788–813. [Google Scholar] [CrossRef]
  72. Leung, A.K.Y.; Cohen, D. Within- and Between-Culture Variation: Individual Differences and the Cultural Logics of Honor, Face, and Dignity Cultures. J. Pers. Soc. Psychol. 2011, 100, 507–526. [Google Scholar] [CrossRef]
  73. Gong, Z.; Chen, Y.; Wang, Y. The Influence of Emotional Intelligence on Job Burnout and Job Performance: Mediating Effect of Psychological Capital. Front. Psychol. 2019, 10, 2707. [Google Scholar] [CrossRef]
  74. Chen, Y.C.; Huang, Z.L.; Chu, H.C. Relationships between Emotional Labor, Job Burnout, and Emotional Intelligence: An Analysis Combining Meta-Analysis and Structural Equation Modeling. BMC Psychol. 2024, 12, 672. [Google Scholar] [CrossRef]
  75. Zhao, H.; Jiang, J. Role Stress, Emotional Exhaustion, and Knowledge Hiding: The Joint Moderating Effects of Network Centrality and Structural Holes. Curr. Psychol. 2022, 41, 8829–8841. [Google Scholar] [CrossRef]
  76. Aljaier, O.; Alzubi, A.; Khadem, A.; Iyiola, K. Exploring the Impact of Workplace Hazing on Deviant Behavior in the Hospitality Sector: The Roles of Emotional Exhaustion and Hope and Optimism. Behav. Sci. 2025, 15, 129. [Google Scholar] [CrossRef] [PubMed]
  77. Stein, M.; Schümann, M.; Vincent-Höper, S. A Conservation of Resources View of the Relationship between Transformational Leadership and Emotional Exhaustion: The Role of Extra Effort and Psychological Detachment. Work Stress 2021, 35, 275–295. [Google Scholar] [CrossRef]
  78. Chou, H.H.; Fang, S.C.; Yeh, T.K. The Effects of Facades of Conformity on Employee Voice and Job Satisfaction: The Mediating Role of Emotional Exhaustion. Manag. Decis. 2020, 58, 417–437. [Google Scholar] [CrossRef]
  79. Connelly, C.E.; Černe, M.; Dysvik, A.; Škerlavaj, M. Understanding Knowledge Hiding in Organizations. J. Organ. Behav. 2019, 40, 779–782. [Google Scholar] [CrossRef]
  80. Rybowiak, V.; Garst, H.; Frese, M.; Batinic, B. Error Orientation Questionnaire (EOQ): Reliability, Validity, and Different Language Equivalence. J. Organ. Behav. 1999, 20, 527–547. [Google Scholar] [CrossRef]
  81. Aaker, D.A.; Day, G.S. The Perils of High-Growth Markets. Strateg. Manag. J. 1986, 7, 409–421. [Google Scholar] [CrossRef]
  82. Kline, R.B. Principles and Practice of Structural Equation Modeling, 3rd ed.; Guilford Press: New York, NY, USA, 2011. [Google Scholar]
  83. Sarstedt, M.; Ringle, C.M.; Hair, J.F. Partial Least Squares Structural Equation Modeling. In Handbook of Market Research; Springer International Publishing: Cham, Switzerland, 2022; pp. 587–632. [Google Scholar]
  84. Enzmann, D.; Schaufeli, W.B.; Janssen, P.; Rozeman, A. Dimensionality and Validity of the Burnout Measure. J. Occup. Organ. Psychol. 1998, 71, 331–351. [Google Scholar] [CrossRef]
  85. Hu, L.; Bentler, P.M. Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives. Struct. Equ. Model. 1999, 6, 1–55. [Google Scholar] [CrossRef]
  86. Hoyle, R.H. The Structural Equation Modeling Approach: Basic Concepts and Fundamental Issues. In Structural Equation Modeling: Concepts, Issues, and Applications; Hoyle, R.H., Ed.; Sage Publications: Thousand Oaks, CA, USA, 1995; pp. 1–15. [Google Scholar]
  87. Byrne, B.M. Structural Equation Modeling with Mplus; Routledge: New York, NY, USA, 2013. [Google Scholar]
  88. Field, A.P. Discovering Statistics Using IBM SPSS Statistics: And Sex and Drugs and Rock ‘n’ Roll, 4th ed.; Sage Publications: London, UK, 2013. [Google Scholar]
  89. Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E. Multivariate Data Analysis, 7th ed.; Pearson: Upper Saddle River, NJ, USA, 2013. [Google Scholar]
  90. Fornell, C.; Larcker, D.F. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  91. Hayes, A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach, 3rd ed.; The Guilford Press: New York, NY, USA, 2022. [Google Scholar]
Systems 13 00195 g001
Figure 1. Conceptual model.
Figure 1. Conceptual model.
Systems 13 00195 g001
Systems 13 00195 g002
Figure 2. Path model. Note: * p < 0.05, *** p < 0.001; ns, not significant.
Figure 2. Path model. Note: * p < 0.05, *** p < 0.001; ns, not significant.
Systems 13 00195 g002
Systems 13 00195 g003
Figure 3. Moderation effect of KD between CQ and EEX.
Figure 3. Moderation effect of KD between CQ and EEX.
Systems 13 00195 g003
Systems 13 00195 g004
Figure 4. Moderation effect of KD between EI and EEX.
Figure 4. Moderation effect of KD between EI and EEX.
Systems 13 00195 g004
Table 1. Constructs and measurement sources.
Table 1. Constructs and measurement sources.
Constructs Source
Cultural Intelligence (CQ)Earley & Stanford [31], Ang et al. [41],
Emotional Intelligence (EI)Darvishmotevali et al. [1]
Perceived Organizational Support (POS)Kurtessis et al. [59]
Cognitive Diversity (KD)Mathuki, E., Zhang, J. [69]
Emotional Exhaustion (EEX)Maslach & Jackson [58], Enzmann et al. [84]
Error Reduction (ER)Rybowiak et al. [80]
Task Performance (TP)K.-J. Chen et al. [18]
Table 2. Descriptive statistics and correlation results.
Table 2. Descriptive statistics and correlation results.
VariablesMeanSDCQEIPOSKDEEXERTP
CQ3.88570.356861
EI3.92330.322490.245 **1
POS3.88670.362380.349 **0.255 *1
KD3.8950.367270.493 ***0.374 **0.474 ***1
EEX3.84790.384830.526 ***0.408 **0.538 ****0.226 *1
ER3.01720.330550.315 **0.448 ***0.269 *0.441 **0.482 ***1
TP3.90350.367070.351 **0.348 **0.329 *0.461 **0.540 ***0.396 **1
Note: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001; KD, cognitive diversity; EEX, emotional exhaustion; ER, error reduction; TP, task performance; CQ, cultural intelligence; EI, emotional intelligence; POS, perceived organizational support.
Table 3. Construct reliability and validity.
Table 3. Construct reliability and validity.
Constructs Cronbach’s AlphaCRAVE
Cultural Intelligence 0.8650.860.57
Emotional Intelligence (EI)0.9260.9130.541
Perceived Organizational Support (POS)0.8030.8180.553
Cognitive Diversity (KD)0.8630.8610.572
Emotional Exhaustion (EEX)0.850.8520.56
Error Reduction (ER)0.7990.8020.535
Task Performance (TP)0.9020.9020.651
Table 4. Fit indices of the measurement model.
Table 4. Fit indices of the measurement model.
CMIN/DFSRMRGFIAFGITILCFIRSMEA
1.7880.04780.9010.9250.9500.9600.052
Table 5. Specific indirect effects.
Table 5. Specific indirect effects.
Path EffectBoot SEBoot LLCIBoot ULCIp
H8a: CQ-EEX-ER0.12950.03540.02780.17140.0044
H8b: CQ-EEX-TP0.13590.0350.0790.22010.000
H9a: EI-EEX-ER0.2940.01490.00440.06420.035
H9b: EI-EEX-TP0.01670.0140.05730.00080.035
H10a: POS-EEX-ER0.02110.01470.04870.00960.043
H10b: POS-EEX-TP0.03790.01850.07780.00530.0121
Note: EEX, emotional exhaustion; ER, error reduction; TP, task performance; CQ, cultural intelligence; EI, emotional intelligence; POS, perceived organizational support.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Bafa, T.A.; Zhang, M.; Chen, C. Integrating Cultural and Emotional Intelligence to Examine Newcomers’ Performance and Error Reduction: A Moderation–Mediation Analysis. Systems 2025, 13, 195. https://doi.org/10.3390/systems13030195

AMA Style

Bafa TA, Zhang M, Chen C. Integrating Cultural and Emotional Intelligence to Examine Newcomers’ Performance and Error Reduction: A Moderation–Mediation Analysis. Systems. 2025; 13(3):195. https://doi.org/10.3390/systems13030195

Chicago/Turabian Style

Bafa, Tesfaye Agafari, Mingyu Zhang, and Chong Chen. 2025. "Integrating Cultural and Emotional Intelligence to Examine Newcomers’ Performance and Error Reduction: A Moderation–Mediation Analysis" Systems 13, no. 3: 195. https://doi.org/10.3390/systems13030195

APA Style

Bafa, T. A., Zhang, M., & Chen, C. (2025). Integrating Cultural and Emotional Intelligence to Examine Newcomers’ Performance and Error Reduction: A Moderation–Mediation Analysis. Systems, 13(3), 195. https://doi.org/10.3390/systems13030195

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop