Does employee empowerment moderate the effect of situational and dispositional variables on emotional exhaustion differently? The COVID-19 crisis context

Jaya Addin Linando (Department of Management, Universitas Islam Indonesia, Yogyakarta, Indonesia)
M. Halim (Department of Management, Universitas Pembangunan Nasional Veteran Yogyakarta, Yogyakarta, Indonesia)

RAUSP Management Journal

ISSN: 2531-0488

Article publication date: 1 December 2022

209

Abstract

Purpose

Building on the conservation of resources (COR) theory, this study aims to investigate employee empowerment’s moderation effect on the relationship of situational (job satisfaction, affective commitment) and dispositional (positive affectivity, emotional intelligence) variables toward the emotional exhaustion of service employees amidst the pandemic.

Design/methodology/approach

In total, 288 service employees from various sectors in Indonesia participate as the study’s respondents. This study applies a two-stage structural equation modeling approach to test the hypotheses.

Findings

The results show that employee empowerment moderates situational and dispositional variables differently. While employee empowerment significantly influences situational variables, a different situation is found on dispositional variables, that employee empowerment does not significantly influence these variables. This study’s findings portray the COR theory in practice and clarify the importance of employee empowerment for employees with particular attributions.

Research limitations/implications

The present study bears four limitations: the cross-sectional design; no exploration of dispositional and situational variables’ antecedents; the findings are limited to the service workers; and lastly, this study only takes Indonesian samples.

Practical implications

From a practical perspective, this study reveals which type of service employees are responsive to empowerment policy and which are prone to experience emotional exhaustion, particularly during a crisis.

Social implications

By understanding what factors determine employee empowerment’s effectiveness, managers could maximize the impacts of their empowerment policies. Subsequently, it will create better service deliveries which might benefit the broader societal scope.

Originality/value

This study contributes to both theoretical and practical understanding. Theoretically, this study adds and promotes using a categorical lens to examine the pattern of interactions between organizations and employees.

Keywords

Citation

Linando, J.A. and Halim, M. (2022), "Does employee empowerment moderate the effect of situational and dispositional variables on emotional exhaustion differently? The COVID-19 crisis context", RAUSP Management Journal, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/RAUSP-06-2022-0168

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Jaya Addin Linando and M. Halim.

License

Published in RAUSP Management Journal. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode


1. Introduction

More than one year after the first detected case, the COVID-19 pandemic still becomes a significant concern worldwide. Particularly for service workers, the pandemic brought many challenges as it affected their emotional health and intensified the unpredictable customer emotions they have to serve (Loustaunau et al., 2020). Most studies examine the COVID-19 effects on service workers either only focusing on the negative impacts of the pandemic (Johnson, Ebrahimi, & Hoffart, 2020; Rosemberg et al., 2021) or examining the work arrangement alternatives as triggered by the pandemic (Gross, Asante, Pawluk, & Niemeläinen, 2021; Linando et al., 2022). Only a handful of studies try to investigate the effort organizations and managers could perform to minimize the pandemic’s negative effects on their workers (Phungsoonthorn & Charoensukmongkol, 2022), creating a gap of knowledge on this particular front. The undesirable work features for service workers during the pandemic and the existing knowledge gap triggered the authors to investigate which employees would likely be able to cope well with working during the pandemic and which would unlikely keep up. Further, the authors also aim to add what could organizations and managers do to help service workers cope with the pandemic.

The authors set emotional exhaustion as the indicator of “failure” to cope with working amidst the pandemic. Meanwhile, various independent variables representing positive personal characteristics and individual–organizational relationships act as “the resources” employees possess to avoid emotional exhaustion at work. Such interpretations of “resources” align with previous studies (Charoensukmongkol & Puyod, 2022; Thanacoody et al., 2014). That depiction of the “battle” between “resources” against “failure” service workers endure during the pandemic is relevant to what Hobfoll (1989) postulates on the conservation of resources (COR) theory. Furthermore, this study also aims to test the role of employee empowerment as the source of resource enhancement at work amidst the COVID-19 pandemic. The addition of employee empowerment is also significant according to COR theory, wherein social support plays an essential role in the resource conservation process (Hobfoll, 2001). Accordingly, COR will serve as the basic theory to explicate this study’s argumentation and discussion.

This study offers two contributions. First, from a theoretical angle, this study will extend the knowledge of variable categorizations. While the discourse of situational and dispositional attributions separation has been long established (Miller et al., 1981), to date, only a few management and organization studies (Chhabra & Srivastava, 2022; Ilies et al., 2011) apply clustered situational and dispositional variables interplay within a single frame. Such a situation restricts understanding of how different variable categories react to particular variables. The present study aims to complement the scant literature by depicting the unique categorical comparative analysis in the COVID-19 pandemic context. The authors examine the effects of employee empowerment on two variable categories: situational (affective commitment and job satisfaction) and dispositional attribution (positive affectivity and emotional intelligence).

Second, this study presents information to help managers craft practical organizational policies. During the crisis, organizations should concentrate on managing resources strategically (Drucker, 2012), making an effort to comprehend which employee’s resources (situational, dispositional, both or none) will productively react to organizational strategy (employee empowerment), becoming more relevant than ever. The findings of this study will reveal to which type of employees an employee empowerment policy will work. In addition, this study will also show which type of employees are prone to experience emotional exhaustion amidst the COVID-19 crisis so that managers can pay particular attention to them.

2. Literature review

This study applies the COR theory (Hobfoll, 1989) as the theoretical framework to explain the interplay between tested variables. The COR theory has been established as a reliable basis for understanding the processes involved in experiencing and coping with stress (Hobfoll, 2001). The COR theory explains that individuals are motivated to protect their current resources (conservation) and acquire new resources (acquisitions) (Hobfoll, 1989). The present study interprets selected situational and dispositional variables as the resources employees possess.

Researchers (Mischel, 1968; Storms, 1973) propose that two main attributions generally explain how humans behave. The first is dispositional, an internal driver of human behavior, including relatively stable features such as personality, traits, attitudes and desires (Miller et al., 1981; Storms, 1973). The second is situational, a situation-related behavior triggered by external stimuli (Miller et al., 1981). This study categorizes positive affectivity and emotional intelligence as dispositional variables because of their personality-like and stable features (Mayer & Salovey, 1997; Watson et al., 1988). On the other hand, the degree of job satisfaction and affective commitment depends on external stimuli such as culture and leadership style (Lok & Crawford, 2001), which act as situational variables.

2.1 Hypotheses justifications

Job satisfaction is the satisfaction measure of workers toward their job-related factors such as the relationship with their supervisor, benefits, peers or the job itself (Locke, 1969). The authors argue that job satisfaction negatively influences emotional exhaustion. The claim is based on Eagly and Chaiken’s (1993) assertion that individuals who evaluate an object favorably tend to engage in behaviors that support the object and vice versa. Job satisfaction indicates the favorable assessment employees give toward their job, making those satisfied with their jobs unlikely to experience emotional exhaustion as it might hinder their job progression.

During the pandemic, workers are exposed to many uncertainties at work, enhancing the stress level in their working circumstances (Charoensukmongkol & Suthatorn, 2021). In working during the pandemic, job satisfaction acts as a source of resilience (Giménez-Espert et al., 2020), enabling the workers to cope with unprecedented extreme circumstances. In addition, within various service sector occupations, job satisfaction has been proven to negatively influence emotional exhaustion (Mena & Bailey, 2007; Saxton et al., 1991). To verify this argumentation, the authors propose the following hypothesis:

H1a.

Job satisfaction negatively influences emotional exhaustion during the COVID-19 pandemic.

The authors estimate that affective commitment negatively impacts emotional exhaustion because of the COVID-19 pandemic, which made the professional sphere uncertain. Such a situation may embolden the risk of emotional exhaustion, whereas commitment may lessen the uncertainty (Tang & Vandenberghe, 2020). Affective commitment also plays a role in buffering the instance of emotional exhaustion among employees (Öztürk et al., 2017); other studies (Lapointe, Vandenberghe, & Panaccio, 2011) empirically find that affective commitment negatively influences emotional exhaustion. In addition, recent studies on the affective commitment during the pandemic reveal that affective commitment links to positive organizational outcomes that conceptually contradict emotional exhaustion. For instance, affective commitment relates to job-related well-being (Mihalache & Mihalache, 2022), organizational citizenship behavior (Alshaabani et al., 2021) and presenteeism (El-Kurdy et al., 2022) during the pandemic. Based on those argumentations, the proposed hypothesis is as follows:

H1b.

Affective commitment negatively influences emotional exhaustion during the COVID-19 pandemic.

Emotional intelligence is the ability to rationalize, access and produce the ideal emotions to enhance emotional and intellectual growth (Mayer & Salovey, 1997). Empirical studies (Chan, 2006; Moon & Hur, 2011) find that emotional intelligence negatively relates to emotional exhaustion. During COVID-19, some studies (Moroń & Biolik-Moroń, 2021; Sun et al., 2021) found that emotional intelligence relates negatively to undesirable emotions management. It might be because of the emotional intelligence feature as an ability to regulate and perform an accurate rationale of emotions (Mayer et al., 2008). Therefore, emotion management is one of the critical factors determining individuals’ survival amidst the pandemic (Dowrick et al., 2021). Consequently, it is logical to infer that an individual with good emotional management can deal well with emotional exhaustion during the pandemic:

H1c.

Emotional intelligence negatively influences emotional exhaustion during the COVID-19 pandemic.

Positive affectivity defines positive emotions people possess and determines how they interact with environments (Ashby et al., 1999). A person with positive affectivity will feel passionate, focused and energetic (Watson et al., 1988). Empirical research (Lee & Chelladurai, 2016; Linando & Sitalaksmi, 2017) discovered that positive affectivity negatively relates to emotional exhaustion. As individuals with positive affectivity tend to experience pleasurable moods, they should be spirited at work and consequently implausible to encounter emotional exhaustion. The authors argue that employees with a high degree of positive affectivity will likely cope with the work challenges amidst the pandemic. That is because those workers with positive affectivity tend to have good resilience to deal with the crisis, as also proven by Zhang et al.’s (2021) study of workers’ affectivity during the pandemic. Hence, the authors postulate that those employees with a high degree of positive affectivity will be more immune from experiencing emotional exhaustion during the pandemic:

H1d.

Positive affectivity negatively influences emotional exhaustion during the COVID-19 pandemic.

2.2 Moderating role of employee empowerment

The word “empowerment” has various dimensions and a broad range of definitions. However, in essence, empowerment relates to power authorization (Honold, 1997). In the service sector context, it plays an imperative role in ensuring organization and customers relationship transpires in harmony (Lashley, 1999). That is because, in service sectors, employees are commonly interpreted as “the service” given by the company (Chebat & Kollias, 2000). The authors argue that using employee empowerment during the pandemic will positively impact the workers. The ground for such a claim is Morris and Feldman’s (1996) assertion that four critical emotional work dimensions affect emotional exhaustion:

  1. emotional display frequency;

  2. attentiveness to required display rules;

  3. variety of displayed emotions; and

  4. emotional dissonance (Morris & Feldman, 1996).

During the COVID-19 pandemic, those dimensions were distorted in practice.

For instance, many questions might emerge about whether the workers still need to maintain the emotional display’s standard duration while delivering online services or whether they still need to express various emotions. The pandemic also dismisses or decreases the degree of supervision. Consequently, it declines work ambiguity and uncertainty as the workers become more independent and are expected to make decisions on their own. The low degree of ambiguity and uncertainty makes the workers more adaptable to delivering services (Chebat & Kollias, 2000), which the authors posit will decrease emotional exhaustion. The argument is in line with other researchers’ arguments (Hochschild, 2003; Rafaeli & Sutton, 1987) that autonomy given to workers to express their emotions at work will lead to positive outcomes.

Albeit both selected dispositional and situational variables in this study act as favorable factors for the workers, the authors argue that employee empowerment will only enhance the negative impact of situational variables toward emotional exhaustion. This statement is grounded on Thomas and Velthouse’s (1990) explanation that the empowerment process involves the interaction between the work context and individual personality. Hence, empowerment will more likely affect situational variables rather than dispositional variables. Researchers (Campbell, 1963; Heider, 1958) also commonly argue that dispositional variables tend to be stable in various circumstances regardless of external stimuli. Henceforth, the authors hypothesize the following:

H2.

Employee empowerment significantly enhances the negative relationship between situational variables and emotional exhaustion.

3. Method

3.1 Research design and respondents

The data were gathered using online questionnaires. Primarily, the questionnaires were distributed through the authors’ and their colleagues’ social media groups, making the respondent reach beyond the regional (province, in Indonesia) scope. This study applied a convenience sampling approach, and it does not limit the sectors – all service business workers in Indonesia might fill out the questionnaire. The respondents were also informed that the data was anonymous and would only be used for academic research purposes, and they consented to it. Firstly, the authors obtained 303 replies, which were then filtered by omitting the respondents who stopped working because of the COVID-19 pandemic. Finally, 288 replies were further examined. Table 1 shows the detailed descriptive data.

3.2 Measures

All measurements use a six-point Likert scale to deter central tendency bias, with 1 = “strongly disagree” to 6 = “strongly agree.” The questions are in Bahasa Indonesia to suit the language used by the respondents. All scales were translated from English into Bahasa Indonesia by a competent translator company: the Center for International Language and Cultural Studies (CILACS).

This study uses Maslach and Jackson’s (1981) scale, which consists of nine items to assess emotional exhaustion. The measurement for emotional exhaustion happened in the context of working during the COVID-19 pandemic. This study uses Seashore et al.’s (1982) scale, which consists of three items to assess job satisfaction. This study uses Allen and Meyer’s (1990) scale, which consists of eight items for affective commitment to measure organizational commitment. To assess emotional intelligence, this study uses the Wong and Law Emotional Intelligence Scale (Wong & Law, 2002). The present study treated emotional intelligence as a unidimensional construct aligned with the commonly applied practice in management studies (Schlaegel et al., 2022).

To assess positive affectivity, this study uses I-PANAS-SF (Thompson, 2007), which consists of five items. Lastly, this study uses the five employee empowerment items proposed by Hayes (1994). This study also controlled five demographic variables that have been found to be significantly related to emotional exhaustion which are age, gender (1 = male, 2 = female), marital status (1 = single, 2 = married) and work tenure (1 = <2 years, 2 = 2–8 years, 3 = >8 years). In addition, the authors also controlled work mode [1 = work from home (WFH), 2 = work from office (WFO) with adjustments, 3 = mix between WFH and WFO]. Most respondents work in the educational sector (83,3%), so the authors also controlled the work sector (1 = educational sector, 2 = non-educational sector).

4. Data analysis and results

4.1 Preliminary analysis of the measurement model

Before testing the hypotheses, this study first conducted a confirmatory factor analysis using AMOS 26 to test the research constructs’ validity. Then, following the recommendations from Hair, Black, Babin, and Anderson (2014), this study removed indicators to increase model fit and the average variance extracted (AVE) from <0.50 to >0.50. Finally, based on the factor loadings and standardized residual covariances, the authors removed EE_2, AC_3 and AC_7 to improve the model fit and AVE. Table 2 shows that the proposed research model has met convergent validity. In particular, the composite reliability (CR) and Cronbach’s alpha are above the threshold (>0.70), as recommended by Anderson and Gerbing (1988). The results presented in Table 2 show that the factor loadings are all above the threshold (>0.50): CR ranged from 0.799 to 0.928, while AVE ranged from 0.503 to 0.678. These results confirm sufficient convergent validity for the constructs of this study.

For discriminant validity assessment, the square root of AVE is compared with the between-constructs correlation for each variable. The results show that the square roots of AVE for all variables are greater than between constructs correlation; hence, the results fulfill discriminant validity criteria (Hair et al., 2014). After testing the constructs’ validity, this study assessed the measurement model’s goodness of fit (GOF) indices. The six-factors model has χ2 = 2122,549, RMSEA = 0.054 (i.e. <0.08) which is acceptable (Kline, 2015); SRMR = 0.063, CMIN/DF = 2.135, CFI = 0.902 and TLI of 0.900 also meet the threshold (Hair et al., 2014). Based on the overall evaluation of the GOF measurement model, the proposed model has met the model fit so that the GOF measurement model in this study can be accepted.

Because all measurements are collected from a common source, common method bias may exist in the data. Therefore, the authors conducted Harmans’ single-factor test per Podsakoff et al.’s (2003) suggestion. The results of the fit statistic showed that the single-factor model did not fit the data well (χ2 = 8,421.114, p < 0.001; RMSEA = 0.137; CFI = 0.328; SRMR = 0.238). These results suggest that common method bias is not an issue in the observed data.

4.2 Hypotheses testing

This study used structural equation modeling (SEM) to examine the hypotheses. The control variables were entered into Step 1, and the independent variables were entered into Step 2. The model in Step 2 shows that job satisfaction negatively relates to emotional exhaustion (β = −0.305, p < 0.01). Therefore, H1a is supported. Affective commitment (β = −0.209, p < 0.01), positive affectivity (β = −0.241, p < 0.01) and emotional intelligence (β = −0.151, p < 0.01) also associate negatively with emotional exhaustion. Therefore, H1b–d are also supported. Table 3 shows the detailed testing results.

To test H2, this study first tested the interaction of all research variables using the mean-centered approach, as Aiken and West (1991) suggested. Then, following the approach proposed by Baron and Kenny (1986), this study built one additional SEM step to examine the moderating effects of employee empowerment. The third model examines the effect of the interaction terms on the dependent variable. The interaction between the situational variables and employee empowerment in this study was assessed by examining the relationship between the situational variables and emotional exhaustion at high (1 SD above the mean) and low (1 SD below the mean) values of employee empowerment.

Step 3 indicates that the interaction effect between job satisfaction and employee empowerment weakens emotional exhaustion (β = −0.173, p < 0.05) when employee empowerment is high. Step 3 also shows that the interaction effect of affective commitment and employee empowerment weakens emotional exhaustion (β = −0.184, p < 0.05) when employee empowerment is high. Employee empowerment moderated the negative relationship of both job satisfaction and affective commitment to emotional exhaustion, as shown by the simple slope analysis in Figure 1. When individuals have higher job satisfaction and affective commitment, a higher degree of employee empowerment will lower emotional exhaustion.

In addition to the main hypotheses testing, the authors also conducted an exploratory analysis concerning employee empowerment’s moderating effect on the relationship between dispositional variables and emotional exhaustion. The exploratory analysis results reveal insignificant moderation effect of employee empowerment on positive affectivity (β = 0.029, p > 0.05) and emotional intelligence (β = −0.126, p > 0.05) correlations toward emotional exhaustion. Overall, the results assert that employee empowerment moderates the effect of situational and dispositional variables on emotional exhaustion differently. Furthermore, the authors address the moderator’s effect size (f2) to present the findings comprehensively. Kenny (2018) classifies interaction terms f2 of 0.005, 0.01 and 0.025 as small, medium and large, respectively. The effect size of the interaction term in the present study has a value of 0.094, indicating a large effect.

5. Discussion

The findings that all independent variables negatively influence emotional exhaustion are hardly surprising as both theoretical perspectives and past empirical findings (Chan, 2006; Judge et al., 2009; Lapointe et al., 2011; Saxton et al., 1991) reach similar conclusions. During the pandemic, like in any other standard (not crisis) conditions, employees with a high degree of positive affectivity, emotionally intelligent, satisfied with their job and affectively committed to their organization tend to be able to cope with emotional exhaustion at work. Nevertheless, this study provides fresh knowledge by revealing the different interaction effects on each tested variable category during the unprecedented COVID-19 crisis.

The moderation effect of employee empowerment only affects situational variables and does not affect dispositional variables. These different patterns explain Hobfoll, Halbesleben, Neveu and Westman (2018) corollaries in an empirical setting. Those having a high degree of selected dispositional variables (positive affectivity and emotional intelligence) are the ones who possess resources. They are less susceptible to resource loss and more capable of resource attainment. Those employees are naturally safe from stress and negative emotional experiences as they do not fulfill the three conditions where stress might occur: the resources are threatened; the resources are lost; and the effort to gain resources fails (Hobfoll et al., 2018). Henceforth, the existence of employee empowerment is unlikely to have much effect on employees with high dispositional aspects. The findings on the relationship between employee empowerment and dispositional variables align with the first Hobfoll et al.’s corollary.

On the other hand, the findings on the relationship between employee empowerment and situational variables explicate the second and third corollaries from Hobfoll et al. (2018). The second corollary covers resource loss, and the third corollary is about resource gain. Those losing resources, which in this study are shown as having a low degree of situational variables (unsatisfied and uncommitted), will likely repeat the loss of resources. Hence, when given more freedom to act independently (empowered), employees with low situational resources will have a higher degree of emotional exhaustion, which symbolizes losing other resources. A similar explanation applies to those possessing resources (satisfied and committed). Like the case of resource loss (Corollary 2), resource gain (Corollary 3) also has a spiraling nature. Those with strong resources will likely reiterate owning, gaining and preserving resources (lower degree of emotional exhaustion) when given the momentum (empowered).

These findings also explain the importance of resources on each employee’s perception. Those who already possess dispositional resources will not place empowerment as a valuable resource; hence, it does not impact them. In contrast, because situational resources are more fluctuating than dispositional variables, the employees whose resources are mainly situational will value empowerment more. That is because empowerment may act as the potential replacement to counterbalance the condition in case their situational resources are lost. This explanation is pertinent to Hobfoll’s (1989) thesis.

6. Limitations and suggestion

While the present study did not observe the common method bias threat according to a posteriori test, future studies may consider including a temporal separation survey to enhance the research design robustness a priori. Second, future researchers need to explore the nomological network of this research. This study did not test other antecedents in both dispositional and situational factors. The selected variables are also hypothesized to influence emotional exhaustion negatively. Another variable with another tone of hypothesis may generate a different finding pattern. Third, while this study may contribute to understanding service workers further, the findings might be attached to the context and cannot be fully generalized for other occupational types.

Furthermore, the majority of the respondents work in the educational sector. Future researchers may consider collecting respondents from various service sectors in a better composition to enhance the findings’ generalizability. Fourth, this study only takes an Indonesian sample. Future researchers may replicate the research model in other locations to further investigate the model’s universality.

7. Theoretical implications

The present study adds to the knowledge of the interaction of the tested variables, particularly in the context of crisis. Furthermore, following the limited extant studies in management and organization domains, this study stimulates the use of a categorical lens to see the pattern of interactions beyond single variables. The present study provides evidence for the use of dispositional and situational categorization in management and organizational studies. Each variable category may have a different interaction pattern with particular variables. This study also contributes to the understanding of COR theory, wherein different resources (dispositional or situational) bear different resource conservation results. This study’s empirical findings may also help future researchers better understand these three aspects:

  1. Hobfol’s resource corollaries in empirical settings;

  2. the subjective importance of resources; and

  3. and the rationale of replacement resources in practice.

8. Practical implications

This study focuses on service workers’ emotional exhaustion, especially during the COVID-19 pandemic that heavily impacted service businesses. The findings reveal that workers who possess positive affectivity are emotionally intelligent, satisfied with their job, are affectively committed to the organization and are relatively safe from emotional exhaustion. It means that companies should focus on employees who do not hold the abovementioned characteristics, as they are the ones prone to experience emotional exhaustion. Therefore, training programs that potentially develop positive affectivity and emotional intelligence may be fruitful. Furthermore, this study shows that employee empowerment will help to reduce emotional exhaustion, especially for employees who are affectively committed to the organization and satisfied with their job.

However, employee empowerment may not always have a positive impact. The findings show that employee empowerment has the opposite effect on employees who are unsatisfied with their job and not affectively committed to the organization. For these employees, empowerment will amplify the degree of emotional exhaustion instead. In conclusion, companies must understand their employees’ characteristics before creating organizational policies, as each employee may require unique treatment.

9. Conclusion

This study confirms the negative relationship between selected dispositional (positive affectivity and emotional intelligence) and situational variables (job satisfaction and affective commitment) toward emotional exhaustion. The results also confirm that the interaction between employee empowerment and situational factors plays an essential role in reducing emotional exhaustion. On the other hand, employee empowerment does not significantly affect the interaction between dispositional factors and emotional exhaustion. Drawing from the COR theory, this study proposes employee empowerment as one of the policies a company can produce to help its employees preserve the resources amidst the crisis. Nevertheless, empowerment should not be applied to all employees, considering it is a double-edged sword. It may turn out positive for employees with high situational variables and harmful for employees with low situational variables. Finally, this study portrays the logic of resource management during a crisis, specifically during the COVID-19 pandemic.

Figures

Moderating effects of employee empowerment

Figure 1.

Moderating effects of employee empowerment

Descriptive data

Data N (%)
Gender
Male 117 (40.6)
Female 171 (59.4)
Generation
Boomers and Gen X 179 (62.1)
Gen Y 97 (33.7)
Gen Z 12 (4.2)
Marital status
Single 47 (16.3)
Married 241(83.7)
Work tenure
<2 years 21 (7.3)
2–8 years 66 (22.9)
>8 years 201 (69.8)
COVID-19 work adjustment
Work from home (WFH) 194 (67.4)
Still work from office (WFO) with adjustments 70 (24.3)
Mix of WFH and WFO/work in shifts 24 (8.3)
Industry sector
Education 240 (83.3)
Non-education 48 (16.7)

Result of the measurement model, validity and reliability

Construct Total items After deletion Items Factor loadings α CR AVE
Emotional exhaustion 9 8 EE_1 0.753 0.907 0.904 0.544
EE_3 0.78
EE_4 0.699
EE_5 0.791
EE_6 0.855
EE_7 0.613
EE_8 0.743
EE_9 0.714
Positive affectivity 5 5 PA_1 0.791 0.911 0.913 0.678
PA_2 0.873
PA_3 0.72
PA_4 0.842
PA_5 0.879
Emotional intelligence 16 16 SEA 0.833 0.797 0.799 0.503
OEA 0.579
UOE 0.715
ROE 0.686
Self-emotion appraisal 4 4 SEA_1 0.651 0.824 0.832 0.560
SEA_2 0.837
SEA_3 0.857
SEA_4 0.616
Other’s emotion appraisal 4 4 OEA_1 0.615 0.838 0.842 0.581
OEA_2 0.641
OEA_3 0.871
OEA_4 0.878
Use of emotion 4 4 UOE_1 0.706 0.889 0.894 0.680
UOE_2 0.849
UOE_3 0.877
UOE_4 0.856
Regulation of emotion 4 4 ROE_1 0.870 0.918 0.922 0.747
ROE_2 0.894
ROE_3 0.778
ROE_4 0.909
Affective commitment 8 6 AC_1 0.869 0.904 0.907 0.625
AC_2 0.752
AC_4 0.623
AC_5 0.774
AC_6 0.717
AC_8 0.962
Job satisfaction 3 3 JS_1 0.889 0.701 0.764 0.532
JS_2 0.484
JS_3 0.756
Employee empowerment 5 5 Eemp_1 0.692 0.863 0.864 0.560
Eemp_2 0.767
Eemp_3 0.799
Eemp_4 0.700
Eemp_5 0.777

Interactive effect of employee empowerment on independent variables and emotional exhaustion

Variable Emotional exhaustion
Step 1
(β)
Step 2
(β)
Step 3
(β)
Gender 0.063
Age −0.221* −0.242** −0.239**
Marital status 0.141
Tenure 0.111
Sector 0.095
COVID-19 work adjustment effect 0.033
Job satisfaction −0.305** −0.331**
Affective commitment −0.209** −0.197**
Positive affectivity −0.241** −0.213**
Emotional intelligence −0.151** −0.164**
Employee empowerment −0.431** −0.459**
Job satisfaction × employee empowerment −0.173*
Affective commitment × employee empowerment −0.184*
Positive affectivity × employee empowerment 0.029
Emotional intelligence × employee empowerment −0.126
R2 0.515 0.609
Notes:

*p < 0.05; **p < 0.01

Author contributions are as follows: Jaya Addin Linando – Corresponding Author, Conceptualization (Lead); Data curation (Equal); Formal analysis (Equal); Funding acquisition (Lead); Investigation (Lead); Methodology (Supporting); Project administration (Lead); Resources (Lead); Software (Supporting); Supervision (Lead); Validation (Lead); Visualization (Supporting); Writing – original draft (Lead); Writing – review & editing (Lead).

M. Halim: Conceptualization (Supporting); Data curation (Equal); Formal analysis (Equal); Funding acquisition (Supporting); Investigation (Equal); Methodology (Lead); Project administration (Supporting); Resources (Supporting); Software (Lead); Supervision (Supporting); Validation (Supporting); Visualization (Lead); Writing – original draft (Supporting); Writing – review & editing (Equal).

References

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions (Vol. 11, p. 212). London: Sage Publications.

Allen, N. J., & Meyer, J. P. (1990). The measurement and antecedents of affective, continuance and normative commitment to the organization. Journal of Occupational Psychology, 63(1), 118. doi: 10.1111/j.2044-8325.1990.tb00506.x.

Alshaabani, A., Naz, F., Magda, R., & Rudnák, I. (2021). Impact of perceived organizational support on OCB in the time of COVID-19 pandemic in Hungary: Employee engagement and affective commitment as mediators. Sustainability, 13(14), 7800. doi: 10.3390/su13147800.

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411423. doi: 10.1037/0033-2909.103.3.411.

Ashby, F. G., Isen, A. M., & Turken, A. U. (1999). A neuropsychological theory of positive affect and its influence on cognition. Psychological Review, 106(3), 529550. doi: 10.1037/0033-295x.106.3.529.

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 11731182. doi: 10.1037//0022-3514.51.6.1173.

Campbell, D. T. (1963). Social attitudes and other acquired behavioral dispositions. Psychology: A study of a science. Study II. Empirical substructure and relations with other sciences (Vol. 6, pp. 94172). McGraw-Hill. Investigations of man as socius: Their place in psychology and the social sciences. doi: 10.1037/10590-003.

Chan, D. W. (2006). Emotional intelligence and components of burnout among Chinese secondary school teachers in Hong Kong. Teaching and Teacher Education, 22(8), 10421054. doi: 10.1016/j.tate.2006.04.005.

Charoensukmongkol, P., & Puyod, J. V. (2022). Mindfulness and emotional exhaustion in call center agents in the Philippines: Moderating roles of work and personal characteristics. The Journal of General Psychology, 149(1), 7296. doi: 10.1080/00221309.2020.1800582.

Charoensukmongkol, P., & Suthatorn, P. (2021). How managerial communication reduces perceived job insecurity of flight attendants during the COVID-19 pandemic. Corporate Communications: An International Journal, 27(2), 368387. doi: 10.1108/CCIJ-07-2021-0080.

Chebat, J. C., & Kollias, P. (2000). The impact of empowerment on customer contact employees' roles in service organizations. Journal of Service Research, 3(1), 6681. doi: 10.1177/109467050031005.

Chhabra, B., & Srivastava, S. (2022). Paved with good intentions: Role of situational and dispositional influences on employees' unethical pro-organizational behavior. International Journal of Organizational Analysis. doi: 10.1108/IJOA-03-2022-3191.

Dowrick, A., Mitchinson, L., Hoernke, K., Mulcahy Symmons, S., Cooper, S., Martin, S., Vera San Juan, N., & Vindrola-Padros, C. (2021). Re-ordering connections: UK healthcare workers' experiences of emotion management during the COVID-19 pandemic. Sociology of Health & Illness, 43(9), 21562177. doi: 10.1111/1467-9566.13390.

Drucker, P. (2012). Managing in turbulent times, London: Routledge.

Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes, New York, NY: Harcourt Brace Jovanovich.

El-Kurdy, R., El-Nemer, A., Yousef, A., Elsaidy, W., & Hamdan-Mansour, A. (2022). The moderation effect of affective commitment on the relationship between job stress and presenteeism among obstetric healthcare workers during COVID-19 pandemic. The Open Nursing Journal, 16(1), doi: 10.2174/18744346-v16-e2203090.

Giménez-Espert, M. D. C., Prado-Gascó, V., & Soto-Rubio, A. (2020). Psychosocial risks, work engagement, and job satisfaction of nurses during COVID-19 pandemic. Frontiers in Public Health, 8, 566896, available at: www.frontiersin.org/articles/10.3389/fpubh.2020.566896 doi: 10.3389/fpubh.2020.566896.

Gross, D. P., Asante, A., Pawluk, J., & Niemeläinen, R. (2021). A descriptive study of the implementation of remote occupational rehabilitation services due to the COVID-19 pandemic within a workers' compensation context. Journal of Occupational Rehabilitation, 31(2), 444453. doi: 10.1007/s10926-020-09934-7.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis: Pearson new international edition, 7th ed., Pearson Education, New York.

Hayes, B. E. (1994). How to measure empowerment. Quality progress, 27(2), 4146.

Heider, F. (1958). The psychology of interpersonal relations (Vol. 9, p. 326). John Wiley & Sons, New York, doi: 10.1037/10628-000.

Hobfoll, S. E. (1989). Conservation of resources: A new attempt at conceptualizing stress. American Psychologist, 44(3), 513524. doi: 10.1037/0003-066X.44.3.513.

Hobfoll, S. E. (2001). The influence of culture, community, and the nested-self in the stress process: Advancing conservation of resources theory. Applied Psychology, 50(3), 337421. doi: 10.1111/1464-0597.00062.

Hobfoll, S. E., Halbesleben, J., Neveu, J. P., & Westman, M. (2018). Conservation of resources in the organizational context: The reality of resources and their consequences. Annual Review of Organizational Psychology and Organizational Behavior, 5(1), 103128. doi: 10.1146/annurev-orgpsych-032117-104640.

Hochschild, A. R. (2003). The managed heart: Commercialization of human feeling, twentieth anniversary edition, with a new afterword (2nd ed.). University of California Press, California, available at: www.jstor.org/stable/10.1525/j.ctt1pp0cf

Honold, L. (1997). A review of the literature on employee empowerment. Empowerment in Organizations, 5(4), 202212. doi: 10.1108/14634449710195471.

Ilies, R., Johnson, M. D., Judge, T. A., & Keeney, J. (2011). A within-individual study of interpersonal conflict as a work stressor: Dispositional and situational moderators. Journal of Organizational Behavior, 32(1), 4464. doi: 10.1002/job.677.

Johnson, S. U., Ebrahimi, O. V., & Hoffart, A. (2020). PTSD symptoms among health workers and public service providers during the COVID-19 outbreak. Plos One, 15(10), e0241032. doi: 10.1371/journal.pone.0241032.

Judge, T. A., Woolf, E. F., & Hurst, C. (2009). Is emotional labor more difficult for some than for others? A multilevel, experience-sampling study. Personnel Psychology, 62(1), 5788. doi: 10.1111/j.1744-6570.2008.01129.x.

Kenny, D. A. (2018). Moderator variables: Introduction. Retrieved from https://davidakenny.net/cm/moderation.htm

Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). New York, NY: Guilford Publications.

Lapointe, É., Vandenberghe, C., & Panaccio, A. (2011). Organizational commitment, organization-based self-esteem, emotional exhaustion, and turnover: A conservation of resources perspective. Human Relations, 64(12), 16091631. doi: 10.1177/0018726711424229.

Lashley, C. (1999). Employee empowerment in services: A framework for analysis. Personnel Review, 28(3), 169191. doi: 10.1108/00483489910264570.

Lee, Y. H., & Chelladurai, P. (2016). Affectivity, emotional labor, emotional exhaustion, and emotional intelligence in coaching. Journal of Applied Sport Psychology, 28(2), 170184. doi: 10.1080/10413200.2015.1092481.

Linando, J. A., & Sitalaksmi, S. (2017). Does emotional labor mediate the relationship between affectivity and emotional exhaustion in Indonesian tourist village? (A study of Pentingsari village) [Universitas Gadjah Mada]. Retrieved from http://etd.repository.ugm.ac.id/penelitian/detail/130771

Linando, J. A., Halim, M., Rasman, R., & Arifin, A. H. (2022). Work flexibility arrangements for educators: Which one is best for whom? Insights from Indonesia. International Journal of Educational Management, 36(6), 970983. doi: 10.1108/IJEM-01-2022-0011.

Locke, E. A. (1969). What is job satisfaction? Organizational Behavior and Human Performance, 4(4), 309336. doi: 10.1016/0030-5073(69)90013-0.

Lok, P., & Crawford, J. (2001). Antecedents of organizational commitment and the mediating role of job satisfaction. Journal of Managerial Psychology, 16(8), 594613. doi: 10.1108/EUM0000000006302.

Loustaunau, L., Scott, E., Petrucci, L., & Stepick, L. (2020). Low-wage service workers are facing new emotional hazards in the workplace during COVID-19. The Conversation, Retrieved from http://theconversation.com/low-wage-service-workers-are-facing-new-emotional-hazards-in-the-workplace-during-COVID-19-140619

Maslach, C., & Jackson, S. E. (1981). The measurement of experienced burnout. Journal of Organizational Behavior, 2(2), 99113. doi: 10.1002/job.4030020205.

Mayer, J. D., & Salovey, P. (1997). What is emotional intelligence? In P. Salovey & D. J. Sluyter (Eds), Emotional development and emotional intelligence: Educational implications (pp. 334). New York, NY: Basic Books.

Mayer, J. D., Roberts, R. D., & Barsade, S. G. (2008). Human abilities: Emotional intelligence. Annual Review of Psychology, 59(1), 507536. doi: 10.1146/annurev.psych.59.103006.093646.

Mena, K. C., & Bailey, J. D. (2007). The effects of the supervisory working alliance on worker outcomes. Journal of Social Service Research, 34(1), 5565. doi: 10.1300/J079v34n01_05.

Mihalache, M., & Mihalache, O. R. (2022). How workplace support for the COVID-19 pandemic and personality traits affect changes in employees' affective commitment to the organization and job-related well-being. Human Resource Management, 61(3), 295314. doi: 10.1002/hrm.22082.

Miller, F. D., Smith, E. R., & Uleman, J. (1981). Measurement and interpretation of situational and dispositional attributions. Journal of Experimental Social Psychology, 17(1), 8095. doi: 10.1016/0022-1031(81)90008-1.

Mischel, W. (1968). Personality and assessment, Wiley, New York.

Moon, T. W., & Hur, W. M. (2011). Emotional intelligence, emotional exhaustion, and job performance. Social Behavior and Personality: An International Journal, 39(8), 10871096. doi: 10.2224/sbp.2011.39.8.1087.

Moroń, M., & Biolik-Moroń, M. (2021). Trait emotional intelligence and emotional experiences during the COVID-19 pandemic outbreak in Poland: A daily diary study. Personality and Individual Differences, 168, 110348. doi: 10.1016/j.paid.2020.110348.

Morris, J. A., & Feldman, D. C. (1996). The dimensions, antecedents, and consequences of emotional labor. The Academy of Management Review, 21(4), 9861010. doi: 10.2307/259161.

Öztürk, E. B., Karagonlar, G., & Emirza, S. (2017). Relationship between job insecurity and emotional exhaustion: Moderating effects of prevention focus and affective organizational commitment. International Journal of Stress Management, 24(3), 247269, doi: 10.1037/str0000037.

Phungsoonthorn, T., & Charoensukmongkol, P. (2022). How does mindfulness help university employees cope with emotional exhaustion during the COVID-19 crisis? The mediating role of psychological hardiness and the moderating effect of workload. Scandinavian Journal of Psychology, 63(5), 449461. doi: 10.1111/sjop.12826.

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879903. doi: 10.1037/0021-9010.88.5.879.

Rafaeli, A., & Sutton, R. I. (1987). Expression of emotion as part of the work role. The Academy of Management Review, 12(1), 2337. doi: 10.2307/257991.

Rosemberg, M. A. S., Adams, M., Polick, C., Li, W. V., Dang, J., & Tsai, J. H. C. (2021). COVID-19 and mental health of food retail, food service, and hospitality workers. Journal of Occupational and Environmental Hygiene, 18(4-5), 169179. doi: 10.1080/15459624.2021.1901905.

Saxton, M. J., Phillips, J. S., & Blakeney, R. N. (1991). Antecedents and consequences of emotional exhaustion in the airline reservations service sector. Human Relations, 44(6), 583595. doi: 10.1177/001872679104400604.

Schlaegel, C., Engle, R. L., & Lang, G. (2022). The unique and common effects of emotional intelligence dimensions on job satisfaction and facets of job performance: An exploratory study in three countries. The International Journal of Human Resource Management, 33(8), 15621605. doi: 10.1080/09585192.2020.1811368.

Seashore, S. E., Lawler, E. E., Mirvis, P., & Cammann, C. (1982). Observing and measuring organizational change: a guide to field practice, New York, NY: Wiley.

Storms, M. D. (1973). Videotape and the attribution process: Reversing actors' and observers' points of view. Journal of Personality and Social Psychology, 27(2), 165175. doi: 10.1037/h0034782.

Sun, H., Wang, S., Wang, W., Han, G., Liu, Z., Wu, Q., & Pang, X. (2021). Correlation between emotional intelligence and negative emotions of front-line nurses during the COVID-19 epidemic: A cross-sectional study. Journal of Clinical Nursing, 30(3-4), 385396. doi: 10.1111/jocn.15548.

Tang, W. G., & Vandenberghe, C. (2020). Is affective commitment always good? A look at within-person effects on needs satisfaction and emotional exhaustion. Journal of Vocational Behavior, 119, 103411. doi: 10.1016/j.jvb.2020.103411.

Thanacoody, P. R., Newman, A., & Fuchs, S. (2014). Affective commitment and turnover intentions among healthcare professionals: The role of emotional exhaustion and disengagement. The International Journal of Human Resource Management, 25(13), 18411857. doi: 10.1080/09585192.2013.860389.

Thomas, K. W., & Velthouse, B. A. (1990). Cognitive elements of empowerment: An “interpretive” model of intrinsic task motivation. The Academy of Management Review, 15(4), 666681. doi: 10.2307/258687.

Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect schedule (PANAS). Journal of Cross-Cultural Psychology, 38(2), 227242. doi: 10.1177/0022022106297301.

Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 10631070. doi: 10.1037/0022-3514.54.6.1063.

Wong, C. S., & Law, K. S. (2002). The effects of leader and follower emotional intelligence on performance and attitude: An exploratory study. The Leadership Quarterly, 13(3), 243274. doi: 10.1016/S1048-9843(02)00099-1.

Zhang, X., Jiang, X., Ni, P., Li, H., Li, C., Zhou, Q., Ou, Z., Guo, Y., & Cao, J. (2021). Association between resilience and burnout of front-line nurses at the peak of the COVID-19 pandemic: Positive and negative affect as mediators in Wuhan. International Journal of Mental Health Nursing, 30(4), 939954. doi: 10.1111/inm.12847.

Acknowledgements

Funding: This work was supported by Pusat Pengembangan Manajemen (PPM) UII.

Corresponding author

Jaya Addin Linando can be contacted at: addin.linando@uii.ac.idAssociate editor: Renata Schirrmeister

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