Int. Journal of Business Science and Applied Management, Volume 18, Issue 1, 2023
The Effect of Leader's Emotional Intelligence and Role-
Breadth Self-Efficacy on Proactive Behaviour at Work
Praise Choeni
Optentia Research Focus Area, North-West University
Vanderbijlpark 1900, South Africa
Sunday Samson Babalola*
Department of Management, Walter Sisulu University
Butterworth, 4960, South Africa
Tel: +27474016211
Chiyem Lucky Nwanzu
Department of Psychology, Delta State University
Abraka, Nigeria
The literature makes it clear that there is a need for proactivity among employees for the effective
functioning of an organisation. This study aimed to determine the effect of a leader's emotional
intelligence (LEI) and role-breadth self-efficacy (RBSE) on proactive behaviour at work (PBW). The
sample comprises 204 employees of selected customs clearing companies in Zimbabwe. A cross-
sectional design was adopted, and a self-administered questionnaire compiled from standardised scales
on the substantial variables was used for data collection. Data analysis showed that LEI and RBSE
independently and jointly predict PBW, and the relationships are of practical value, as indicated by the
large effect sizes. However, compared to RBSE, LEI has a stronger relationship with PBW. The
conclusions are that LEI and RBSE are of value for PBW. Therefore, it is recommended that, in
enhancing PBW, the two factors should be considered in an organisation's work design, recruitment,
selection, and training and development programmes.
Keywords: leaders' emotional intelligence, role-breadth self-efficacy, proactive behaviour at work
Int. Journal of Business Science and Applied Management /
Knowledge of the factors that promote or hinder proactive practises is essential for the survival of
organisations. Today's employees face many job demands and increased work pressures, yet they are expected
to be effective and efficient (Davidescu et al., 2020; Griffin et al., 2007). Employees need to develop strategies
to undertake rapid changes, learn to think ahead and act to achieve the anticipated results and keep up with rapid
changes from the global market forces organisations (Turner, 2017). For example, due to recent technology,
employees may need to be equipped with additional skills to remain at the forefront of their industry (Osborne
& Hammoud, 2017), as the dynamic nature of the workplace requires the willingness and ability of employees
to act and make decisions proactively (Ellis, 2012). This may imply that much work is to be done, but fewer
people do it.
Proactive behaviour at work (PBW) refers to employees' anticipatory actions to improve work
circumstances and avoid uncertainties (Grant & Ashford, 2008). Parker and Collins (2010) emphasised that
PBW aims to bring about change within the organisation by improving work methods and initiating innovative
ideas, expressing concerns, and taking immediate action to prevent the reoccurrence of problematic situations.
Although much-documented evidence indicates the importance of PBW, promoting the behaviour is still
underexplored (Hong et al., 2016). It is worth further investigating the best possible ways to promote PBW.
It can be assumed that a leader's emotional intelligence (LEI) is crucial to enhancing PBW. Emotionally
intelligent leaders often help employees develop various ways of working without barriers to positive work
outcomes (Parker et al., 2010). LEI refers to leaders' ability to recognise and control their emotions and those of
others (Mayer et al., 2008). Emotional intelligence enables leaders to work with their employees effectively
(Coetzee & Schreuder, 2013). People who can control and understand their emotions are believed to be
emotionally intelligent (Shapiro, 2008). Van Rooy and Viswesvaran (2004) suggest that LEI can significantly
enhance employee PBW. Similarly, Whitehurst (2015) agreed that LEI is essential in cultivating and imparting a
compelling vision that enables employees to be passionate and proactive.
Role-breadth self-efficacy (RBSE) is also a motivating concept in promoting PBW (Cheah et al., 2019).
RBSE encompasses a person's perception of their ability to execute specific tasks and behaviours, focusing on
integrative and interpersonal roles. In simple terms, RBSE is how people feel confident enough to perform
broader and more proactive roles, even those that extend beyond traditionally prescribed technical requirements
(Parker, 1998). Therefore, it is vital to determine how an individual's confidence in their ability relates to PBW.
Additionally, more studies are needed as the extent to which LEI and RBSE influence PWB is unknown.
PBW has gained substantial research interest for two fundamental reasons. First, several studies have
linked PBW with effective organisational functioning. For example, there is a relationship between proactive
and innovative work behaviour (Nurjaman et al., 2019) and career success (Ling et al., 2017). Second, PBW can
be developed (Jia et al., 2020; Nguyen et al., 2020). To maximise the benefits of PBW, complete knowledge of
its predictors is necessary. Andersson (2015) emphasised the need for continuous identification of the
antecedents and consequences of PBW. This study will help to understand the conditions that cultivate
employee proactivity. It will help organisations stimulate and encourage proactive work behaviour. Moreover,
individual employees are bound to benefit by understanding how embracing proactive behaviour will foster
employees' ability to control their work and initiate action towards the desired results. The study will also help
organisations develop strategies that promote proactive behaviour among employees.
The role of LEI in leadership has received a great deal of discussion and support. Leaders with high
emotional intelligence can achieve positive affective states and withstand adverse emotional conditions without
negative results (Sistad, 2020). Emotional intelligence involves one's ability to understand one's own and others'
emotions (Davies et al., 1998). Accurately assessing and expressing one's emotions provides several advantages
in interpersonal relationships, such as self-confidence and easy rapport (Arora, 2017). The interpersonal benefits
offered to individuals with high emotion perceptions enable them to perform their duties, among others,
effectively. Emotional intelligence is necessary for leaders' effectiveness (Bartz et al., 2018). The influence of
LEI on leadership emergence, effectiveness, effective leader outcomes, and transformational leadership has
received much empirical confirmation. For example, the study by Liman et al. (2019) indicated that head
teachers of secondary schools' self-management and self-awareness significantly and positively affect their
performance. Emotional intelligence positively correlates with leadership emergence and transformational and
transactional leadership styles (McCullough, 2015). In a review of the literature, Chirania and Dhal (2017)
concluded that emotional intelligence has a strong positive correlation with entrepreneurial abilities.
Proactive behaviour is widely approached from three perspectives. One approach examines proactive
behaviour from a complementary perspective, categorising proactive behaviour into general and specific
proactive behaviour (Crant, 2000). Another approach classifies proactive behaviour into three distinct
Praise Choeni, Sunday Samson Babalola and Chiyem Lucky Nwanzu
categories: proactive organisational behaviour, individual proactive behaviour, and coworker-oriented proactive
behaviour (Hashemi et al., 2012). The third approach classifies proactive behaviour as proactive behaviour at
work or proactive work behaviour (Parker & Collins, 2010). In this study, proactive behaviour will be examined
following the third approach. According to Parker and Collins (2010), PBW is discretionary behaviour that aims
to change the internal organisational environment. These authors identified four constructs (taking charge,
individual innovation, problem prevention, and voice) that constitute PBW.
Taking charge occurs when employees seek to improve work performance, including work structures,
practises, and routines, which involves voluntary, constructive, and change-oriented efforts to bring about
positive and functional change (Morrison & Phelps, 1999). Taking charge can be equated to extra-role
behaviour because it is voluntary. However, it is distinct from other forms of behaviour in that it is naturally
change-oriented and aims at improvement. Problem prevention is self-directed and anticipatory action to prevent
the reoccurrence of work problems (Frese & Fay, 2001). Individual innovation is focused on perceiving new and
growing opportunities and producing and executing new ideas. It also involves novelty, differentiating it from
voice, and taking charge (Parker & Collins, 2010). Voice occurs when employees engage in constructive
expression to improve the work environment's standard procedures (Parker & Collins, 2010). Promotive
behaviour, like constructive challenges, tends to improve rather than merely criticise (LePine & Van Dyne,
Studies have identified various forms of relationship between LEI and proactivity. For example, team LEI
influenced the relationship between team empowerment and proactivity (Erkutlu & Chafra, 2012). Gupta and
Bajaj (2017) presented a conceptual framework linking LEI with employee creativity and theoretically
established the moderating role of the psychological climate in the relationship. The supervisor's emotional
intelligence (selfawareness, selfmanagement, and social awareness) significantly affected subordinates' daily
performance (Callahan, 2016). LEI significantly impacts team innovation performance, partially mediated by
leader-member exchange and team psychological safety (Wang et al., 2019). LEI moderates the relationship
between job characteristics and organisational citizenship behaviour (OCB) (Asadullah et al., 2020). Managers'
emotional intelligence significantly affected the OCB dimensions of altruism, courtesy, conscientiousness, and
civic virtue (Ölçer et al., 2014). Group LEI improves group performance by improving group-level cohesion,
and at the individual level, group LEI positively affects person-group fit (Zhang et al., 2020). Therefore, it is
hypothesised that:
H1. Leaders' emotional intelligence positively predicts proactive behaviour at work.
2.1. Role Breadth Self-Efficacy and Proactive Work Behaviour
RBSE is a unique, intentional, focused, and lasting phenomenon. There is a common understanding that an
individual's level of RBSE is based on one's ability to mobilise competence (Srikanth & Jomon, 2015). The
reason is that individuals should have confidence in their ability to achieve goals. Self-doubters usually suffer
setbacks and give up, while self-confident people will likely keep at it and succeed (Tsai et al., 2011).
Several studies highlight the importance of RBSE in improving employee PBW because employees are
confident to be proactive and overcome obstacles (Hwang et al., 2015; Martin et al., 2013). According to
(Parker et al., 2010), the belief that one can be effective at work is relevant in proactive behaviour because such
behaviour involves a high potential psychological risk to the individual. For example, proactive employees may
have to deal with resistant and inconvincible others. Therefore, RBSE gives employees the confidence to adapt
to proactivity outcomes. Axtell (2000) argued that RBSE is one of the most crucial determinants of employees'
tendency to develop ideas to improve things.
A study by López-Domínguez et al. (2013) revealed that employees with high RBSE perceive their job
roles more broadly and actively and perform a broader range of tasks than employees with lower RBSE. Kim et
al. (2015) also posited that proactivity at work is associated with many uncalculated risks. Therefore, employees
must believe they can bring positive organisational change against all obstacles. Employees with high RBSE are
known to see opportunities in their environment and perceive an increased probability of success through
proactive behaviour (Wu & Parker, 2017). Furthermore, Strauss et al. (2009) argued that employees should be
confident in their ability to engage in proactive behaviour because proactivity involves questioning the status
quo. Hence, it requires a person with a strong level of RBSE to perform such a question. RBSE is considered a
proximal predictor of PBW. Typically, employees with a high sense of RBSE develop strategic skills when
faced with challenges requiring proactive action (Griffin et al., 2007). According to Griffin et al. (2010), people
high in RBSE believe that acting proactively will succeed. Thus, they are motivated to engage in proactive
behaviour. Although people with low-role RBSE are less sure of their ability to perform tasks outside their
prescribed roles successfully, they perceive proactive behaviours as riskier.
The existing research reports that RBSE strongly predicts behaviours, such as change-oriented OCB and
PBW (López-Domínguez et al., 2013; Parker et al., 2006). Hwang et al. (2015) and Sonnentag and Spychala
(2012) found a link between RBSE and PBW. Den Hartog and Belschak (2012) also found that individuals with
high RBSE are more likely to display proactive behaviour than those with low RBSE. Employees requiring
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higher levels of job control and high time pressure experienced higher levels of RBSE, showing more proactive
behaviour (Sonnentag & Spychala, 2012). RBSE strongly predicted individual, team, and organisational
proactivity (Griffin et al., 2007). Ohly and Fritz (2007) emphasised that RBSE is crucial in improving
proactivity. RBSE had a positive effect on (1) pro-organisational proactive behaviour among those with a higher
collective self-concept, (2) pro-supervisor proactive behaviour among those with a higher relational self-
concept, and (3) pro-self-proactive behaviour among those with a higher individual self-concept (Hwang et al.,
2015). RBSE predicts PBW and mediates the relationship between a proactive personality and PBW
(Yuspahruddin et al., 2021). RBSE mediates the relationship between humble leadership and PBW (Li, 2021),
supportive supervision and job crafting (Han, 2020), job control, and proactive behaviour (Sonnentag &
Spychala, 2012). RBSE and the employees taking charge are significantly correlated, and the willingness to take
risks partially mediates the relationship (Lou, 2020). Role breadth self-efficacy moderates the link between
mutual support and sustainable job performance (Cheah et al., 2019).
H2: Role breadth self-efficacy predicts PBW.
LEI and RBSE are specific forms of emotional intelligence and self-efficacy, respectively. Studies have
identified various forms of relationship between generic emotional intelligence and generic self-efficacy. For
example, emotional intelligence, directly and indirectly, affects self-efficacy (Sun & Lyu, 2022). Self-efficacy
mediated the association between emotional intelligence and job satisfaction (Sökmen & Sarikay, 2022), team
cohesion (Black et al., 2019) and creativity (Qahir et al., 2022). Given this nomological network of emotional
intelligence and self-efficacy, it is argued that since LEI and RBSE independently impact PWB positively, they
will also jointly impact PWB positively. Therefore, it is hypothesised that:
H3: Leaders' emotional intelligence and role breadth self-efficacy jointly predict PBW
An overview of the existing literature reviewed a lack of studies on the relative contribution and influence
of situational factors and personality traits on employee behaviour, including PBW. Several studies that
examined personality and emotion never investigated the relative impact of the two classes of variables on
behaviour (Cooper, 2018). However, the few studies that have contributed to addressing the gap have published
insightful findings. For instance, Hasan and Eldous (2020) reported
that the situation is more influential than a
person's personality in predicting aggressive behaviour. Therefore, it is hypothesised that:
H4: Leaders' emotional intelligence and role breadth self-efficacy differ in their contribution to PBW.
3.1. Design and Participants
The research design was cross-sectional since data were collected from the sample at one point, and data
were obtained using questionnaires. Questionnaires were appropriate because they are less expensive, easy to
administer and enable data collection from a large pool of participants quickly and efficiently (Bless et al.,
2013). In terms of method, this study is quantitative, as a standardised questionnaire adapted from previous
studies was the only data collection technique (Ijigu et al., 2023). The quantitative approach is appropriate, as it
is beneficial when examining relationships and describing and determining cause-and-effect interactions
between variables (Zaman et al., 2021).
The target population was 600 employees working in customs clearing agent companies at the Beitbridge
border post in the Matabeleland South Province of Zimbabwe. The present study used multisampling techniques
to select the sample. The first step involved using a purposive sampling method to select the clearing agent
companies. The second step involved using simple random sampling to select respondents from participating
companies. Before administering the questionnaire, ethical approval and permission to conduct the investigation
were obtained from the Venda University Research and Ethics Office, after permission was obtained from the
Human Resources Department of each participating company for its employees to participate in the study.
Consequently, informed consent was obtained from the participants. Participants received the
questionnaires distributed at their workplaces and were asked to submit the completed questionnaires to their
supervisors. The supervisors subsequently handed the completed questionnaires to the research team. Three
hundred questionnaires were distributed to the participants of the clearing agent companies, and 235 were
returned in two weeks. This gives a response rate of 78%. However, after sorting through the questionnaires,
some were not completed adequately. Therefore, 204 (68 %) were used for data analysis. This return rate is
satisfactory, as it exceeded survey response rate levels and trends in organisational research (Mellahi & Harris,
2016). The sample size is adequate, as it met the maximum sample-to-item ratio of 5-1 and the sample-to-
variable ratio of 20-to-1 requirements (Memon et al., 2020; Tsang et al., 2017).
The participants consist of 116 (56.9%) males, 88 (43.1%) females, 82 (40.2%) senior employees, 79
(38.7%) junior employees, and 43 (21.1%) management staff. Seventy-six (13.2%) hold a diploma, 29 (14.2%)
Praise Choeni, Sunday Samson Babalola and Chiyem Lucky Nwanzu
a degree, 27 (13.2%) an ordinary level, 27 (23, 2%) certificate, 29 (14.2%) honours, 25 (12.3%) advanced level,
and 1 (1.5%) master's degree certificates. Educational qualifications indicate that the participants in this study
are sufficiently literate, which justified the adoption of the self-report measure in data collection (Nwanzu &
Babalola, 2020). One hundred and fifty-eight (77.5%) were permanent, 24 (11.8%) interns, 18 (8.8) temporary,
and 4 (1.9%) contract employees. The mean age of the participants was 30.4 years (SD, 7.62; 38 years). All
employee categories were represented in the sample. The analysis was carried out at the individual level.
3.2. Measures
3.2.1. Leaders' Emotional Intelligence Measure
The Wong and Law (2002) leaders' emotional intelligence scale was used. This is a 16-item measure, and
the responses to each item were rated using a 7-point Likert scale ranging from 1 = strongly disagree, 2 =
disagree, 3 = somewhat disagree, 4 = neutral, 5 = somewhat 6 = agree to 7 = strongly agree. A sample item on
the scale "has a good sense of why they have certain feelings most of the time." The reliability of this scale was
considered acceptable, with an α of 0.95 in one study (Boerrigter, 2017). For the present study, Cronbach's α of
0.86 was observed.
3.2.2. Measurement of Proactive Behaviour at Work
The measure adopted for proactive behaviour at work was a combination of items on three standardised
scales. These scales are Frese et al.'s (1997) 7-item scale on personal initiative, a 6-item scale on voice
behaviour developed by Van Dyne and LePine (1998), and Morrison and Phelps's (1999) 10-item scale on
taking charge behaviour. This combination was adjudged to represent the existing PBW models adequately.
Each item on the scale is rated using a 5-step scale ranging from 1 (absolutely false) to 5 (absolutely true. Some
items included in this instrument are "I am particularly good at realising ideas." "I often try to correct a faulty
procedure or practise," and "I get involved with issues affecting my company's quality of life." The three scales
with good psychometric properties are well adopted in the literature (e.g., Deng et al., 2020; Nsereko et al.,
2018). For the present study, the measure had an α of 0.78, adjudged adequate for internal consistency reliability
and the convergent aspect of construct validity (Field, 2018).
3.2.3. Role-Breadth Self-Efficacy Measure
Parker's (1998) RBSE scale was adopted. This is a five-point Likert scale with seven items and a response
option ranging from 1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, and 5 =
strongly agree. Some items included in this instrument are: "I would feel confident to represent my work area in
meetings with senior management" and "I would feel confident writing a proposal to spend money in my work
area." Previous studies reported that Cronbach's alpha for the scale ranges between α = 0.73 and α = 0.96 (Axtell
& Parker, 2003; Yuspahruddin et al., 2021). In the present study, an α of 0.86 was observed.
3.3. Statistical Tool
Regression analysis was then adopted as a statistical tool to test the hypotheses. Regression analysis is a
parametric test; therefore, assumptions associated with its use were considered in the design of this study. For
example, the Likert scaling format used to collect data met the requirement to collect data at the interval level.
The data collected for this study were independent of each other, which met the independent response
requirement (Nwanzu & Babalola, 2019). Scatter plots produced with IBM-SPSS on the data showed the
linearity of the relationship between each pair of variables. The Shapiro-Wilk statistics were significant at 0.12,
indicating a normal distribution. The Durbin-Watson test statistics of 1.93 and 1.97 were acceptable in
autocorrelation (Field, 2018).
3.4. Control Variables
In the data analysis, sociodemographic factors of age and gender were included as control variables. These
sociodemographic variables were treated as control variables; theories and empirical studies have linked them to
this study's independent and dependent variables. For instance, social role theory (Eagly, 1987) accounts for
gender differences. Socioemotional selectivity theory (Khetjenkarn & Agmapisarn, 2020) acknowledged age
differences in social behaviour. Empirically, gender and age influence employee perceptions of voice (Korkmaz,
2020; Sağlam et al., 2019).
3.4.1. Common Method Variance
Data for this study were collected with self-report measures. Since self-report measures have the potential
for common method variance (CMV), some design controls widely recommended in the literature were
implemented. CMV refers to systematic variance shared between study observed variables attributable to the
measurement method adopted rather than the constructs the variables represent (Cooper et al., 2020). The design
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control adopted includes having the items in the dependent variable first on the questionnaire before the items in
the independent variables, presenting the substantial variable of the study in different response options, ensuring
the anonymity and confidentiality of the respondents, and making the questionnaire and the items clear, brief,
and easy to comprehend (Liman et al., 2019; Nwanzu. & Babalola, 2020; Rodríguez-Ardura & Meseguer-
Artola, 2020).
3.4.2. Ethical Considerations
The study was conducted among clearing agent employees at the Beitbridge border, Zimbabwe, and ethical
issues were considered. The purpose of the study was made clear to the participants. For example, participants
were informed that their participation was voluntary and that they could withdraw from the research should they
wish to do so. In ensuring anonymity and confidentiality, participants' names or any form of identification were
not requested or obtained. Participants were also assured that there would be no harm in participating in the
4.1. Reliability and Validity
The reliability of the internal consistency of the measures was tested with Cronbach's alpha. The
coefficients obtained are presented in Table 1. Alpha statistics within α = 0.75 and α = 0.86 are considered
satisfactory (Wagner & Skowronski, 2019). The scales adopted in the present study have a high acceptance and
usage in the literature, indicating face and content validity (Karimi et al., 2020; Mirjana et al., 2018). The
Cronbach's alpha statistics obtained in this study also supported the convergent validity of the measures (Field,
2018). The moderate Pearson r obtained on LEI and PBW and RBSE and PBW also supported the convergent
validity of the measures. Table 1 also shows zero-order correlations in study variables. The zero-order
correlation revealed a significant positive relationship between the variables. The most vital degree of
relationship was between RBSE and PBW. The weakest relationship was between gender and LEI. The modest
zero-order correlation between the predictors and the criterion variables indicates the absence of
multicollinearity in the model.
Table 1: Mean, SD, Coefficient Alpha, and Zero-Order Correlations of The Study Variables
No. of
Note: ** < 0.001; * < 0.05
Table 2 shows a simple regression analysis predicting PBW from LEI. Statistics show that LEI
significantly predicted PBW (β = 0.33, 95% CI [0.04 - 0.10], t = 5.08, p < 0.001). Therefore, Hypothesis 1 was
supported. The observed B value indicates that a one-unit increase in LEI brings a 0.07-unit increase in PBW. R
also indicates that LEI accounts for about a 12% variance in PBW, and R
of 0.12 indicates a significant effect.
Analysis of variance test (ANOVA), F (1; 199) = 25.87, p < 0.001, indicates that the regression was statistically
significant, which means that PBW can be predicted from LEI (good model). The slight difference between R
(0.12) and adjusted R
(0.11), which is 0.01, indicates good cross-validation; this model can be applied to other
samples from the same population.
Table 2 also shows a simple regression analysis that predicts PBW from RBSE. Statistics show that RBSE
significantly predicted PBW (β = 0.45, 95% CI [0.22 - 0.38], t = 5.08, p < 0.001). Therefore, Hypothesis 2 was
supported. Analysis of the variance test (ANOVA), F (1; 202) = 50.60, p < 0.001, indicates that the regression
was statistically significant, which means that PBW can be predicted from LEI (good model). The observed B
value indicates that a one-unit increase in LEI brings a 0.30-unit increase in PBW. R
also indicates that LEI
accounts for about 0.19% variance in PWB, and R
of 0.20 indicates a significant effect. The slight difference
between R
(0.20) and adjusted R
(0.19, which is 0.01) indicates good cross-validation; this model can be
applied to other samples from the same population.
Praise Choeni, Sunday Samson Babalola and Chiyem Lucky Nwanzu
Table 2: Simple Regression of LEI and RBSE in PBW
Adj R
21.96{19.33, 24.59}
0.07 {0.04, 0.10}
15.88{12.13, 19.45}
0.30{.22, 0.38}
Criterion variable: PWB = proactive behaviour at work
Table 3 shows the variances of LEI and RBSE separately and jointly explained in PBW. The variable
entered on the first block is LEI. For this block, R = 48, p < 0.001 indicates support for hypothesis 3. The R
this block was 0.12, meaning LEI explains a 12% variance in PBW. The statistical significance of the f-ratio of
25.87 for this block or model is p < 0.001. This value is below the critical value of 0.05. The regression equation
explained a significant proportion of PBW variance at this first stage. The variable entered on the second block
is RBSE. Adjusted R
for this block or model is 0.21, meaning LEI and RBSE explain a 21% variance in PBW.
The statistical significance of the f-ratio for this block is p < 0.001. This value is lower than the critical value of
p < 0.05. The first and second steps of the regression equation explain a significant proportion of the PBW
variance. The R statistics for the first and second blocks indicate that the correlation between LEI and PWB was
0.48, while RBSE and PWB were 0.15 (48-33). These statistics indicate that, compared to RBSE, LEI has a
stronger relationship with PBW, supporting Hypothesis 4.
Table 3: Hierarchical Multiple Regression on the Contribution of LEI and RBSE to PBW
Change Statistics
Adj R
F Change
Sig F
This study determined the effect of LEI and RBSE on PWB among employees from customs clearing
companies in Zimbabwe. The study tested four hypotheses generated from the empirical and theoretical
literature. Hypothesis 1 proposed that LEI positively affects PBW, and the collected data confirmed the model,
which is in line with studies by Erkutlu and Chafra (2012), Gupta and Bajaj (2017), and Wang et al. (2019).
Several plausible explanations for this pattern of observation abound in the literature. For instance, leaders with
superior emotional appraisal skills can treat their employees with approval and respect, facilitating employee
behaviours that benefit them and the organisation (Moss et al., 2006). Leaders with high emotional perceptions
impart specific understanding and control in their workplace relationships, motivating employees to cherish
their leader and display desirable outcomes (Wong & Law, 2002). Leaders with high emotional intelligence can
realise their employees' needs; such leaders are likely to possess supportive behaviours that enhance proactivity
(Rahim & Malik, 2010). Since emotional intelligence consciously and subconsciously enables the evaluation
and adjustment of emotions, leaders with high emotional intelligence are likely to succeed in evoking positive
behaviours among their employees (Zineldin & Hytter, 2012).
Hypothesis 2 proposed that RBSE positively affects PBW, and the data confirmed the model. Some related
studies in the existing literature also reported similar observations (Hwang et al., 2015; Li, 2021; Sonnentag &
Spychala, 2012; Yuspahruddin et al., 2021). Several factors explained the positive effect of RBSE on PBW.
RBSE indicates confidence, which therefore assists employees in promoting being proactive and overcoming
obstacles (Hwang et al., 2015; Parker et al., 2010). RBSE gives employees the confidence they need to adapt to
proactivity outcomes. Employees with high RBSE are known to see opportunities in their environment and
perceive an increased probability of success through proactive behaviour (Wu & Parker, 2017). Individuals with
high RBSE believe that proactive behaviour will result in successful outcomes and are motivated to engage in
proactive behaviour. On the contrary, individuals with low-role RBSE are less sure of their ability to take on
Int. Journal of Business Science and Applied Management /
tasks outside their prescribed roles successfully, and they perceive proactive behaviours as carrying more risk
(Griffin et al., 2010).
Hypothesis 3 proposed that LEI and RBSE would have a combined positive effect on PBW, and data
analysis confirmed the model. Therefore, Hypothesis 3 was supported. This finding is related to Singh and
Pathardikar's (2011) observation that personality traits and emotional intelligence jointly predict leadership
effectiveness and the study by Estrada et al. (2016) that found personality variables and emotional intelligence
significantly impact problem-solving styles. These findings indicated that when these factors are combined, they
are favourably predisposed to PBW, thus likely resulting in a positive outcome.
Mathematically, the addition of two positives makes another positive. Hypothesis 4 proposed that LEI and
RBSE will differ in their contribution to PBW. This hypothesis was supported. The difference was in favour of
LEI, and this is because leadership in the organisation essentially controls the expression of personal
characteristics (including personality) and the behaviour of the employees. In addition to the positive significant
predictive relationship of LEI and RBSE on PBW, the observed effect sizes are large, indicating that the effect
is essential and of practical value.
5.1. Theoretical Contribution
This study has contributed to the LEI, RBSE and PBW literature. When examining LEI and RBSE as
predictors of PBW in a single study, this study has expanded the literature on the relationship between the three
variables. This study supported social role theory (Eagly, 1987) and socio-emotional selectivity theory
(Khetjenkarn & Agmapisarn, 2020) with the positive effect of LEI and RBSE on PBW when age and gender
were controlled. The present study has the potential to contribute to theory and practise.
5.2. Limitations and Recommendations for Future Research
Since the self-report measure adopted in the present study is mainly associated with weaknesses such as
social desirability bias, it is recommended that further studies collect data with interviews to obtain enough
subjective feedback from participants. This study was carried out in one occupation, which limits implications
for generalising the results. Therefore, it is recommended that further studies be carried out with other
occupational groups and larger companies to determine whether LEI and RBSE on PBW would remain the same
in different sectors and occupational groups. Furthermore, this study used a cross-sectional design with a weak
potential for cause-effect interpretation. Therefore, it is recommended that future studies embark on a
longitudinal study to determine whether the influence of LEI on PBW remains stable over time. Finally, this
study was limited to examining the direct effects of LEI and RBSE on PBW. As expected, intervening factors
are possible with the relationship between organisational behaviour variables. Therefore, it is recommended to
examine plausible mediators and moderators. Some researchers (e.g., Gupta & Bajaj, 2017) have suggested the
psychological climate as a mediating variable in LEI and innovative work behaviour.
5.3. Practical Implications
This study made observations that have practical value for organisational practises. First, LEI and RBSE
independently and jointly impact PWB in an organisationally desirable direction. Second, although LEI and
RBSE independently contribute positively to the employee expression of PBW, the former contributes more. A
practical lesson from these findings and related others is that organisations need emotionally intelligent leaders
with the characteristics that evoke PBW among employees. Providing organisations with emotionally intelligent
leaders is achievable through recruitment, selection, and training processes. Some studies (e.g., Gilar-Corbi et
al., 2018; Idowu & Adegboyega, 2020; Kotsou et al., 2019) have confirmed the efficacy of various methods and
programmes. Another practical implication is the need for organisations to have high RBSE employees. High
RBSE symbolises task confidence, and PBW results from felt task confidence in the employee. Again,
organisations could have high RBSE through work design, recruitment, selection, and training processes. The
efficacy of these practises been noted in the literature. For example, a longitudinal investigation revealed that as
a member of an active improvement group, increased task control, breadth of training, improved quality of
communication, and job enrichment were related to increased RBSE (Axtell & Parker, 2003; Parker, 1998).
5.4. Conclusions
The focus of this study was the influence of leaders' emotional intelligence and role breadth self-efficacy
on proactive work behaviour. The stepwise multiple regression analysis results indicated that LE and RBSE
contributed to proactive work behaviour. However, RBSE contributed the most. This clearly shows that an
organisation with emotionally intelligent leaders and high RBSE employees is bound to produce proactive
employees at work and thus enhance individual and organisational success.
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