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Effect of Employee Engagement on Turnover Intentions in Deposit
Money Banks in Delta State
1
Joseph E Ekpenyong,
2
Ebulogu Onyekachukwu Gladys,
3
De. Robert Ike Eke FCA,
1
Department of Business Administration, Well Spring University, Benin City, Edo State, Nigeria
2
Department of Business Education, Delta State University in affiliation with College of Education,
Edjeba, Warri, Delta state, Nigeria
3
Department of Accounting, Well Spring University, Benin City, Edo State, Nigeria
DOI:
https://dx.doi.org/10.47772/IJRISS.2025.91100452
Received: 11 November 2025; Accepted: 21 November 2025; Published: 17 December 2025
ABSTRACT
This study investigates the effect of employee engagement on turnover intentions in the banking industry in
Warri, Delta State, Nigeria. High employee turnover has become a critical challenge in the sector, disrupting
operations and increasing recruitment and training costs. Drawing on the behavioral, emotional, and cognitive
dimensions of employee engagement, the study examines how each dimension influences employees’
intentions to leave their organizations. A quantitative research design was employed, using structured
questionnaires administered to 316 bank employees selected through stratified random sampling. Data were
analyzed using descriptive statistics and multiple regression analysis. The findings revealed that behavioral
engagement (β = 2.030, p < 0.01), emotional commitment (β = 2.043, p < 0.01), and cognitive engagement (β
= 2.034, p < 0.01) each had a significant negative effect on turnover intentions. The model demonstrated strong
explanatory power, with an R² value of 0.66, indicating that 66% of the variation in turnover intentions could
be attributed to these engagement factors. The results suggest that employees who are behaviorally active,
emotionally connected, and cognitively involved are less likely to consider leaving their jobs. The study
concludes that fostering comprehensive engagement strategies—encompassing emotional attachment, active
participation, and intellectual involvement—can effectively reduce turnover intentions and enhance workforce
stability. It recommends that bank management in Nigeria’s banking sector prioritize initiatives that build
loyalty, promote involvement in decision-making, and encourage continuous professional development to
strengthen employee retention and organizational performance.
Keywords: Employee engagement, Turnover intentions, Behavioral engagement, Emotional commitment,
Cognitive engagement, Banking sector.
INTRODUCTION
Employee engagement refers to the emotional connection, enthusiasm, and dedication an employee exhibits
toward their job and organization—manifested when the employer creates conditions that enable greater
productivity, efficiency, and commitment. Engaged employees are more likely to experience higher job
satisfaction, stronger morale, reduced misconduct, and lower turnover intentions (Smith, 2024). Yet despite
employer efforts, many Nigerian organizations continue to struggle with maintaining sustained engagement,
resulting in declining job satisfaction and elevated turnover propensities. Indeed, employee engagement
reflects the emotional attachment an individual has to the organization and their work, emphasizing “the
involvement and enthusiasm of employees in their work and workplace” (Gallup, 2022).
Globally, the scale of disengagement is staggering: the Gallup 2022 Global Workplace Report found that 79%
of employees worldwide are not engaged—60% not engaged and 19% actively disengaged—thereby
undermining team performance and organizational success (Gallup, 2022). Theoretical anchors of the concept
trace back to William A. Kahn (1990), who conceptualized employee engagement as the harnessing of one’s
physical, cognitive, and emotional selves into role performance within an organisation. An organisation with
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high employee engagement would thus be expected to outperform one with low engagement (Kahn, 1990;
Wottard & Shuck, 2011).
In the context of Nigeria’s banking industry, the link between engagement and critical outcomes such as
retention, job satisfaction, and discretionary effort is particularly important. Banking institutions face tight
regulatory regimes, evolving digital services, competitive pressures, and an environment where employee
turnover can pose elevated risks (e.g., fraud, disruptions, loss of institutional knowledge). Given this,
investigating whether employee engagement can predict turnover intentions in the banking sector makes both
practical and academic sense.
Employee engagement can be broken down into three key dimensions:
• Behavioral engagement – the visible efforts and discretionary behaviors employees invest in their
work;
• Emotional commitment – the affective bond and sense of belonging employees feel toward the
organisation;
• Cognitive engagement – the psychological investment and mental focus devoted to one’s tasks.
Understanding how these dimensions jointly or separately influence turnover intentions is vital for
designing effective human-resource interventions.
Although the theoretical link between engagement and turnover intentions is well supported, there are key
gaps. Some research emphasises top-down managerial strategies (such as internal communication and
leadership behaviours) as primary drivers of engagement, while other studies emphasise bottom-up agency,
meaning employees’ own perceptions, meaning-making, and feedback processes. The divergence of
perspectives highlights the need for a more integrative theoretical framework that reconciles both managerial
control and employee agency.
Specifically for Nigerian banks, there is a paucity of empirical work examining how the three engagement
dimensions function as predictive determinants of turnover intentions. This study therefore investigates
employee engagement as a predictor of turnover intentions among employees of Deposit Money Banks in
Delta State, Nigeria. This study holds significance for multiple stakeholders. For bank managers and human-
resource professionals, it offers insights into which dimensions of engagement most influence retention,
enabling targeted strategies to reduce disruptive and costly employee turnover. For policy makers and
regulatory bodies (such as the Central Bank of Nigeria and the Chartered Institute of Personnel Management
of Nigeria), findings may inform sector-wide policies and frameworks aimed at improving employee welfare,
job satisfaction, and retention within the banking sector. Academically, it contributes to the literature on
organisational behaviour and employee retention by contextualising the engagement–turnover link within an
emerging-economy banking setting—specifically Delta State, Nigeria. For employees themselves, the
research underscores how meaningful engagement (via behavioral, emotional and cognitive investment) may
enhance organisational loyalty and job fulfilment. Finally, the study lays groundwork for future research in
other sectors and regions within Nigeria.
Geographically, this research focuses on Warri, Delta State—a major commercial and administrative hub in
southern Nigeria—and specifically on selected branches of commercial and micro-finance banks operating
there. Conceptually, the study is delimited to three constructs of employee engagement (behavioral, emotional,
and cognitive) and their relationship with turnover intentions as the dependent variable. The study population
comprises banking staff at various levels (frontline, customer-service, and middle-management), excluding
senior executives whose turnover drivers may differ. Temporally, the research focuses on engagement and
turnover intentions observed within the past four years (post-COVID-19), capturing recent economic,
technological and organisational changes in the banking industry. The broad objective of this study is to
determine if employee engagement—in the forms of behavioral engagement, emotional commitment, and
cognitive engagement—can predict job satisfaction and turnover intentions in Deposit Money Banks in Delta
State. The specific objectives are:
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1. Assess the effect of behavioral engagement on turnover intentions among bank employees in Deposit
Money Banks in Delta State.
2. Examine the impact of emotional commitment on employees’ intentions to leave the banks.
3. Investigate how cognitive engagement influences turnover intentions in the Deposit Money Banks in
Delta State.
LITERATURE REVIEW
2.1 Conceptual Review
2.1.1 Turnover Intentions
Employee turnover intentions refer to the psychological state in which an employee exhibits the desire or
intention to leave their current organization—whether due to low wages, job dissatisfaction, poor welfare, or
other unfavourable conditions. For example, early foundational work by James Mobley, Roderick Horner and
Dennis Hollingsworth (1978) defined turnover intentions as the thoughts an employee has about quitting his or
her job or finding a new job outside the workplace boundaries. Over time, research has identified multiple
antecedents of turnover intentions including job dissatisfaction (with aspects such as work environment, job
responsibilities, compensation, supervision), communication breakdowns, low employee engagement, limited
or perceived stalled career progression, and unfavourable work culture or environment.
The consequences of high turnover intentions can be significant for any organisation: actual turnover, leading
to recruitment and training costs; loss of organisational knowledge and talent; declines in productivity as
remaining employees may become demotivated; and weaker organisational performance due to loss of
continuity and institutional memory.
From a practitioner standpoint, turnover intentions signal an early warning: organisations can respond with
retention strategies (improving job satisfaction, enhancing engagement, supporting work-life balance),
managerial interventions (recognition, growth opportunities, supervisor support), and organisational
development initiatives (improving culture, communication, and career paths).
2.1.2 Employee Engagement
The concept of employee (or work) engagement is central in the retention literature. William Kahn (1990)
introduced engagement as the harnessing of organisational members’ selves to their work roles—people employ
and express themselves physically, cognitively, and emotionally during role performances. Over time, scholars
such as Wilmar Schaufeli & Arnold Bakker (2004) refined this into the psychological state of work engagement:
“a positive, fulfilling, work-related state of mind that is characterised by vigour, dedication and absorption.”
This definition emphasises three dimensions:
• Behavioural/Physical Engagement: the effort, initiative, attendance and extra role behaviours that go
beyond basic job requirements. Employees showing behavioural engagement are active, proactive, and
committed to organisational goals.
• Emotional Engagement (Emotional Commitment): the affective attachment and identification with
the organisation—feeling valued, belonging, proud, and emotionally connected to the workplace.
Employees high on emotional commitment display loyalty and resilience in the face of adversity.
• Cognitive Engagement: the mental investment, focus, absorption and thoughtful connection to work
tasks. Cognitively engaged employees see work as meaningful, seek to learn, innovate, and align their
thinking with organisational objectives.
Numerous empirical findings indicate that higher engagement (in its various dimensions) is associated with
better job performance, increased organisational citizenship behaviours, higher job satisfaction, and importantly
for this study, lower turnover intentions.
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2.1.3 Job Satisfaction
Job satisfaction remains a cornerstone concept in organisational behaviour and is frequently examined in relation
to turnover intentions and engagement. It describes an employee’s positive emotional response to their job after
evaluating various job facets (e.g., leadership style, clarity of role, reward systems, empowerment). In the
Nigerian context (and more broadly), researchers have shown that transformational leadership, clarity of job
responsibilities, fair and competitive rewards, and empowerment enhance job satisfaction, which in turn reduces
turnover intentions.
2.2 Theoretical Review
2.2.1 Social Exchange Theory
Originally proposed by George C. Homans (1958) Davlembayeva and Alamanos, (2025), Social Exchange
Theory (SET) posits that individuals engage in social interactions (including employee–employer relationships)
based on a cost–benefit calculation and expectations of reciprocity. In the employment context, when employees
feel that they receive organisational support, fair treatment, opportunities, and recognition, they are more likely
to reciprocate with loyalty, higher engagement, and lower intention to leave. In contrast, perceived imbalance
(high cost, low reward) drives withdrawal behaviours including turnover intentions.
2.2.2 Job Embeddedness Theory
Terence R. Mitchell (and colleagues) proposed Job Embeddedness Theory to explain retention through the
breadth of forces—on‐ and off‐the-job—that keep employees “stuck” or embedded in their current positions
(links, fit, sacrifice). There are on-the-job factors (organizational fit, relationships, career opportunities) and off-
the-job/community factors (family, community ties, local amenities). Meta-analytic evidence shows that higher
job embeddedness is negatively related to turnover intentions and actual turnover. For example, one meta-
analysis (N ≈ 42,907) found both on- and off-the-job embeddedness negatively correlated with turnover
intentions, even after controlling for job satisfaction and alternatives. (On-job embeddedness had stronger
negative associations).
PubMed
2.2.3 Turnover Models (Mobley, Price, Unified Model)
Classic turnover theory, such as the Mobley Model (1977) Hom, and Seo (2024), positions intention to quit as
a proximal antecedent to actual turnover, where job dissatisfaction, perceived alternatives, and thoughts of
quitting are critical stages. Price Model emphasises organizational commitment and job satisfaction. Later
unified turnover models synthesize the process: employee morale, market labour mechanisms, intentions to stay
or leave, and final turnover behaviour. These models provide a broad framework to locate the current study
(engagement → job satisfaction → turnover intention → turnover) within a decision-making process.
2.2.4 Theory of Planned Behaviour (TPB)
Theory of Planned Behaviour (Ajzen, 1991) provides another useful lens: individuals’ intentions (e.g., to quit)
are shaped by attitudes toward the behaviour (job), subjective norms (what others expect), and perceived
behavioural control (ease/difficulty of staying or leaving). In the workplace, job satisfaction and engagement
influence employees’ attitudes; work-life balance and organisational culture affect norms; and perceived
alternatives and constraints influence behavioural control — altogether shaping turnover intentions and
ultimately turnover.
2.3 Empirical Review
In the Nigerian banking context and globally, several studies bridge engagement, job satisfaction, and turnover
intentions. For example, a study on Pakistani banks found that employee engagement reduces turnover intentions
via intrinsic motivation mediation (Iqbal et al., 2025).
agasr.org A study on Pakistani private banks identified
work overload, employee engagement and job stress as significant predictors of turnover intentions.
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ojs.rjsser.org.pk Meta-analytic and field studies of job embeddedness confirm its strong negative relationship
with turnover intentions (Wang et al., 2024). PMC+1 In Nigeria, one study found job satisfaction, job stress,
organisational identification, justice and leader-member exchange influenced turnover intentions in banks.
HRMars Studies also show that work–life balance initiatives reduce turnover intentions among bank employees
in Rivers State. journaleconomics.org
2.4 Gaps in the Literature
While the literature is rich, several gaps remain. First, many existing studies use engagement as a unidimensional
construct (often emotional or general engagement) rather than examining behavioural, emotional and cognitive
dimensions separately. As some authors (e.g., Saks & Gruman, 2014) argue, a more multidimensional
perspective provides deeper insight into how engagement influences turnover intentions. Second, most empirical
research in Nigeria has been conducted at a broad national level or across sectors rather than in the banking
industry within specific states (such as Delta State) which have distinctive dynamics (stress, long hours, high
customer pressure). Third, much of the literature predates the post-COVID-19 era; given the shifts in employee
expectations and working arrangements since the pandemic, updated insights are needed. This study therefore
seeks to fill these gaps by examining all three dimensions of engagement (behavioural, emotional, cognitive) in
deposit money banks in Delta State, reflecting post-pandemic realities.
METHODOLOGY
3.1 Research Design
This study adopted a descriptive survey research design to investigate the effect of employee engagement
on turnover intentions in the banking industry in Delta State. This design was deemed appropriate as it allows
for the collection of data directly from respondents in their natural work environments, enabling the researcher
to describe, explain, and interpret the relationships among variables without manipulating them (Creswell &
Creswell, 2018).
3.2 Population of the Study
The population for this study comprised all employees working in the major commercial banks located in
Warri, Delta State. These include employees of banks such as First Bank of Nigeria, United Bank for Africa
(UBA), Zenith Bank, Guaranty Trust Holding Company (GTCO), and Access Bank, among others. Based on
available data from the Nigerian Deposit Insurance Corporation (NDIC, 2023), the estimated population of
bank employees in Warri, Delta State is approximately 1,500.
3.3 Sample Size and Sampling Technique
Using the Taro Yamane formula for determining sample size at a 95% confidence level and 5% margin of
error, the sample size was calculated as:
n=N1+N(e)2=15001+1500(0.05)2=316
Therefore, a sample size of 316 respondents was selected. A stratified random sampling technique was
used to ensure proportional representation from various banks and job categories.
3.4 Research Instrument
A structured questionnaire was developed and used for data collection. The instrument was divided into
sections: Section A captured demographic information, while Section B consisted of questions measuring
employee engagement (behavioral engagement, emotional commitment, and cognitive engagement), and
Section C focused on turnover intentions. A 5-point Likert scale ranging from Strongly Agree (4) to Strongly
Disagree (1) was employed.
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3.5 Validity and Reliability of the Instrument
The questionnaire was subjected to content and face validity by academic experts in Human Resource
Management and Organizational Behavior. For reliability, a pilot study was conducted using 30 respondents
from two banks not included in the main study. The Cronbach’s Alpha coefficients for the scales were 0.81
(behavioral engagement), 0.79 (emotional commitment), 0.83 (cognitive engagement), and 0.85 (turnover
intention), indicating acceptable internal consistency (Nunnally & Bernstein, 1994).
3.6 Method of Data Collection
Data were collected through the administration of physical copies of the questionnaire and, in some cases,
through online Google Forms for respondents who preferred electronic submissions. Research assistants were
employed to assist in data distribution and retrieval.
3.7 Method of Data Analysis
Descriptive statistics such as mean and standard deviation were used to summarize respondents’ demographic
characteristics and responses. To test the hypotheses, multiple regression analysis was used to examine the
influence of the independent variables (behavioral engagement, emotional commitment, and cognitive
engagement) on the dependent variable (turnover intention). Data were analyzed using Statistical Package
for the Social Sciences (SPSS) version 26. A 5% level of significance was adopted to determine the
acceptance or rejection of the null hypotheses.
3.8 Model Specification
To empirically examine the effect of employee engagement on turnover intentions, the study adopts a linear
regression model expressed as:
TI=β0+β1BE+β2EC+β3CE+ϵ
Where:
• TI = Turnover Intention (Dependent Variable)
• BE = Behavioral Engagement
• EC= Emotional Commitment
• CE = Cognitive Engagement
• β0 = Intercept (constant term)
• β1,β2,β3 = Coefficients of the independent variables
• ϵ= Error term (captures other factors not included in the model)
This model allows the study to determine the individual and combined effects of different dimensions of
employee engagement on employees’ intention to leave their jobs in the banking sector in Edo State.
DATA ANALYSIS AND INTERPRETATION
Table 1: Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.78
.66
.53
.59406
The regression result presented in Table 4.1 offers insight into the relationship between employee engagement
and turnover intentions among employees in the banking industry in Edo State. The correlation coefficient (R)
of 0.78 indicates a strong positive relationship between the independent variables—namely behavioral
engagement, emotional commitment, and cognitive engagement—and the dependent variable, which is
turnover intentions. This suggests that changes in the levels of employee engagement are strongly associated
with changes in turnover intentions.
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The coefficient of determination (R²) is 0.66, implying that approximately 66% of the variation in turnover
intentions can be explained by the three dimensions of employee engagement. This means that employee
engagement factors have a substantial influence on whether or not employees intend to leave their jobs. The
remaining 34% of the variation is likely explained by other factors not captured in the model, such as salary
satisfaction, job stress, career advancement opportunities, and organizational culture.
Additionally, the adjusted R² value of 0.53 reflects the proportion of the variance explained by the independent
variables after adjusting for the number of predictors in the model. This means that even after accounting for
the number of variables included, the model still explains 53% of the variability in turnover intentions,
demonstrating a relatively good model fit for predictive purposes.
The standard error of the estimate (0.59406) further confirms the model's accuracy. It measures the average
distance between the observed data points and the predicted values from the regression equation. A smaller
standard error, such as the one observed here, indicates that the model’s predictions closely match the actual
data, reinforcing the reliability of the results.
Overall, the regression summary reveals that employee engagement has a significant and meaningful impact
on turnover intentions in the banking sector of Edo State which is inline with result of Imade et al., 2025. The
findings emphasize the importance of fostering high levels of behavioral engagement, emotional commitment,
and cognitive engagement in order to reduce employee turnover. For managers and policymakers, this provides
empirical evidence to support strategic human resource practices aimed at improving employee retention
through focused engagement initiatives.
Table 2: ANOVA
Model
Sum of
Squares
df
Mean Square
F
Sig.
Regression
.459
4
.115
7.25
.000
Residual
74.463
211
.353
Total
74.921
215
The Analysis of Variance (ANOVA) is used to determine whether the regression model as a whole is
statistically significant, that is, whether the independent variables jointly predict the dependent variable
effectively.
From the table:
The Regression Sum of Squares (SSR) is 0.459, which shows how much of the total change in turnover
intentions can be explained by the predictors (behavioral engagement, emotional commitment, and cognitive
engagement).
· The F-statistic is 7.25, with a significance value (p-value) of 0.000, which is well below the conventional
threshold of 0.05.
4.1 Implication of the Results
The F-statistic of 7.25 and the p-value of 0.000 indicate that the regression model is statistically significant
at the 5% significance level. This means that, collectively, the independent variables—behavioral
engagement, emotional commitment, and cognitive engagement—have a significant impact on turnover
intentions among employees in the banking industry in Edo State.
In other words, the model provides a satisfactory fit for the data, and there is strong evidence that employee
engagement dimensions are significant predictors of whether bank employees intend to stay with or leave their
organization.
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The ANOVA results support the conclusion that the regression model is reliable and that the employee
engagement components under investigation play a crucial role in explaining the variance in employee
turnover intentions. This validates the study conducted by Naufer and Kumar (2020) and the need for strategic
engagement initiatives in the banking sector to reduce turnover and improve employee retention.
Table 3: Coefficients
Predictor
B
Std. Error
Beta
t
Sig.
Tolerance
VIF
(Constant)
4.095
.554
—
7.396
.000
—
—
BE
2.030
.068
1.031
.446
.000
.995
1.005
EC
2.043
.077
1.038
.555
.000
.995
1.005
CE
2.034
.071
1.033
.482
.000
.991
1.009
This table shows the results of a multiple regression analysis examining how behavioral engagement (BE),
emotional commitment (EC), and cognitive engagement (CE) affect turnover intentions.
4.1.1 Interpretation of Individual Predictors:
Constant (Intercept):
B = 4.095, t = 7.396, p = .000
This indicates the expected value of turnover intention when all predictors are equal to zero. It is statistically
significant, suggesting a meaningful base level of turnover intention independent of engagement factors
4.2 Behavioral Engagement (BE):
The positive B-value indicates that an increase in behavioral engagement significantly reduces turnover
intentions. The effect is statistically significant (p < 0.05).The Beta = 1.031 suggests BE has a strong
standardized influence on turnover intentions. Tolerance = .995 and VIF = 1.005 indicate no multicollinearity
concern.
4.3 Emotional Commitment (EC):
EC has a positive and significant effect on reducing turnover intentions. The Beta value shows that EC
contributes substantially to explaining variations in turnover intentions. Again, no multicollinearity issues
are indicated.
4.4 Cognitive Engagement (CE):
CE also has a significant positive influence on reducing turnover intentions. Like the other predictors, CE’s
effect is strong and statistically significant. Tolerance and VIF values indicate healthy levels of independence
between predictors.
• All three dimensions of employee engagement—behavioral, emotional, and cognitive—have strong,
positive, and statistically significant effects on reducing turnover intentions.
• The Beta coefficients are all close to or slightly above 1.0, indicating that each form of engagement is
a substantial predictor of turnover intentions.
• The VIF and Tolerance values indicate that there is no multicollinearity, affirming the reliability of
the model.
The results show that increased levels of behavioral engagement, emotional commitment, and cognitive
engagement are all associated with significantly lower turnover intentions among bank employees in Edo
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State. The findings reinforce the importance of holistic employee engagement strategies in improving
employee retention in the banking sector.
4.5 Test of Hypotheses
The study investigated the effect of employee engagement on turnover intentions in the banking industry in
Edo State by examining three dimensions of engagement: behavioral engagement, emotional commitment,
and cognitive engagement. To test the hypotheses, multiple regression analysis was employed, and the results
were evaluated at a 5% level of significance.
The first hypothesis tested whether behavioral engagement had a significant effect on turnover intentions
among bank employees. The regression result showed a standardized coefficient (Beta) of 1.031, with a p-
value of 0.000. Since the p-value is less than the 0.05 threshold, the null hypothesis was rejected. This indicates
that behavioral engagement significantly influences employees’ intention to stay or leave, implying that
employees who are behaviorally engaged are less likely to consider leaving their organizations.
The second hypothesis evaluated the influence of emotional commitment on turnover intentions. The analysis
revealed a standardized coefficient (Beta) of 1.038 and a p-value of 0.000. Again, the p-value was below the
0.05 significance level, leading to the rejection of the null hypothesis. This suggests that emotional
commitment has a significant impact on turnover intentions. In practical terms, employees who feel
emotionally connected to their organization are more likely to remain committed and less likely to seek
employment elsewhere.
The third hypothesis assessed whether cognitive engagement significantly affects turnover intentions. The
regression output produced a standardized coefficient (Beta) of 1.033 and a p-value of 0.000. As with the
previous hypotheses, the null hypothesis was rejected due to the p-value being less than 0.05. This result
confirms that cognitive engagement—employees’ mental focus and absorption in their work—also
significantly reduces the likelihood of turnover.
In summary, the regression results provided robust evidence that all three dimensions of employee engagement
(behavioral, emotional, and cognitive) have a statistically significant effect on turnover intentions in the
banking sector of Edo State. Enhancing these forms of engagement can serve as a strategic tool to reduce
employee attrition and strengthen organizational stability.
The study examined the effect of employee engagement on turnover intentions in the banking sector in Edo
State by analyzing three dimensions: behavioral engagement, emotional commitment, and cognitive
engagement. The results of the regression analysis revealed that each of these variables significantly affects
turnover intentions.
4.6 Behavioral Engagement and Turnover Intentions
The findings indicate that behavioral engagement has a significant and negative relationship with turnover
intentions among employees in the banking sector. This implies that employees who are actively involved in
their roles, demonstrate initiative, and display consistent work effort are less likely to consider leaving their
organization. This aligns with the work of Schaufeli and Bakker (2004), who argued that engaged employees
are proactive and energetic, making them less inclined to quit. Similarly, Saks (2006) emphasized that
behavioral manifestations of engagement, such as dedication and perseverance, are inversely related to
turnover intentions. The implication for banks is that fostering employee behaviors that align with
organizational goals can reduce the propensity to resign.
4.7 Emotional Commitment and Turnover Intentions
The analysis also revealed that emotional commitment significantly influences turnover intentions. Employees
who are emotionally attached to their organizations, who share in its values, and who feel a sense of belonging,
are more likely to stay. This supports the findings of Allen and Meyer (1990), who developed the three-
component model of organizational commitment, stating that affective (emotional) commitment plays a key
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role in retaining staff. Moreover, Halbesleben and Wheeler (2008) found that emotionally committed
employees report greater job satisfaction and a lower desire to leave their jobs. For bank management, this
underscores the importance of building a strong organizational culture and emotional ties between employees
and the institution.
4.8 Cognitive Engagement and Turnover Intentions
Cognitive engagement was also found to be a significant predictor of turnover intentions. Employees who are
mentally immersed in their work and who find their roles intellectually stimulating are less likely to
contemplate quitting. This finding echoes Kahn’s (1990) foundational theory on personal engagement, which
posits that when individuals are cognitively invested in their tasks, they derive meaning and purpose from
work, leading to greater job satisfaction and reduced turnover. Rich, Lepine, and Crawford (2010) also found
cognitive engagement to be a key antecedent to organizational citizenship behaviors and lower attrition.
4.8.1 Policy Implication
From a policy standpoint, these findings suggest that banking institutions in Edo State should not only develop
policies that enhance the behavioral and emotional connection of employees to the organization but should
also create job roles that challenge and intellectually engage employees. Investment in leadership
development, mentorship programs, and employee feedback systems may further help banks enhance
engagement and minimize turnover.
This study investigated the effect of employee engagement on turnover intentions in the banking industry in
Edo State, Nigeria, using behavioral engagement, emotional commitment, and cognitive engagement as
independent variables. The regression analysis revealed several key insights:
1. Behavioral engagement significantly and negatively impacts turnover intentions, indicating that
employees who are behaviorally engaged are less likely to consider leaving their jobs.
2. Emotional commitment also showed a significant negative effect on turnover intentions,
demonstrating that employees emotionally attached to their organizations have lower turnover
tendencies.
3. Cognitive engagement was found to significantly reduce turnover intentions, highlighting that
mentally involved employees are more inclined to remain with their employers.
These findings align with previous empirical studies and engagement theories, reinforcing the relevance of
these engagement dimensions in enhancing employee retention in the banking sector.
CONCLUSION
This study examined the effect of employee engagement on turnover intentions among bank employees in Edo
State, Nigeria, focusing on behavioral, emotional, and cognitive dimensions. The results revealed that all three
dimensions significantly and negatively influence turnover intentions, with behavioral engagement (β = 2.030,
p < 0.01), emotional commitment (β = 2.043, p < 0.01), and cognitive engagement (β = 2.034, p < 0.01) jointly
explaining 66% of the variation in turnover intentions. These findings indicate that employees who are
behaviorally active, emotionally connected, and cognitively involved are less likely to consider leaving their
organizations. The study underscores the importance of holistic engagement strategies in promoting employee
retention and organizational stability. Bank management should foster emotional attachment through
supportive leadership, enhance behavioral engagement via participatory practices, and strengthen cognitive
engagement by providing intellectually stimulating work environments. Policy initiatives that integrate
engagement-driven human resource practices can further reduce turnover, enhance morale, and improve
service delivery. Overall, the study contributes to the understanding of engagement–retention dynamics within
Nigeria’s banking sector and provides actionable insights for practitioners seeking to improve workforce
stability and organizational performance.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025
Page 5776
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RECOMMENDATIONS
Based on the findings, the following recommendations are made:
1. Bank management should design and implement engagement initiatives that promote employee
participation, involvement in decision-making, and clear performance expectations.
2. Banks should invest in building a strong organizational culture that fosters loyalty, mutual respect, and
a sense of belonging among employees.
3. Managers should assign intellectually stimulating tasks, encourage innovation, and provide
opportunities for employees to apply critical thinking and problem-solving skills.
4. Institutions should implement regular training, mentorship programs, and open feedback channels to
support professional growth and reinforce engagement.
5. Regular assessments of employee engagement levels should be conducted to identify gaps and
implement timely interventions to retain talent.
REFERENCES
1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision
Processes, 50(2), 179–211.
https://doi.org/10.1016/0749-5978(91)90020-T. (sciencedirect.com)
2. 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), 1–18.
https://doi.org/10.1111/j.2044-8325.1990.tb00506.x. (bpspsychub.onlinelibrary.wiley.com)
3. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods
approaches (5th ed.). Sage Publications.
4. Davlembayeva, D., & Alamanos, E. (2025). Social exchange theory: A review. In S. Papagiannidis (Ed.),
TheoryHub (Theory entry). Newcastle University / TheoryHub. Retrieved from
https://open.ncl.ac.uk/theories/6/social-exchange-theory/. (open.ncl.ac.uk)
5. Gallup, Inc. (2022). State of the Global Workplace: 2022 Report. Gallup, Inc. (2022 report on
engagement). Retrieved from Gallup website (report).
6. Halbesleben, J. R. B., & Wheeler, A. R. (2008). The relative roles of engagement and embeddedness in
predicting job performance and intention to leave. Work & Stress, 22(3), 242–256.
https://doi.org/10.1080/02678370802383962. (tandfonline.com)
7. Homans, G. C. (1958). Social behavior as exchange. American Journal of Sociology, 63(6), 597–606.
https://doi.org/10.1086/222355. (web.ics.purdue.edu)
8. Imade Iduozeea, Omoyebagbe R. DANIAb, Matthew Iduozee (2025) Employee Engagement and
Organisational Performance In Some Selected Eateries In Edo State. Nigeria Journal of Management
Studies, Unilag. Vol. 27 No. 3 (2025).
9. Iqbal, S., Maroof, L., et al (2025). Impact of Employee Engagement on Turnover Intentions with the
Mediating Role of Intrinsic and Extrinsic Motivation in Start-ups. Journal of Innovative Research in
Management Sciences, 6(3). (
agasr.org)
10. Kahn, W. A. (1990). Psychological conditions of personal engagement and disengagement at work.
Academy of Management Journal, 33(4), 692–724.
https://doi.org/10.2307/256287
11. Mobley, W. H. (1977). Intermediate linkages in the relationship between job satisfaction and employee
turnover. Journal of Applied Psychology, 62(2), 237–240. https://doi.org/10.1037/0021-9010.62.2.237
12. Mobley, W. H., Horner, S. O., & Hollingsworth, A. T. (1978). An evaluation of precursors of hospital
employee turnover. Journal of Applied Psychology, 63(4), 408–414. https://doi.org/10.1037/0021-
9010.63.4.408. (PubMed)
13. Naufer F. Z. and Kumar P. D. A. S. (2020): Impact of Employee Engagement on Turnover Intention:
Study of Third Space Global (Pvt) Limited. Kelaniya Journal of Human Resource Management Volume
15 | Issue 01 | Page 71
14. NDIC. (2023). Annual Report of the Nigerian Deposit Insurance Corporation.
https://ndic.gov.ng
15. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill
16. Rich, B. L., Lepine, J. A., & Crawford, E. R. (2010). Job engagement: Antecedents and effects on job
performance. Academy of Management Journal, 53(3), 617–635.
https://doi.org/10.5465/amj.2010.51468988
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025
Page 5777
www.rsisinternational.org
17. Saks, A. M. (2006). Antecedents and consequences of employee engagement. Journal of Managerial
Psychology, 21(7), 600–619.
https://doi.org/10.1108/02683940610690169
18. Saks, A. M., & Gruman, J. A. (2014). What do we really know about employee engagement? Human
Resource Development Quarterly, 25(2), 155–182. https://doi.org/10.1002/hrdq.21187
19. Saks, Alan M. (2006) Antecedents and consequences of employee engagement. Journal of Managerial
Psychology, 21(7), 600-619. DOI: 10.1108/02683940610690169 ResearchGate+1
20. Schaufeli and Wilmar B. (2004) ”Job demands, job resources and their relationship with burnout and
engagement: a multi-sample study.” Work & Stress. (Definition of engagement) wilmarschaufeli.nl+1
21. Schaufeli, W. B., & Bakker, A. B. (2004). Job demands, job resources, and their relationship with burnout
and engagement: A multi‐sample study. Journal of Organizational Behavior, 25(3), 293–315.
https://doi.org/10.1002/job.248
22. Shuck, B., & Wollard, K. (2010). Employee engagement and HRD: A seminal review of the foundations.
Human Resource Development Review, 9(1), 89–110. https://doi.org/10.1177/1534484309353560.
(journals.sagepub.com)
23. Wang, Xin; Liu, Ming; Leung, Angela YM; Jin, Xiaoyan; Dai, Hongxia; Shang, Shaomei. (2024) Nurses’
job embeddedness and turnover intention: A systematic review and meta-analysis. Int J Nurs Sci.
11(5):563-570. DOI: 10.1016/j.ijnss.2024.10.003
PMC+1
24. William, M & Katin.U (1990). The evolution of the employee engagement concept: communication
implications. Corporate Communications: An International Journal 16(4), 328-346
25. Wollard, K. K., & Shuck, B. (2011). Antecedents to employee engagement: A structured review of the
literature. Advances in Developing Human Resources, 13(4), 429–446.
https://doi.org/10.1177/1523422311431220. (journals.sagepub.com)
26. Yıldız, S. M. (2024). Exploring the Relationships among Internal Marketing, Work Engagement, Job
Performance and Turnover Intention: An Empirical Application in Sports Organizations. ERISS, 9(1),
15–26. (
dergipark.org.tr)
