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DOI: https://doi.org/10.34069/AI/2024.73.01.27
How to Cite:
Khalid, K., & Boraji, A.J. (2024). From high-performance work systems to retention: The engagement, proactivity, and
performance bridge. Amazonia Investiga, 13(73), 318-330. https://doi.org/10.34069/AI/2024.73.01.27
From high-performance work systems to retention: The engagement,
proactivity, and performance bridge
:
Received: December 14, 2023 Accepted: January 26, 2024
Written by:
Komal Khalid1
https://orcid.org/0000-0001-7220-6962
Amna Jamal Boraji2
https://orcid.org/0009-0007-4792-6280
Abstract
This quantitative study explores the effects of high-performance work systems on employee retention
through individual factors such as job engagement, employee proactive behavior, and employee
performance. The study utilizes a sample of 279 employees employed in the healthcare sector in Saudi
Arabia. For hypotheses testing, structural equational modeling was used through SmartPLS4. The findings
highlight the influence of HPWS on increased employee proactive behavior, employee performance, and
job engagement, resulting in increased employee retention. Additionally, a serial indirect effect of employee
proactive behavior, job engagement, and employee performance was found to positively influence the
relationship between high-performance work systems and employee retention. High-performance work
systems can promote job engagement in Saudi organizations by offering challenging work, autonomy, skill
development, and performance feedback. Engaged workers stay longer. Job engagement promotes a
positive work environment and community, which increases employee retention. Employee proactive
behavior also makes employees feel valued and invested in their work, which can increase retention. The
study enhances current knowledge on the role of high-performance work systems in the Saudi healthcare
sector considering Vision 2030 by examining the potential mediators between high-performance work
systems and employee retention.
Keywords: High-performance work system, job engagement, employee proactive behavior, employee
performance, employee retention.
,
, . 279
. , SmartPLS 4
, ,
.
, ,
, .
, , , .
. .
,
.
1
PhD, Associate Professor, Department of Human Resource Management, Faculty of Economics and Administration, King Abdulaziz
University, Saudi Arabia. WoS Researcher ID: O-6590-2015
2
Master Student (Human Resource Management), Faculty of Economics and Administration, King Abdulaziz University, Jeddah,
Saudi Arabia.
Khalid, K., Boraji, A.J. / Volume 13 - Issue 73: 318-330 / January, 2024
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2023 .
: , , , ,
Introduction
High-performance work systems (HPWS) are
integrated human resource methods that boost
employee productivity and performance. HPWS
is also called a high-commitment work system,
high participation work system, and efficient
human resource management (Zhu et al., 2018).
HPWS requires selective hiring, employment
security, decentralization of decision-making,
extensive training, information sharing, and fair
compensation (Zhang, 2019).
An employee's proactive behavior (EPB)
improves the workplace. Proactive employees
solve problems, suggest improvements, and
change organizations (Wu, 2019). These
employees have better career and personal
outcomes, which improves organizational
development and performance. Proactivity is
essential to an organization's success (Al-Tit,
2020).
Organizations need job engagement (JE) to boost
employee performance, retention, and output.
Engaged employees help organizations achieve
their goals (Anitha, 2014). Organizations should
provide recognition, development, and
communication to boost employee engagement
(Jaharuddin & Zainol, 2019).
High turnover costs and disrupts a company, so
employee retention (ER) is crucial.
Organizations should promote work-life balance,
a positive work environment, competitive
compensation and career development, and
exceptional performance to increase JE (Papa et
al., 2020). HPWS improves JE, but employee
proactivity may also improve it. Proactive
employees may boost performance and retention,
but only sometimes. Employee proactivity,
performance, and retention must be clarified
beyond HPWS and JE.
The current study proposes that HPWS (i.e.,
staffing, training and development,
compensation, performance management, career
development, and information sharing) influence
employee proactive behavior (e.g., problem-
solving and identification of opportunities). As a
result, employees will engage more in their work
and organizational activities by being more
enthusiastic regarding their work activities and
focusing on their job. The study also claims that
engaged employees have the higher task and
contextual
willingness to stay with the organization for a
longer period.
Saudi Arabia needs HPWS to succeed in
infrastructure and economic diversification.
HPWS will help Vision 2030 by improving
productivity, innovation, and competitiveness
through JE, creativity, and continuous
improvement. Vision 2030 and the National
Transformation Program are increasing private-
sector healthcare contributions in Saudi Arabia.
By 2030, the number of licensed medical
institutions, privatized government services,
healthcare, IT, digital records, and qualified
Saudi nurses will increase (Rahman & Al-Borie,
2021). This improves operational efficiency,
product and service quality, and market
adaptability.
Literature review
High-performance work systems
High-performance work systems (HPWS) are
several performance-enhancing activities
included in a collection of distinct but linked HR
practices that are intended to improve employees'
abilities and efforts. HPWS, also called high
commitment work practices, high participation
work practices, and best HR methods (Zhu et al.,
2018). HPWS is a set of HR practices that boost
employee productivity, performance, loyalty,
and skills, making utilization of human resources
to gain an ongoing competitive advantage (Zhu
et al., 2018; Pak & Kim, 2016). HPWS's main
components are selective hiring, employment
security, decentralized decision-making,
extensive training, information sharing, and fair
payment (Li et al., 2019; Zhu et al., 2018).
Employee’s proactive behavior
In the organization, proactivity is a way for
employees to improve or change their work
environment (Al-Tit, 2020, Arefin et al., 2015).
Wu et al. (2019) defined a proactive employee as
one who introduces or applies new work ideas,
makes suggestions to improve the work
environment, and identifies and solves work
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performance issues. Such an employee improves
organizational effectiveness and career
development for himself and the organization
(Al-Tit, 2020).
HPWS gives employees resource entitlements.
This may be especially beneficial for low-
proactivity workers, who may be less inclined to
negotiate special arrangements and may rely
heavily on HPWS's more structured, collective
approach to motivate them (Zhang et al., 2019).
HPWS affects EPB because it is linked to
positive work behaviors. Proactive employees
will get more resources and work better with
HPWS. Thus, proactive employees need HPWS
to improve performance (Martín et al., 2017).
HPWS increases EPB by improving employee
motivation, abilities, and performance (Martín et
al., 2017). HPWS promotes human capital
through recruitment and training and attracts
talent through competitive compensation (Teo et
al., 2020). As HPWS develops KSA, employees
are more likely to take positive action, believing
they can improve their work and efficiency (Shin
& Jeung, 2019). Thus, the following hypotheses
state:
H1: High-performance work system has a
positive and significant impact on employee
proactive behavior.
Job engagement
Job engagement is a positive attitude toward the
organization and its beliefs (Jaharuddin &
Zainol, 2019). JE also refers to the harnessing of
engaging employees to their job responsibilities,
so when performing at work, people use their
bodies, minds, and feelings for expressing
themselves. (Ozyilmaz, 2020). It involves
enthusiasm, dedication, and absorption while
allocating personal resources and energy to work
(Eldor et al., 2020).
Conservation of resources (COR) theory states
employees invest resources in coping with risky
conditions and defending against resource loss to
preserve and acquire resources (Hobfoll et al.,
2018). When they do not perform well, people
get stressed and take more proactive measures to
maintain their jobs and stay engaged. They must
work hard and be proactive in their careers (Jang
et al., 2020).
H2: Employee proactive behavior has a positive
and significant impact on job engagement.
Employee performance
Employee performance is a multidimensional
phenomenon and a significant element in
determining the success or failure of an
organization (Sendawula et al., 2018). It covers
positive and negative employee activities and
behaviors that help achieve the organization's
objectives (Singh, 2016). Employee performance
is one of the most significant organizational
outcomes in work and organizational psychology
(Diaz-Vilela et al., 2015). Task and contextual
performance are its two main dimensions
(Khalid, 2020).
Task performance supports technological core
procedures and maintenance, characterized as
employee efficacy to achieve organizational
goals. Contextual performance effects
organizational tasks through contributing to the
organizational environment and culture. It
involves conflict resolution, and interpersonal
cooperation (Sendawula et al., 2018; Khalid,
2020).
Engaged employees exhibit various productive
behaviors that enhance synergetic team efforts
toward organizational goals (Breevaart et al.,
2015). These synergistic efforts boost employee
performance (Bakker, 2017). Engaged workers
can spread their feelings throughout the
organization, which drives their efforts and
performance (Bakker & Demerouti, 2014). High
JE helps employees handle more work and
improve their performance. High JE, persistence,
and task focus improve performance (Bal & De
Lange, 2015).
H3: Job engagement has a positive and
significant impact on employee performance.
Employee retention
Employee retention refers to the many steps
organizations take to retain employees (Papa et
al., 2020). Das & Baruah (2013) emphasized that
encouraging employees to stay if possible or until
the project is finished is the key to success.
Industrial globalization has changed employee
attitudes toward their organizations. Thus,
organizations must retain educated and skilled
workers during high turnover (Diah et al., 2020).
Retention depends on many factors, including
peer support (Ali et al., 2017), recruitment and
selection, job preview, awards and recognition,
worklife balance, training and development,
transformational leadership, and organizational
citizenship behavior (Tian et al., 2020).
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Nguyen & Duong (2021) found that motivated,
competent, and skilled people perform well,
which is important for an organization's
competitiveness and employee retention. This
shows that employees will stay if they feel
accomplished (Alshery & Ahmad, 2016).
According to Syahreza et al. (2017), if a business
manages employee maintenance well, employees
will be disciplined, loyal, and work ethic.
Maslow's theory of motivation suggests that
employees who are satisfied with their needs will
be motivated to meet higher-level needs.
Retaining staff will motivate them to perform
better to meet increased demands (Papa et al.,
2020).
H4: Employee performance has a positive and
significant impact on employee retention.
When any organization applies HPWS then this
will lead to influence and effect the performance
of employees (Karadas & Karatepe, 2018).
HPWS elicit desirable behavior and attitude from
employees, such as a desire to learn, an
awareness of the objective of their work, an
increase in engagement, and proactive initiatives
(Jang et al., 2020). These employee actions and
attitudes establish a connection to the
organization and ensure that the employee will
continue to work for the organization while
generating effective performance (Bal & De
Lange, 2015).
Among the multiple benefits of JE, effective EP,
and ER stand out, as engaged employees tend to
be more devoted to the organization and its
objectives, which leads to enhanced EP and
improved outcomes (Pandita & Ray, 2018). JE
relates to creativity, workplace vigor, EP, and
greater ER (Bal & De Lange, 2015).
Maden (2015) explains the existence of a
relationship between HPWS and ER. This
relationship is serially mediated by an
employee's proactive behavior and JE. Using the
principle of conservation of resources (COR), we
can construct this relationship (Jang et al., 2020).
Some employees may become stressed when
they do not perform well; therefore, they will be
motivated to improve their proactive behavior so
that they are engaged with their work and strive
to demonstrate proactive behavior.
Consequently, the effect of JE will have a
mediated effect on employee performance. There
is a favorable connection between JE and EP
(Pandita & Ray, 2018). Therefore, we
hypothesized:
H5: The relationship between a high-
performance work system and employee
retention is serially mediated by employee
proactive behavior, job engagement, and
employee performance.
Figure 1. Theoretical Model
Methodology
Data Collection
This research used a quantitative analysis
method. Data were collected in three phases from
June 1, 2023, to December 30, 2023, with two
months between each phase. The first phase
collected demographic and HPWS data. The
second phase collected JE, EPB, and EP data. In
the final phase, ER data were gathered. Research
assistants and healthcare friends collected the
data. To translate scale items from English to
Arabic, a special translator officer translated the
questionnaire by using back-to-back translation
method. With language experts and pilot testing,
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sentence meanings were preserved during
translation. During the translation process, it was
assured with the help of language experts and
pilot testing that the meanings of the sentences do
not lose their essence.
Sample and procedure
Saudi doctors, nurses, and administrative staff in
public and private healthcare were surveyed
using a hard copy and soft copy self-administered
survey. Data were collected from Saudi Arabia's
four largest cities (i.e., Jeddah, Makkah,
Madinah, and Riyadh). The hospital's ethics
committee and HR department approved the
questionnaire before distribution. This study
used purposive sampling. The present study used
purposive sampling to select participants most
likely to know about the research area so that it
can enhance study relevance and accuracy. Thus,
sampling aims to represent the population
accurately. All variables in this study apply to the
healthcare industry to avoid sampling errors
caused by data collection and processing errors.
A total of 400 questionnaires were distributed in
five largest hospitals (i.e., based on numbers of
beds), from each city. Twenty questionnaires
were distributed to participants (i.e., doctors,
nurses, and administrative staff) in each hospital.
The questionnaires were personally distributed
by email and postal service. Those who did not
respond were contacted through three polite
reminders, each separated by one week until no
further communication was received. To
maintain the participant's privacy, empty
envelopes were supplied to those who submitted
their responses using personal administration or
email.
To minimize social desirability bias and common
method variance, several strategies were
implemented. These included assuring
respondents that their information would be used
solely for research purposes and would be kept
strictly confidential. Additionally, the dependent
and independent variable distribution occurred in
separate phases and sections. Additionally, the
data was gathered in stages to prevent
respondents from establishing associations
between their responses and other variables. In
the first phase of data collection (including
demographic variables, and HPWS items), 384
responses were received. In the second phase of
data collection (), 327 responses were received.
However, in the last phase, a total of 279
responses were received for final data analysis.
From all the three phases of data collection,
incomplete responses were removed. After
conducting Cook and Leverage distances test
(i.e., by removing outliers) only 260 usable
responses remain.
The HPWS variable was measured with its
dimensions (i.e., selective staffing, internal
mobility, employment security, clear job
description, and result-oriented appraisal)
through a 15-item scale developed by Sun et al.
(2007). Employee performance was measured
including its two dimensions (i.e., contextual
performance and task performance) through a
13-item scale developed by Koopmans et al.
(2013). JE was measured through a 12-item
scale, which was developed by Drake. (2012).
EPB was measured by using 9-items scale
developed by Bateman et al. (1993). Whereas,
ER was measured through 7-items scale
developed by Egan et al., (2004) and Kassim
(2006). All variables were measured on a 5-point
Likert scale with 1 being strongly disagreed and
5 strongly agree.
SmartPLS 4 and SPSS version 29 were utilized
to perform the data analysis. When examining
and predicting variables, partial least squares
structural equation modeling (PLS-SEM) is
highly recommended (Hair et al., 2020).
Results and discusión
Descriptive and Correlation Statistics
The demographics indicated that there were
71.4% men and 28.6% women. Most participants
(40.3%) were between the ages of 40 and 50, held
bachelor's degrees (61.9%), were married
(82.1%), and had worked for the same
organization for over 20 years (45.3%). Most
participants were employed in healthcare.
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Table 1.
Descriptive Statistics and Pearson Correlation Analysis
Descriptive Statistics
Pearson Correlations Analysis
Mean
SD
HPWS
JE
EPB
EP
ER
HPWS
3.586
0.465
1
JE
4.057
0.375
**
.474
1
EPB
3.950
0.422
**
.436
**
.594
1
EP
3.805
0.426
**
.394
**
.607
**
.583
1
ER
3.818
0.541
**
.595
**
.510
**
.435
**
.521
1
Note: **. Correlation is significant at the 0.01 level (2-tailed).
Table 1 displays the correlations between HPWS, JE, EPB, EP, and ER. JE is significantly correlated with
EPB (r = 0.594**), EP (r = 0.607**), and ER (r = 0.510**). There is a significant correlation between
employee performance, EPB, and ER (r = 0.583**, 0.435**, respectively).
Assessment of reflective measurements
To ensure the validity and reliability of the study
scale, Confirmatory composite analysis (CCA) is
used (Henseler et al., 2014). Table 2 assessment
of reflective measurement displays the factor
loadings for each research variable. The findings
show that each of the factor loadings is more than
the cutoff value of 0.40. (Hair et al., 2020). As
shown in Table 2, for all items, factor loading
ranges from 0.419 to o.817. According to studies
by Hair et al. (2021), the reliability values
(Cronbach alpha, Rho-A, and composite
reliability) should exceed 0.7, and the values for
the AVE must be higher than 0.5.
Table 2.
Assessment of Reflective Measurement
Items
Type
Loadings
CA
rho-A
CR
AVE
VIF
HPWS1-
HPWS15
Reflective
0.457-
0.756
0.871
0.879
0.891
0.557
1.289 - 2.462
EPB3-EPB9
Reflective
0.419-
0.559
0.834
0.843
0.875
0.501
1.409- 1.770
JE1-JE12
Reflective
0.645 -
0.817
0.898
0.904
0.917
0.552
1.699 -2.548
EP1 - EP12
Reflective
0.491-
0.632
0.842
0.854
0.876
0.514
1.356 - 1.894
ER1 - ER4
Reflective
0.697 -
0.738
0.781
0.785
0.897
0.511
1.252 - 1.319
Note: CA= Cronbach alpha; CR = Composite reliability; AVE = Average variance extracted; VIF = Variance
inflation factor
The range of the CA level is between 0.781 and
0.898. rho_A's levels fall between 0.785 to 0.904.
As a result, the coefficients of CR fall between
0.875 to 0.917. The chosen measures' validity is
supported by the AVE numbers (0.501 0.557),
because each of them is greater than 0.5. (Hair et
al., 2020). By demonstrating that each variable
has significant inter-scale relations that meet the
requirements for convergent validity.
Multicollinearity is not a problem in this analysis
because collinearity diagnostics were also carried
out, and all variance inflation factor (VIF) values
were far below 3 (Table 2).
Discriminant validity
Fornell-Larcker and Hetro-Trait Mono-Trait
criteria are used to measure discriminant validity
(Gannon et al., 2021). According to the findings
in Table 3, FornellLarcker criterion and
heterotrait-monotrait (HTMT) demonstrate that
the data's discriminant validity is acceptable.
Acceptable HTMT values should be less than
0.85, according to research conducted by
Henseler et al. (2014). The square root of the
construct's AVE must be greater than the
correlation values for all the constructs for the
Fornell-Larcker criterion results to be considered
acceptable (Fornell & Larcker, 1981).
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Table 3.
Discriminant Analysis (HTMT and Fornell-Larcker Criterion)
Hetro-Trait Mono-Trait (HTMT) Criterion
Fornell-Larcker Criterion
HPWS
JE
EPB
EP
ER
HPWS
JE
EPB
EP
ER
HPWS
0.746
JE
0.529
0.488
0.743
EPB
0.479
0.695
0.453
0.622
0.707
EP
0.438
0.705
0.605
0.413
0.628
0.677
0.716
ER
0.528
0.742
0.443
0.705
0.431
0.593
0.665
0.697
0.715
Note 1: The bold numbers in diagonal in Fornell- Larcker section are square root of AVE of each construct, and
other numbers are correlation between constructs.
Hypothesis testing
Table 4 shows the results of testing our
hypothesis that was used for the study. HPWS
strongly impacts EPB positively, according to
calculations of the direct link between the two
factors ( = 0.453, t-value =12.326, p < 0.000)
Thus, H1 was supported. Similarly, table 4
emphasizes the direct influence of EPB on JE
( = 0.622, t-value = 14.312, p < 0.000), thus
showing a strongly significant and positive
impact of EPB on JE. Thus, supporting H2.
While, JE has a significant and positive impact
on EP ( = 0.628, t-value = 14.490, p < 0.000),
this supports H3. Moreover, the EP has a
significant and positive impact on ER ( = 0.799,
t-value = 32.180, p < 0.000), these results support
H4.
.
Table 4.
Hypothesis Testing
Hypo-
thesis
Direct / Indirect
Effect
Path
Coefficient
T
Value
P
Value
Bias
BCCI
Hypothesis
Support
5.00%
95.00%
1
H
> EPB-HPWS
0.453
12.362
0.000
0.016
0.366
0.509
Supported
2
H
> JE-EPB
0.622
14.312
0.000
0.007
0.518
0.694
Supported
3
H
> EP-JE
0.628
14.490
0.000
0.006
0.53
0.700
Supported
4
H
> ER-EP
0.797
32.180
0.000
0.002
0.735
0.837
Supported
5
H
HPWS -> EPB -> JE
> ER-> EP -
0.141
5.372
0.000
0.01
0.089
0.185
Supported
Note: High Performance Work Systems (HPWS); Job Engagement (JE); Employee Proactive Behavior (EPB);
Employee Performance (EP); Employee Retention (ER); Bias Corrected Confidence Intervals (BCCI).
The product coefficient approach (indirect effect)
was used to explore the potential mediation
effects of EPB, JE, and EP. Using bias-corrected
bootstrap confidence intervals (CI), the
significance of the indirect effects was evaluated
(Gannon et al., 2021). For the sequential
mediation between HPWS and ER through EPB,
JE, and EP, the results show that the impact of
HPWS on ER is sequentially mediated by EPB,
JE, and EP [ = 0.141, p < 0.000, CI = (0.089,
0.185)], hence proving H5. Nevertheless, as the
HPWS rises, the projected direct relationship's
direction shifts, indicating that as ER rises, so do
the levels of JE, EPB, and EP. This illustrates the
importance of ER's effect on sequential
mediation.
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Figure 2. Results (Hypothesis Testing)
Model evaluation
The findings of the assessment of the structural
model are presented in Table 5. Evaluation of a
model's predictive ability should mainly
concentrate on one major target variable which is
(HPWS). Construct cross-validity redundancy is
displayed in Table 5. Numerous criteria were
used to explain and predict the fluctuation in
endogenous variables caused by exogenous
variables (HPWS), as recommended by (Hair et
al., 2020). The fact that all the Q2predict are
significantly more than (0.00) for NFI must be
(greater than 0.90), and the SRMR score should
be (less than 0.08). As we can see in Table 5 the
endogenous variables (EPB, JE, EP, and ER) are
having a large predictive relevance as Q2predict
values for all the endogenous variables is higher
than 0.350, means that the study model
accurately represents the empirical data and has
a great capacity for prediction (Shmueli et al.,
2019). Regarding the value of SRMR, it is
(0.078) and the NFI value is (0.919) this gives
additional proof that the model fit is sufficient.
Table 5.
Model Evaluation
Variables
SRMR
NFI
Predict
2
Q
Effect
2
Q
High Performance Work Systems
0.078
0.919
Job Engagement
0.364
Large
Employee Proactive Behavior
0.483
Large
Employee Performance
0.395
Large
Employee Retention
0.461
Large
for Predictive Relevance
2
SRMR (Standardized Root Mean Square Residual); NFI (Normed Fit Index); QNote:
This study aimed to investigate the sequential
mediation process that links HPWS to ER by
looking at the roles of EPB, JE, and EP. The
results obtained provide empirical evidence of a
significant indirect sequential mediation effect of
HPWS on ER via these mediators. It was
discovered that HPWS influences EPB
positively, suggesting that organizations with
effective work systems are more likely to
encourage employees to take initiative. This
finding is consistent with prior research
highlighting the positive influence of HPWS on
employee behaviors and attitudes (Arefin et al.,
2015; Karadas & Karatepe, 2018; Li et al., 2019;
Zhang et al. 2019). The positive relationship
between EPB and JE suggests that proactive
employees are more likely to be engaged in their
work, contributing to their overall job
satisfaction and organizational commitment
(Jang et al., 2020; Hobfoll et al., 2018).
Moreover, JE was positively associated with EP,
highlighting the significance of the psychological
state of employees in enhancing their
performance. These results are consistent with
previous research demonstrating the positive
impact of JE on a variety of organizational
outcomes (Bal & De Lange, 2015; Jaharuddin &
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Zainol, 2019; Pandita & Ray, 2018). The results
indicate a positive correlation between JE and
EP, indicating that engaged employees tend to
demonstrate higher levels of performance in their
roles. This finding supports previous research
showing a positive correlation between JE and
EP (Chada et al., 2022).
Overall, the results of this study demonstrate the
importance of HPWS in fostering EPB, which
ultimately results in increased JE and enhanced
EP. In addition, the sequential mediation model
demonstrates that EPB, JE, and EP mediate the
relationship between HPWS and ER.
Theoretical implications
HPWS is designed to provide employees with a
range of resources and benefits that can increase
their motivation and commitment to the
organization (Zhu et al., 2018). HPWS may
provide employees with opportunities for skill
development, feedback on their performance,
autonomy in decision-making, and access to
valuable information and resources (Sun et al.,
2007). Social exchange theory (SET) states that
these resources and benefits can be seen as
"inputs" that employees contribute to their
organization, with the expectation of receiving
"outputs" in return, such as job security, career
advancement, and other forms of recognition or
compensation (Blau, 2017). When employees
perceive that their organization is meeting their
expectations and providing them with valuable
inputs and outputs, they are more likely to engage
in proactive behaviors (Cropanzano et al., 2017;
Imran & Atiya, 2020). The SET implies that
HPWS can positively influence ER through EPB,
JE, and EP by providing employees with
valuable resources and benefits (Tian et al.,
2020). When employees perceive that their
organization is investing in their development
and well-being, they are more likely to
reciprocate by engaging in positive work
behaviors, which can contribute to their retention
(Jang et al., 2020; Teo et al., 2020).
Practical implications
HPWS involve a collection of HR processes
intended to enhance organizational performance
by stimulating employee skills, motivation, and
involvement. In the healthcare sector, where
employee retention and turnover are key issues,
understanding the association among HPWS, JE,
EPB, and performance is crucial. The research
findings on HPWS recommend that
organizations that implement these practices can
attain a wide range of benefits, including
increased productivity, profitability, EP, and ER.
In Saudi Arabia, organizations can implement
HPWS and can improve the quality of human
capital by promoting employee development and
training. This is particularly important in Saudi
Arabia, where there is a shortage of skilled
workers in certain industries. HPWS can help
organizations to attract and retain talented
employees by offering opportunities for career
advancement and skill-building.
The implementation of HPWS can have a
positive impact on ER in Saudi organizations
through the promotion of JE, EPB, and EP.
HPWS can promote JE by providing employees
with challenging work, autonomy, opportunities
for skill development, and feedback on their
performance. Engaged workers are more
committed and loyal to the organization because
they feel purpose and satisfaction. Thus, HPWS
can boost JE in Saudi Arabian healthcare
organizations, lowering turnover and retaining
talent. Therefore, by promoting JE, organizations
may foster a supportive workplace culture and a
feeling of belonging within their workforce,
leading to increased retention.
Employee proactivity is a significant factor in
determining ER. A HPWS encourages
employees to be proactive, creative, and
engaged. HPWS can foster ownership and
involvement by letting employees speak up,
make decisions, and solve problems. Valued and
empowered employees are likelier to take the
initiative and improve their workplace. This EPB
fosters employee loyalty and ownership.
Encouraging EPB also helps employees feel
more invested in their work and feel that their
contributions are valued, which can lead to
increased retention.
The relationship between EP and retention is
strong. HPWS emphasize skill development,
feedback, and performance standards. Saudi
healthcare organizations can improve staff skills
by investing in training and development.
Engaged and proactive employees with the right
skills and resources perform better and provide
better patient care. Employee performance
improves organizational outcomes, job
satisfaction, and turnover intentions. HPWS can
help Saudi Arabian healthcare organizations
retain skilled and motivated employees by
increasing job engagement, proactive behavior,
and performance. This improves organizational
performance, patient care, and workforce
sustainability.
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Future direction and limitation
The results above have several limitations. First,
data were collected in three two-month phases.
Cross-sectional studies show temporal causation
but not causality. Thus, future studies should test
for reversed effects and validate the conceptual
model's hypotheses using cross-lagged panel or
longitudinal designs. Second, we conducted an
individual-level evaluation of HPWS. Complex
organizations with many managers and non-
managers may have HPWS agreement issues due
to within-group and between-group agreements.
Thus, future studies may need a multi-level
approach to agreement issues. Thirdly,
information was gathered from the Saudi
Arabian health sector. Limits generalization. Our
HPWS may not be as important in other service
scenarios as in health. Future research should
tailor HPWS to the sample-taking service.
Finally, including turnover and absenteeism in
the model would help future studies.
Conclusion
The research indicates that HPWS have an
important and positive effect on EPB, JE, EP, and
ER in the healthcare industry of Saudi Arabia.
This study results emphasizes the wide-ranging
benefits of HPWS that range beyond its direct
impacts. This sequential mediation underscores
the significance of job engagement and proactive
behaviors in utilizing HPWS to improve
retention and performance. The results also
depict that HPWS can significantly improve the
healthcare industry's capacity to provide high-
quality care by fostering a stable and engaged
workforce by promoting a supportive work
environment.
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