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DOI: https://doi.org/10.34069/AI/2023.65.05.19
How to Cite:
Parveen, M., & Alahmadi, S.H. (2023). Maximizing job performance through HRD mechanisms: An empirical investigation of the
mediating role of multidimensional capital using PLS-SEM analysis. Amazonia Investiga, 12(65), 196-211.
https://doi.org/10.34069/AI/2023.65.05.19
Maximizing job performance through HRD mechanisms: An empirical
investigation of the mediating role of multidimensional capital using
PLS-SEM analysis
PLS-SEM
Received: April 30, 2023 Accepted: June 2, 2023
Written by:
Musrrat Parveen1
https://orcid.org/0000-0002-3796-8061
Web of Science Researcher ID: A-5238-2013
www.researcherid.com/rid/A-5238-2013
Samaher Homoud Alahmadi2
https://orcid.org/0009-0006-0058-8395
Abstract
The primary objective of this study was to
investigate the effect of HRD mechanisms on
human capital (HC), social capital (SC), and
psychological capital (PsyC), and their ultimate
impact on job performance (JP). The study
collected 201 fully completed questionnaires
from nurses, pharmacists, dentists, physicians,
and psychologists out of 330 healthcare
professionals. The survey questionnaire was used
to assess the impact of HRD mechanisms on the
three capitals, which are human, psychological,
and social, and their effect on job performance.
The Smart PLS-SEM software was employed to
test the research hypotheses and fit the
conceptual model of the research. The results
revealed that the dimensions of HRD
mechanisms have a significant and positive
impact on job performance, and human capital,
social capital, and psychological capital have an
influential mediating role. The findings can assist
healthcare settings in enhancing job performance
by focusing on the indicators highlighted in the
study. This paper provides empirical evidence
supporting the theory of HRD mechanism and its
impact on psychological, human, and social
capital, ultimately leading to enhanced job
performance in the healthcare industry. The
study presents a comprehensive comparison lens
to examine the relative contribution of HRD
330
201
PLS-SEM
1
Ph.D, Associate Professor, Faculty of Economics and Administration, Department of Human Resource Management, King
Abdulaziz University, Saudi Arabia.
2
(Student Id No. 2201598) pursing, Executive Master of Human Resources program (EHRM), Faculty of Economics and
Administration, Department of Human Resource Management, King Abdulaziz University, Jeddah, Saudi Arabia
Parveen, M., & Alahmadi, S.H. / Volume 12 - Issue 65: 196-211 / May, 2023
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mechanisms and the three capitals to healthcare
professionals' job performance. This comparison
helps to define the roles of each of the capitals in
healthcare sectors and advances the development
of theories concerning the significant
relationship between HRD mechanisms and the
three capitals leading to job performance.
Keywords: HRD Mechanism, Human capital,
Social capital, Psychological capital, Job
performance, Healthcare professionals,
Healthcare settings, PLS-SEM analysis.
PLS-SEM
Introduction
Capital, including labor, technology, and land, is
crucial for organizations' asset accumulation and
returns (Dobrowolski et al., 2022). Human
capital, comprising education, experience, and
skills, enhances organizational effectiveness
(Ganguly et al., 2019). Education and experience
are critical factors determining knowledge and
ability (Hindasah & Nuryakin, 2020). Alongside
human capital, other forms of capital foster
competitiveness (Huang et al., 2020).
This study explores the impact of HRD
mechanisms on human, psychological, and social
capital, as well as their influence on job
performance (Huang et al., 2020). Psychological
capital reflects individuals' psychological state
and enhances organizational performance (Park
et al., 2017). Social capital encompasses
relationships, obligations, norms, and
expectations among employees, which also
contribute to organizational performance (Tran et
al., 2020). The study adopts a three-dimensional
conceptual framework, focusing on personnel
within organizations. It aims to investigate the
relationships between HRD mechanisms,
different forms of capital, and job performance.
The study will consider various aspects of HRD
mechanisms, different dimensions of capital, and
explore the mediating role of job performance.
This study aims to explore the influence of
human, psychological, and sociological capital
on employee work performance in industries
with high returns and employee diversity. While
the importance of all three capitals in enhancing
performance is not extensively researched,
integrating them can provide a holistic
understanding of their collective impact (Yang &
Lin, 2009). By examining these capitals
simultaneously, their relative contributions to job
performance can be better understood (Huang et
al., 2020). Although literature debates the
dominant influence among these capitals, the
study will investigate the overall impact of all
forms of capital on job performance. To
comprehend their differential contributions, this
research will compare the relationships and
effects of these three capital categories. In
evaluating employee performance, it is argued
that psychological factors, which are not easily
measurable, should be considered alongside
employee interactions with colleagues,
customers, and service staff (Marchante &
Ortega, 2012).
Theoretical Framework and Hypothesis
Development
The resource-based view (RBV) theory serves as
the study's theoretical foundation, highlighting
the significance of resources and capabilities in
establishing sustainable competitive advantage.
Human resources encompass individuals'
knowledge, skills, and talents contributing to
their productivity (Polyhart et al., 2021). The
RBV framework is well suited for examining the
effects of HRD methods on developing HC, SC,
and PsyC (Mackey & Barney, 2019). It provides
a framework to integrate human, psychological,
and social capital into job performance. By
developing and leveraging unique human,
organizational, and physical resources,
companies can gain sustainable competitive
advantage through the RVB paradigm (Fenech et
al., 2019). HRD mechanisms serve as the means
to create and enhance employees' human,
psychological, and social capital.
HRD mechanisms enhance employees' human,
psychological, and social capital. HRD processes
develop employees' skills, knowledge, and
abilities, enhancing human capital. Positive
psychological states like optimism and resilience
are fostered through HRD, enhancing
psychological capital (Nolan & Garavan, 2016).
Similarly, HRD helps establish social
relationships and networks, enhancing social
capital (Kuchinke, 2014). By developing and
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leveraging these capitals, organizations can
improve employee work performance. Higher
human capital leads to increased productivity and
value creation. Greater psychological capital
boosts engagement, motivation, and
commitment. Higher social capital provides
access to resources and support, improving job
performance. Integrating these capitals using the
resource-based view theory allows organizations
to take a comprehensive approach to human
resource development, addressing various
aspects of employee growth for improved
performance. The study aims to assess the
impact, significance, and relationship of HRD
mechanisms with human, psychological, and
social capital and evaluate the mediating role of
HRD mechanisms on job performance through
these capitals.
Literature Review
According to Huang et al., (2020), this study
assessed HRD mechanisms using indicators like
career development, training and development,
performance appraisal, and compensation.
Descriptive statistics indicated that coaching,
individual development strategies, and unbiased
career guidance were significant factors in career
development. Sinha (2020) emphasizes the need
for organizations to provide training for
employees' career improvement and personal
development. Participants reported receiving
appropriate guidance based on their job
requirements. Yu et al., (2022) investigated the
dimension of training and development in HRD
mechanisms, highlighting the importance of
knowledge, skills, and training programs. The
study found that organizations recognized the
value of training programs in meeting employees'
training needs across all quality components.
The study focused on performance appraisal,
finding that organizations prioritize growth and
development. Employee performance is
evaluated based on well-defined objectives and
measurable outcomes, with quality discussions
and feedback during performance reviews.
Objective criteria and constructive feedback are
deemed important in performance appraisal
(Otoo & Mishra, 2018). Compensation was
evaluated in terms of remuneration, allowances,
job performance, and practices. Descriptive
statistics showed that organizations offered
competitive remuneration and allowances. Job
performance played a crucial role in determining
incentives and compensation practices aligned
with organizational goals. This aligns with the
argument that job performance influences
compensation practices (Anitha, 2014).
HRD mechanisms aim to enhance employees'
skills, knowledge, competencies, and abilities
through approaches like mentoring, training
programs, and career development (Jerin, 2021).
Career development involves setting goals,
identifying skill gaps, and acquiring new
knowledge for advancement (Shuck et al., 2018).
Performance appraisal, a part of HRD, assesses
employees' job performance against established
standards and expectations (Dangol, 2021). It
provides feedback, identifies training needs, and
guides professional development (Dagar, 2014).
Performance appraisal results inform targeted
HRD strategies for improving performance and
achieving career goals (Song, 2022).
Compensation is intertwined with HRD,
attracting and retaining employees through
monetary and non-monetary rewards (Nadarajah
et al., 2012). Competitive compensation
packages motivate employees and link pay to
performance and advancement opportunities.
HRD enhances employee skills, increasing their
value to the organization and reflecting in their
compensation (Torraco & Lundgren, 2020).
HRD and compensation work together to
improve productivity and retain top talent.
HRD Mechanisms and the three various
capitals
The study evaluated various types of capital,
including human capital (HC), psychological
capital (PsyC), and social capital (SC), to
understand their association with HRD
mechanisms. Descriptive statistics revealed that
employees' ability to apply new knowledge
effectively improves their work performance
(Albrecht et al., 2015). HRD mechanisms
support employees' learning abilities, enabling
them to generate new and innovative ideas.
The study evaluated the impact of HRD on three
types of capital: HC, PsyC, and SC. The HC
dimension was assessed through respondents'
statements about their work performance, skill
development, and knowledge acquisition. The
results revealed that HRD mechanisms improved
the respondents' ability to transform new
knowledge into effective beliefs, leading to better
work performance. Moreover, HRD facilitated
their learning abilities, enabling them to convert
current knowledge into innovative concepts.
Regarding the PsyC, the respondents reported
that HRD helped them feel more confident in
analyzing long-term issues and developing
solutions. They also felt more represented in
departmental meetings and able to contribute to
conversations about the company's direction.
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Another notable finding was that employees
were psychologically strong enough to devise
several solutions in difficult situations and
pursue their professional goals with rigor. Based
on these attributes, the respondents believed that
they were successful in organizing their
responsibilities simultaneously, anticipating
future challenges, and managing workplace
uncertainties. However, they also reported
experiencing setbacks and encountering
workplace diversity.
These findings are supported by previous
research proclaimed by (Reio Jr & Batista, 2014),
who noted the positive impact of HRD on PsyC,
and (Park at al., 2021), who highlighted the
importance of PsyC for problem solving and goal
achievement. Muduli et al., (2019) also
emphasized the challenges of workplace
diversity and the need for HRD to address them
effectively.
The SC dimension was assessed through
statements related to social relationships,
interactions, opportunities realization, behavioral
consistency, and helping behavior (Oh et al.,
2022). The study found that most employees had
close relationships with their colleagues and
cooperated with them despite differences in
opportunities. The employees also shared the
organization's values of helping others
(Alagaraja et al., 2015). In addition, effective
HRD programs can help employees stay up-to-
date with new technologies and trends,
enhancing their ability to perform their jobs
efficiently and add value to the organization
(Wen et al., 2019). Based on these findings, the
following hypothesis is proposed:
H1a. Human Resource Development
mechanisms shows positive impact on human
capital.
H1b. Human Resource Development
mechanisms shows positive impact on
psychological capital.
H1c. Human Resource Development
mechanisms shows positive impact on social
performance.
H1d. Human Resource Development
mechanisms shows positive impact on job
performance.
Human Capital
The concept of HC relates to intangible assets,
such as knowledge and skills that individuals
possess and can use to create economic value.
Research has shown that investing in HC can
have significant implications for organizations. It
is widely acknowledged that HC is crucial for
workers to acquire new skills and knowledge,
produce high-quality work, and achieve success
in their careers. The HC theory has a significant
amount of evidence that supports the importance
of HC in determining job performance. HC
theory suggests that individuals can gain capital
through education, training, and schooling,
which can enhance productivity for both
individuals and organizations. Although several
studies have examined the link between HC and
firm performance (Chowdhury et al., 2014), few
studies have investigated the impact of HC on
individual employee performance (Bontis &
Fitzenz, 2002).
Chowdhury et al., (2014) have highlighted that
the nature of job tasks is a significant factor in
determining the relationship between employees'
HC and JP. According to their research, task-
specific experience has a greater impact on small
firms' revenue productivity than firm-specific
HC. Therefore, when examining the relationship
between an individual's HC and their JP, it is
essential to consider the job's nature (Ozyilmaz,
2020). For instance, employees in customer-
facing positions in the hospitality industry need
to incorporate emotional intelligence and
emotional inputs into their daily work (Wen et
al., 2019).
Building upon prior research, it has been found
that job demands and resources moderate the
relationship between HC and JP. Specifically,
Bakker & Demerouti (2017) found that job
resources, such as social support and feedback,
could enhance the relationship between HC and
JP, while high job demands, such as heavy
workload and time pressure, can weaken the
relationship. Therefore, in order to maximize the
positive impact of HC on JP, organizations
should aim to create a work environment that
provides employees with sufficient job resources
and minimizes job demands (Albrecht at al.,
2015). Based on these findings, the following
hypothesis is proposed:
H2: Human capital has a positive impact on job
performance.
Psychological Capital
According to Ivanovic & Ivancevic (2022),
having high psychological capital (PsyC) can
help individuals consistently succeed and
navigate their path in the right direction.
Individuals with high PsyC possess qualities
such as overcoming obstacles, demonstrating
persistence in the face of adversity, and
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maintaining a positive attitude towards their
achievements in the present and future.
Moreover, PsyC is considered a psychological
resource that can be objectively evaluated,
developed, and managed. Employees with high
PsyC can take control of organizational
outcomes and are highly effective and
determined in achieving their goals.
Furthermore, PsyC can enhance employees'
confidence in their decision-making abilities,
encourage them to take calculated risks, and
enable them to sustain the business even in
challenging situations.
Research suggests that PsyC has a significant
impact on workplace attitudes, as well as
creativity and innovation (Luthans et al., 2007).
PsyC refers to a set of personal assets that can
improve employee well-being and productivity
while also reducing workplace stress and
burnout. One of the advantages of PsyC is its
developmental nature, which means that
individuals with lower levels of PsyC can
develop or enhance their skills in this area
(Luthans et al., 2007). Research from various
cultures strongly supports the benefits of PsyC
for problem-solving and maintaining
organizational competitiveness. Furthermore,
having high PsyC can lead to better overall well-
being, both inside and outside of work. Based on
these findings, we propose the following
hypothesis:
H3. Psychological capital has a positive impact
on job performance.
Social Capital
Carnevale & Hatak (2020) define "social capital"
as a broad concept that encompasses the potential
benefits an organization can derive from
interactions among its members. They describe
social capital as "social networks and the norms
of reciprocity and trust that emerge from them."
Social capital is considered an intangible asset of
any organization, and positive interactions
among stakeholders are an essential part of it.
When there is mutual trust in connections, social
capital can be sustained. Furthermore, as social
capital increases, new social equilibria may
emerge among participants, leading to higher
levels of cooperation, reciprocity, trust, and
overall community well-being (Wilton, 2019).
While challenging to obtain, social capital is a
vital component for companies and requires
effort to develop. Although extensively studied
in institutional settings, the causes and effects of
social capital remain unclear. Social capital
encompasses factors such as mutual respect and
obligation, trust between group members,
reciprocity, and the free exchange of information
and knowledge, among others. High levels of
social capital have been linked to positive
organizational outcomes, including increased
sales and revenue (Kenedi et al., 2022). Despite
growing recognition of its importance, there
remain significant gaps in empirical research on
social capital. There is a positive correlation
between social capital and occupational
happiness. Based on this reasoning, we propose
the following hypothesis:
H4: Social capital has a positive and significant
impact on job performance.
HRD Mechanisms and Job Performance
To explore the relationship between HRD
mechanisms and JP, the study examined by
(Swanson, 2022) on various aspects of JP, such
as specific job opportunities, performance
standards and expectations, performance level,
job effectiveness, employee comparison, and the
quality of work. The results revealed that
employees were able to meet their job
responsibilities and perform according to
established standards and expectations. They
reported satisfactory performance levels and
were effective in their roles. The study also found
that employees outperformed their colleagues in
the same position and produced high-quality
work.
HRD mechanisms refer to the various methods
and processes used to educate, train, and develop
employees within an organization. Examples of
HRD mechanisms include on-the-job training,
mentoring programs, and formal education and
development classes. Several studies have shown
a positive correlation between HRD mechanisms
and JP. However, the role of different types of
capital in this relationship has been overlooked
due to the varying dimensions of capital (Huang
et al., 2020). Regular training and development
opportunities can provide employees with the
skills and knowledge necessary to perform their
job effectively, which can contribute to their job
satisfaction and motivation (Marchante &
Ortega, 2012).
HRD mechanisms, like training, mentoring, and
career development, significantly impact job
performance (JP). They enhance employees'
knowledge, skills, and abilities, increasing
efficiency and effectiveness (Soo et al., 2017).
HRD also boosts motivation, satisfaction, and
engagement, leading to improved JP (Avey et al.,
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2011). Additionally, HRD helps employees adapt
to job changes and new technologies, enhancing
JP and organizational value. It can be delivered
through on-the-job training, formal education, or
e-learning. Customization, regular review, and
updates optimize the effectiveness of HRD
mechanisms for individuals and organizations
(Kim et al., 2017). This aligns with Huang et al.'s
(2020) argument that HRD, along with human,
psychological, and social capital, helps cope with
stressful conditions. Research suggests self-
efficacy improves work performance. Therefore,
HRD mechanisms are crucial for supporting
employee development, improving JP, and
strengthening human, psychological, and social
abilities. Thus, we propose the hypothesis:
H5: Human capital mediates between HRD
mechanism and Job performance.
H6: Psychological mediates between HRD
mechanism and Job performance.
H7: Social capital mediates between HRD
mechanism and Job performance.
Figure 1. Theoretical Model
Research Methodology
Research Method
The study employs a quantitative research
method to achieve the study's research
objectives. The method was chosen because it
successfully delivered numerical (or non-textual)
information to relate HRD mechanism and job
performance through human, psychological and
social capital (Huang et al., 2020). The study
quantitatively analyzed the HRD methods and its
relationship to job performance rather than
conducting an in-depth assessment.
Population and Sampling
The target population for the study were
healthcare professionals who are working in
private industries inside the kingdom of Saudi
Arabia, and it was distributed within nurses,
pharmacists, dentists, physicians and
psychologists exclusively in Jeddah, Dammam
and Riyadh. However, given the cost and time
constraints, the study employed a representative
sample of employees using probability sampling
strategy.
Sample Size
The study analyzed data from 201 employees
(including nurses, pharmacists, dentists,
physicians and psychologists) out of the initial
330 participants. These employees had over 3
years of experience and worked in various public
and private healthcare settings. The survey
included full-time staff members in healthcare
professions and public and private healthcare
sectors.
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Research Instruments
The study employed survey questionnaire as a
research instrument to evaluate the impact of
HRD mechanism on the three various capitals
which are human, psychological and social, and
how it lead to job performance. This study's data
collection process was inspired by prior related
research related to HRD, SC, PsyC, HC and JP.
As the research tool for this study, a survey
questionnaire was used which was adopted from
the scales of Huang et al. (2020). The rational for
using the instrument is that it allows
incorporating measurement procedures that
require primary data from respondent by asking
questions (Taherdoost, 2016). To outline the
overall goal of the questions I started the
questionnaire with statement included the
purpose, benefits and assurance of anonymity of
the respondents. After the statement, there was
four parts for the respondents to fill. First part
included demographic details to regulate the type
of targeted respondents. Second part HRD
mechanism, which included four subcategories
(Career Development – Training – Performance
Appraisal - Compensation). The last parts were
specified for each variable separately (HC - PsyC
- SC – JP). Given the time span, the study was
conducted using cross-sectional surveys and
questions were close ended. The study assessed
the survey questionnaire using the 5-point Liker
scale that range from strongly disagree to
strongly agree.
Result Analysis
The questionnaire collected demographic data
and assessed HRD mechanisms (career
development, training, performance appraisal,
and compensation), human capital,
psychological capital, social capital, and job
performance. Frequency descriptive statistics
were used to analyze the gathered data and
achieve research objectives. The analysis
examines the association between HRD
mechanisms and job performance, considering
human, social, and psychological capital. The
subsequent sections provide an overview of the
analysis based on respondent information.
Table 1 shows the results related to the
demographic characteristics of the statistical
sample that was analyzed. These characteristics
included gender, age, marital status, working
experiences, education, healthcare professionals
and healthcare settings of the respondents.
Table 1.
Demographic Analysis
N
%
Gender
Male
76
37.8%
Female
125
62.2%
Age
18-24 years
18
9.0%
25-34 years
76
37.8%
35-44 years
36
17.9%
45-54 years
37
18.4%
55-64 years
34
16.9%
Experience
1-3 years
49
24.4%
4-6 years
31
15.4%
7-9 years
29
14.4%
10-12 years
12
6.0%
13-15 years
80
39.8%
Education
Diploma holder
17
8.5%
Bachelor
36
17.9%
Master and above
148
73.6%
Marital Status
Married
138
68.7%
Unmarried
63
31.3%
Healthcare Professionals
Nurses
51
25.4%
Pharmacists
10
5.0%
Dentists
21
10.4%
Physicians
26
12.9%
Psychologists
93
46.3%
Healthcare Settings
Private
76
37.8%
Public
125
62.2%
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Testing Descriptive Statistics
The descriptive analysis has been performed with
the help of SPSS software version 25 to test the
mean score, standard deviation and normality
assumptions of the gathered data from
respondents. For this reason, the study has used
the descriptive statistics to demonstrate the
measurement items of HRD mechanism, capital
and JP.
Table 2.
Descriptive Statistics & Bivariate Pearson Correlation
Descriptive
Bivariate Pearson Correlations
Mean
SD
1
2
3
4
5
Gender
1.6219
0.486
AGE
2.965
1.266
Marital Status
1.313
0.465
Working Experience
3.213
1.658
Education level
2.651
0.630
Healthcare Professionals
3.497
1.676
Healthcare Settings
1.621
0.486
Human Resource Development (HRD)
3.958
0.713
1
Human Capital (HC)
4.312
0.551
**
.693
1
Psychological Capital (Psy.C)
4.035
0.523
**
.661
**
.702
1
Social Capital (SC)
3.999
0.617
**
.668
**
.659
**
.746
1
Job Performance (JP)
4.325
0.527
**
.479
**
.579
**
.610
**
.590
1
Note 1: **. Correlation is significant at the 0.01 level (2-tailed).
Table 2 shows that HRD mechanism has been
assessed with the help of career development,
training and development, performance appraisal
and compensation. The table 2 indicates that
mean score of all items were greater than 2.5
reflecting general agreement of respondents on
the statements (Huang et al., 2020). Whereas
absolute values of Bivariate Pearson Correlations
(less than 8) affirm that, there was no violation of
normality in the data (Katou, 2009). The standard
deviation of the results indicates that they are
closely related to the mean, which correlate the
significance of the results.
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Table 3.
Fitting Measurement Model
The PLS-SEM method utilizes three criteria,
namely reliability, convergent validity, and
divergent validity, to assess the fitness of
measurement models. The model analysis
algorithm has yielded the following results. To
evaluate reliability, three criteria, namely factor
load coefficients, Cronbach's alpha, and
combined reliability, have been used. Factor load
measurement is indicative of a strong level of
significance and high correlation between
observation and factor variables. A factor
analysis value above 0.5 signifies a well-defined
structure. Cronbach's alpha is an acceptable final
indicator if the value is above 0.7, but for
variables with a small number of questions, a
value of 0.6 has been introduced as the limit of
Cronbach's alpha coefficient. Combined
reliability is more realistic and accurate than
Cronbach's alpha because it factors in the
importance of indices with higher factor loads in
the calculation of CR. Therefore, CR values
provide a more accurate representation of the
structure. Convergent validity, the second
criterion used to assess the fitness of
measurement models in the partial least squares
method, has yielded higher average variance
extracted (AVE) and composite reliability
values. This indicates better construct reliability
and validity, leading to results that are more
reliable. All Variance Inflation Factor (VIF)
values were found to be less than 5, meeting the
criteria for independence between the model and
variables. The primary objective is to maximize
the explained variance in the dependent
constructs while also assessing the quality of data
based on measurement model characteristics.
The indicators suggest that the greater the
correlation, the better the fit.
a
Constructs Items Type Loadings rho-A CR AVE VIF
Job Performance
Human Resource Development
Human Capital
Psychological Capital
Social Capital
CDHRD1
CDHRD1
CDHRD1
CHRD1
CHRD1
CHRD1
Reflective
0.768
0.929 0.931 0.939 0.561
2631
0.738
2411
0.706
1834
0.624
1724
0.750
2442
0.761
2469
PAHRD1
0.789
2671
PAHRD1
0.764
2886
PAHRD1
0.782
2547
TDHRD1
0.753
2200
TDHRD1
0.791
2437
TDHRD1 0.793 2555
HC1
Reflective
0.873
0.801 0.812 0.883 0.716
1918
HC2
0.783
1495
HC3 0.879 2035
PC1
Reflective
0.710
0.834 0.837 0.878 0.547
1610
PC2
0.794
2006
PC4
0.738
1737
PC5
0.707
1558
PC6
0.711
1633
PC7 0.773 1707
SC1
Reflective
0.721
0.834 0.852 0.878 0.549
1737
SC2
0.652
1599
SC3
0.607
1407
SC4
0.828
2224
SC5
0.793
2184
SC6 0.815 2570
JP1
Reflective
0.822
0.860 0.867 0.900 0.643
2222
JP2
0.837
2259
JP4
0.826
2023
JP5
0.706
1606
JP6 0.810 1989
a= cronbach alpha; CR = composite reliability; AVE = average variance extracted; VIF = variance inflation factor; BCCI =
bias corrected confidence interval.
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Figure 2. PLS –SEM Algorithm
To address the issue of multicollinearity, a
discriminant validity test was conducted using
the Fornell-Larcker Criterion and HTMT
Criterion technique. The Fornell & Larcker
(1981) criterion was utilized to examine the
model's discriminant validity, wherein the
diagonal values of constructs should be greater
than their correlation with other constructs. As
presented in Table 4, the square root of all
diagonal values for each construct exceeds its
correlation with other constructs. The heterotrait-
monotrait (HTMT) approach's accepted values
can be lower than 0.85 (Henseler et al., 2015).
The results affirm the discriminant validity of the
model.
Table 4.
Discriminant validity using Fornell-Larcker Criterion and HTMT Criterion
Prognostic relevance of study model
To assess the prognostic relevance of the model,
the current study utilized two methods: R2 and
cross-validated redundancy. Previous research
has utilized R-squared to determine the model's
predictive power (Hair, 2011; Henseler et al.,
2015). If the R2 value is greater than 0.26, it is
considered substantial, while a value within the
range of 0.13 to 0.26 is deemed moderate, and a
value within the range of 0.02 to 0.13 is
considered weak. In the present study, the R2
values for human capital, psychological capital,
social capital, and job performance all fall within
the substantial range. Furthermore, cross-
validated redundancy is another factor used to
assess the quality of the research model. The
blindfolding technique in SmartPLS is used to
accomplish this, and it requires the researcher to
exclude certain data values, which are then
HC HRD JP Psy.C SC HC HRD JP Psy.C SC
HC 0.846
HRD 0.699 0.749 0.805
JP 0.609 0.515 0.802 0.723 0.566
Psy.C 0.710 0.641 0.720 0.739 0.866 0.721 0.840
SC 0.676 0.680 0.625 0.728 0.741 0.814 0.749 0.742 0.832
Fornell-Larcker Criterion
Hetro-Trait Mono -Trait (HTMT) Criterion
Note: The bold numbers in diagonal in Fornell -Larcker section are square root of AVE of each construct, and other numbers are
correlation between constructs
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treated as missing values. The blindfolding
running technique employs an omission distance
of 7, and after this process, certain values are
generated and compared to the assumed results to
determine how close or far they are from the
actual results. The criterion for determining the
model's prognostic relevance is that the values
must be above 0, and Table 5 demonstrates that
the current study satisfies this criterion. The
cross-validated redundancy for human capital is
0.343, for psychological capital, it is 0.218, for
social capital, it is 0.247, and for job
performance, it is 0.345.
Table 5.
Prognostic accuracy and relevance of the model
Hypothesis Testing
Table 6 displays the beta values that indicate the
strength and significance of the positive
relationship between the independent and
dependent variables, as well as the mediators.
The results show that Human resource
development has a substantial impact on Job
performance (β = 0.532, mean 0.537, SD = 0.040,
t = 13.389, p = 0.000), and it also has a positive
and significant effect on Human capital (β =
0.699, mean 0.701, SD = 0.032, t = 22.16, P =
0.000), Psychological capital (β = 0.641, mean
0.647, SD = 0.042, t = 15.34, P = 0.000), and
Social capital (β = 0.680, mean 0.701, SD =
0.032, t = 22.16, P = 0.000). Moreover, Human
capital has a positive and significant effect on Job
performance (β = 0.144, mean 0.143, SD = 0.078,
t = 1.836, P = 0.018), while Psychological capital
(β = 0.498, mean 0.504, SD = 0.083, t = 6.022, P
= 0.000) and Social capital (β = 0.165, mean
0.162, SD = 0.072, t = 2.361, P = 0.019) also have
significant effects on Job performance.
The findings indicates that Human capital
mediates the link between human resource
development and job performance. The values of
indirect effects (β = 0.100, t = 1.840, P = 0.000)
are significant, which clearly depicts that human
capital partially mediates the impact of human
resource development on job performance.
Hence, the findings support H2.
Secondly, the outcomes also reveals that
Psychological capital mediates the link between
human resource development and job
performance. The results reveal that indirect
effects (β = 0.326, t = 5.461, p = 0.000) are
significant and support H3.
Finally, the results also suggest that Social
capital partially mediates these effects, because
the indirect effect (β = 0.110, t = 2.336, p =
0.020) are significant. Therefore, H4 is accepted.
Overall, all the hypothesis are significant and
acceptable.
Table 6.
Results of Hypothesis Testing
Variables R-Squared (R2) (Q2)
Human Capital 0.488 0.343
Psychological Capital 0.411 0.218
Socail Capital 0.462 0.247
Job Performance 0.549 0.345
5.00% 95.00%
H1a HRD -> HC 0.701 0.032 22.16 0.000 0.003 0.628 0.754 Supported
H1b HRD -> Psy.C 0.647 0.042 15.340 0.000 0.006 0.558 0.716 Supported
H1c HRD -> SC 0.682 0.036 19.134 0.000 0.002 0.602 0.739 Supported
H1d HRD -> JP 0.537 0.040 13.389 0.000 0.005 0.440 0.597 Supported
H2 HC -> JP 0.143 0.078 1.836 0.018 -0.001 -0.006 0.308 Supported
H3 Psy.C -> JP 0.504 0.083 6.022 0.000 0.006 0.310 0.642 Supported
H4 SC -> JP 0.162 0.072 2.361 0.019 -0.003 0.030 0.316 Supported
H5 HRD -> HC -> JP 0.100 0.055 1.840 0.000 -0.001 0.000 0.210 Supported
H6 HRD -> Psy.C -> JP 0.326 0.058 5.461 0.000 0.007 0.198 0.429 Supported
H7 HRD -> SC -> JP 0.110 0.048 2.336 0.020 -0.002 0.021 0.220 Supported
Bias
Bias Corrected
Hypothesis Supported
Note: HRD denotes Human Resource Development;HC denotes Human Capital; Psy.C denotes Psychological Capital;SC denotes Social Capital; JP
denotes Job Performance
Hypothesis
Direct / Indirect Effect
Sample Mean
STDEV
T Value
P values
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Discussion
The primary objective of this study was to
examine how the implementation of HRD
(Human Resource Development) mechanism
affects the human, psychological, and social
capital of healthcare professionals working in
public and private healthcare facilities in Saudi
Arabia, and how this ultimately affects their job
performance. The research conducted was both
descriptive and quantitative in nature. The above-
mentioned literature's theories were utilized and
incorporated to improve our comprehension of
how HRD impacts social, psychological, human
capital, and job performance.
The findings indicate that the HRD mechanism
has significant and substantial impact on job
performance. These results are in agreement with
a previous study by Soo et al., (2017), which
suggests that the HRD mechanism has a
significant effect on job performance in
healthcare settings. The results demonstrate that
Human Resource Development has a significant
effect on Job performance (β = 0.532, mean
0.537, SD = 0.040, t = 13.389, p = 0.000),
providing support for our hypothesis H1d.
Avey et al., (2011) research suggests that Human
Resource Development has a positive and
significant impact on Human capital (β = 0.699,
mean 0.701, SD = 0.032, t = 22.16, P = 0.000),
which supports hypothesis H1a. Similarly, (Reio
& Batista, 2014) found that Human Resource
Development has a positive influence on
psychological capital (β = 0.641, mean 0.647, SD
= 0.042, t = 15.34, P = 0.000), thus supporting
hypothesis H1b. Alagaraja et al., (2015) revealed
that Human Resource Development significantly
affects social capital (β = 0.680, mean 0.701, SD
= 0.032, t = 22.16, P = 0.000), lending support to
hypothesis H1c. Finally, Albrecht's et al., (2015)
study discloses that Human capital has a positive
and significant effect on Job performance (β =
0.144, mean 0.143, SD = 0.078, t = 1.836, P =
0.018), thereby supporting hypothesis H5.
Park's et al., (2021) research indicated that
psychological capital has a significant impact on
Job performance (β = 0.498, mean 0.504, SD =
0.083, t = 6.022, P = 0.000), providing evidence
in support of hypothesis H6. Furthermore,
research by (Jeong et al. 2022) demonstrated that
Social capital has a significant effect on Job
performance (β = 0.165, mean 0.162, SD = 0.072,
t = 2.361, P = 0.019), thus confirming hypothesis
H7.
Table 6 reveals that the outcomes illustrate how
social, psychological, and human capital serve as
mediators in the association between HRD
mechanism and Job performance. Both the direct
and indirect effects are meaningful, indicating
partial mediation, which corresponds to (Huang
et al., 2020) research.
The current study used two things to determine
the prognostic relevance of our model; first is R2
and the second is cross-validated redundancy.
The findings in table 5 indicates that HRD
mechanism have a Strong and significant effect
on human, psychological, social and Job
performance. In the current research, R2 values
of human capital, psychological capital, social
capital and job performance lies in substantial
case. However, the criterion of the predictive
relevance of model by cross-validated
redundancy (Q2) is that values must be above
than 0, and Table 5 shows that the current study
fulfills this criterion. Cross-validated redundancy
for Human capital is 0.343, Psychological capital
is 0.218, Social capital is 0.247 and Job
performance is 0.345. Table 7 clearly shows the
SRMR value (0.071) and NFI value (0.921)
further validated a good fit model.
Table 7.
Model assessment through Blindfolding effect
Variables SRMR NFI SSO SSE
Q2Q2 Effect
HRD
HC 603.00 396.47 0.343 Medium
Psy.C 1206.00 942.60 0.218 Medium
SC 1206.00 908.59 0.247 Medium
JP 1005.00 658.53 0.345 Medium
0.071
0.921
Note: SRMR(Standardized Root Mean Square Residual); NFI (Normed Fit Index); SSO
(Sum of Squares of Observations); SSE (Sum of Squares of Errors)
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Conclusion
Our study confirms the significant impact of
HRD mechanisms and the three forms of capital
on healthcare professionals in public and private
sectors. It identifies key HRD practices and the
mediating effect of psychological, social, and
human capital on job performance. The findings
suggest organizations can improve job
performance by focusing on these capitals. The
study contributes to theory, methodology, and
practice, emphasizing the importance of
satisfied, social employees for productivity.
Employee psychological and sociological factors
play a crucial role in enhancing job performance
through HRD mechanisms.
Theoretical implication
This study offers empirical evidence supporting
the theory of HRD mechanism and its impact on
Psychological, Human, and social capital,
ultimately leading to enhanced job performance
in the healthcare industry. The results highlight
the usefulness of HRD mechanisms such as
training, coaching, and career development in
significantly influencing job performance by
enabling employees to acquire the necessary
knowledge, skills, and abilities to perform their
jobs effectively (Soo et al., 2017). Moreover,
these mechanisms can improve employee
motivation, job satisfaction, and engagement,
resulting in better job performance (Avey et al.,
2011). HRD mechanisms enhance employee
adaptability, job performance, and organizational
value. Methods like on-the-job training, formal
education, and e-learning can be effective.
Customized and regularly updated HRD
approaches align with individual and
organizational needs, ensuring relevance and
effectiveness (Kim et al., 2017).
Overall, HRD mechanisms enhance job
performance by strengthening human,
psychological, and social abilities. This study
explores the individual effects of the three
capitals on performance, highlighting their
importance in improving service employee
performance. Previous research supports the
critical role of all three capitals in employee
development (Wen et al., 2019).
Practical implications
PLS analysis provided practical insights for
healthcare professionals in Saudi Arabia, guiding
managers on improving job performance through
HRD and capital forms. Professionals
acknowledged the value of HRD for their
development and maintaining work-life balance.
Organizations can leverage this model to achieve
long-term goals and pursue further progress.
Limitations of the Study
Limitations include not using all subscales and
treating variables as a single summarization.
Future research should explore specific subscales
like career development, compensation, and
performance appraisal. Longitudinal studies with
larger, more detailed data are recommended.
Increasing the number of respondents beyond
201 would yield results that are more accurate.
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