Content uploaded by Abdul Basit
Author content
All content in this area was uploaded by Abdul Basit on Sep 26, 2023
Content may be subject to copyright.
Journal of Policy Research, 9(2), 300-319.
https://jprpk.com
https://doi.org/10.5281/zenodo.8210698
300
Evaluating Moderating Effect of Organizational Transformation on Relationship of Strategic HRM Practices and
Employee Retention
Abdul Aziz Khan Niazi
1
, Shumaila Inam
2
, Tehmina Fiaz Qazi
3
, Abdul Basit
4
, Ifra Aziz Khan Niazi
5
Abstract
Turnover is a symptom of a critical structural issue such as inadequate retention management, companies should consider
what makes people commit to being loyal and successful. The easiest way to retain employees is to increase their level of
satisfaction, but this will only be effective if properly performed. To retain skillful employees, Strategic Human Resource
Management (SHRM) practices are required. The purpose of study is to examine the moderating effect of organizational
transformation on SHRM practices and employee retention in manufacturing area. Data is collected from employees of
textile sector through questionnaire consisted 384 responses. Data statistically analyzed through structural equation
modelling using Warp PLS. Results shows that SHRM practices and its dimensions have a significant impact on employee
retention, and organizational transformation has a moderating role in the impact of SHRM and on employee retention. The
results of study are useful for management of the companies by way of improving the employee retention. This study
contributes in the body of knowledge by way of testifying the hypothesized relationships.
Keywords: Strategic human resource management, recruitment & selection, training & development, employee retention
and organizational transformation
1. Introduction
The field of Strategic Human Resource Management (SHRM) was developed in 1970s. The basic premise of SHRM is to
manage employees according to fast changing environment. Explicitly, it is linked with financial performance of company
(Fahim, 2018). Researchers have defined SHRM as making of policies for human resource deployments to achieve goals
of an organization (Fahim, 2018). In simple words, implicitly, SHRM is associated with employees within an organization.
Basically, employees are the key for the success of any company. It is obvious that if company will not be able to manage
its employees effectively then company may have to bear cost and it may also vicious for the existence of company (Fahim,
2018).
All in all, this is the brief introduction of SHRM. There are different researchers who put effort in this regard. For example,
studied SHRM in supply chain. These researchers highlight that previously this area was neglected by the researchers
(Lengnick-Hall et al., 2013) Moreover, Mitchell et al. (2013) investigate the impact of SHRM on financial performance of
the company. Martin et al. (2016) introduce the new typology that link SHRM practices with corporate governance at firm
level. Fahim (2018) highlight that SHRM practices enhance employee retention. However, literature clearly neglect the
catalytic role of organizational transformation in the association between SHRM practices and employee retention.
Employee turnover results in company downsizing due to the employee morale which is lowered. The lowered morale
results in decreased retention rate of employees. Here exists a study gap on the concept of what SHRM practices needs to
consider that aid in retaining the employees of the organization especially in the context of voluntary and involuntary
turnover. Most of the studies have surpassed on the issue but still there exists a gap for investigating the issue of employee
retention. In particular, the role of organizational transformation moderating the relationships of different constituent
variables of job retention was the research gap found (Fahim, 2018).
High employee turnover in private sector organizations is a major problem (Rasal, 2019). Management of the corporations
is keen to understand the dynamics of employee retention. Employee retention is a serious agenda of HRM research (Hassan
& Govindhasamy, 2020). Lot of research has surpassed on the issue but still there is lot of room for investigation of the
issue of job retention. Particularly the moderating role of organizational transformation on the relationships of different
constituent variables of job retention (Fahim, 2018). Therefore, the study is designed to address this critical issue. By
considering this catalytic role of corporate governance in fact this is the first study, in which it is studying that organizational
transformation moderates the association between Strategic Human Resource Management Practices and employee
retention.
2. Literature Review and Hypotheses Development
The main purpose of this review is to develop a theoretical background of this study and identify SHRM practices, employee
retention, and organizational transformation. Firstly, it reviews literature on relevant theories, and relationship related to
1
Assistant Professor, Institute of Business & Management, University of Engineering and Technology Lahore, Pakistan
2
Research Scholar, Institute of Business & Management, University of Engineering and Technology Lahore, Pakistan
3
Hailey College of Banking & Finance, University of the Punjab, Lahore, Pakistan
4
Lahore Institute of Science & Technology, Lahore, Pakistan
5
Faculty of Management Studies, UCP Business School, University of Central Punjab, Lahore, Pakistan
Niazi et al….
301
SHRM practices, employee retention, and organizational transformation. Moderation effect of organizational
transformation on the relationship between SHRM practices and employee retention.
2.1. Strategic Human Resource Management (SHRM)
Fahim (2018) posited that Human Resource Management (HRM) is the best practices for the retention of employees.
Besides it Delery and Roumpi (2017) indicates that HRM practices do not simply contribute to the sustainable competitive
advantage like SHRM researches hypothesize. HRM practices help in reducing constraints of demand and supply with
increasing level of motivation. It is also suggested that human resource practices are the controller for making knowledge
management system more effective (Delery & Roumpi, 2017). To obtain a competitive benefit in market, HRM is a crucial
part (Nanyangwe & Phiri, 2021). Employees who working in implementing the mission of the company and their turnover
puts the company's identity and guiding principles at jeopardy. In relationships of theory and planning, SHRM is such an
area who is accountable in maintaining strategies in the ground of strategic human resources maintenance in accordance
with the organization's general strategies. Whereas, HRM is tasked with implementing the developed strategies in the form
of SHRM to maintain these types of employees. In actuality, HRM is pragmatic and objective while SHRM is theoretical
and subjective (Sepahvand & Khodashahri, 2021). Greer (2021) states human resources are much important now a day as
organizations are growing faster and they have to compete their advantage. So, it is key that distinctive proficiencies are
only gained through when an organization have skillful personnel, well reputed organizational culture. Early HRM is
considered as a strategic and logical approach for the management of organization. And is identified as the most valuable
asset of organization where employees work and they contribute to the achievement of the organization’s objectives
(Armstrong, 2006). Currently organizations are become move towards the concept of “strategic management” instead of
HRM.
2.2. Employee Retention
Retention of employees means "the various policies and practices that let employee stick to an organization for the long
period of time" (Kloutsiniotis & Mihail, 2020). According to Choy and Kamoche (2021) here are some factors that effect
on employee turnover as compensation and benefits, location of work place, environment of work place, administration,
high customer communication, work relations with other workers. Employee retention generally influenced by the policies
of recruitment and human resource practices. Worldwide huge number of organizations facing the challenge to retain their
most skillful employees. Nowadays, organizations can involve their employees by enhancing their talent and progressively
it can be tradition of an organization to enhance and promote human capital. Ultimately this is helpful in retention of
employees (Radadiya & Pandey, 2020). Maintaining competent employees and passing along their expertise and knowledge
to individuals is crucial given the significance and necessity of training and empowerment of persons to enter the labor
market as well as advancement of their career anchors and job careers. Kloutsiniotis and Mihail (2020) emphasized that
governments are facing problems not just in the private sector but also in maintaining their professional workers. Employee
retention within the organizations is an important parameter for assessing any organization's success (Hassan &
Govindhasamy, 2020). According to Malik et al. (2020) now a day, companies are focused on managing human resource.
HRM practices and employee retention has significant relationship. The turning of employees is a critical challenge for
organizations, but companies’ employees leave are closely related to HR practices and therefore a holistic understanding
of the relationship between HRM and retention of employees would help companies make the right decisions to achieve
business results while maintaining an appropriate level of resources (Hassan & Govindhasamy, 2020). Parmenter and
Barnes (2021) suggest that a culturally capable initial workforce, culturally suitable support instruments and access to
proficient expansion of prospects are significant retention aspects. According to Malik et al. (2020) now a day, companies
are focused on managing human resource. HRM practices and employee retention has significant relationship. By
implementing HRM practices employees get motivation and positive attitude towards work which can ultimately reduce
the turnover rate of employees within organization. Since qualified employees are one of the company's most valuable
intellectual capital, employee retention aims to keep them on board for as long as possible. Employee retention is the method
by which a company is able to keep its prospective workers in order for them to stay loyal to the company for a longer
amount of time. More specifically, HR professionals need to deal with dysfunctional turnover in a proactive manner
(Fernando & Wulansari, 2020). Retaining staff in a business is a crucial factor in determining that organization's success
rate. The industrial sector has been expanding toward worldwide, which has changed how employees interact with their
employers. Therefore, businesses must find ways to keep skilled and educated individuals on staff when there is a huge
turnover ratio (AlQershi et al., 2022).
2.3. Organizational Transformation
Process of transformation associated with the change of business model. Whenever challenges related to behavioral
management are took to light outcomes of transformational process cannot be achieved. Mostly the employee resists in the
process of transformation in organization (Buschmeyer et al., 2016). Attitude at the organizational and individual level has
strong and basic impact in the success of transformation from a constructor to a solution provider (Buschmeyer et al., 2016).
Kumar Basu (2015) states that transformational leadership boost up change in organization by inducing personnel behaviors
Niazi et al….
302
and raising stages of work engagement. Many of the research has surpassed on transformational leadership as it is important
and vital key in the change process of organization (Middleton et al., 2015). Digital transformation (DT) is increasingly
establishing itself as a persistent theme in existing theoretical and expert discussions (Hanelt et al., 2021). Moreover, it is a
deliberate significance (Nadkarni & Prügl, 2021) and digital transformation influencing and become a challenge for HR
with in organization (Andriole, 2017; Benner & Waldfogel, 2020; Correani et al., 2020). In the context of identifying new
approaches and current research on global digitalization, the most important aspect of digital transformation is a radical
shift in thinking generalizations, work methods, and organizational management that meets the goals and objectives of the
digital paradigm of economics and management. As previously highlighted, the major objective in implementing the digital
paradigm of business and finance should be on the execution of business operations, which will allow organizations to stay
competitive with competing brands in a growingly "digital" world; to convert the structure and restructure the organization
as a whole to effectively adjust to new digital environment; to try to escape from the gravity of conventional methods to
business process organization and maximize the potential of modern digital technology (Voronkova et al., 2021). A
numerous financial institutions are trying to adopt the changes which are banking sector in Bangladesh has adopt and go
through a big transformation as upgradation of IT system, execution of globally friendly banking systems and customer
service developments (Julia et al., 2019). IT-business alignment and digital transformation are among the many concepts
that are closely related to IT-enabled organizational transformation (Vial, 2019).
2.4. Hypotheses Development
2.4.1. Strategic Human Resource Management Practices and Employee Retention
Nowadays human resource management has purpose to create strategic capabilities. By creating these strategies, they attract
experienced, competent and proficient employees in their organization. However, management of organization always put
effort to its valuable employees to avoid voluntary turnover. Organizations which provide their employees training and
development, reward system employees get satisfied and subsequently their retention (Shirazi & Hosseini Robat, 2015).
There are a lot of HRM practices which can be introduced as several HRM practices can be introduced as its aspects. By
introducing these HR practices aspects can motivate employees, satisfied them, and they can feel committed with the
organization. Ultimately, it helps from leaving the organization (Aburumman et al., 2020). Thus, hypothesize that:
H1: SHRM practices are positively related to Employee Retention.
H2: The outbound open innovation has a significant association with strategic innovation.
2.4.2. Recruitment and Selection and Employee Retention
Selection is a method to choose a suitable candidate to fill the vacant position. Selection of candidate is done through a
required and proper procedure who is traced to the required procedure of the organization. Selection process is a wide range
process and it can be more extend in large companies. According to Dany and Torchy (2017) selection process is a method
to select the person who are fit to job position. Selection of right and match to job position employee is necessary for the
execution, costs, and legal obligations (Brown et al., 2019).
H2: Recruitment and selection has significant impact on Employee Retention.
2.4.3. Training and Development and Employee Retention
Training and development has relation with employee retention. Organization gives opportunities to their employees to
enhance their skills through training and it gives them a level of satisfaction from the organization, which leads to stay with
organization. It is a challenge for the HR authorities is to advance and recognize the career development strategies. With
the implementation of these strategies employees get motivation to put their least effort in organization, they feel to face
challenges and work with enthusiastically. On the other side with the great motivation of employees’ organizations able to
its targeted purpose and can achieve their goals (Jeffrey & Prasetya, 2019). Based on the above discussion, we hypothesize
that:
H3: Training and Development has impact on Employee Retention.
2.4.4. Performance and Appraisal and Employee Retention
Performance appraisal can also be considered as bridge of communication in management and employees. So, it is directly
linked with retention. Organizations needs to understand that employees take it into serious for a positive employee
performance analysis Jeffrey & Prasetya, 2019). HR managers need to retain those employees who perform efficiently and
whereas employees which are showing low performance improve them through appraisal system. Kim and Rhee (2011)
posit that through a proper and effective appraisal system a business can flourish and employees get development. Based
on the above discussion, the following hypothesis is given;
H4: Performance appraisal has impact on employee retention.
2.4.5. Compensation and Benefits and Employee Retention
Organizations have to plan such type of direct and indirect methods of employee benefits and their contribution for the high
retention. Employers not only can rely non-financial incentives but need to give them financial incentives as compensation
(Khalid & Nawab, 2018). These financial incentives give to their personnel commitment, satisfaction and it became the
persuasive factor for personnel to stay with organization. If it is decided that only monetary compensation is main factor
Niazi et al….
303
that give to employees and they wiling to retain in organization is not true. Because many of the other competitors gives
high salary packages and high monetary benefits. Many other factor should be take into account for the retention
(Sepahvand & Bagherzadeh Khodashahri, 2021). These factors are important that promotes commitment of employees.
Human resource managers need to focus on these factors (Vu & Nwachukwu, 2020). Based on the above discussion, the
following hypothesis is given:
H5: Compensation and Benefits has impact on Employee Retention.
2.4.6. Moderating Role of Organizational Transformation SHRM Practices and Employee Retention
For an organization to achieve their goals effective human resources are essential and important. However, organizations
always cannot stop to leave their valuables employees but obviously adopting efficient human resources policies and
procedures management can severely reduce its occurrence (Shirazi & Hosseini Robat, 2015). Regarding all phases of
talent management, including recruiting, selecting, compensating and rewarding, developing, and retaining the right people,
the managers and employees values directly influence how they think (Kamel, 2019). For the retention of employees’
strategic human resource management is important and has a big impact. In some studies, employee retention is viewed by
Iranian Journal of Management Studies Sepahvand and Bagherzadeh Khodashahri (2021) as the outcome of the application
of strategic human resource strategies and policies that help employees stay with the organization by offering a work
environment that satisfies their demands.
H1.1: Organizational transformation moderates the relationship between strategic human resource management practices
and employee retention.
H6: Organizational transformation moderates the relationship between Compensation and benefits and employee
retention.
H7: Organizational transformation moderates the relationship between Performance appraisal and employee retention.
H8 Organizational transformation moderates the relationship between training and development and employee retention.
H9: Organizational transformation moderates the relationship between recruitment and selection and employee retention.
3. Research Methodology
Philosophy of this research is positivism. As term research philosophy refers to a system of beliefs and assumptions about
the development of knowledge (Ryan, 2018). This research is a deductive approach to test the relationships among SHRM
practices, employee retention and as moderator organizational transformation. As this research is deductive in nature thus
used the quantitative approach including well-structured questionnaires. Population under study is employees of
manufacturing sector. Data is gathered through top and middle level employees working in textile companies in Lahore.
The sample size was 384. Sample size is selected by using Krejcie and Morgan (1970) sample size determination table. It
is used because in this study total number of population is unknown. Convenience sampling is used with web intercept, in
which initially population members are approached to identify next members that help the researcher for collection of data
because no data of employees is available. Email and face-to-face employee meetings were used to collect data. Through a
self-administered survey, data are gathered. Current study has 31 items in the construct. Response rate was 70% as total
470 questionnaires were distributed out of which 390 were taken back. Out of 390 questionnaires, some were not filled
properly. So those were obsoleted, and 330 questionnaires were used as a sample. Data is gathered from 330 respondents;
employees working in textile company in Lahore, Pakistan. Companies in Lahore and Raiwind were visited for this purpose.
The data is collected from 4 textile companies. Data was mainly gathered from Kohinoor Textile Mills, Kohinoor Mills
Limited, and Aashiana Fabrics Lahore Aashiana Silk Fabrics Lahore.
4. Analysis and Result
The following section of this research consists explaining techniques which are used by researcher to perform the analysis
of the study. Data is analyzed through a statistical tool Warp PLS. Tables, models, and visual representations of the data
that are simple for the researcher to read and understand make up statistical analysis. One goal is to use the same method
of analysis throughout so that the researcher who is now working on the subject and other researchers worldwide can
understand it.
4.1. Data Analysis
The data analysis is done on the basis of the views of employees of textile industry. It is probable to find suggestions for
new insights allied to strategic human resource management practices in the Pakistani textile industry and further studies
about this subject. The data gathered through questionnaires is analyzed through Warp PLS Structural Equation Modeling.
Warp PLS is used to obtain correlations, Cronbach’s alpha, composite reliability, and factor analysis and test the
hypotheses. Following are the analysis through which gathered data is analyzed.
1. Assessment of Measurement Model
A. Outer model assessment
I. Reliability test
Niazi et al….
304
• Composite reliability
• Indicator reliability (CFA)
• Indicator weights (VIFs)
II. Validity test
• Convergent validity
• Discriminant validity
• Normalized combined loadings and cross loadings
B. Inner model assessment
III. Coefficient of determination (R2)
IV. Path coefficients (PLS-SEM)
V. Predicative relevance (Q2)
VI. Effect size (f2)
2. Overall model fit
3. Multivariate regression analysis
4.2. Assessment of Measurement Model
The size of model tried to analyze whether or not theoretical constructs (variables inside the study) have
been efficiently measured by way of the objects. Model of this study used a reflective measurement model. The model
(reflective model) of this study assessed through internal consistency reliability i.e. composite reliability, Confirmatory
Factor Analysis (CFA), and validity test as convergent validity, discriminant validity. Convergent and discriminant validity
is analyzed through the factor loadings and Average Variance Extracted (AVE) and discriminant validity is also evident
through square root of AVEs.
4.3. Framework at abstract level
H1: Strategic human resource management has impact on employee retention
H1.1: Organizational transformation moderates the relationship between strategic human resource management practices
and employee retention.
Figure 1: Output at Abstract Level
4.4. Conceptual framework at manifest level
H2: Recruitment and selection has impact on employee retention.
H3: Training and development has impact on employee retention.
H4: Performance appraisal has impact on employee retention.
H5: Compensation and benefits has impact on employee retention.
H6: Organizational transformation moderates the relationship between compensation and
benefits and employee retention.
H7: Organizational transformation moderates the relationship between performance
Niazi et al….
305
appraisal and employee retention.
H8: Organizational transformation moderates the relationship between training and
development and employee retention.
H9: Organizational transformation moderates the relationship between recruitment and
selection and employee retention.
Figure 2: Output at Manifest Level
5. Outer Model Assessment
While stating a measurement model form of relationship between construct and measurements must be taken into. Using a
model like a common factor model can help with latent variable measurement, which is the process of ensuring that local
independence is met for a particular collection of observable variables or indicators. Measurement model are categorized
into two types as reflective and formative (Richter et al., 2015).
5.1. Reliability
Relaibility is the extent to which the aptitude of a factor produce the same or extensively similar results on repeated data.
CFA is conducted as it is the requirement for the calculation of factor analysis. Hair et al. (2012) suggested that the validity
of the latent construct can be calculated by undertaking convergent validity and discriminant validity. Therefore, reliability
and validity of the data is examined.
5.2. Composite and Indicator Reliability
To measure the reflective model composite and indicator reliability is assessed. Indicator reliability shows that how much
of each indicator’s variance is explained by its construct. It is examined through the square root of indicator loading.
Through Composite reliability it is measured how much a scale or survey has internal consistency (Na-Nan et al., 2018).
In following table; Composite reliability = CR
Cronbach's alpha = C.Alpha
Avg. variances extracted = A.VE
Full collinearity VIFs= VIFs
Minimum values= Min
TD
(R) 3i
PA
(R) 3i
CB
(R) 3i
RS
(R) 3i
ER
(R) 12i
OT
(R) 7i
R2= 0.36
B= 0.34
P< 0.01
B= 0.21
P< 0.01
B= 0.35
P< 0.01
B= 0.26
P< 0.01
B= 0.35
P< 0.01
B= 0.17
P< 0.01
B= 0.21
P< 0.01
B= 0.46
P< 0.01
Niazi et al….
306
Maximum values = Max
Median = Med
Mode = Mode
Skewness = Skew
Exc. Kurtosis = E.Kur
Unimodal- RS = RS
Unimodal-KMV = KMV
Normal-JB = JB
Normal-RJB = RJB
Table 1: Latent Variable Standardized Coefficients
Des.
R&S
T&D
PA
C&B
ER
OT
OT*
R&S
OT*
T&D
OT*
PA
OT*
C&B
CR
0.767
0.92
0.885
0.897
0.904
0.93
1
1
1
1
C.Alph
0.748
0.87
0.805
0.827
0.883
0.912
1
1
1
1
A.VE
0.548
0.794
0.721
0.744
0.54
0.655
1
1
1
1
VIFs
1.914
2.309
2.96
2.383
3.051
2.179
3.423
5.808
5.482
3.879
Min
-3.25
-3.15
-3.62
-2.47
-4.14
-3.74
-1.728
-2.463
-1.47
-2.44
Max
1.52
1.28
1.367
1.46
1.891
1.511
6.566
5.877
5.86
6.673
Med
0.11
0.18
0.121
0.29
0.119
0.2
-0.264
-0.29
-0.34
-0.24
Mode
1.27
0.18
0.502
0.29
0.501
0.2
1.16
-0.262
-0.34
-0.38
Skew
-0.62
-0.86
-1.02
-0.46
-0.76
-1.57
3.47
2.995
3.301
3.37
E.Kur
0.28
0.31
1.52
-0.35
1.15
2.74
17.90
14.05
14.02
18.70
RS
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
KMV
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
JB
No
No
No
No
No
No
No
No
No
No
RJB
No
No
No
No
No
No
No
No
No
No
Aforementioned table represents composite reliability CFA. Cronbach's alpha, average variances extracted and full
collinearity VIFs is also examined. According to Ahmad and Ahmad (2019) value of composite reliability significant if
value is 0.70 to 0. 90. Through the Cronbach´s alpha internal consistency of the variables is measured that the how are close
to each other. It provides prediction of reliablity (Hair et al., 2014). It’s accepted minimum value is 0.70 whereas .60 is also
acceptable in social sciences. The reciprocal of tolerance is defined as multi collinearity. Some studies suggest that the
acceptable value of VIF is less than 10, whereas some argue and suggests maximum value is 10 (Henseler et al., 2015).
According to Ahmad and Ahmad (2021) acceptable value of AVE is 0.5. Table 1 presents that variable has significance
reliability. Value of every construct is above 0.70, as the value of recruitment and selection is 0.767 which shows that
variable has good reliability. As it is also proved through the value of Cronbach´s alpha is also significant. Overall results
show that the values are significant and construct has reliability.
5.3. Indicator weights
Variance Inflation Factor (VIF) measures the impact of multi collinearity between variables in multiple regression variables.
Multi collinearity occurs when independent variable has correlations with each other. Presence of multi collinearity affect
regression analysis. VIF for a regression model variable is capable the magnitude relation of the model variance to the
variance of a model that has only independent variable. A high VIF indicates that the linked independent variable has high
collinear with the other variables.
Table 2: Variance Inflation Factors (VIFs)
RS
TD
PA
CB
ER
OT
OT*R
OT*T
OT*P
OT*C
P value
VIF
ES
RS1
0.524
<0.001
1.511
0.451
RS2
0.529
<0.001
1.522
0.46
RS3
0.233
<0.001
1.027
0.089
TD1
0.364
<0.001
2.059
0.316
TD2
0.385
<0.001
2.801
0.353
TD3
0.373
<0.001
2.359
0.331
PA1
0.4
<0.001
1.992
0.352
PA2
0.41
<0.001
2.022
0.355
Niazi et al….
307
PA3
0.37
<0.001
1.5
0.293
CB1
0.398
<0.001
2.368
0.354
CB2
0.404
<0.001
2.479
0.364
CB3
0.356
<0.001
1.524
0.282
ER1
0.108
0.027
1.49
0.061
ER2
0.145
0.005
2.551
0.11
ER3
0.132
0.009
2.27
0.092
ER4
0.111
0.024
1.92
0.065
ER5
0.13
0.01
2.158
0.089
ER6
0.138
0.007
2.349
0.101
ER7
0.13
0.01
1.813
0.089
ER8
0.117
0.018
2.28
0.073
ER9
0.121
0.015
2.27
0.077
ER10
0.125
0.013
2.757
0.082
ER11
0.115
0.02
1.782
0.07
ER12
0.13
0.01
2.341
0.089
OT1
0.18
<0.001
2.637
0.15
OT2
0.17
<0.001
2.477
0.137
OT3
0.19
<0.001
3.982
0.162
OT4
0.18
<0.001
2.755
0.144
OT5
0.16
0.002
1.829
0.12
OT6
0.18
<0.001
2.517
0.143
OT7
0.18
<0.001
2.545
0.145
OT*R
1
<0.001
1
OT*T
1
<0.001
1
OT*P
1
<0.001
1
OT*C
1
<0.001
1
Notes: P values < 0.05 and VIFs < 2.5 are desirable for formative indicators; VIF = indicator variance inflation factors,
WLS = indicator weight-loading sign (-1 = Simpson's paradox in l.v.); ES = indicator effect size.
Table 3: Block Variance Inflation Factors
RS
TD
PA
CB
OT*RS
OT*TD
OT*PA
OT*CB
ER
2.031
2.068
2.63
1.988
3.768
12.548
8.368
1.3
Variance inflation factors range from 1 is considered that is VIF is not correlated, between 1-5 is correlated, and greater
than 5 highly more multi collinearity is exist between variables. Some authors suggest a more conservative level of 2.5 or
above. As Table 3 represents the variance inflation factors. Most of the variables has significant value of VIF and as well
also their p value is also significant. Recruitment and selection has VIF 1.51 which tells that multi collinearity inflates the
variance by a recruitment and selection of 50% compared to a model with no multi collinearity.
5.3.1. Convergent Validity
Convergent validity refers to how closely the new scale is related to other variables and other measures of the same
construct. Not only should the construct correlate with related variables but it should not correlate with dissimilar, unrelated
ones. Convergent validity is a measure of the quality of a measurement instrument where the instrument itself is usually a
set of statement questions (Rasoolimanesh, 2022). Convergent validity is an extend how the measurement constructs are
relating with other constructs and other measures the equivalent variables statements (Rasoolimanesh, 2022). Convergent
validity is assessed through the links between question statements and latent variables on the basis of loadings and cross-
loadings. The coefficients of the question-statements with the primary latent variable are called factor loadings or loadings
while the coefficients of the question-statements with the other latent variables are called cross loadings.
Factor loading indicates up to which context a factor explains a variable. It explains inconsistency of the variable on a
specific factor. In the SEM analysis, equal or greater to 0.7 factor loading shows that the factor extracts sufficient variance
from that variable. According to state that factor loadings greater than 0.30 considered as acceptable at minimum level,
0.40 are acceptable as an important and factor loadings are 0.50 or higher is considered significant.
Niazi et al….
308
Table 4: Factor Loadings (at Abstract Level)
SHRP
ER
OT
OT*SHRP
RS1
0.749
RS2
0.597
RS3
0.319
TD1
0.699
TD2
0.804
TD3
0.774
PA1
0.701
PA2
0.767
PA3
0.784
CB1
0.686
CB2
0.749
CB3
0.698
ER1
0.569
ER2
0.764
ER3
0.699
ER4
0.584
ER5
0.687
ER6
0.732
ER7
0.685
ER8
0.621
ER9
0.639
ER10
0.659
ER11
0.609
ER12
0.687
OT1
0.83
OT2
0.792
OT3
0.862
OT4
0.812
OT5
0.741
OT6
0.809
OT7
0.815
OT*SHRP
0.412
1
Table 5: Factor Loadings (At Manifest Level)
R&S
TD
PA
CB
ER
OT
RS1
0.861
RS2
0.869
RS3
0.383
TD1
0.867
TD2
0.917
TD3
0.888
PA1
0.872
PA2
0.876
PA3
0.796
CB1
0.889
CB2
0.901
CB3
0.794
ER1
0.569
ER2
0.764
ER3
0.699
ER4
0.584
Niazi et al….
309
ER5
0.687
ER6
0.732
ER7
0.685
ER8
0.621
ER9
0.639
ER10
0.659
ER11
0.609
ER12
0.687
OT1
0.83
OT2
0.792
OT3
0.862
OT4
0.812
OT5
0.741
OT6
0.809
OT7
0.815
Table 6: Normalized Combined Loadings and Cross Loadings (At Abstract Level)
SHRP
ER
OT
OT*SHRP
RS1
0.772
RS2
0.809
RS3
0.519
TD1
0.74
TD2
0.706
TD3
0.716
PA1
0.662
PA2
0.711
PA3
0.713
CB1
0.665
CB2
0.649
CB3
0.72
ER1
0.668
ER2
0.727
ER3
0.707
ER4
0.718
ER5
0.705
ER6
0.713
ER7
0.682
ER8
0.696
ER9
0.712
ER10
0.677
ER11
0.749
ER12
0.706
OT1
0.693
OT2
0.768
OT3
0.711
OT4
0.743
OT5
0.705
OT6
0.763
Niazi et al….
310
OT7
0.742
OT*SHRP
0
1
Table 7: Normalized Combined Loadings and Cross Loadings (At Manifest Level)
RS
TD
PA
CB
ER
OT
OT*
RS
OT*
TD
OT*
PA
OT*
CB
SE
P value
R1
0.861
0.05
<0.001
R2
0.869
0.05
<0.001
R3
0.383
0.053
<0.001
T1
0.867
0.05
<0.001
T2
0.917
0.049
<0.001
T3
0.888
0.049
<0.001
P1
0.872
0.05
<0.001
P2
0.876
0.05
<0.001
P3
0.796
0.05
<0.001
C1
0.889
0.049
<0.001
C2
0.901
0.049
<0.001
C3
0.794
0.05
<0.001
E1
0.569
0.052
<0.001
E2
0.764
0.05
<0.001
E3
0.699
0.051
<0.001
E4
0.584
0.052
<0.001
E5
0.687
0.051
<0.001
E6
0.732
0.051
<0.001
E7
0.685
0.051
<0.001
E8
0.621
0.052
<0.001
E9
0.639
0.051
<0.001
E10
0.659
0.051
<0.001
E11
0.609
0.052
<0.001
E12
0.687
0.051
<0.001
O1
0.83
0.05
<0.001
O2
0.792
0.05
<0.001
O3
0.862
0.05
<0.001
O4
0.812
0.05
<0.001
O5
0.741
0.051
<0.001
O6
0.809
0.05
<0.001
O7
0.815
0.05
<0.001
O*R
1
0.049
<0.001
O*T
1
0.049
<0.001
O*P
1
0.049
<0.001
O*C
1
0.049
<0.001
Cross loading is examined if the loading of external constructs is higher with loadings of other. If constructs have cross
loadings, then their external loadings exceed and show convergent validity between constructs. Output is used for results
of the convergent validity of the measurement instrument. Combined loadings and cross-loadings computed from the two
matrices as one is the loadings of un-rotated matrix as structure matrix and the loadings of rotated matrix as pattern matrix.
The value of loadings always lies between -1 to 1 (RVSPK et al., 2020). For the reflective model loadings are high whereas
the cross loadings are low. Table 7 present Warp PLS output of normalized combined loading and cross-loadings, and
factor loadings. The latent variables i.e. R&S, T&D, PA, ER are listed at the top of the column and their indicators names
are on each row. By analyzing their values overall construct has convergent validity and are statistically significant. As the
value are according to the criteria that the loadings are less than < 0.70 and the (p-value < 0.05) and cross loadings are low
(RVSPK et al., 2020).
5.3.2. Discriminant validity test
Discriminant validity measures whether the constructs are theoretically highly related to each other or not related each
other. Discriminant validity coefficients smaller in degree than the coefficients of convergent validity. According to (Khan
Niazi et al….
311
et al., 2019) convergent validity and discriminant validity calculations can be used to determine the validity of the latent
concept. As a result, in this study, the validity and reliability of the derived data were assessed before the data were analyzed.
Table 8: Correlations among l.vs. with sq. rts. of AVEs (At Abstract Level)
Description
SHRP
ER
OT
OT*SHRP
SHRP
0.705
ER
0.748
0.664
OT
0.554
0.617
0.81
OT*SHRP
-0.34
-0.201
-0.412
1
Table 9: Correlations among l.vs. with sq. rts. of AVEs (At Manifest Level)
RS
TD
PA
CB
ER
OT
OT*
RS
OT*
TD
OT*
PA
OT*
CB
RS
0.74
TD
0.628
0.891
PA
0.602
0.647
0.849
CB
0.515
0.534
0.682
0.863
ER
0.52
0.633
0.666
0.67
0.664
OT
0.339
0.452
0.496
0.534
0.617
0.81
OT*RS
-0.11
-0.19
-0.29
-0.23
-0.09
-0.352
1
OT*TD
-0.18
-0.23
-0.37
-0.27
-0.2
-0.324
0.814
1
OT*PA
-0.24
-0.32
-0.40
-0.26
-0.25
-0.391
0.753
0.86
1
OT*CB
-0.16
-0.25
-0.25
-0.24
-0.157
-0.42
0.677
0.785
0.819
1
Discriminant validity concept introduce by (Campbell & Fiske, 1959) in his study arguing on assessment of validity test.
Inter correlations between measures estimate through the correlation coefficient. Correlations between measures can be
high or low. AVE is computed for the assessment of discriminant validity. Square root of every AVE is calculated. Test is
applied to see the square root of each AVE value with each constructs and it must be larger than the correlation among any
pair of constructs.
Table 10: P Values for Correlations (At Abstract Level)
Description
SHRP
ER
OT
OT*SHRP
SHRP
1
<0.001
<0.001
<0.001
ER
<0.001
1
<0.001
<0.001
OT
<0.001
<0.001
1
<0.001
OT*SHRP
<0.001
<0.001
<0.001
1
Table 11: P Values for Correlations (At Manifest Level)
RS
TD
PA
CB
ER
OT
OT*R
OT*T
OT*P
OT*C
RS
1
<0.001
<0.001
<0.001
<0.001
<0.001
0.052
0.001
<0.001
0.005
TD
<0.001
1
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
-<0.001
PA
<0.001
<0.001
1
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
CB
<0.001
<0.001
<0.001
1
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
ER
<0.001
<0.001
<0.001
<0.001
1
<0.001
0.093
<0.001
<0.001
0.005
OT
<0.001
<0.001
<0.001
<0.001
<0.001
1
<0.001
<0.001
<0.001
<0.001
O*R
0.052
<0.001
<0.001
<0.001
0.093
<0.001
1
<0.001
<0.001
<0.001
O*T
0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
1
<0.001
<0.001
O*P
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
1
<0.001
O*C
0.005
<0.001
<0.001
<0.001
0.005
<0.001
<0.001
<0.001
<0.001
1
AVE measures the detail difference of the construct. The value of AVE for every measure should be at least 0.50 whereas
0.70 is considered as good. A comparison of the square root of AVE and factor correlation coefficients is given the table.
Similarly, it is concluding by seeing the results that there that there is no correlation value greater than the square root of
AVE. it shows that all the variables are valid. Diagonal column must be higher than the correlation between latent variables
Niazi et al….
312
in same column (Sholihin & Dwi, 2013). Table shows that the AVE on diagonal column is higher than the correlation
between same constructs so it indicates that criteria of discriminant validity is fulfilled.
For the fitness of model adjusted R2 is considered best way. It is computed by adjusting sample size and number of
predictors. It is used to compare the R2 values of different models. In this study the value of adjusted R2 is 52 % which
means 52% changes in employee retention (dependent variable) is due to the recruitment and selection; training and
development, performance appraisal, compensation and benefits. Other 48% variation is due to the other variables not
included in this research.
5.4. Inner Model Assessment
Regression analysis is performed to test hypothesis. Structural model inner assessment is done through path coefficient, F2,
P and T-values. These values determine the whether the hypothesized constructs are significance or not. Significant values
show that there is correlation between hypothesized constructs. T value should be of ≥ 1.96 in significance level 0.05. Effect
size (f2) is change in R2 when an exogenous variable is adding or removed from the model. It evaluates that which extent
each variable is contributing in model fitness (Cho et al., 2020). Analysis presents that are path coefficient are statistically
significant.
Table 12: Regression analysis
Path
F2
T
Β
P-Value
SHRMP
0.542
14.09
0.716**
<0.001
OT* SHRMP
0.047
2.389
0.133**
<0.001
RS → ER
0.033
1.107
0.26**
<0.001
TD →ER
0.225
6.351
0.34 **
<0.001
PA →ER
0.141
6.548
0.21 **
<0.001
CB →ER
0.242
3.810
0.35 **
<0.001
OT*RS →ER
0.113
6.447
0.35**
<0.001
OT*TD →ER
0.126
8.655
0.46**
<0.001
OT*PA→ER
0.069
-3.797
0.21 **
<0.001
OT*CB→ER
0.049
3.131
0.17 **
<0.001
Table 12 summarizes the regression analysis of each latent variable. Analysis present all hypotheses are accepted. The
relationship between recruitment and selection and Employee Retention is significant. Recruitment and selection has direct
effect on employee retention. Organizations should perform some strategic measures to retain it competent (Kundu & Lata,
2017). The outcome of this objective can be deduced as, selection and recruitment practices of HRM results to an
improvement in employee retention (Mihes et al., 2019). Organizational transformation also moderates the relationship
between strategic human resource management practices and employee retention. As Sepahvand and Bagherzadeh
Khodashahri (2021) suggest that strong SHRM practices increase the socialize new employees, it increase its commitment
with organization, their values. For the assessment of inner model, further two quality fit indices are take into consideration.
Table 13: Q2, R 2 Coefficients
Path
ER
R-squared coefficients
0.356
Q-squared coefficients
0.684
Q2 measures predictive validity of a model. It evaluates the model that values are corresponding according to expectations
(Hair Jr. et al., 2014). It measures the predictive relevance of the dependent variable. Q-square values above zero reflects
the values of endogenous variable has predictive relevance for the structural model. Values 0.02, indicates that endogenous
variable has small, 0.15 medium, and 0.35 high predictive relevance (Hair Jr. et al., 2014). In this study endogenous variable
employee retention has Q2 = 0.684, which represents that this model has high predictive relevance.
5.5. Overall Model Fit
Fitness of model indicates that the data of proposed model is fit well. These indices are Average Path coefficient (APC),
Average R2 (ARS), Tenenhaus goodness of fit (GoF). As suggested by (Kock & Lynn, 2012) values of APC and ARS must
be significant if the value of P is less than 0.05. Whereas, Tenenhaus’ GoF should be above 0.36. Results obtained in the
analysis shows that the value of APC, ARS, and Average adjusted R-squared (AARS) are significant has the P value less
than 0.05. Through GOF descriptive power of model is measured Cohen’s (1988) thresholds for small, medium, and large
effect sizes. According to Tenenhaus et al. (2005) if the value of GOF is lower than 0.1 it suggests that the descriptive
power of model is too low for consideration.
Niazi et al….
313
Table 14: Model Fitness Indices (At Abstract Level)
Model fit and quality indices
Score
Criteria
Informa
tion
Average path coefficient
(APC)=0.424,
P<0.001
P<0.05
Signific
ant
Average R-squared (ARS)
(ARS)=0.495,
P<0.001
P<0.05
Signific
ant
Average adjusted R-squared (AARS)
(AARS)=0.491,
P<0.001
P<0.05
Signific
ant
Average block VIF
(AVIF)=1.105
Acceptable if AVIF ≤ 5 ideal if AVIF ≤ 3,3
Accepta
ble
Average full collinearity VIF
(AFVIF)=2.103
Acceptable if AFVIF ≤ 5 ideal if AFVIF ≤
3,3
Accepta
ble
Tenenhaus GoF (GoF)
(GoF)=0.566
Small if GoF ≥ 0.1 medium if GoF ≥ 0.25
large if GoF ≥ 0.36
Large
Sympson's paradox ratio (SPR)
(SPR)=0.500
Acceptable if the SPR ≥ 0.7 ideal if SPR =
1
Rejecte
d
R-squared contribution ratio (RSCR)
(RSCR)=0.920
Acceptable if RSCR ≥ 0.9 ideal RSCR = 1
Accepta
ble
Statistical suppression ratio (SSR)
(SSR)=1.000
Acceptable if SSR ≥ 0.7
Accepta
ble
Nonlinear bivariate causality direction
ratio (NLBCDR)
(NLBCDR)=0.50
0
Acceptable if NLBCDR ≥ 0.7
Rejecte
d
Table 15: Model Fitness Indices (At Manifest Level)
Analyzed results show the value of GOF is 0.530 which represents that model has high explanatory power of model.
According to feasibility test results of the model as a whole, all of the criteria reached the expected value limit and meet
the recommended goodness of fit indices critical limit so that the modeling results could be accepted or worthy of analysis.
Whereas on the other hand value of Sympson's paradox ratio (SPR), R-squared contribution ratio (RSCR) and Nonlinear
bivariate causality direction ratio (NLBCDR) not meet according to the criteria. SPR measures that the how much level of
model is free from Simpson’s paradox instances (Kock, 2015). An instance of Simpson’s paradox means the sign difference
between the path coefficient and a correlation associated with a pair of linked variables. It indicates the causality problem,
suggesting that a hypothesized path is either immutable or reversed. Standardized SPR is considered if it is equal to 1 that
shows there is no instances of Simpson’s paradox in a model. Analyzed results shows that model has Simpson’s paradox
instances (SPR) =0.500 which means 50 percent of paths in a model are free from Simpson’s paradox instances. The RSCR
Model fit and quality indices
Score
Criteria
Information
Average path coefficient
(APC)=0.269,
P<0.001
P<0.05
Significant
Average R-squared (ARS)
(ARS)= 0.356,
P<0.001
P<0.05
Significant
Average adjusted R-squared (AARS)
(AARS)= 0.339,
P<0.001
P<0.05
Significant
Average block VIF
(AVIF)= 4.338
Acceptable if AVIF ≤ 5 ideal if AVIF
≤ 3,3
Acceptable
Average full collinearity VIF
(AFVIF)= 3.339
Acceptable if AFVIF ≤ 5 ideal if
AFVIF ≤ 3,3
Acceptable
Tenenhaus GoF (GoF)
(GoF)= 0.530
Small if GoF ≥ 0.1 medium if GoF ≥
0.25 large if GoF ≥ 0.36
Large
Sympson's paradox ratio (SPR)
(SPR)=0.500
Acceptable if the SPR ≥ 0.7 ideal if
SPR = 1
Rejected
R-squared contribution ratio (RSCR)
(RSCR)= 0.678
Acceptable if RSCR ≥ 0.9 ideal RSCR
= 1
Rejected
Statistical suppression ratio (SSR)
(SSR)= 0.875
Acceptable if SSR ≥ 0.7
Acceptable
Nonlinear bivariate causality direction
ratio (NLBCDR)
(NLBCDR)=0.50
0
Acceptable if NLBCDR ≥ 0.7
Rejected
Niazi et al….
314
index measure up to how much level R-squared contributions is free from negative and it comes R-squared contributions
(Kock, 2015). When the independent variable creates negative contribution to the R-squared of dependent variable then
this contribution shows that the independent variable is reducing the ratio of discrepancy explained in the criterion. This
key is similar to the SPR. SPR is calculated on the basis of actual value of R squared contributions. Whereas RSCR is
calculated by dividing the total of positive R-squared contribution on total of absolute R-squared contributions whether the
positive or negative in the model. Ideal value of RSCR is 1 which means that there are no negative R-squared contributions
in a model, acceptable values of RSCR are equal to or greater than 0.9, represents that the sum of positive R-squared
contributions in a model makes up at least 90 percent of the total sum of the absolute R-squared contributions in the model.
SSR measures up to which extent a model is free from statistical suppression instances (MacKinnon et al., 2000). When
the path coefficient is greater than the correlation of pair linked variables then statistical suppression follows. So, Simpson’s
paradox instance is a statistical suppression occurs when there is causality problem. It suggests that the hypothesis either
reversible or implausible
The NLBCDR measures the support of the causal links in a model which is provide by bivariate nonlinear coefficients of
association. Acceptable ratio of NLBCDR is equal to or greater than 0.7 .7 means 70% of path-related instances in a model
the support for the reversed hypothesized direction of causality is weak or less. The analyzed model shows that (NLBCDR)
=0.500 so 50% path-related instances in a model the support for the reversed hypothesized direction of causality is less.
Less means causality direction of hypotheses is sustained.
It can be stated that this test resulted in a fairly good confirmation of the variables and the causal relationship between
variables. So, the overall model test shows fairly good results or following expectations, meaning that the empirical data
(field data) is sufficient to support the developed theoretical model.
Table 16
Hypotheses
Statement
Beta
coefficient
Status
H1
Strategic human resource management has impact on employee
retention
0.72 (**)
Accepted
H1.1
Organizational transformation moderates the relationship between
strategic human resource management practices and employee
retention.
0.13 (**)
Accepted
H2
Recruitment and selection has impact on employee retention.
0.26(**)
Accepted
H3
Training and development has impact on employee retention.
0.34 (**)
Accepted
H4
Performance appraisal has impact on employee retention.
0.21 (**)
Accepted
H5
Compensation and benefits has impact on employee retention.
0.35 (**)
Accepted
H6
Organizational transformation moderates the relationship between
Compensation and benefits and employee retention.
0.17 (**)
Accepted
H7
Organizational transformation moderates the relationship between
Performance appraisal and employee retention.
0.21 (**)
Accepted
H8
Organizational transformation moderates the relationship between
training and development and employee retention.
0.46 (**)
Accepted
H9
Organizational transformation moderates the relationship between
recruitment and selection and employee retention.
0.35 (**)
Accepted
Note(s): *p < 0.05, **p < 0.01, ***p < 0.001
6. Discussion Summary of Results
Summary of result shows us about the results obtained from testing hypothesis. First hypothesis tells us that SHRM
practices has strong relationship with employee retention. By applying the effective strategic HRM practices employees
can retain. First hypothesis statement is “Strategic human resource management has impact on Employee Retention”.
Testing proves that hypothesis 1 is supported (β =0.72 1, t = 14.09 p < 0.01). Hypothesis H1.1 also support that
“Organizational Transformation moderates the relationship between SHRM practices and Employee Retention”. Through
test it proves (β =0.13, t = 2.389 p < 0.01).
The second hypothesis after analysis suggested that, recruitment and selection has strong relationship with employee
retention. It shows focusing on competent recruitment can retain employees in organization. Highly competent and skillful
recruitment ultimately have impact on employee retention. H2 is stated as follows, “Recruitment and selection has impact
on employee retention.” Results tells us that H2 is supported and it proves (β = .357, t = 1.107p < 0.01).
Niazi et al….
315
The third hypothesis explores through the training and development employee retention can be controlled. As to train the
employees is necessary (Elnaga & Imran, 2013). Organizations should provide such an environment where employees can
train and develop their skills and professional level. H3 is “Training and development has impact on employee retention.”
Hence, H3 is supported by results (β = 0.34, t = 6.351 p < 0.01).
The fourth proposed hypothesis is also supported. It tells us the relationship between performance appraisal and employee
retention. And it suggested that performance appraisal play vital role and it has significant role to enhance employee
retention (Aleem & Bowra, 2020). H4 is written as follows, “Performance Appraisal has impact on Employee Retention.”
(β = 0.21, t = 6.548 p < 0.01).
The fifth hypothesis in this research thesis states that, “Compensation and benefits has impact on employee retention.” The
result also shows (β = 0.35, t = 3.810 p < 0.01). It means compensation and benefits has strong impact on employee retention
with in organization. Because by providing good compensation, and care about employees, it makes employees satisfied
with their job and they will stay for a longer period of time within organization.
Hypothesis sixth show the moderating effect of organization transformation on the relationship between compensation and
benefits and employee retention. Through results moderating effect is shown (β = 0.17, t = 3.131 p < 0.01).
Seventh Hypothesis indicates the moderating relationship between strategic human resource management practices and
employee retention, organizational transformation is acting as a moderator in suggestion. Organizational transformation
strengthens the relationship between performance appraisal and employee retention. Statement of H7 is, “Organizational
Transformation moderates the relationship between Performance Appraisal and Employee Retention”. Whereas, results
shows that (β = 0.21, t = -3.797p < 0.01).
Furthermore, H8 through result moderating effect of organizational transformation has been proved. During transformation
when an organization develop such type of practices through which employees can train then it’s ultimately cause to stay
employees with in organization. Hypothesis is, “Organizational transformation moderates the relationship between training
and development and employee retention” and the results are, (β =0.46, t = 8.655p < 0.01).
6.1. Discussion of Results
In a fast and growing and competitive economic change to retain a skillful and talented employee is a crucial challenge for
organizations. As it is a key factor for the success or failure of organizations. Therefore, through effective and creative
policies employees can be retained. In previous studies relationship of strategic human resource management practices with
the relationship of employee retention has been studied. Through research it is found that the strategies of human resource
management are most crucial and effective to retain the employees within organization. Through a remarkable and best
strategic HRM practices retention of employees can be done at NBE (Fahim, 2018). In present study impact of strategic
human resource management practices and employee retention is analyzed. As well as also investigate the moderation
effect of organizational transformation on employee retention and SHRM practices. And the results obtained from testing
the first hypothesis confirmed SHRM practices has impact on employee retention. Findings of this study is also confirmed
the moderation effect of organizational transformation on the relationship between strategic human resource management
practices and employee retention. Organizational transformation moderates and have positive impact on Employee
retention.
In addition, it confirmed the H5 and H6 that there is a strong positive relationship of compensation and benefits with
employee retention 0.35. 0.35 showed that the compensation and benefits had a greater value of variance and high effect
with regard to affecting the employee retention, which are consistent with the theoretical foundations of the research.
According to Irabor and Okolie (2019) compensation and benefits is a major aspect that shows how much an organization
is committed to its employees. And it is the persuasive cause for an employee to retain in organization. However, only pay
or salary is not enough to motivate and retain the employees in organization. So, many of the other factors are counted that
makes an effect the decision of employee to retain with in organization. These factors effect in employee commitment in
organization and there must be put an effort to encounter these factors sideways with compensation. The results obtained
from testing the hypothesis confirmed the moderating role of organizational transformation in the relationship between
employee retention and strategic HRM practices, which is consistent with the theoretical foundations of the Elacio et al.
(2020). Findings of this study is consistent with the results of Piol et al. (2021) and it supported the hypothesis. Their results
show organizations should use and apply an upscale workplace strategy, it can increase to retain employees and the business
of organization ca be avoiding from interferences.
During a transformation with in organization an effective leadership can be reform and influence the transformation period.
In result it enhances effectiveness of organization, their satisfaction level, and it obviously retain the employees. Testing
the moderating effect of organizational transformation on the relationship between recruitment and selection and employee
retention, which is consistent with the theoretical foundations of the research. Findings of this study are consistent with the
results obtained by (Elacio et al., 2020; Fahim, 2018). An organization should take certain steps to maintain its valuable
employees since it recruits new personnel. In order to achieve this, organizations should have competitive advantages in
tempting and staying their competent employees. They should also offer opportunities to current employees and job
Niazi et al….
316
candidates that comparable. Findings of this study are consistent with (Fahim, 2018; Reina and Scarozza, 2021) purpose of
training is to acclimate new hires to the workplace, boost commitment, and introduce values, strategies, and objectives. A
suitable training program should offer opportunities for learning and development and, as a result, it enhances efficiency
of employee and organizational competitiveness.
6.2. Theoretical and Practical Contribution
As in fast growing economic conditions Employee Retention is a very sensitive aspect for the management research during
last few decades. The main contribution of this study is to investigate the effect of organizational transformational on
relationship of strategic human resource management practices and employee retention. Whenever an organization brings
transformation in any terms as digital transformation, updating new software, or transformation in culture then management
has to face the challenge to retain its employees. So, results of this study has shown that strategic human resource
management practices have relationship on employee retention. With the help of HRM strategies competent employees can
be retained. The study has many contributions to literature as well as a practical guidance to HR managers, policy makers
and top management of organizations. This study concludes that during transformation periods HR managers making ways
to retain the employees must focus on implementing strong HRM policies. Findings of this study provides some important
aspects related to employee retention in Pakistan’s manufacturing sector by applying strong HRM strategies during
transformation period. Due to its practical value in improving HRM practices that can affect retention, the study offers
useful information for HRM and development practitioners.
6.3. Practical Implication
This study put attention to the advancement of HRM strategic practices and recommends strong HRM practices are crucial
during turnover procedure as an antecedent of its components (recruitment and selection, training and development,
performance and appraisals, compensation and benefits). And as a fundamental connection between organization and the
employees’ turnover at the person level. Advance, counting organizational transformation in relation with turnover,
provides greater understanding of the method by which company’s influence the turnover procedure. Typically, a critical
finding for organizations looking for ways of tending to worker retention.
7. Conclusion
In this study, examined the moderating effect of organizational transformation on SHRM practices and employee retention.
Also detail researched on the dimensions of SHRM practices with the relationship of employee retention. Findings of this
study gives contribution to the managerial level implications in decision making. This study helpful to understand to retain
employees within organization. We tested our data on SPSS and Warp PLS that was collected through textile companies in
Pakistan. All the hypothesis also accepted as the p-value of all variables is less than .05. The results show strong reliability
due to composite reliability (CR) is greater than 0.80. The past studies have researched on the relationship of HRM and
employee retention. Findings of our study is consistent with (Karimi & Parsafar, 2017; Shirazi & Hosseini Robat, 2015).
Their study reveals that the granting payments to employees helps them to enabling the efficiency of organization, it controls
costs, and furthermore it attracts new vigilant employees and also in retain them. Organizations which provides rewards to
their employees, get satisfied, motivates them (Sepahvand & Bagherzadeh Khodashahri, 2021).
In addition, our research findings provide other valuable insights into how strategic HRM practices interact with
organizational transformation in influencing employee retention. That is, we found strategic HRM practices to be positively
related to employee retention when employees perceived organization as a place with high participation, high level of
commitment, brand reputation for competitive advantage, communicating effectively with colleagues and their superiors
as encouraging, and enabling them to engage in expressing their comments and suggestions for addressing and solving
critical work problems and issues. The study also showed that the performance appraisal of valuable employees is usually
carried out through self-monitoring. In this hypothesis, the moderating role of job engagement has less strength and
intensity. This research has both theoretical and practical implications, as it contributes to literature as it introduced new
conceptual framework by studying strategic human resource management practices with relationship of employee retention
but also further studied the dimension of strategic human resource management practices separately with the relationship
of employee retention. All findings are based on information taken from respondents.
7.1. Limitation of Study and Future Recommendation
Similar to earlier investigations, the current study had some limitations. The following are the study's main limitations:
First off, this study only includes limited firms, it does not include data from all industrial industries or other textile
companies. Data is gathered from four textile businesses. And everyone who was currently employed was the target.
Additionally, even though this study only looks at a small portion of employee retention and organizational transformation,
many other factors exist that are also important but are not examined, such as job engagement, job security, job assignment
and opportunities, work environment, telecommunication and participation. The study is conducted in a limited time frame
and limited resources. Study cannot be generalizing to other manufacturing sector due to sample constraint and their culture
variations. This study only conducted on private sector business not includes government sectors. If the research is
Niazi et al….
317
conducted on broader level and also include private and government both sectors, then results may vary significantly.
Therefore, further investigation is required to check icluding more factors on a broader level. If the research is carried out
by using other sampling technique by adding more factors then results can vary and genralize on broeader level.
References
Aburumman, O., Salleh, A., Omar, K., & Abadi, M. (2020). The impact of human resource management practices and
career satisfaction on employee’s turnover intention. Management Science Letters, 10(3), 641-652.
Ahmad, I., & Ahmad, S. B. (2019). The mediation effect of strategic planning on the relationship between business skills
and firm’s performance: Evidence from medium enterprises in Punjab, Pakistan. Opción: Revista de Ciencias
Humanas y Sociales(24), 746-778.
Ahmad, I., & Ahmad, S. B. (2021). Effect of managerial skills on the performance of small-and medium-sized enterprises:
A case study in Pakistan. The Journal of Asian Finance, Economics and Business, 8(4), 161-170.
AlQershi, N. A., Mokhtar, S. S. M., & Abas, Z. B. (2022). CRM dimensions and performance of SMEs in Yemen: The
moderating role of human capital. Journal of Intellectual Capital, 23(3), 516-537.
Andriole, S. J. (2017). Five myths about digital transformation. MIT Sloan Management Review, 58(3).
Armstrong, M. (2006). Strategic Human Resource Management-A Guide to Action 3rd Ed.
Benner, M. J., & Waldfogel, J. (2020). Changing the channel: Digitization and the rise of “middle tail” strategies. Strategic
Management Journal.
Brown, C., McManus, C., Davison, I., Gill, P., & Lilford, R. (2019). Using recruitment and selection to build a primary
care workforce for the future. Education for Primary Care, 30(3), 128-132.
Buschmeyer, A., Schuh, G., & Wentzel, D. (2016). Organizational transformation towards Product-Service Systems–
empirical evidence in managing the behavioral transformation process. Procedia CIRP, 47, 264-269.
Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix.
Psychological bulletin, 56(2), 81.
Cho, G., Hwang, H., Sarstedt, M., & Ringle, C. M. (2020). Cutoff criteria for overall model fit indexes in generalized
structured component analysis. Journal of Marketing Analytics, 8(4), 189-202.
Choy, M. W., & Kamoche, K. (2021). Identifying stabilizing and destabilizing factors of job change: A qualitative study
of employee retention in the Hong Kong travel agency industry. Current Issues in Tourism, 24(10), 1375-1388.
Cohen, S. (1988). Perceived stress in a probability sample of the United States.
Correani, A., De Massis, A., Frattini, F., Petruzzelli, A. M., & Natalicchio, A. (2020). Implementing a digital strategy:
Learning from the experience of three digital transformation projects. California Management Review, 62(4), 37-
56.
Dany, F., & Torchy, V. (2017). Recruitment and selection in Europe Policies, practices and methods 1 Policy and practice
in European human resource management (pp. 68-88): Routledge.
Delery, J. E., & Roumpi, D. (2017). Strategic human resource management, human capital and competitive advantage: Is
the field going in circles? Human Resource Management Journal, 27(1), 1-21.
Elacio, A. A., Balazon, F. G., & Lacatan, L. L. (2020). Digital transformation in managing employee retention using agile
and C4. 5 algorithm. no, 15217, 15217-15225.
Elnaga, A., & Imran, A. (2013). The effect of training on employee performance. European journal of Business and
Management, 5(4), 137-147.
Fahim, M. (2018). Strategic human resource management and public employee retention. Review of Economics and
Political Science, 3(2), 20-39.
Fernando, Y., & Wulansari, P. (2021). Perceived understanding of supply chain integration, communication and teamwork
competency in the global manufacturing companies. European Journal of Management and Business
Economics, 30(2), 191-210.
Greer, C. R. (2021). Strategic human resource management: Pearson Custom Publishing.
Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling
(PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106-121.
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural
equation modeling in marketing research. Journal of the academy of marketing science, 40(3), 414-433.
Hanelt, A., Bohnsack, R., Marz, D., & Antunes Marante, C. (2021). A systematic review of the literature on digital
transformation: Insights and implications for strategy and organizational change. Journal of Management Studies,
58(5), 1159-1197.
Hassan, Z., & Govindhasamy, C. (2020). An Investigation on Extrinsic and Intrinsic Rewards on Employee Retention
among Gen Y: A Study in Malaysian Manufacturing Companies. Journal of Business and Economic Analysis, 3(1),
55-69.
Niazi et al….
318
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based
structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135.
Irabor, I. E., & Okolie, U. C. (2019). A review of employees’ job satisfaction and its affect on their retention. Annals of
Spiru Haret University. Economic Series, 19(2), 93-114.
Jeffrey, I., & Prasetya, A. B. (2019). The employee performance assessment and employee training, on employee intension.
Jurnal Aplikasi Manajemen, 17(1), 56-65.
Julia, T., & Kassim, S. (2019). Exploring green banking performance of Islamic banks vs conventional banks in Bangladesh
based on Maqasid Shariah framework. Journal of Islamic Marketing.
Kamel, N. (2019). Implementing talent management and its effect on employee engagement and organizational
performance. Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference.
Karimi, A., & Parsafar, E. (2017). The relationship between human resource retention system and organizational
commitment of employees (case study: one of the privatized banks). International Journal of Information Science
and Management, 190, 110-119.
Khalid, K., & Nawab, S. (2018). Employee participation and employee retention in view of compensation. SAGE Open,
8(4), 2158244018810067.
Khan, G. F., Sarstedt, M., Shiau, W. L., Hair, J. F., Ringle, C. M., & Fritze, M. P. (2019). Methodological research on
partial least squares structural equation modeling (PLS-SEM): an analysis based on social network
approaches. Internet Research, 29(3), 407-429.
Kim, J.-N., & Rhee, Y. (2011). Strategic thinking about Employee Communication Behavior (ECB) in public relations:
Testing the models of megaphoning and scouting effects in Korea. Journal of Public Relations Research, 23(3),
243-268.
Kloutsiniotis, P. V., & Mihail, D. M. (2020). The effects of high performance work systems in employees’ service-oriented
OCB. International Journal of Hospitality Management, 90, 102610.
Kock, N., & Lynn, G. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and
recommendations. Journal of the Association for information Systems, 13(7).
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-
Collaboration (ijec), 11(4), 1-10.
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological
Measurement, 30(3), 607-610.
Kumar Basu, K. (2015). The leader's role in managing change: Five cases of technology‐enabled business transformation.
Global Business and Organizational Excellence, 34(3), 28-42.
Kundu, S. C., & Lata, K. (2017). Effects of supportive work environment on employee retention: Mediating role of
organizational engagement. International Journal of Organizational Analysis.
Lengnick-Hall, C. A., Beck, T. E., & Lengnick-Hall, M. L. (2011). Developing a capacity for organizational resilience
through strategic human resource management. Human Resource Management Review, 21(3), 243-255.
Malik, E., Baig, S. A., & Manzoor, U. (2020). Effect of HR Practices on Employee Retention: The Role of Perceived
Supervisor Support. Journal of Public Value and Administrative Insight, 3(1), 1-7.
Martin, G., Farndale, E., Paauwe, J., & Stiles, P. G. (2016). Corporate governance and strategic human resource
management: Four archetypes and proposals for a new approach to corporate sustainability. European Management
Journal, 34(1), 22-35.
MacKinnon, D. P., Krull, J. L., & Lockwood, C. M. (2000). Equivalence of the mediation, confounding and suppression
effect. Prevention science, 1, 173-181.
Middleton, J., Harvey, S., & Esaki, N. (2015). Transformational leadership and organizational change: how do leaders
approach trauma-informed organizational change… twice? Families in Society, 96(3), 155-163.
Miheso, P., Manyasi, J., & Wanjere, D. (2019). Effect of recruitment and selection practices on employee retention in
SACCOS in Kakamega County. The Strategic Journal of Business & Change Management, 6(3), 356-360.
Mitchell, R., Obeidat, S., & Bray, M. (2013). The effect of strategic human resource management on organizational
performance: The mediating role of high‐performance human resource practices. Human Resource Management,
52(6), 899-921.
Nadkarni, S., & Prügl, R. (2021). Digital transformation: A review, synthesis and opportunities for future research.
Management Review Quarterly, 71(2), 233-341.
Na-Nan, K., Chaiprasit, K., & Pukkeeree, P. (2018). Factor analysis-validated comprehensive employee job performance
scale. International Journal of Quality & Reliability Management, 35(10), 2436-2449.
Nanyangwe, J., & Phiri, J. (2021). The Influence of Marketing Strategies on Growth and Sustainability in the Original
Equipment Manufacturing Industry. Open Journal of Business and Management, 9(3), 1446-1461.
Niazi et al….
319
Parmenter, J., & Barnes, R. (2021). Factors supporting indigenous employee retention in the Australian mining industry: A
case study of the Pilbara region. The Extractive Industries and Society, 8(1), 423-433.
Piol, E. L., Lacatan, L. L., & Pulumbarit, J. P. (2021). Predictive Analysis of the Enrolment of Elementary Schools Using
Regression Algorithms. Int. J. Emerg. Technol. Adv. Eng, 11(11), 184-188.
Radadiya, M. U., & Pandey, R. K. (2020). Employee retention & organizational culture. Purakala, 31(4), 633-645.
Rasal, M. M. P. (2019). A Study of Motivation in Foundries of Kolhapur District. Management, 142-144.
Rasoolimanesh, S. M. (2022). Discriminant validity assessment in PLS-SEM: A comprehensive composite-based approach.
Data Analysis Perspectives Journal, 3(2), 1-8.
Reina, R., & Scarozza, D. (2021). Human resource management in the public administration Organizational development
in public administration (pp. 61-101): Springer.
Richter, N. F., Cepeda, G., Roldán, J. L., & Ringle, C. M. (2015). European management research using partial least squares
structural equation modeling (PLS-SEM). European Management Journal, 33(1), 1-3.
RVSPK, R., Priyanath, H., & Megama, R. (2020). Methods and rules-of-thumb in the determination of minimum sample
size when applying structural equation modelling: A review. J Soc Sci Res, 15(2), 102-109.
Ryan, G. (2018). Introduction to positivism, interpretivism and critical theory. Nurse researcher, 25(4), 41-49.
Sepahvand, R., & Bagherzadeh Khodashahri, R. (2021). Strategic human resource management practices and employee
retention: A study of the moderating role of job engagement. Iranian Journal of Management Studies, 14(2), 437-
468.
Shirazi, A., & Hosseini Robat, S. M. (2015). Analysis of impact of human resource management’s practices over
employee’s retention. Journal of Development & Evolution Mnagement, 1393(19), 11-18.
Sholihin, M., & Dwi, R. (2013). SEM-PLS with WarpPLS 3.0. Andi. Yogyakarta.
Tenenhaus, M., Vinzi, V. E., Chatelin, Y. M., & Lauro, C. (2005). PLS path modeling. Computational statistics & data
analysis, 48(1), 159-205.
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic
Information Systems, 28(2), 118-144.
Voronkova, V., Nikitenko, V., Oleksenko, R., Cherep, O., Andriukaitiene, R., & Briki, I. (2021). Digital paradigm of
economy and management in the conditions of global human transformation. Technology Transfer: Innovative
Solutions in Social Sciences and Humanities, 37-40.
Vu, H. M., & Nwachukwu, C. (2020). Strategic human resource management, organizational culture and academic staff
retention: Literature review. Economics Management Innovation, 12(2), 5-13.
