analytics should be conceptualizing on the bases of early
adaptation stage, which consequently, enable the organizations to identify and formulate their predictors of competitive advantage. However, various factors related to
intuitional isomorphism manipulate the organizational early
adaptation ability in relation to their HR analytics, which
mitigate the firm’s ability to sustain a competitive advantage.
2.3 HR Analytics, Human Capital,
and Organizational Sustainability
In a contemporary business environment, organizations are
required to spend on their human capital aiming to develop
and sustain their core competencies. Adaptation of HR
analytics by the organization significantly contributes toward
organizational long-term sustainability. Implication of HR
analytics in business organizations is conceptualized as
one-time effort by the organizational management, which is
significantly associated with organizational sustainability
and growth (Minbaeva 2018). It is the main responsibility of
the firm’s HR practitioners to adopt analytical methodologies (Boon et al. 2018) for better decision making related
with human resource management functions. Analytics must
be conceptualized based on context in order to generate
consequential inferences. It is essential for the HR practitioners to recognize the quality of the data before the data
entry process. Inferential and descriptive statistical models
coupled with structure equation modelling, correlation
matrices, and regression models should enhance the firm’s
capacity to recognize how organizational human capital
significantly contribute toward firm’s sustainability and
growth (Angrave et al. 2016). HR analytics can be perceived
as a strategic tool used to optimize the organizational
insights on how to gain a competitive advantage in today’s
contemporary business environment. Organizations that
invest in human capital and consider employees to be a
valuable asset are more enabled to gain competitive advantage as compared to others. In addition, it has been recommended in past studies that organizational management and
HR practitioners should formulate a mental liaison in terms
of how organizational human capital significantly associated
with organizational sustainability and future growth by using
HR analytics. It has been evident that due to the growing
adaptation of Human Resource Information System (HRIS)
organizations have the ability to store its data in one place;
this, in turn, enhance organization’s ability to retrieve
desired information effectively (Fitz-Enz and John Mattox
2014).
Based on gap identification and a comprehensive literature review, the following theoretical model and propositions are developed to study the effect and value of each
variable (Fig. 1).
Proposition 1 Human resource analytics (HRA) is significantly contributing toward organizational sustainability.
Proposition 2 Organizations’ readiness to use HRA to
mediate relationship between HR analytics and organizational sustainability.
Proposition 3 Trained human capital mediates relationship between HRA and organizational sustainability.
3 Research Methodology
Based on literature review one dependent variable (Organizational Sustainability), one independent variable (Human
Resource Analytics), two mediators (Organizations’ Readiness to use HRA and Human Capital). To collect primary
data, a five-point Likert scale questionnaire was used. The
questionnaire was distributed to 600 human resource professionals working in the automobile sector operating in
GCC, and 271 responded. In the cross-sectional study, primary data was collected using stratified random sampling.
4 Analysis and Findings
Collected data was coded in SPSS-22. Overall Cronbach’s
alpha value (a = 0.865) ensured reliability of instrument and
permits further analysis (Table 1).
Furthermore, reliability values for each variable, i.e.,
organizational sustainability (a = 0.971, human capital
(a = 0.826), and organizations’ readiness to use HR analytics (a = 0.782) ensured the adequacy of questionnaire as
recommend by Nunnally (1978). To test the propositions,
correlation and regression analysis were performed
(Table 2).
Correlation between human resource analytics and organizational sustainability (r = 0.765, p < 0.05), human capital and organizational sustainability (r = 0.871, p < 0.05),
and organizations’ readiness to use HR analytics (r = 0.709,
p < 0.05) are evidencing significant relationship among the
tested variables (Table 3).
Regression values for each independent variable; human
resource analytics (b = 0.322, p = 0.009), human capital
(b = 0.426, p = 0.004), and organizations’ readiness to use
HR analytics (b = 0.337, p = 0.011) ensured significant
contribution of independent variables to organizational sustainability. In addition to acceptance of first proposition,
these values permit mediation test for proposed model and
given proposition (Table 4).
To test the second proposition, human capital is used
mediator in step one and in second step HR analytics is used
as independent. (b = 0.526, p = 0.002), is changed to
HR Analytics, Fad or Fashion for Organizational Sustainability
105
adaptation stage, which consequently, enable the organizations to identify and formulate their predictors of competitive advantage. However, various factors related to
intuitional isomorphism manipulate the organizational early
adaptation ability in relation to their HR analytics, which
mitigate the firm’s ability to sustain a competitive advantage.
2.3 HR Analytics, Human Capital,
and Organizational Sustainability
In a contemporary business environment, organizations are
required to spend on their human capital aiming to develop
and sustain their core competencies. Adaptation of HR
analytics by the organization significantly contributes toward
organizational long-term sustainability. Implication of HR
analytics in business organizations is conceptualized as
one-time effort by the organizational management, which is
significantly associated with organizational sustainability
and growth (Minbaeva 2018). It is the main responsibility of
the firm’s HR practitioners to adopt analytical methodologies (Boon et al. 2018) for better decision making related
with human resource management functions. Analytics must
be conceptualized based on context in order to generate
consequential inferences. It is essential for the HR practitioners to recognize the quality of the data before the data
entry process. Inferential and descriptive statistical models
coupled with structure equation modelling, correlation
matrices, and regression models should enhance the firm’s
capacity to recognize how organizational human capital
significantly contribute toward firm’s sustainability and
growth (Angrave et al. 2016). HR analytics can be perceived
as a strategic tool used to optimize the organizational
insights on how to gain a competitive advantage in today’s
contemporary business environment. Organizations that
invest in human capital and consider employees to be a
valuable asset are more enabled to gain competitive advantage as compared to others. In addition, it has been recommended in past studies that organizational management and
HR practitioners should formulate a mental liaison in terms
of how organizational human capital significantly associated
with organizational sustainability and future growth by using
HR analytics. It has been evident that due to the growing
adaptation of Human Resource Information System (HRIS)
organizations have the ability to store its data in one place;
this, in turn, enhance organization’s ability to retrieve
desired information effectively (Fitz-Enz and John Mattox
2014).
Based on gap identification and a comprehensive literature review, the following theoretical model and propositions are developed to study the effect and value of each
variable (Fig. 1).
Proposition 1 Human resource analytics (HRA) is significantly contributing toward organizational sustainability.
Proposition 2 Organizations’ readiness to use HRA to
mediate relationship between HR analytics and organizational sustainability.
Proposition 3 Trained human capital mediates relationship between HRA and organizational sustainability.
3 Research Methodology
Based on literature review one dependent variable (Organizational Sustainability), one independent variable (Human
Resource Analytics), two mediators (Organizations’ Readiness to use HRA and Human Capital). To collect primary
data, a five-point Likert scale questionnaire was used. The
questionnaire was distributed to 600 human resource professionals working in the automobile sector operating in
GCC, and 271 responded. In the cross-sectional study, primary data was collected using stratified random sampling.
4 Analysis and Findings
Collected data was coded in SPSS-22. Overall Cronbach’s
alpha value (a = 0.865) ensured reliability of instrument and
permits further analysis (Table 1).
Furthermore, reliability values for each variable, i.e.,
organizational sustainability (a = 0.971, human capital
(a = 0.826), and organizations’ readiness to use HR analytics (a = 0.782) ensured the adequacy of questionnaire as
recommend by Nunnally (1978). To test the propositions,
correlation and regression analysis were performed
(Table 2).
Correlation between human resource analytics and organizational sustainability (r = 0.765, p < 0.05), human capital and organizational sustainability (r = 0.871, p < 0.05),
and organizations’ readiness to use HR analytics (r = 0.709,
p < 0.05) are evidencing significant relationship among the
tested variables (Table 3).
Regression values for each independent variable; human
resource analytics (b = 0.322, p = 0.009), human capital
(b = 0.426, p = 0.004), and organizations’ readiness to use
HR analytics (b = 0.337, p = 0.011) ensured significant
contribution of independent variables to organizational sustainability. In addition to acceptance of first proposition,
these values permit mediation test for proposed model and
given proposition (Table 4).
To test the second proposition, human capital is used
mediator in step one and in second step HR analytics is used
as independent. (b = 0.526, p = 0.002), is changed to
HR Analytics, Fad or Fashion for Organizational Sustainability
105