HIGH PERFORMANCE WORK SYSTEMS (HPWSs) AND HR …€¦ · HPWSs have the common interdependent and comprehensive objective of attracting, selecting, managing, training, retaining and

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International Journal of Management (IJM) Volume 11, Issue 7, July 2020, pp. 675-694, Article ID: IJM_11_07_060

Available online at http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=11&IType=7

ISSN Print: 0976-6502 and ISSN Online: 0976-6510

DOI: 10.34218/IJM.11.7.2020.060

© IAEME Publication Scopus Indexed

HIGH PERFORMANCE WORK SYSTEMS

(HPWSs) AND HR OUTCOMES: A

SUSTAINABLE SOLUTION FOR HIGHER

EDUCATION

Shakeel Sarwar

Assistant Professor, School of Business, Management and Administrative Sciences,

The Islamia University of Bahawalpur, Pakistan

Dr. Owais Shafique

Assistant Professor, School of Business, Management and Administrative Sciences,

The Islamia University of Bahawalpur, Pakistan

Dr. Mazhar Abbas*

Assistant Professor, Department of Management and MIS,

College of Business Administration,

University of Hail, Hail Kingdom of Saudi Arabia.

Basheer M. Al-Ghazali

Assistant Professor, Department of Business Administration,

Dammam Community College,

King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

*Corresponding Author Email: [email protected] & [email protected]

ABSTRACT

Purpose of this study was to investigate the impact of high performance work

systems (HPWSs) on human resource (HR) outcomes in higher education of Pakistan.

Cross sectional design is used to collect the data from 178 regular faculty members

working at COMSATS University Islamabad. The results of partial least square

structural equation modelling analysis revealed that ability enhancing, motivation

enhancing and opportunity enhancing HPWSs has a direct and significant effect on

HR outcomes. Study also proved the moderating role of resource based view (RBV)

between ability enhancing HPWSs, motivation enhancing HPWSs and HR outcomes.

However, current study rejected the moderating role of RBV between opportunity

enhancing HPWSs and HR outcomes. The study concluded the sustainable solution of

long term positive HR outcomes by implementing unique bundles of HPWSs. In line

with suggestions, the study contributes to the literature in designing unique bundle of

High Performance Work Systems (HPWSs) and HR Outcomes: A Sustainable Solution for Higher

Education


HPWSs. Finally, current study discusses the implications and limitations and suggests

areas for future research.

Key words: High performance work systems, airline industry, AMO framework

Cite this Article: Shakeel Sarwar, Dr. Owais Shafique, Dr. Mazhar Abbas and

Basheer M. Al-Ghazali, High Performance Work Systems (HPWSs) and HR

Outcomes: A Sustainable Solution for Higher Education, International Journal of

Management, 11(7), 2020, pp. 675-694.

http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=11&IType=7

1. INTRODUCTION

Employees are believed to be an essential strategic asset for any organization (Roslender,

Monk & Murray, 2020). Therefore, in order to achieve the strategic advantage, organizations

need to continuously invest in employees‟ skills and pay attention to performance driven

human resource practices (Bindhya & Harikumar, 2020; Zaharie and Osoian, 2013).

Likewise, higher education institutions (HEIs) strive to attract and retain the talent, train and

motivate the faculty and provide compatible research environment in order to develop the new

generations (Lew, 2009). Previous researches agree that successful implementation of

performance driven human resource practices empower the faculty and generates positive HR

outcomes e.g. lower absenteeism and turnover (Saeed, Tasmin, Mehmood & Hafeez, 2020).

Researchers believe that faculty members play the vital role in enhancing university

performance through many ways such as academic reputation, research quality and

community services (Alazmi and Alazmi, 2020) and positive HR outcomes are prerequisite to

achieve this. Thus, high performance human resource (HR) practices generate positive

behavioral HR outcomes that ultimately promote the university performance. Concisely,

universities need to implement the high performance HR practices in order to achieve better

individual HR outcomes and university performance.

1.1. Problem Background

Higher education in Pakistan starts after twelve years of schooling that engages the students in

advanced training and research activities to make them compatible in all walks of national

life. Higher education is considered as the highly prioritized level of education because it

provides the skilled workforce to the industry hence leads the nation through resources,

productivity and solutions (HamidUllah, 2005). Projection of higher education in a country

ensures availability of qualified professionals in the fields of agriculture, medicine,

engineering and applied sciences. A country's social and economic development depends

upon the quality of its higher education (Kayani, Akbar, faisal, Kayani & Ghumman, 2017).

The question of quality in higher education is directly related to the outcomes of its

faculty members (HamidUllah, Ajmal & Rehman, 2011). As university teachers are main

pillars in ensuring the quality of higher education system so progress in higher education is

wholly based upon the positive behaviors of the faculty members.

Despite the substantial growth in higher education institutions (HEIs) of Pakistan in the

recent years, higher education system of Pakistan is considered underdeveloped in

comparison to the world. Hoodbhoy (2009) pointed that none of Pakistan's HEIs comes even

close to being a university in the real sense of the word. As unfortunately, in 2019 no

Pakistani university could make its place among the top 600 universities of the world ranked

by The Times Higher Education World University Rankings

(www.timeshighereducation.com, 2019). Whereas, (25) neighboring Chinese and (9) Indian

Shakeel Sarwar, Dr. Owais Shafique, Dr. Mazhar Abbas and Basheer M. Al-Ghazali


universities have made their place in the same list. This indicates a big room for improvement

in Pakistan‟s higher education system. According to the same ranking that is majorly based

upon faculty output dimensions, Pakistan has the world‟s weakest higher education system

while United States and United Kingdom have the strongest (https://tribune.com.pk/, 2016).

Researchers have identified various problems causing negative HR outcomes of faculty

members of higher education institutions. According to Iqbal (2004), poor recruitment and

selection practices, inadequate development of faculty, insufficient support for research,

ineffective management practices, inefficient use of available resources and inadequate

funding are the few reasons causing lower productivity in Pakistan‟s higher education

institutions. Likewise Arshad (2003) pointed that there is no faculty development system for

university teachers in Pakistan. He also mentioned that university teachers are not ready to

accept challenges or take extra workload because they are not offered any extra financial

rewards.

Concisely, we need to generate positive HR outcomes of faculty members in order to

boost the quality of higher education sector of Pakistan. For this, major reforms in human

resource (HR) practices are required. One system that may rectify our problems is the high

performance work systems (HPWSs).

Researchers define high performance work systems through various ways. Way (2002),

for example, define it as function of interrelated human resource practices such as selection,

motivation and development of the workforce to gain the sustainable competitive advantage.

Another author i.e. Datta et al. (2005) elaborate the HPWSs as system that promotes faculty

productivity and make them the source of strategic advantage. Similarly, Guthrie et al. (2009)

commented that HPWSs enhances the employees‟ skills, motivation and commitment to

perform. Number of researchers has explored the relationship between HPWSs and HR

outcomes (Patel et al., 2013; Fu et al., 2015). United States Department of Labor (1993)

concluded that the firms using performance generated HR practices gain better shareholder

return.

1.2. Research Questions

The general purpose of this study is to investigate the impact of unique bundle of HPWSs on

faculty HR outcomes and understanding the reasons and process of above mentioned impact.

So based upon the purpose, following research questions arise;

Do ability enhancing, motivation enhancing and opportunity enhancing unique set of

high performance work systems (HPWSs) have a positive impact on faculty HR

outcomes of higher education sector?

Does Resource Based View (RBV) have a significant positive impact on HR

outcomes?

Does Resource based view (RBV) plays a moderating role between ability enhancing,

motivation enhancing and opportunity enhancing HPWSs and HR outcomes i.e.

employee‟s attitude and behavior?

2. LITERATURE REVIEW

2.1 High Performance Work Systems (HPWSs)

HPWSs have the common interdependent and comprehensive objective of attracting,

selecting, managing, training, retaining and motivating Human Resources, eliciting desired

attitudes and behaviors, in order to achieve organizational goals (Kellner et al., 2017). This

objective may be accomplished by creating a fit between the KSA´s of an employee and the

tasks, duties and responsibilities required by a job (Úbeda-García et al., 2018). HPWSs can


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facilitate employee involvement, skills enhancement and stronger motivation (Özçelik, Aybas

& Uyargil, 2016). Generally speaking, HPWSs is believed to be a combination of HR

functions aimed to enhance skills, abilities and productivity for sustainable competitive

advantage (Zhu, Liu & Chen, 2018).

To explore the HR function involved in building HPWSs, Posthuma et al. (2013)

conducted an extensive literature review from 1992 to 2011 and highlighted 61 HR practices

discussed 2042 times in various researches as potentially viable for becoming the part of

HPWSs. Among these 61, 9 practices are more frequently used either individually or in

interrelated groups are selection and recruitment; training and development; performance

management and appraisal; promotions, compensation and benefits; job design; employee

relations; effective communications; retention, turnover and exit management.

According to researchers, HPWSs are the „best fit‟ group of HR practices aimed to

achieve synergistic impact on organizational outcomes (Rabl et al., 2014). Investigations

prove that outcomes achieved through individual HR practices are far less than achieved

through the selected best fit of related practices due to the synergistic impact (Demortier et al.,

2014). E.g. launching self-managed teams in organization without training reduces the

expected results from teamwork (Kroon, Van & Timmers, 2013). So a smartly chosen

combination of HPWSs makes organizations‟ more flexible and participative by transforming

their structure to achieve greater strategic advantage (Kalleberg, 2006).

The AMO approach was initially suggested by Appelbaum et al., (2000) derived from

Bailey (1993) work where he concluded that employees‟ efforts in organizations may be

ensured through the necessary skills, appropriate motivation and opportunity to participate.

This approach was later verified by Bailey, Berg & Sandy (2001). So the AMO framework

consists of three elements of “Best fit” that enhance together employee performance i.e.

individual ability (A), motivation (M), and the opportunity to participate (O) (Claudia, 2015).

This approach believes that employees‟ productivity in an organization is based upon his/her

ability, motivation and opportunity to involve in organizational functions. Organizations may

generate long term advantage by improving the employee‟s ability, enhancing their

motivation and providing sufficient opportunities for growth, this ultimately leads toward

improved productivity and higher organizational performance (Bailey, Berg & Sandy, 2001).

As previous discussions show, due to the variety of high performance HR practices, it is

difficult to select a common bundle to achieve HR Practices-employee productivity linkage.

This phenomenon opposes the universalistic perspective which states as “One practice that

effectively contributing to an organization may be applied to another organization in the same

manner” (Schimansky, 2014).

By believing role of AMO framework in “best fit” selection of HR, several authors have

developed three dimensional criteria of HR practices selection i.e. skill-enhancing HR bundle

(Ability), motivation-enhancing HR bundle and opportunity-enhancing HR bundle

(Appelbaum et al., 2000). Each bundle represents a combination of HR practices that share

the same purpose. Ability enhancing practices include comprehensive recruitment, rigorous

selection, and extensive training (Jiang et al., 2012). Typical HR practices classified within

the motivation enhancing domain are related to incentives and rewards, extensive benefits,

and career development (Subramony, 2009). Finally, the opportunity-enhancing HR bundle

includes initiatives to empower employees to contribute to organizational goals, such as

employee participation in firm decision making, and the use of communication channels from

the firm to employees (Subramony, 2009).



1.2. HR Outcomes

High Performance Work Systems (HPWSs) improve employees‟ abilities, skills, and

motivation and gives them opportunities to contribute (Jiang et al., 2012). Human capital

theory (Crook et al., 2011) and the behavioral perspective (Schuler & Jackson, 1987) serve as

the primary theoretical bases for deriving the causal impact of HPWSs on employee ability,

skill and motivation. Thus, desirable HR outcomes, such as lower voluntary turnover and

absenteeism positively affect the productivity of employees.

HR outcomes like employee‟s intention to leave and absenteeism can be influenced

through performance oriented HR practices (Huang, 2000). While the early models of Beer et

al. (1984) and Guest (1989) provided conceptual foundation of the link between HR practices

and outcomes, the empirical research to explore this link emerged in 1990‟s in the work of

Huselid (1995) and many others. Later this link became a key part of literature and research

(Huang, 2000).

Assessing that committed employees are valuable asset, the conceptual framework of this

study highlights that there is a direct impact of unique bundles of HPWSs on HR outcomes to

enhance the HEIs‟ performance. It is being assumed that if faculty is motivated and

committed than they will be more productive and effective; the satisfaction with their job i.e.

duties and responsibilities make the faculty more productive as compared to dissatisfied and

confused members; and intention to stay affects their performance positively as compared to

intention to leave the institution. It means HPWSs contribution depends upon the above

mentioned HR outcomes (Guest, 2011).

Thus, in this study, it is assumed that the employee‟s behaviors are directly affected by

HPWSs. The Figure 2.1 explains the relationship between HPWSs and faculty HR outcomes.

Thus, based on the literature review and the above discussion following relationships are

hypothesized. These hypotheses focus on the direct relationships between HPWSs and

faculty‟s behavior.

Hypothesis 1: Ability Enhancing HPWSs (AEH) are positively related to HR Outcomes

Hypothesis 2: Motivation Enhancing HPWSs (MEH) are positively related to HR Outcomes

Hypothesis 3: Opportunity Enhancing HPWSs (OEH) are positively related to HR Outcomes.

2.3. Resource Based View- Sustainable Solution

The resource based view (RBV) theory was introduced by Wernerfelt (1984) in his article

“Resource based view of the firm”. The central focus of RBV is the exploitation and

implementation of firm resources to gain a competitive advantage (Wernerfelt, 1984). The

resource based view (RBV) is an economic tool that helps organization to identify and

implement key available resources. By implementing the strategic resources in key processes,

organizations can achieve competitive advantage (Wernerfelt, 1984). If the organization‟s

vital resources are heterogeneous and immoveable, then short term competitive advantage can

be transformed into sustainable competitive advantage (Barney, 1991).

In the continuation of the previous work Barney (1995) provided the VRIO framework

and concluded that a firm´s potential to achieve a competitive advantage depends on the

value, rarity, inimitability and organizational focus of its resources and capabilities.


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Table 1 The VRIO framework and competitive advantage

Valuable? Rare? Costly to

imitate?

Exploited by

the

organization?

Competitive

implications

Strengths or

weaknesses

No – – No Competitive

disadvantage

Weakness

Yes No – Competitive

parity

Strength

Yes Yes No Temporary

competitive

Advantage

Strength and

distinctive

competence

Yes Yes Yes Yes Sustained

competitive

advantage

Strength and

sustainable

distinctive

competence

Source: Adapted from Barney and Hesterly (2010)

As this literature developed, the Resource base view (RBV) theory provided base to the

above arguments that HPWSs directly affect employee HR outcomes (Paauwe and Boselie,

2003). Perhaps, the resource based theory helped to understand the conversion of HPWSs into

high employee performance. Hence, motivation, job satisfaction and organizational

commitment made an employee a valuable asset and become more productive, rare, and

irreplaceable (MacDuffie, 1995).

This research proposes that unique bundle of HPWSs affects the HR outcomes (employee

behavior), ultimately induces the positive HR outcomes of faculty members. Simultaneously,

HPWSs become a capability when they fulfill the requirement of RBV i.e. value they add,

rare, inimitable and organization focused.

Therefore following hypotheses are developed.

Hypothesis 4: Resource Based View (RBV) is positively related to HR Outcomes

Hypothesis 5: RBV Moderates the Relationship between ability enhancing HPWSs and HR

Outcomes

Hypothesis 6: RBV Moderates the Relationship between motivation enhancing HPWSs and

HR Outcomes

Hypothesis 7: RBV Moderates the Relationship between opportunity enhancing HPWSs and

HR Outcomes

Figure 1 Research Framework

Ability Enhancing HPWSs

Resource Based View

HR Outcomes

Opportunity Enhancing HPWSs

Motivation Enhancing HPWSs



3. RESEARCH METHODOLOGY

3.1. Research Design

The main goal of this causal study is to investigate the impact of HPWSs on HR outcomes so

positivist approach is used as it supports the questionnaire for data collection through survey

design and statistical analysis for hypotheses testing that the relation may be explained and

generalized (Malhotra & Birks, 2000).

3.2. Research Strategy

The target population of this study is the regular faculty members of COMSATS University

Islamabad. Through convenience sampling data was collected from 178 faculty members

using a questionnaire (Instrument is attached in annex). The instrument of this study was

adopted from the work of Guerci et al. (2015) for measuring ability, motivation and

opportunity enhancing HPWSs, Jiang et al. (2012) for measuring HR outcomes (i.e. turnover

intentions and absenteeism) and Barney (1997) for measuring sustainable solution i.e. RBV).

For face validity, the instrument was sent to following experts;

Table 2 Experts for Validity

Expert title and

Designation

Institution Field Mean of

communication

Response

Dr. Inmaculada Beltran-

Martin

Associate Professor

Business management

and Marketing

Department, Universitat

Jaume I., Spain

Strategic Human

Resource Management

Email Suggested on

AMO

measurement

Dr. Tay Lee Chin

Assistant Professor

Department of

management, Tunku

Abdul Rehman

University, Malaysia

Management Email Suggested on

AMO and HR

outcomes

measurement

Dr. S. Sridhar

Adjunct Professor

Department of Business

Administration, AIMIT,

India

Human Resource

Management

Email Suggested on RBV

and Overall look of

the tool

Suggestions received from above mentioned experts (Emails attached in Appendix) were

incorporated in the instrument and measurement scale was sent back to the same experts again

to validate the instrument.

4. DATA ANALYSIS AND FINDINGS

Before proceeding for advanced data analysis, raw data collected during the survey was

examined to ensure the accuracy, consistency, eligibility and completeness of the respondents

as recommended by various researchers (Zikmund, 2013).

4.1. Data Coding

After the careful screening, the data was coded and entered into SPSS V20. The coding of the

data was performed on the variable view page of the SPSS and each variable was coded

according to the combination of alphabets of what makes the name of the variable. Again, a

number was assigned to each item based on its position in the questionnaire. For instance,

ability enhancing HPWSs (AEH) construct that has 5 items were coded as AEH1, AEH2,

AEH3, AEH4 and AEH5. Each of the coding was made against the respective statements. The

procedure applied in coding ability enhancing HPWSs (AEH) was applied to code all other

independent variables.


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Table 3 Variable Coding

Variables Code

Ability Enhancing HPWSs AEH

Motivation Enhancing HPWSs MEH

Opportunity Enhancing HPWSs OEH

Resource Based View RBV

HR Outcome HRO

4.2. Fundamental Statistical Assumption

Initially, data was tested for some basic statistical assumptions such as multicollinearity,

regarding the study variables to be able to confirm the results and to deal with some basic

errors such as Type I and Type II error.

4.2.1. Multicollinearity Test

With respect to Hair et al., (2010), multicollinearity test infers the association between two or

more exogenous variables where the independent variable demonstrates little correlation with

other independent variables. If multicollinearity among the independent variables is high then

the most reliable statistical test for multicollinearity is identification of variance inflation

factor (VIF) and tolerance with standard threshold of VIF less than 5 and tolerance more than

0.2 (Tabachnick & Fidel, 2013).

Table 4 Multicollinearity Test

Model Collinearity Statistics

Tolerance VIF

AEH .903 1.107

MEH .777 1.286

OEH .959 1.042

RBV .735 1.360

a. Dependent Variable: HRO

Note: AEH = Ability Enhancing HPWSs; MEH = Motivation Enhancing HPWSs; OEH = Opportunity

Enhancing HPWSs; RBV = Resource Based View; HRO = HR Outcomes.

All variables in the table 4 have their value of tolerance greater than 0.2 and VIF value

less than 5 which means there is no multicollinearity exist between the variables.

Also, to detect the existence of multicollinearity among the independent latent construct

correlation matrix was generated from the SPSS as can be seen in Table 5 The values

indicates that none of the independent latent construct is highly correlated with one another

i.e. to say all the values on the correlation matrix are below the critical value (r=.9). This

indicates the non-existence of correlation among the variables (Hair, et al., 2010).

Table 5 Correlations

AEH MEH OEH RBV HRO

AEH Pearson Correlation 1

MEH Pearson Correlation .064 1

.229

OEH Pearson Correlation -.027 .098 1

.604 .064

RBV Pearson Correlation .246 -.323 -.191 1

.000 .000 .000

HRO

Pearson Correlation .210 .253 .017 .213 1

.000 .000 .748 .000

.047 .002 .036 .002 .000



4.3. Descriptive Statistics of the Study

After the screening process of data the description of statistical analysis for the study

variables is determined by using descriptive analysis where the statistical value of all

variables such as dependent variables, independent variable and moderating variables are

analyzed. The descriptive statistics for study variables as shown in the table 6 presents the

minimum and maximum scores, the values of standard deviation and mean of the study

variables as employed in this study, as previously mentioned in chapter three the

questionnaire used in this study was designed on seven point likert scale ranging from 1 to 7.

Table 6 shows that the mean scores of the study variables are within the range of 3.17 to

4.77, the value of standard deviation for the study variables ranges from 0.91 to 1.2.

Table 6 Results of Descriptive Statistics of the Study Variables

Variable N Minimum Maximum Mean Std. Deviation

AEH 178 1.00 7 3.7648 1.11762

MEH 178 1.29 5.86 3.1732 .91031

OEH 178 1.25 7 4.7703 1.00790

RBV 178 1.20 6.30 3.7992 1.26035

HRO 178 1.00 6.29 3.5072 1.23003



4.4. Assessment of PLS-SEM Path Model

To evaluate the PLS-SEM path, analysis of data is carried out in two basic steps i.e.

measurement model and structural model as suggested by Henseler et al. (2009) and Chin

(1998).

4.4.1. Measurement Model

In outer model evaluation, the measurement model is carried out to ensure the constructs

validity and reliability. In line with arguments of Vinzi et al. (2010) outer loading should be

0.5 and above. Based upon the following argument all the items in outer loading that are

below than 0.5 should be deleted one by one with lowest value, this technique is also

validated by (Hair et al., 2012) as it improves the quality of data. According to Hair et al.

(2011), while performing the outer model evaluation individual items reliability, internal

consistency reliability, content validity, discriminant validity and convergent validity must be

ascertained.

4.4.1.1. Individual Item Reliability

To determine the convergent validity, loading and cross-loadings of the variables are

examined first, as pre-requisite for assessing the outer model. In line with the criteria

suggested by the Hair et al. (2014), convergent validity is attained by meeting the criteria that

factor loading of each item is above 0.6 and no single loading of an item from other construct

is higher than the construct being measured. The result in table 4.5 reveals that no individual

item has value of outer loading less than 0.6 so all 50 items are included in the instrument.

4.4.1.2. Internal Consistency Reliability

Internal consistency reliability is the extent to which all items on a particular subscale

measure the same concept (McCrae et al., 2011). The acceptable value for composite

reliability defined in the literature (Hair et al., 2011) should not be lower than the threshold

value of 0.7, and the average variance extracted (AVE) acceptable value should be at least


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0.5. The table 7 shows that all the variables are highly reliable, and the AVE value of each

variable is above than the cutoff point of 0.50, which shows that the measurement model is

reliable for further analyses. The Cronbach‟s alpha is also calculated to validate the internal

consistency of the constructs. As per the rule of thumb given by George and Mallery (2003),

the value of greater than 0.9, 0.8 and 0.7 are classified as excellent, good and acceptable

respectively. Table 7 below shows the AVE, Cronbach‟s alpha and composite reliability

scores of all variables.

Table 7 Construct Reliability, Cronbachs Alpha, Composite Reliability and AVE of all the Latent

Variables

Construct Items Loading Cronbach's

Alpha

Composite

Reliability

Average Variance Extracted

(AVE)

Ability

Enhancing

HPWS

0.890 0.919 0.694

AEH1 0.824

AEH2 0.829

AEH3 0.845

AEH4 0.889

AEH5 0.775

Motivation

Enhancing

HPWSs

0.886 0.913 0.636

MEH1 0.788

MEH2 0.807

MEH3 0.834

MEH4 0.731

MEH5 0.8

MEH6 0.82

Opportunity

Enhancing

HPWSs

0.842 0.891 0.671

OEH1 0.796

OEH2 0.865

OEH3 0.749

OEH4 0.861

Resource

Based View

0.924 0.937 0.623

RBV1 0.884

RBV2 0.824

RBV3 0.767

RBV4 0.765

RBV5 0.81

RBV6 0.717

RBV7 0.763

RBV8 0.756

RBV9 0.804

HR Outcomes 0.931 0.944 0.707

HRO1 0.789

HRO2 0.823

HRO3 0.844

HRO4 0.85

HRO5 0.861

HRO6 0.863

HRO7 0.853



4.4.1.3. Discriminant Validity

According to Farrell and Rudd (2009), discriminant validity is the extent to which a particular

latent variable is different from other latent variables. In this study, discriminant validity is



predicted by the AVE values, the criteria proposed by (Fornell & Larcker, 1981).

Discriminant validity is obtained by evaluating the correlation between the latent variables

along with the square root of AVE (Fornell & Larcker, 1981). Fornell and Larcker (1981)

recommended the use of AVE of 0.50 or greater to assess discriminant validity. They also

recommended that the square root of AVE should be above the value of the latent variables.

To examine discriminant validity, this study analyzed the model‟s external consistency and

compared the value of AVE of all latent variables. The table 8 shows that the square root of

AVE is greater than the correlation among the latent variables, indicating adequate

discriminant validity (Fornell & Larcker, 1981). After performing CFA, none of the variables

are dropped even the deletion of some items. However, Hair et al. (2013) argued that a

variable with two items should not be subject to removal.

Table 8 Discriminant Validity Matrix (Fornell-Larcker Criterion)

AEH FP HRO MEH OEH RBV

AEH 0.833

FP 0.107 0.784

HRO 0.214 0.509 0.841

MEH 0.065 0.172 0.284 0.797

OEH 0.011 0.209 0.169 0.168 0.819

RBV 0.247 0.179 0.229 -0.295 -0.056 0.789



Figure 2 Measurement Model (PLS Algorithim)

4.4.2. Structural Model

In this study there are two structural models i.e. direct relationship structural model and

structural model that includes moderating variables.


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4.4.2.1. Direct Relationships

According to Hair et al. (2013), the paths with non-significant or signs of opposite direction to

the hypothesized relationships do not accept the hypotheses, while significant paths

empirically provide statistical evidence of causality of the relationships in the model. Before

the mediating effect was tested, bootstrapping with a resample of 500 was run to get the t-

value to assess if direct relationships exist.

A total of 05 direct relationships with faculty productivity and HR outcomes are tested in

this study and all are significantly supported as shown in Table 9

Figure 2 displays the path coefficients, t-values, p-values along with the standard

deviation values. Based on these results, decision is made to support or reject a hypothesis.

The t-values are obtained from bootstrapped procedure (with 500 sampling iterations for 178

cases observations). Hair et al. (2013) argued that bootstrapping serves as a proxy of

parameters for standard error. As Hair et al. (2013) explained, the paths that are non-

significant or showing signs the opposite direction to the hypothesized do not support prior

hypotheses while significant paths empirically support the proposed causal relationship.

Before the mediating effect is tested, bootstrapping with a resample of 500 was run to get the

t-value to assess if the direct relationships are significant. Figure 3 and Table 9 show the

bootstrapping results as discussed below;

Hypothesis 1: Ability Enhancing HPWSs (AEH) are positively related to HR Outcomes

The result from the output of the PLS algorithm and bootstrapping shows a positive and

significant association between AEH and HR Outcomes (β = 0.114, t = 2.255). Therefore,

Hypothesis 1 is supported.

Hypothesis 2: Motivation Enhancing HPWSs (MEH) are positively related to HR Outcomes

A significant and positive relationship between MEH and HR Outcomes is found (β = 0.3477,

t = 7.281). Hence, Hypothesis 2 is supported.

Hypothesis 3: Opportunity Enhancing HPWSs (OEH) are positively related to HR Outcomes.

A positive and significant association between OEH and HR Outcomes (β = 0.127, t = 3.115)

is found. Hence, hypothesis 3 is supported.

Hypothesis 4: Resource Based View (RBV) is positively related to HR Outcomes

A positive and significant association between RBV and HR Outcomes (β = 0.311, t =

6.970) is found. Hence, hypothesis 4 is supported.

Table 9 Results of hypothesis testing (Direct effects)

Hypotheses Relationship Beta SE t-value P-value Decision

H1 AEH -> HRO 0.114 0.050 2.255 0.025 Supported

H2 MEH -> HRO 0.347 0.048 7.281 0 Supported

H3 OEH -> HRO 0.127 0.041 3.115 0.002 Supported

H4 RBV -> HRO 0.311 0.045 6.970 0 Supported





Figure 3 Bootstrapping (Direct Relationships)

4.4.2.2. The Moderating Effects

A test of moderation as pointed out by Ramaya et al. (2011) is applied to evaluate how

moderator variable effects the direction or strength of the relationship between the

independent and dependent variable. Consistent with previous idea, moderator variable are

typically introduced when there is inconsistent relationship or weak relationship between the

independent variable and dependent variable.

There are number of techniques available to test the moderation effects such as hierarchal

regression procedure that has three steps. However, the drawback of this technique is that

researchers have to calculate the interaction terms manually by using functions,

transformation, computation, and taking the product of each pair. Another technique is the

cross products of the indicator of the independent variable and the moderator (Chin et al.,

2003; Dawson, 2014). In this study, the researcher applied the moderating variable as an

additional construct using the cross product of the indicator of the predictor variable and the

moderator (Chin et al., 2003). This method of testing is called a product indicator approach.

Subsequently, an interaction model was tested by creating interaction terms between ability

enhancing HPWSs (AEH), motivation enhancing HPWSs (MEH), opportunity enhancing

HPWSs (OEH) and HR Outcomes. This model included the moderating effect of Resource

Based View (strategic implementation of abilities, motivation and opportunities framework)

on the relationship between AEH, MEH, OEH and HR Outcomes. This product indicator

approach involved determining the path coefficients and t-values. Figure 4 illustrates the

moderating effect of the Resource Based View.

Based on Hair et al. (2013) analysis of the moderation effect, the results suggest that the

relationship between AEH, MEH and HR Outcomes would be strengthened by strategic

implementation of AMO i.e. RBV. This result signifies that positive nexuses between AEH,

MEH and HR Outcomes are stronger for firms with long term strategic implementation of

AMO through resource based view. Simultaneously, analysis also shows that relationship

between OEH and HR Outcomes are not affected by RBV in Pakistan‟s perspective. As

shown in table 10 out of three (3) moderating interaction hypothesis two (2) hypothesis are

significant at p<0.05 and remaining one (1) is insignificant at p<0.05.


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Table 10 Moderator Hypothesis Testing


H9 AEH_Mod -> HRO 0.137 0.050 2.737 0.006 supported

H10 MEH_Mod ->HRO 0.119 0.056 2.147 0.032 supported

H11 OEH_Mod -> HRO -0.030 0.054 0.555 0.579 Not Supported

Note. *p < 0.05 (t = 1.96)


Enhancing HPWSs; RBV = Resource Based View; HRO = HR Outcomes; Mod = Moderator.

Hypothesis 5: RBV Moderates the Relationship between AEH and HR Outcomes

As shown in Table 10 and Figure 4, resource based view (moderating variable) showed a t-

value of 2.737, which is more than the cutoff value of 1.96, indicating that the result is

statistically significant. Thus, the result showed credible evidence of the moderating effect of

RBV on the relationship between AEH and HR Outcomes (β = 0.137, t = 2.737, p = 0.006).

Hence, hypothesis 5 is supported.

Hypothesis 6: RBV Moderates the Relationship between MEH and HR Outcomes


value of 2.147, which is more than the cutoff value of 1.96, indicating that the result is

statistically significant. Thus, the result showed credible evidence of the moderating effect of

RBV on the relationship between MEH and HR Outcomes (β = 0.119, t = 2.147, p = 0.032).

Hence, hypothesis 6 is supported.

Hypothesis 7: RBV Moderates the Relationship between OEH and HR Outcomes


value of 0.555, which is less than the cutoff value of 1.96, indicating that the result is

statistically insignificant. Thus, the results prove no moderating effect of RBV on the

relationship between OEH and HR Outcomes (β = -0.030, t = 0.555, p = 0.579). Hence,

hypothesis 7 is not supported.

Figure 4 Bootstrapping Moderating Effect



5. CONCLUSION AND RECOMMENDATIONS

5.1. Conclusion

This sub-section provides the highlights of the key findings and relates them with the research

objective by answering research questions. The main objective of the investigation was to

evaluate the impact of high performance work systems (HPWSs) on faculty HR outcomes in

higher education sector in the presence of resource based view (RBV) as moderator. In

essence, this study has made a significant breakthrough by evaluating a unique set of ability,

motivation and opportunity enhancing high performance work systems (HPWSs) in the light

of RBV and confirms its strategic impact on faculty outcomes. Hence, this study provides the

answers of the research questions mentioned previously.

Research questions RQ1 and RQ2 examine the direct effect while RQ3 evaluates the

moderating effect. The results of PLS-SEM path modeling disclosed that ability enhancing,

motivation enhancing and opportunity enhancing bundle of high performance work systems

have a significant impact on faculty HR outcomes. Results of findings revealed that in direct

effects all four hypotheses were supported as shown in table 11 below;

Table 11 RQ1 and RQ2 - Direct Effects


H1 AEH -> HRO 0.114 0.050 2.255 0.025 Supported

H2 MEH -> HRO 0.347 0.048 7.281 0 Supported

H3 OEH -> HRO 0.127 0.041 3.115 0.002 Supported

H4 RBV -> HRO 0.311 0.045 6.970 0 Supported


Enhancing HPWSs; RBV = Resource Based View; HRO = HR Outcomes; FP = Faculty Productivity.

Above mentioned table revealed that effect of ability enhancing HPWSs on HR outcomes,

motivation enhancing HPWSs on HR outcomes, opportunity enhancing HPWSs on HR

outcomes HR outcomes on Faculty Productivity and Resource Based View on HR outcomes

are significant and positive. This implies that in the environment where careful HPWSs are

implemented carefully, employee HR outcomes are improved in a significant way. These

findings are in line with those of Úbeda-Garcíaet al. (2014), where ability, motivation and

opportunity HPWSs was found to positively influence the employee behaviors. Also, it

implies that organizations that need to improve their HR outcomes should capitalize on

HPWSs (Amin, Ismail, Rasid, & Selemani, 2014). Hence, the findings of this study are

consistent with previous findings that prioritize careful implementation of HPWSs as a

significant element in performance improvement (Georgiadis & Pitelis, 2012).

The PLS-SEM path modeling also revealed that strategic moderating role of Resource

Based View (RBV) on the effects of ability enhancing HPWSs and motivation enhancing

HPWSs on HR outcomes is statistically supported. Importantly, moderating role of RBV on

the effect of opportunity enhancing HPWSs on HR outcomes was not supported. Hence it

confirmed the long term strategic impact of ability and motivation enhancing bundles of

HPWSs on HR outcomes that ultimately nourishes the faculty productivity. Above mentioned

results provide the answer to RQ5 as shown in table 12 below;

Table 12 RQ3 - Moderation Effect


H6 AEH_Mod -> HRO 0.137 0.050 2.737 0.006 supported

H7 MEH_Mod ->HRO 0.119 0.056 2.147 0.032 supported

H8 OEH_Mod -> HRO -0.030 0.054 0.555 0.579 Not Supported


Enhancing HPWSs; RBV = Resource Based View; HRO = HR Outcomes; Mod = Moderator.


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The findings highlighted the fact that resource based view can play a moderating role

between ability enhancing HPWSs (AEH), motivation enhancing HPWSs (MEH) and HR

outcomes i.e. employee‟s behavior, this is in line with (Barney, 1991) study, i.e. if the bundle

of HPWSs is valuable, rare, inimitable and organizational focused, long term HR outcomes

may be achieved. Although the moderation of RBV on the effect of opportunity enhancing

HPWSs on HR outcomes was not confirmed in this study, this does not invalidate the

propositions of AMO because previous studies have confirmed the effects. In particular, the

insignificant relationship could be a result of environmental and economic factors that directly

impacts the available opportunities compared to developed economies.

5.2. Recommendations and Implications

The findings of this study recommends and imply that, in order to achieve greater faculty HR

outcomes, there is need to implement unique bundles of HPWSs (Combs et al., 2006;

Appelbaum et al., 2000). That is, there is need for greater synergy between performance

oriented HR practices and human resource strategies to ensure the faculty members to

discharge positive behaviors. Also, the effect of ability enhancing HPWSs was positively

related with the HR outcomes of faculty members, implying that the more management

focuses on enhancing faculty abilities, the greater will be the positive effect on their HR

outcomes.

2nd

, Findings of this study indicate motivation enhancing HPWSs influence the faculty HR

outcomes. The implication is shows HEIs management needs to pay adequate attention to

performance based compensation system capable of eliciting positive HR outcomes and

faculty productivity. Furthermore, the findings of the study also revealed a significant effect

of opportunity enhancing HPWSs on faculty HR outcomes. This indicates that faculty

empowerment, autonomy of work and knowledge shearing positively influences the HR

outcomes. Specifically, management of HEIs needs to involve the faculty in job design and

important decision making.

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HIGH PERFORMANCE WORK SYSTEMS (HPWSs) AND HR …€¦ · HPWSs have the common interdependent and comprehensive objective of attracting, selecting, managing, training, retaining and