analysis of the combined and split up effects of …...measurement of organizational innovation in...

Bahria University Journal of Management & Technology: Vol.2, No. 2 pp. 24-37

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Analysis of the Combined and Split up Effects of Strategic Human

Resource Practices on Knowledge Management Capacity and Firm-

Innovation

Rab Nawaz Lodhi1, Shahbaz Sharif2, Ayesha Naeem3 1,2Department of Economics and Business Management, University of Veterinary and Animal Sciences, UVAS Business

School, Lahore, Pakistan 3Institute of Business and Management, University of Engineering and Technology, Lahore, Pakistan

ABSTRACT

This study was organized to test the combined and split effects of Strategic Human resource

(SHR) practices on organizational innovation and on knowledge management capacity. Data was

collected through survey questionnaires from 300 private bank sector employees including bank

officers, administrative officers, middle and upper management and then applied partial least square

(PLS) technique to elaborate the relationships between independent and dependent variables. The

findings of this study showed that each specific SHR practice has a positive effect on knowledge

management capacity and organizational innovation except (i) “selective staffing” and (ii) “training”

dimensions of SHR. They have week but positive impact on knowledge management capacity and

organizational. In addition, the combined effect of SHR practices on knowledge management capacity

and organizational innovation was also significant and positive. This study has contributed to

managerial and theoretical implications and lastly, limitations and future research were also discussed.

Keywords: SHR practices, Firm Innovation, Knowledge-management capacity, PLS

Introduction

Strategic human resource practices are the key element to improve firm performance and

innovation as they are a crucial resource to translate firm needs and employees behavior (Sánchez,

Marín, & Morales, 2015). Hence, HR managers need to manage their employee's compensation,

staffing, training, participation and performance-based appraisals as this engage their employees in

developing a new idea or sharing an existing idea, method, and policy which increases organizational

innovation. SHR practices and firm innovation had been investigated in the wide range of all places in

the world (Beugelsdijk, 2008; Camelo-Ordaz, Garcia-Cruz, Sousa-Ginel, & Valle-Cabrera, 2011;

Chang, Gong, Way, & Jia, 2013; Diaz-Fernandez, Bornay-Barrachina, & Lopez-Cabrales, 2017;

Eriksson, Qin, & Wang, 2014). However, the existing literature had utilized the innovation

measurement as product innovation (Lopez‐Cabrales, Pérez‐Luño, & Cabrera, 2009; Shipton, Fay,

West, Patterson, & Birdi, 2005), IT, administrative and process innovation (Bondarouk & Kees Looise,

2005; Jimenez-Jimenez & Sanz-Valle, 2005; Verburg, Den Hartog, & Koopman, 2007). The

measurement of organizational innovation in form of exploitation and exploration has rarely been

identified in the existing literature (Fındıklı, Yozgat, & Rofcanin, 2015), particularly unexplored in

Pakistan banking sector.


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In addition, HRM practices and knowledge management had also been recognized in many

contexts while rare has been recognized with knowledge management capacity. The objective of the

present study was (1) to analyze the relationship between SHR practices and firm innovation; (2) Too

much extent SHR affect the knowledge sharing, acquisition, and application. The contribution of this

study can be summarized to check the impact of SHR practices on the knowledge management capacity.

SHR practices also contributed to firm innovation in the form of exploration and exploitation. The term

strategy used to analyze the employee’s knowledge at a firm place and firm performance.

Literature Review/Theoretical Framework

Strategic Human Resource practices (SHRPs)

The idea which utilizes employees in an effective and efficient manner to achieve competitive

edge is the strategic human resource practices. Strategic human resource management creates

relationship between employees and firm innovation. HRM practices are designed to formulate firm

innovation and knowledge sharing, acquisition and application. Today, many companies involved in

innovation process to increase their productivity level and market demand (Afacan Fındıklı, Yozgat, &

Rofcanin, 2015). Exploitation and exploration are two important strategies which are used to sustain

and improve firm innovation. Exploitation means to share existing knowledge among organizational

employees and management while exploration means to develop a new idea, theory or method (Curado,

2008). Strategic human resource practices such as training, staffing, performance appraisal, active

participation, and compensation have a positive effect on firm performance (Sánchez et al., 2015). SHR

management is important to the development of human capital to achieve firm goals and targets (Collins

and Clark, 2003; Jackson et al., 2014). Knowledge management as a tool to promote productivity and

flexibility of firm to meet competencies (Davenport and Volpel., 2001; Sveiby et al., 2005).

SHR practices and Firm Innovation - Exploration and Exploitation

Organizations should use their resources in an effective way to ensure profit in short and long

run, they maintain new skills and new market situations which demanded by new customers.

Exploration and exploitation strategies are used to reduce the internal tension and manages firm

management control system (Schuler RS and Jackson SE., 1987). Some SHR practices were associated

with firm innovation and knowledge sharing, acquisition and implication (Afacan Fındıklı et al., 2015).

Firm innovation may be different from each other for example exploration declared as experiments to

develop the new idea while exploitation is the extension of existing technologies and idea or method

(Zhao et al., 2014).

Innovativeness is conceptualized to encourage innovation and has closely related to sharing

knowledge and knowledge application to attain firm’s goal (Ferraresi et al., 2012). The literature shows

that this study examines the relationship between SHR practices and firm innovation and knowledge

management capacity. SHR practices are used to develop the skills of workers and employees to

increase the productivity level and firm flexibility (Swart and Kinnie, 2009).

Exploration and exploitation process was increased by SHR practices. SHR practices help to

promote exploration and exploitation for the accurate use of firm capital and resources (Afacan Fındıklı

et al., 2015). Another study shows that firm innovation is positively and significantly influenced by

SHR practices (Nasurdin, 2011). A firm cannot transfer knowledge among employees easily without

SHR management (Chung et al., 2007). Without the implementation of SHR practices, the knowledge


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management has no direct effect on firm performance (Sánchez et al., 2015). After depth discussion,

the hypothesis was generated:

H1: SHR practices have a positive and significant effect on exploration and exploitation as a

firm innovation

SHR practices and Knowledge management capacity

Knowledge management capacity is the form of sharing, acquiring and application of

knowledge which can be enhanced through the use of strategic human resource practices (Afacan

Fındıklı et al., 2015). There was a positive and significant relationship between knowledge management

and firm performance (Shehu Aliyu, Bello Rogo, & Mahmood, 2015).

SHR practices provide meaning to the application of shared knowledge and acquire more

knowledge to develop the firm innovativeness (Ferraresi et al., 2012). Knowledge management capacity

was significantly and positively influenced by the implementation of performance appraisal and

compensation (Ferraresi et al., 2012). It is important that organizational changes based on the

development of competencies of human available resources. SHR management is used to in order to

increase competencies to manage knowledge (Chourides et al., 2003). If organization enables

employees to share, acquire and apply knowledge in firm innovation then firm financial performance,

productivity can be increased. SHR management is organized to make employees competencies by

sharing knowledge, acquiring knowledge and application in a systematic manner.

SHR practices are established to achieve the knowledge management (Nonaka and Takeuchi,

1995; Hall, 2001; Davenport and Volpel, 2001; Jelenic, 2010). Effective knowledge of employees must

be evaluated by SHR practices such as staffing and performance appraisal (Wang and Noe, 2010; Chen

and Huang, 2009). SHR practices are used to allow employees to improve their behaviors to achieve

firm goals (Scarbrough, 2003; Collins and Clark, 2003; Von Krogh, 1998). The behavior of knowledge

sharing and knowledge application can be derived from performance appraisal and compensation

benefits (Gold et al., 2001; Chen and Huang, 2009).

H2: SHR practices have positive and significant effect on knowledge- economy i.e. sharing,

acquiring and application

Research methodology

Sample and procedure

This study covered private banking sector operating in Pakistan. The participants were full-time

employees including bank officers, administrative officers, middle and upper management. 430 survey

questionnaires were distributed among employees and out of 430, 327 questionnaires were collected

but 300 of them were answered completely. Hence, the participant’s response rate was 69.77%. The

participants participated in survey research were 72% males and 28% females. The 68% participants

were below 30 years of age, 26% were between the age of 30-39, 5% participants were between 40-49

and only 1% above 50 year of age. The participants also categorized into different designations such as

51% were bank officers, 25% were administrative personnel, 22% were middle management and only

2% were upper management.


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Construct Measurements

All construct measurements were adopted from the prior literature and measured on 5 point

Likert scale, representing 1= strongly disagree to 5= strongly agree.

SHR Practices

The SHR practices construct included 5 dimensions i.e. training, compensation, performance-

based appraisal, staffing and active participation and was measured by adopting 15 items scale from

Collins and Clark (2003) and Chen and Haung (2009). Each dimension contained 3 items and the

Cronbach alpha coefficient for the combined SHR practices was 0.889. While, the alpha coefficient for

training was 0.74, compensation was 0.714, performance-based appraisal was 0.711, staffing was 0.734

and participation was 0.76.

Firm Innovation

Firm innovation means any change in firm performance made through employees by using firm

resources and practices. Firm innovation construct included two dimensions; exploration and

exploitation and adopted from 12 items scale of Zi-Lin He and Poh-Kam Wong (2001) and Jansen et

al., (2009). Each dimension contained 6 items and the Cronbach alpha coefficient of exploitation was

0.890 and exploration was 0.856. While, the Cronbach alpha of combined firm innovation construct

was 0.909.

Knowledge management capacity

The three dimensions of knowledge management capacity including knowledge acquisition,

sharing and application were evaluated with eight items scale developed by Lin HF & Lee GG, (2005),

Chen and Huang (2009b) & Gold AH, Malhotra (2001). Knowledge sharing and knowledge acquisition

contained 3 items and knowledge application contained 2 items. Cronbach alpha coefficient for

knowledge acquisition was 0.844, knowledge sharing was 0.838 and knowledge application was 0.826.

While, the Cronbach alpha for the whole construct was 0.891.

Data analysis

Testing measurement model

Smart PLS-SEM 3 was applied to test the validity and reliability of measurement constructs

and the nature of relationships among them. The rationale for using this software is its advanced

reporting features and it’s user-friendly. PLS algorithm was applied to evaluate the convergent and

discriminant validity known as construct validity. Researchers advocated that (1) factor loadings must

be greater than 0.70, (2) AVE must be greater than 0.5 and (3) Composite reliability must be greater

than 0.70 for convergent validity assessment (Joseph F. Hair, 2013; Joseph F. Hair, 2014 & Coltman,

2008). We have found that all items of SHR practices, firm innovation and knowledge management

capacity had factor loadings greater than 0.7 (Table.1) except STAF1 (λ=0.658) and TRAIN3 (λ=0.543)

and hence removed from the model. Moreover, the average variance extracted of all constructs were

also greater than 0.50, hence, it could be said that convergent validity of all constructs was valid in both

construct wise & item wise. Fornell & Larcker., 1891 typology was used to assess the discriminant

validity of constructs. The most recommended criteria for evaluating discriminant validity is “Fornell

and Larcker., 1981” which is a multiple trait evaluation techniques of constructs. This method makes

the comparison of each construct’s AVE value with square inter-correlation of another construct in the

PLS model (Joseph F. Hair, 2013; Andrew M Farrell, 2009). The value of all constructs was greater


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than 0.7 and also greater than the value of another construct (Table.2). These results supported our

measurement model discriminant validity.

Table 1. Factor loadings/Average variance extracted/Cronbach alpha

Variable/Items Loading Reliability(α) AVE

Compensation 0.714 0.636

COMP1 0.817

COMP2 0.818

COMP3 0.756

Selective Staffing 0.734 0.713

STAF2 0.886

STAF3 0.823

Training 0.740 0.634

TRAIN1 0.828

TRAIN2 0.763

Active Participation 0.760 0.608

AP1 0.702

AP2 0.850

AP3 0.780

Performance appraisal 0.711 0.634

PA1 0.766

PA2 0.794

PA3 0.828

Exploration 0.856 0.581

EXP1 0.739

EXP2 0.730

EXP3 0.778

EXP4 0.802

EXP5 0.758

EXP6 0.765

Exploitation 0.890 0.646

EXT1 0.753

EXT2 0.814

EXT3 0.795


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EXT4 0.862

EXT5 0.837

EXT6 0.753

Knowledge sharing 0.838 0.756

KS1 0.810

KS2 0.910

KS3 0.885

Knowledge acquisition 0.844 0.762

KAC1 0.862

KAC2 0.879

KAC3 0.877

Knowledge application 0.826 0.851

KAPP1 0.925

KAPP2 0.920

Table 2: Fornell and Larcker. (1981)

COMP EXT EXP FI KAPP KAC KS KMC AP PA SHRP STAF TRA

IN

Compensation 0.798


Exploration 0.504 0.637 0.762

Firm innovation 0.583 0.916 0.893 0.709

Knowledge

Application 0.5 0.581 0.538 0.62 0.923

Knowledge

acquiring 0.728 0.558 0.533 0.604 0.503 0.873

Knowledge

Sharing

0.516 0.608 0.52 0.626 0.784 0.51 0.869

Knowledge

management

capacity

0.684 0.682 0.62 0.721 0.872 0.794 0.9 0.76

Active Participation 0.621 0.552 0.555 0.612 0.501 0.625 0.484 0.63 0.78

Performance

appraisal 0.537 0.583 0.546 0.625 0.491 0.578 0.523 0.62 0.66 1.0

SHRP 0.824 0.646 0.636 0.709 0.581 0.745 0.592 0.75 0.86 1.0 0.656


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Selective Staffing 0.568 0.473 0.502 0.538 0.414 0.54 0.445 0.55 0.65 1.0 0.804 0.845

Training 0.57 0.433 0.479 0.503 0.446 0.531 0.422 0.55 0.52 1.0 0.742 0.542 0.796

Note: Diagonal values represent discriminant validity and other correlation coefficients**

COMP=Compensation, EXT=exploitation, EXP=exploration, FI=firm innovation, KAPP=knowledge

application, KAC=knowledge acquiring, KS=knowledge sharing, KMC=knowledge management capacity,

AP=active participation, PA=performance appraisal, SHRP=strategic human resource management,

STAF=selective staffing and TRAIN=training

Regression analysis

1st order measurement constructs relationships

Smart-PLS generated T-statistics to test the inner & outer model significance level by applied

a technique, called bootstrapping. The procedure followed the 500 subsamples from the original sample

312 (maximum iterations with stop value-7) with replacement to standard errors in bootstrap which give

output in form of T-statistics values for significance testing of the Path model. Structural equation

modeling (SEM) was used to test the effects of SHR practices on the knowledge management capacity

and firm innovation (see table 3). The two-tail test is applied at 5% significant level (P<0.05) standard

error. A t-statistics value must be greater than 1.96, then it can be say that there is a significant

association (Wong, 2013).

The compensation factor of SHR practices showed positive and significant effect on firm

innovation (β=0.206***, t=17.431) and knowledge management capacity (β=0.218***, t=16.425). The

second factor of SHR practices, active participation also showed significant and positive effect on firm

innovation (β=0.197***, t=18.362) and knowledge management capacity (β=0.209***, t=21.463). The

third factor performance appraisal revealed significant and positive impact on firm innovation

(β=0.204***, t=19.454) and knowledge management capacity (β=0.216***, t=21.121). Selective

staffing had a positive and significant effect on firm innovation (β=0.140***, t=17.257) and knowledge

management capacity (β=0.148***, t=18.157). The training factor had a significant and positive impact

on firm innovation (β=0.117***, t=13.862) and knowledge management capacity (β=0.124***,

t=14.075). Present study proved that all the latent factors of SHR practices influence both knowledge

management capacity i.e. knowledge sharing, acquiring and application and firm innovation i.e.

exploitation and exploration.


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Model 1. The effects of compensation, selective training, training, active participation and

performance appraisal on knowledge-economy and firm innovation

2nd order measurement constructs relationships

This study had further elaborated the combined effect of SHR practices on knowledge

management capacity (β=0.751***, t=24.949) and on firm innovation (β=0.709***, t=24.515). These

significant and positive effects showed that employees developed existing or new idea when they were

exercised by SHR practices in the banking sector. These results of SHR practice’s opportunities are

consistent with other literature studies that have been examined the combined and latent effects of SHR

practices on knowledge management capacity and firm innovation.


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Model 2. The combined effects of SHR practices on knowledge-economy and firm innovation

Model fitness

The coefficient of determination (R²) is a most important measure to test the structural model

fitness. R² evaluated the combined effect of all latent constructs of the exogenous variable on the

endogenous variable (Wong, 2013). In addition, Adjusted R² values reduced the values of R² by the

number of explaining variables & size of a sample. Present research had good predictive accuracy/

adequacy in terms of R² and adjusted R² values because R² is a measure to test the model predictive

adequacy (Joe F. Hair Jr, 2014). The R² and adjusted R² values must be placed between 0 to 1 with the

higher level the high level of predictive accuracy and vice versa (Joseph F. Hair, 2013; Joe F. Hair Jr,

2014). Researchers argued that R² values vary from 0.75, 0.50 to 0.25 which respectively described as

strong, moderate and weak relationship (Hair et al., 2012; Sarstedt, Ringle, Smith, Reams, & Hair, 2014;

Hair et al., 2013; Hair, Sarstedt, Pieper, & Ringle, 2012 and Joe F. Hair Jr, 2014). Table 3 reveals that

there was good predictive accuracy and adequacy from independent constructs to the dependent

constructs.

Table 3. R square and adjusted R square

Constructs R2 T Statistics

(|O/STDEV|)

Adjusted

R2

T Statistics

(|O/STDEV|)

P-values

Exploitation 0.838 50.418 0.838 50.268 0.000

Exploration 0.798 35.107 0.797 34.998 0.000

Firm-innovation 0.502 12.349 0.501 12.288 0.000

Knowledge-application 0.761 35.264 0.760 35.148 0.000


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Multi-collinearity statistics (VIF)

Multicollinearity was assessed by calculating the tolerance (1-R2) and variance inflation factor

(VIF) (Sarstedt, Ringle, Smith, Reams, & Hair, 2014 and Joseph F. Hair, 2014). PLS-SEM explored

multicollinearity for a set of exogenous constructs toward endogenous in the model. VIF calculates as

“1/tolerance” but as a rule of thumb, VIF accepts if its value >=5 then it can be said that the constructs

are highly correlated (Wong, 2013; Sarstedt, Ringle, Smith, Reams, & Hair, 2014 & Coltman, 2008).

R² value facilitates to compute the VIF of constructs (Sarstedt et al., 2014). Table 4 discloses the values

of VIF and tolerance of all constructs under present study, which designates that our data do not contain

any problem of multicollinearity.

Table 4. Collinearity Statistics

Collinearity Statistics

Constructs Tolerance Variance Inflation Factor

VIF

Knowledge-economy 0.435 2.299

Knowledge-sharing 0.191 5.236

Knowledge-acquiring 0.370 2.703

Knowledge-application 0.239 4.184

Firm-innovation 0.498 2.008


Exploration 0.202 4.950

Discussion

This study examined the impact of SHR practices on firm innovation and knowledge

management capacity. SHR practices has been considered an important asset for every organization in

order to acquire suitable solution for innovative performance. Literature studies evaluated the positive

and significant relationship between SHR practices and knowledge management capacity (Afouni,

2007; Haesli & Boxall, 2005; Theriou & Chatzonglou, 2008 and Wang et al., 2012). This study came

from the classical review of mediating relationship of SHR practices on knowledge management and

firm performance (Sánchez et al., 2015). The principal goal of this study was to investigate the effects

of SHR practices on firm innovation and knowledge management capacity in private banking system

as a whole in Punjab, Pakistan.

Knowledge-acquiring 0.630 16.321 0.629 16.257 0.000

Knowledge-sharing 0.809 40.681 0.809 40.556 0.000

Knowledge-economy 0.565 12.565 0.563 12.51 0.000


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All hypotheses were accepted on the following grounds: (1) knowledge-sharing, knowledge-

acquiring and knowledge-application are systematically dependent on the SHR practices in the private

banking sector. (2) Firm exploitation and exploration also systematically dependent on the SHR

practices because SHR practices served as a role model for any industry. (3) All dimensions of SHR

practices substantially influence on knowledge management capacity and firm innovation. Moreover,

training, compensation, performance appraisal, selective staffing and active participation are important

industrial substantial factors that develop the employees' behaviors toward knowledge sharing,

acquiring and its application and on another way, firm exploitation and exploration. It is concluded that

if organization executes SHR practices then it can infuse the employee’s feelings towards independence

and success, then there will be an increase in knowledge sharing, acquiring and application and firm

exploitation and exploration (Sánchez et al., 2015).

The hypothesis 1 result showed that SHR practices are positively correlated with knowledge

management capacity. This result is consistent with the findings of Sanchez et al., 2015. In addition,

the hypothesis 2 result showed that SHR practices are positively correlated with firm innovation. This

result is consistent with the findings of Nawaz et al., 2014; (Afacan Fındıklı et al., 2015) and (Nasurdin,

2011). It is also summarized that the training factor is positively correlated with the knowledge

management capacity. For this reason, it could be said that organization gives more importance to the

training of their employees to get better results in the knowledge management capacity and firm

innovation. Compensation is positively correlated with knowledge management capacity and firm

innovation, which concluded that if organization agrees to compensate their employees, will better

results in sharing, acquiring and applying knowledge and develop new or existing idea for innovative

firm. Performance appraisal is positively correlated with knowledge management capacity and firm

innovation which showed that if the organization measures the employee’s performance on authentic

scales then they will better contribute to knowledge management capacity and firm innovation.

Active participation is positively related to knowledge management capacity and firm

innovation this contributes to the fact that if employees take part in decision making, making policies

and work enhancement then they would learn more which in turn, would encourage knowledge

management capacity and firm innovation. Selective staffing is also positively correlated with

knowledge management capacity and firm innovation, which concluded that if organization selects right

personnel for the available post or his/her qualification is consistent with that post then he/she will

contribute more to knowledge management capacity and firm innovation. These results are consistent

with previous studies (Sánchez et al., 2015); Nawaz et al., 2014; (Afacan Fındıklı et al., 2015) and

(Nasurdin, 2011).

This study has empirical evidence that success of every organization depends upon effective

SHR practices and in turn, employees introduce multiple products throughout their career enhancement

and development. In addition, the employees improve the existing products if they feel any deficiency

of banking product or feel further modifications in existing products. The employees develop an

effective control system that influences the customers, colleagues, and officials. Hence, they facilitate

the existing employees with content to launch a new policy that encourages outsiders to contribute their

personal habits within a bank.

Limitations and Future research

The present study was conducted from empirical evidence by using cross-sectional study

method. So, it is expecting to conduct a longitudinal study to draw continuous fluctuations of different

factors on firm innovation and knowledge management capacity. This study was narrow down and only

depends upon previous literature shreds of evidence, hence, there is a need of more attention to studying


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the hidden factors to affect the firm innovation and knowledge management capacity. Future research

may conduct to explore the substantial factors like management strategy, employee organizational

behaviors, information technologies, organization commitment that provide managerial support to the

knowledge management capacity and firm innovation in a different context. Examination of this study

leads to more investigation because every firm has different strategies. So, we can say that this study

needs to explore more ideas and concepts that help the audience and add to our understanding of firms

in general.

Implications

Implications of the present study are providing to be more effective in the managerial

perspective. SHR practices proved the satisfactory effect on management with a little bit factors but in

future, it may different perspective to achieve the firm goals and objectives. The present study was

extended to SHR practices that acted as a role model to firm innovation, improve management sharing

and performing capabilities. SHR practices like performance appraisal, compensation & merit base

selection provided evidence that industrial system always depends upon managerial practices system,

seminars conduction etc. SHR practices should be implemented in every organization to stable

employee intention. SHR practices used to share and interpret existing or new ideas in the organization

with the collaboration of workers. Sometime SHR practices are used as mediation that has the firm main

focus on SHR practices in the form of the knowledge-economy. Knowledge economy enables

employees in the industry to communicate with each other that are not felt hesitation from requiring

anything from top management. SHR practices also increase organization commitment of employees

and providing evidence for not firing just hiring.

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