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International Journal of Management Studies, 28, No. 2 (July) 2021, pp: 73–101
http://e-journal.uum.edu.my/index.php/ijms
INTERNATIONAL JOURNAL
OF MANAGEMENT STUDIES
How to cite this article:
Rehman, H. M., Au Yong, H. N., & Choong, Y. O. (2021). Impact of management
practices on organisational innovation in the digital age: A study of the manufacturing
industry in Malaysia. International Journal of Management Studies, 28(2), 73-101.
https://doi.org/10.32890/ijms2021.28.2.4
IMPACT OF MANAGEMENT PRACTICES ON
ORGANISATIONAL INNOVATION IN THE DIGITAL
AGE: A STUDY OF THE MANUFACTURING
INDUSTRY IN MALAYSIA
1Haz Mudassir Rehman, 2Au Yong Hui Nee &
3Choong Yuen Onn
1,2 & 3Department of Economic & Department of Business
Faculty of Business and Finance
Universiti Tunku Abdul Rahman, Malaysia
3Corresponding author: choongyo@utar.edu.my
Received: 14/11/2020 Revised: 14/4/2021 Accepted: 19/4/2021 Published: 13/7/2021
ABSTRACT
The manufacturing industry is an indispensable part of the economy,
especially for Malaysia. The manufacturing sector in Malaysia is not
only transforming raw material into products, but also contributing
signicantly to the country’s economy. Malaysia has attained a
signicant position in the world by exporting its manufactured goods.
However, the production services always require innovation to meet
the ever-changing customer demands. With the advent of Industry
4.0, the manufacturing industry faces constant challenges such as
the innovation capability of organizations, and swift and frequent
shifts in the use of technology. These issues may hamper the efforts
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International Journal of Management Studies, 28, No. 2 (July) 2021, pp: 73–101
of manufacturing rms to fully participate in Industry 4.0 Malaysia.
Therefore, the objective of this study is to identify the inuence of
knowledge-oriented leadership, electronic human resource management
(E-HRM), and decentralised organisational structure on organizational
innovation. The current research has adopted a quantitative method to
establish the relationship between these three variables and innovation in
organizations. A total of 218 samples were collected from manufacturing
rms located in Malaysia. Data collected through a self-administered
questionnaire was examined by using SmartPLS software. The results
of this research has added to the body of knowledge in the respective
eld by highlighting the signicance of knowledge-oriented leadership
and E-HRM in predicting organizational innovation. It can further help
stakeholders to plan a way forward in facing Industry 4.0 through the
development of innovation competencies.
Keywords: Decentralized organisational structure, digital age,
electronic human resource management, Industry 4.0, knowledge-
oriented leadership, organizational innovation.
INTRODUCTION
In the digital era, it is important for a country to be innovative in
transforming its economy, especially in the context of a country like
Malaysia. Like other countries, the Gross Domestic Product (GDP) of
Malaysia also depends on the value added by its industries, particularly
the manufacturing industry (MacDougall, 2014). The manufacturing
sector is regarded as an enabler for employment and economic quality.
However, the revolution wrought by Industry 4.0 has changed the way
of running businesses. For example, Industry 4.0 integrated humans
with machines and production processes to create a smart value chain
(Schumacher et al., 2016). Therefore, companies will be confronted
with complexities and challenges in their business operations with
the integration of the concept of organizational innovation. These
challenges are linked to all levels of the organization and will affect the
business processes directly.
To deal with the challenges associated with this rapid change,
organizational innovation has been suggested as a critical factor for
the success of manufacturing rms (Hecklau et al., 2016). Moreover,
innovation is imperative to improve the performance of manufacturing
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International Journal of Management Studies, 28, No. 2 (July) 2021, pp: 73–101
companies. However, innovation does not come on its own, rms
have to adapt suitable management approaches that support the
development of organizational innovation competencies. According
to Shamim et al. (2016), long-term innovation capabilities could
only be realized with the assistance of management practices such as
knowledge-oriented leadership and appropriate structure. In sum, it
is only innovative organizations which will be able to survive in the
dynamic and ever-changing environment of Industry 4.0.
Despite the importance of innovation in the Industry 4.0 thrust,
researchers have mainly discussed only the associated risk and
opportunities (Moeuf et al., 2020; Preuveneers & Ilie-Zudor, 2017).
However, a few recent studies have highlighted the importance of the
technological aspect of innovation (Lorenz et al., 2015; Frank et al.,
2019). It has become clear that there is a gap in this research eld as
past researchers did not consider management practices which were
prompting factors of innovation (Shamim et al., 2016). Mohelska and
Sokolova (2018) also endorsed researches focused on management
approaches (Leadership, HRM and Structure), which recognized the
critical importance of adopting the lens of organizational innovation.
The actual test for rms nowadays is to look for qualied leaders
who can create a knowledge-sharing culture (i.e., knowledge oriented
leader) to respond to any new challenges in a responsive way.
Additionally, the human resource practices that are digitally backed
(E-HRM) are necessary to meet the standards of digitization. Finally,
the decentralized structure that enhances the free ow of information
and promotes autonomy to develop new ideas and innovation plays
a crucial role. In light of this, the current research has focused on
examining how management practices such as knowledge-oriented
leadership, Electronic Human Resource Management (E-HRM)
and decentralised organizational structure inuenced organizational
innovation in light of the challenges of Industry 4.0.
THEORETICAL FOUNDATION
AND LITERATURE REVIEW
Dynamic Capability Theory
Dynamic Capability Theory (DCT) has discussed the development
of capabilities to tackle the shift in business processes (Teece et al.,
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1997). This theory has stated that competitive advantage depended
on the ability to use practices that could develop rm capabilities
to offer new products and services (Parnell, 2011). Organizational
innovation referred to the capability to create possibilities to offer
novel services (Burns, 2016). The application of DCT in this research
was about in terms of the usage of suitable management practices for
the improvement of innovation capabilities. Accordingly, knowledge-
oriented leadership was seen as having a support role in building
organizational innovation capability by encouraging the use of new
and important information that was created, shared and applied for
purposeful outcomes (Mabey et al., 2012). E-HRM, on the other
hand, was seen as assisting rms by motivating employees to train
themselves and meet the rm’s requirements. Similarly, a decentralized
organizational structure will enable rms to develop new ideas that can
lead to a fast response to changes. Through appropriate management
approaches, a rm can build competencies to ensure organizational
innovation capability, ultimately helping to accomplish its strategic
goals in line with Industry 4.0 (Paauwe & Boselie, 2005).
Organisational Innovation
Innovation was initially described in a conceptual way by Schumpeter
(1934) when he was discussing factors of economic growth. He
discovered that innovation was a signicant factor involved in
organizational growth and success. Till today, innovation has been
considered a chief concern for most organizations. In light of the
present day business environment, change is the only constant
phenomenon and this underscore the critical role innovation has
to play. This was because a study has found that innovation would
enable organizational self-efciency to respond to any change faster
than non-innovators (Jiménez-Jiménez et al., 2008).
According to Baregheh et al. (2009), “Innovation is the process of
transforming ideas into new products or processes to advance and
differentiate themselves successfully in their marketplace” (p. 1326).
Innovation is seen as having the power to change a rm, by an action
or response to the external environment, or as a pre-emptive action to
inuence the surrounding environment. Innovation for organizations
is crucial for their growth and success. It determines the continued
existence of companies and can also contribute to their competitive
advantage.
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In the era of digitalization, the introduction of the boundary-less
business environment has increased the complexity of manufacturing
processes. Companies are starting to face many challenges which are
part and parcel of new technological concepts and a fast-changing
environment. These inevitable challenges, including the change of
customer requirements and demands for tailored products, make
marketplaces more volatile. It is making innovation the business
imperative for organizations. Innovation can build the capability of
organizations to tackle rapid changes in the business environment.
However, innovation does not just happen on its own. Appropriate
organizational practices such as knowledge-oriented leadership and
organizational structure are needed to develop innovation (Shamim et
al., 2016; Stock-Homburg, 2013).
Knowledge Oriented Leadership
The leadership of a rm is the key to impact the rm’s performance
and its direction (Nguyen & Mohamed, 2011). Competent leaders
would outline a clear vision for workers that could guide and motivate
them to achieve the rm’s objectives (Ribière & Sitar, 2003). For
knowledge-oriented rms, strong leadership will enable the employees
to regard themselves as assistants in innovative and knowledge
activities. Moreover, leaders should identify and compensate
innovative attempts by their employees, instead of promoting adverse
actions that would endanger knowledge exchange and its application.
A leadership style that comprises components such as inspiration and
interaction is called knowledge-oriented leadership. The concept of
knowledge-oriented leadership was only recently developed (Shamim
et al., 2019) and not very well understood in a true sense (Mohsenabad
& Azadehdel, 2016).
Knowledge-oriented leadership is a necessary instrument that is based
on a mixture of transformational and transactional leadership styles,
along with communication and motivational elements. It would include
knowledge creation, transfer, storage, and its application (Donate &
de Pablo, 2015). Knowledge-oriented leadership was determined
as an action or ability that could encourage new and important
information that has been created, shared, and applied to bring about
positive outcomes (Mabey et al., 2012). This type of leadership has
been suggested for companies, and those who valued knowledge-
oriented leadership were often successful in their businesses (Donate
& de Pablo, 2015).
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Knowledge-oriented leadership is imperative for every organization,
especially for manufacturers. This type of leadership brings about a
number of benets for organizations. It enhances the performance of
organizations and is effective for the development of new products.
An effective leader could act as a role model for employees, promote a
learning environment, motivate them to develop new knowledge, and
would compensate those who were willing to share their ideas and
contribute towards the rm’s organisational knowledge (Naqshbandi
& Jasimuddin, 2018).
Knowledge Oriented Leadership and Organisational Innovation
Modern rms are characterized by their complexity level and experience
of turbulence. The capability to gain competitive advantage depended
on the selection of leadership and innovation (Sheng, 2017). In this
context, a recent development of the knowledge-oriented leadership
concept has gained much attention (Shamim et al., 2019; Donate &
de Pablo, 2015). It offers the instilling of extraordinary potential
within individuals and enables the creation and application of new
knowledge, which is key to innovation performance. Furthermore, the
knowledge managed by this leadership would bring about strategic
changes in a rm’s operations and processes (Donate & de Pablo,
2015; Slezdik, 2013).
Present day business operations are dynamic, which will replace the
manual routine work with machines, and these new tasks would often
require a high level of expertise and skill sets. Hence, knowledge-
oriented leadership becomes an asset for the company, which is hard
to ignore throughout the innovation process. The concept of such a
leader was someone in a position to generate knowledge that could
develop and offer new and transformative solutions for society (Vafaie,
2016). By applying their up-to-date knowledge, they can manage to
produce unique products and services. According to Śledzik (2013),
borrowing the words of Joseph Schumpeter, there were ve different
types of innovations, namely innovation of new product, new methods
of production, new markets, new sources of supply and new ways
to organize the business. Thus, depending on the type of innovation,
leaders can use their wealth of knowledge to plan, organize, lead, and
control the process accordingly.
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It has become evident that organizational innovation depends on the
availability of the latest knowledge and skills. A knowledge-oriented
leadership style will assist in creating the required knowledge and
then processes whatever general knowledge into specic information
that can play a critical role to further the innovation process. The
signicance of knowledge-oriented leadership with respect to
innovation was its emphasis on the role of systems and to always
keep culture and structure in mind (Nam et al., 2017). Knowledgeable
leaders have a vital responsibility to execute a positive and complex
change in order to achieve the company’s goals. This means that their
inuence will create a domino effect, and with minor alterations can
bring about more substantial changes.
A major role that the knowledge-oriented leader plays is to inspire
followers in achieving an innovation objective. The same argument
was used by Kasemsap (2017) in his research which underscored
the importance of knowledge-oriented leadership for innovation. He
argued that knowledge-oriented leaders offered rms the prospect
of developing their unique set of competencies and expertise. These
competencies together with the use of the appropriate knowledge
will create the desired innovation for the company. Such leaders
also motivate employees in taking risk to apply new knowledge that
subsequently facilitates innovation for the organization (Williams &
Sullivan, 2011). The close relationship between a knowledge-oriented
leadership and organizational innovation in modern rms is clearly
evident in the current literature. Therefore, the present study has
hypothesized that:
H1: Knowledge-oriented leadership has a positive and signicant
relationship with organizational innovation.
Electronic Human Resource Management (E-HRM)
The management of employees is an important activity and the
competitiveness of any company depends on its human resource
management functions. The activities that were performed
electronically for employee’s management was known as E-HRM
(Armstrong & Taylor, 2020). According to Bondarouk and Ruël
(2009), “E-Human Resource Management is an umbrella phrase
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covering all possible integration systems and contents between
human resource management and information technology (IT),
seeking at developing value within and across companies for workers
and management” (p. 507). E-HRM is specically designed to apply
information technology (IT) in HRM practices that will in turn, enable
convenient interaction between employees and the company. This
practice includes E-Recruitment and Selection, E-Communication,
E-Learning and E-Performance Appraisal. More specically, E-HRM
has integrated technology to perform HR operations (Bondarouk et
al., 2017).
To meet the challenges of current and future complex markets, rms
require a workforce with a special set of skills, abilities, knowledge,
and motivation to effectively deal with job challenges. Human resource
management (HRM) was seen as an approach for the employment and
development of a qualied workforce to attain the objectives of the
rm (Armstrong & Taylor, 2020). With functions such as recruitment
and selection, communication, training and development and
performance appraisal, E-HRM has highly impacted the performance
of the company (Becker, 2013).
Although E-HRM is a relatively new term, it has the ability to
transmute old-fashioned HRM practices completely. Some optimistic
technological voices have gone to the extent of assuming that, from
a technical perspective, all HR processes should be supported by IT.
To cite an example, in the context of E-Communication, employees
from different locations can still interact with one another using the
email and relevant software. Many companies also have their own
internal communications system with a specic Internet Protocol (IP)
address that employees will be provided, which means that everyone
in the company can access les and communicate with managers
or colleagues using a secured local network. For E-Recruitment,
companies could announce job openings online to ll vacant positions
and even conduct online interviews (Okolie, & Irabor, 2017). For
E-Training and development, employers can easily share training
materials and track trainee learning performance.
One of the most important challenges that most companies faced
nowadays has been the revolution brought about by the internet and
entailed technological changes (al Shobaki et al., 2017). As it has
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also brought about drastic changes in all functions of human resource
management, it has enormous implications in the development
of strategic HRM plans. Moreover, this revolution has resulted
in extensive changes in organizational structures and reduced the
workforce due to the automation applied. Therefore, E-HRM has
emerged as a solution that will enable swift changes and adaptations
to the new dynamic environments (al Shobaki et al., 2017).
Electronic Human Resource Management (E-HRM) and
Organizational Innovation
E-HRM practices have become progressively necessary for the vast
majority of rms around the world because of its ability to make use of
the online knowledge repository to improve organization innovation.
Now is the opportune time for stakeholders to set their E-HRM goals
according to their company’s requirements. It can be to address the
issues of cost reduction, productivity, service improvement, etc.
The E-HRM tool has become inevitable with the recent disruption
triggered by the Covid-19 pandemic, a world-wide scourge that has
made innovation a need rather than a luxury. Since most businesses
nowadays are conducted online, this development has become a
litmus test of the viability of E-HRM.
The emergence of information technology is evident in all our daily
activities, be it in the amazon shopping platform, food delivery
service, or work emails. In other words, IT has impacted all elds and
denitely its inuence on HR practices would not be any different.
In such an IT ecological environment where companies have to
compete for their survival, E-HRM has become more essential than
ever, and organizations must have a survival strategy to continue to
compete successfully. A study conducted by Iqbal et al. (2018) has
concluded that E-HRM could not only help companies to grow, but
also enhance quality labor activities as well. Therefore, E-HRM is
the organizational innovation that has to be embraced in this time of
urgent need. Otherwise, many companies may have to bite the dust,
and many already have.
It is therefore no surprise that many modern companies have been
developed on the foundation of innovative concepts, with E-HRM
amongst the top priority areas under organizational innovation
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(Jonczyk & Buchelt, 2015). E-HRM has always been a primary
concern as it is considered by many experts in the eld as the starting
point for innovation or creativity. Innovative organizations need
to spend more on human resource, and research and development
activities. Previous studies, especially the study by Escribá-Carda et
al. (2014), have all shown a positive connection between E-HRM and
innovation in the organization. This is especially so in practices such
as recruitment and training which are closely linked to organizational
innovation. Empirical research has edalso conrmed that E-HRM
positively affected knowledge creation (Collins & Smith, 2006) as
well as learning and innovation (Nam et al., 2017). Therefore, the
present study has proposed that;
H2: Electronic human resource management has a positive and
signicant relationship with organizational innovation.
Organisational Structure
Organizational structure is the organization of tasks and individuals
within the company in order to achieve the company’s objectives. It
outlines the activities, including the rules, roles and responsibilities
crucial for the success of the company. The common organizational
structure can be characterized as centralized and decentralized in
nature. The centralized structure is the one where only one person
or one authority, either the CEO or executive will make all the
decisions. Some companies have a specically designated department
that will control all the company activities and drive the innovation
performance too. This is generally considered an example of an anti-
innovation approach as there will be boundaries established and
restrictions enforced on all activities. In contrast, a decentralized
structure allows the employees to be involved in decision making and
empowers them to participate in making any decision. In other words,
employees have a say in the planning and execution of new ideas
(Ahmady et al., 2016).
According to O’Grady (2019), “Decentralised organisational structure
seeks to reduce the hierarchy and distribute more decision-making
authority to a greater number of employees. It enables companies to
become more exible and to better handle unanticipated events” (p.
225). In this structure, most decisions are delegated to subordinates
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down the hierarchical order. Furthermore, as reected in the position
adopted in the present research, the research and development activities
that were controlled and managed at lower levels of the organization
would still be a part of the decentralised structure (Bergfors & Larsson,
2009). This structure is usually applied to deal with dynamic business
activities as it offers autonomy to make decisions faster and respond
quickly to change.
Organizational Structure and Organisational Innovation
The level of innovativeness in any company is established by the
formation of their innovative actions. Literature has also discussed
different organizational structure and its effect on the intensity of
innovation (Arora et al., 2014). However, extant literature did not
investigate the mechanism in which any change in structure is critical
for innovation in a company (Argyres et al., 2018). Moreover, it has
been argued for some time now that organizational structure affects
organizational innovation. However, there is still very few empirical
investigations on this matter.
In sum, innovation is all about new ideas and new processes. It
is considered as a key factor for a company’s progress, as well as
crucial for the company’s competitive advantage over other players.
Organizational structure and organizational innovation have a unique
relationship due to their contrasting effects on structural forms
and the tendency to transform (innovation) (Geldes et al., 2017).
Organizational structures are formed to regularize different qualities
including exibility, stability, empowerment, and technology
acceptance. Innovation is the result of these regularizations.
In light of the foregoing discussions, it is clear that organizational
innovation is dependent on organizational structure. More importantly,
the type of organizational structure determines the intensity of
organizational innovation. Centralized organizational structure has
rigid rules to follow and a proper chain of command through which
decisions are processed. However, a decentralized organizational
structure has provided more autonomy for employees in decision
making and a channel for the feedback of ideas. Employees can be
more productive as they are allowed to express their creativity and
participate in innovation. This is because if they feel secure and are
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given the support to think out of the box, they can share ideas and
come up with more innovation.
Extant literature has also documented the relationship between
organizational structure and organizational innovation. A meta-
analysis was conducted by Damanpour (1991) on the relationship
between organizational innovation and other determinants. He found
that organizational structure was signicant for the development
of innovation. Turbulent business environments required dynamic
capabilities which were only possible with decentralization,
resulting in an organizational environment where there would be
less formalization, more exibility and responsiveness (Cosh et al.,
2012). Accordingly, the following hypothesis has been proposed for
the present study:
H3: A decentralized organizational structure has a positive and
signicant relationship with organizational innovation.
Furthermore, in light of the insights gained from the review of the
literature discussed, the following conceptual framework has been
developed for the present study (See Figure 1).
Figure 1
Conceptual Framework of the Study
Knowledge-Oriented
Leadership
Electronic Human Resource
Management
E-Recruitment & Selection
E-Learning
E-Compensation
E-Performance Appraisal
Organisational Structure
Organisational Innovation
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METHODOLOGY
Research Design
Consistent with positivism philosophy, the current research has used a
cross-sectional approach in the collection of its data, and then employed
a quantitative method of data analysis. A quantitative research design
has enabled this study to investigate the relationship between the
independent variables (i.e., knowledge-oriented leadership, E-HRM,
and decentralized organizational structure) and the dependent
variable (i.e., organisational innovation). Data was collected through
questionnaires and analyzed using SmartPLS software. This software
has a better analytical accuracy in the results generated as compared
to the CBSEM (Chin, 2010). The software is also appropriate for the
analysis of causal relationships (Hair et al., 2012).
Sampling Design and Procedures
The population of this research comprised manufacturing companies
that were registered with the Federation of Malaysian Manufacturers
(2018). From each company, one individual (i.e., Owner, Chief
Executive Ofcer, Director, General-Manager, Senior Manager,
Manager, or Executive) was selected to respond to the items about
the practices in the respective organizations as they have better
understanding of the company’s strategies and its operations. Through
a simple random sampling technique, a total of 218 usable responses
were obtained. The rate of response was considered sufcient for a
structured equation modelling (SEM) (Hair et al., 2010).
Questionnaire Design and Structure
A 5-Point Likert scale (i.e., ranging from Strongly Disagree to
Strongly Agree) was used to get the responses for each item.
Section A of the survey questionnaire dealt with the respondent’s
demographic information, whereas Section B contained all the items
about the variables of interest in this study. Six of these items were
on the dependent variable knowledge-oriented leadership. They
were adapted from the research of Donate and de Pablo (2015)
with two exemplary items: “Our company managers assume the
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role of knowledge leaders as a mediator for sharing and applying
knowledge” and “Our company managers behave as advisers, and
controls are just an assessment of the accomplishment of objectives”.
As for the dependent variable E-HRM, the scale was adapted from
Hooi (2006). Four dimensions (i.e., e-recruitment and selection,
e-learning, e-compensation, and e-performance) were covered through
12 items for this variable (Hooi, 2006). Sample items included “Our
company uses recruiting website/job board to identify potential job
candidates” and “Our company is using performance appraisal
software for evaluation purposes”.
The scale for decentralized organizational structure was adapted from
Willem et al. (2007). Four items were used to measure this construct.
Sample items were “Every matter in our company have to be referred
to someone higher up for the nal answer” and “In our company, a
person who wants to make a decision on his own is discouraged”.
These items were included and reverse coded to measure the exibility
of employees for decision making. For the organizational innovation
scale, six items from the study by García-Morales et al. (2012) were
adapted, and the sample items included were, “Our company’s
emphasis is on developing new products” and “Our company has
spent on new product development activities in last 12 months”.
RESULTS
This results section will provide an insight into the demographic
proles of the respondents. It will also discuss the measurement model
and the structural model assessment. The reliability and validity
properties will be explained in the measurement model, while the
hypotheses testing and their results will be discussed in the structural
model.
Respondents’ Demographic Proles
To help the study obtain the viewpoints from both genders equally, the
samples selected comprised 46 percent females and 54 percent males.
Furthermore, 30.6 percent of the respondents were from companies
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located in Selangor, this was followed by Perak and Kuala Lumpur
with 17.3 and 15 percent, respectively. These three states were
considered as industrial hubs and thus, represented the main portion
of the required samples. In addition, most of the respondents (44.5%)
were holding the position of either Senior Manager or Manager,
while 38.5 percent of the respondents fell into the category Owner/
CEO/Director/General Manager. This tier of ofcials are normally
involved in decision making and have great inuence because of their
experience and overall control of a company’s activities (Bahari et al.,
2018). As such, it was crucial to be able to include this latter category
of respondents in the present study. Approximately 84 percent of
the respondents in this study came from the category involved in
decision-making and knew rst hand the policies of the organization
well. A total of 69 percent of the respondents were from the middle
age group, they were between 25 and 44 years old. At the same time,
six percent of the respondents were above 55 years old. The details
are as presented in Table 1.
Table 1
Demographic Details of the Sample
Characteristics
Sample (n = 218)
Frequency Percentage
Gender
Male 117 54%
Female 101 46%
Job Status
Senior Manager/Manager 97 44%
Owner/CEO/Director/General
Manager 84 39%
Executive 37 17%
Age Group
25 to 34 years old 77 35%
35 to 44 years old 74 34%
45 to 54 years old 54 25%
More than 54 years old 13 6%
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Measurement Model
A total of 218 usable responses were collected for a Conrmatory
Factor Analysis (CFA). In order to ensure the best representation
of sample to actual population, the Weighted Partial Least Square
(WPLS) method was applied. It helped to estimate the population
parameters consistently and further assisted in the generalizability of
the results. The percentages of product types were used to revalue the
sample for weighted scores and added to assessment for better results.
Furthermore, for the purpose of validation, items of the variable
with a factor loading above 0.6 were retained (Hair et al., 2015). The
measurement model is depicted in Figure 2.
Figure 2
Measurement Model of Variables Understudy
Note. KOL = Knowledge-Oriented Leadership; EHRM = Electronic Human Resource
Management; ERS = Electronic Recruitment & Selection; LN = Electronic Learning;
CMN = Electronic Communication; EPA = Electronic Performance Appraisal
Firstly, to assess the goodness of measures, validity tests and reliability
tests were conducted. Initially, a construct validity test was conducted
to check the tness of all items of the construct. The item loadings
13
Measurement Model
A total of 218 usable responses were collected for a Confirmatory Factor Analysis (CFA). In order to ensure
the best representation of sample to actual population, the Weighted Partial Least Square (WPLS) method
was applied. It helped to estimate the population parameters consistently and further assisted in the
generalizability of the results. The percentages of product types were used to revalue the sample for weighted
scores and added to assessment for better results. Furthermore, for the purpose of validation, items of the
variable with a factor loading above 0.6 were retained (Hair et al., 2015). The measurement model is shows
in Figure 2. Hence, none of the items was deleted.
Figure 2
Measurement Model Used in the Study
Note. KOL = Knowledge-Oriented Leadership; EHRM = Electronic Human Resource Management; ERS = Electronic Recruitment
& Selection; LN = Electronic Learning; CMN = Electronic Communication; EPA = Electronic Performance Appraisal
Firstly, to assess the goodness of measures, validity tests and reliability tests were conducted. Initially, a
construct validity test was conducted to check the fitness of all items of the construct. The item loadings
with the same criteria of 0.6 were inspected, as this was suggested by Hair et al. (2010). The respective
values confirmed the establishment of the criteria, and hence, no item was deleted.
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with the same criteria of 0.6 were inspected, as this was suggested by
Hair et al. (2010). The respective values conrmed the establishment
of the criteria, and hence, no item was deleted.
Secondly, to check the signicance of the measurement model,
convergent validity was assessed. Random measurement error has
been tested by the examination of Cronbach’s Alpha, Convergent
Validity and Average Variance Extracted (AVE) and there were no
problems detected (see Table 2). Additionally, the AVE has to be
higher than 0.5 (Hair et al., 2010), a standard which all the variables
managed to meet. Hence, all items converged to the respective
hypothesized construct.
Table 2
Construct Reliability and Validity
Construct Reliability and Validity
Cronbach’s
Alpha rho_A
Composite
Reliability
Average
Variance
Extracted
(AVE)
E-HRM 0.927 0.93 0.937 0.557
EC 0.897 0.905 0.936 0.830
EL 0.915 0.919 0.946 0.855
EPA 0.893 0.896 0.934 0.824
ER&S 0.776 0.779 0.87 0.692
KOL 0.894 0.915 0.919 0.654
OS 0.872 0.67 0.894 0.679
OI 0.889 0.897 0.915 0.644
Note. KOL = Knowledge-Oriented Leadership; EHRM = Electronic Human Resource
Management; ERS = Electronic Recruitment & Selection; LN = Electronic Learning;
CMN = Electronic Communication; EPA = Electronic Performance Appraisal; OS =
Decentralized Organisational Structure; OI = Organizational Innovation
A discriminant validity test was performed to address the issue
of multicollinearity. The values of factor loading, and AVE were
compared with the criteria (Hair et al., 2010). The AVE values should
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be more than 0.5 (see Table 2) and the square root of AVE of each
construct is greater than the respective column values, as can be
seen in Table 3. Finally, the criteria for the Variance Ination Factor
(VIF) has also been met with all values less than 5 (Rogerson, 2001).
Therefore, the model and variables were found to be independent of
one another (Hair et al., 2015).
Table 3
Discriminant Validity
E-HRM EC EL EPA ER&S KOL
Dec.
Org.
Structure
Org.
Innovation
E-HRM 0.946
EC 0.846 0.911
EL 0.87 0.626 0.925
EPA 0.784 0.501 0.619 0.908
ER&S 0.836 0.67 0.615 0.545 0.832
KOL 0.559 0.502 0.454 0.365 0.545 0.809
OS 0.067 0.082 0.057 0.135 0.092 0.091 0.824
OI 0.65 0.583 0.592 0.383 0.595 0.553 0.099 0.803
Assessment of Structural Model and Hypotheses
After the measurement model was established, the second step of
the structural model was assessed via a bootstrapping technique of
5000 resamples. All the hypotheses were tested through a structural
path modelling technique. The three main hypotheses were tested
to determine whether the objective of the research study has been
achieved. The results of hypotheses H1 and H2 were supported with
statistical values of 4.595 and 8.606, respectively. However, H3 was
rejected with a t-statistics value 1.068, as is shown in Figure 3 and
Table 4.
Through the thorough structural model analysis, it could be nally
concluded that H1 and H2 were supported, while H3 showed
insignicant results.
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Figure 3
Structural Model
Table 4
Structural Model Assessment
Hypotheses Relationship T-statistics p-value Results
H1Knowledge-Oriented Leadership ->
Organizational Innovation
4.595 0.000 Supported
H2E-HRM -> Organization Innovation 8.606 0.000 Supported
H3Decentralized Organizational Structure ->
Organizational Innovation
1.068 0.285 Not
Supported
DISCUSSIONS
The eld of research on management practices to increase organizational
innovation is growing, owing to the practical and theoretical importance
of rms. The three major practices, namely knowledge-oriented
leadership, E-HRM, and decentralized organizational structure, have
been introduced to improve organizational innovation.
16
Table 4
Structural Model Assessment
Hypotheses
Relationship
P-Value
T-Statistics
Results
H1
Knowledge-Oriented Leadership ->
Organizational Innovation
4.595
0.000
Supported
H2
E-HRM -> Organization Innovation
8.606
0.000
Supported
H3
Decentralized Organizational Structure ->
Organizational Innovation
1.068
0.285
Not Supported
Through the thorough structural model analysis, it could be finally concluded that H1 and H2 were supported,
while H3 showed insignificant results.
DISCUSSIONS
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The rst hypothesis was related to knowledge-oriented leadership
and organizational innovation. The result showed that knowledge-
oriented leadership has a signicant impact on the t-statistics value,
which was 4.595. There could be several explanations for this
signicant impact. According to Yahya and Goh (2002), knowledge
could contribute to creating conditions conducive to innovation in
rms. Nowadays, innovation has become a competitive advantage
for successful organizations. The application of knowledge-oriented
leadership will help in the creation and application of new knowledge
which is necessary for new product development and innovation. This
leadership style also accentuates continuous improvement in the rm
by using implicit and explicit knowledge (Wang & Ahmed, 2007).
The rst objective of this research was achieved by examining
the level at which a knowledge-oriented leadership style was
vital for organizational innovation. The analysis showed that a
specic leadership style that was a mixture of characteristics of
transformational and transactional leadership, and with an extra
motivational component could have a great impact on organizational
innovation performance (DeCarolis, & Deeds, 1999). This leadership
style helps rms to understand that knowledge through R&D
(innovation) is an imperative for improvement and to outperform
competitors. Therefore, nowadays, companies are embracing this
style of leadership which will help them to embark on the journey
towards organizational innovation.
The second objective of the study was to investigate the extent to
which E-HRM could inuence the organizational innovation of
manufacturing rms. With a t-stat value of 8.606, the results have
conrmed that there was a signicant relationship between E-HRM
and the organizational innovation success of rms. In other words,
by accentuating on E-HRM practices, rms can enhance their
organizational innovation. This result was also supported in studies
by other researchers. For example, according to De-Leede and Looise
(2005), a specic approach must be planned in E-HRM to attain
innovative organizational performance. The results of the current
study offer key insights about E-HRM and organizational innovation
for all levels of managerial staff. The results underscored the fact the
employee management was critically important for organizational
innovation. The empirical evidence provided in the present study has
clearly shown that E-HRM (including e-recruitment and selection,
e-learning, e-communication and e-appraisal system) had a crucial
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impact on organizational innovation. Lin (2011) has emphasized
particularly that success in the implementation of organizational
innovation would require the synchronization of all functions of the
E-HRM of a rm. Organizations are made up of employees and every
performance is dependent on how they are managed. E-HRM provides
a complete management solution to achieve the objectives of the
organization, especially in terms of the performance of organizational
innovation. It will help organizations to hire innovation-focused
employees, train, and compensate them accordingly to improve the
performance of the organization.
Finally, the last hypothesis of this study which sought to examine
the relationship between decentralized organizational structure
and organizational innovation has been tested and found to have
insignicant support. The hypothesis was not supported because the
t-value of 1.068 was less than 1.96. It indicated that the change in
decentralized organizational structure had no noteworthy impact on
organizational innovation. Few past studies have found a positive
impact of decentralized structure on organizational innovation
(Marín-Idárraga, & Cuartas, 2016). The authors explained that a more
exibility of the organization structure would allowed employees
to become creative and achieved their full potential, thus helping to
enhance the rm’s performance.
However, the current research also showed results which were contrary
to some studies highlighted in the literature review. For example, there
could be several reasons in support of the insignicant response found
in the present study. Initially, due to advancements in technology and
the less competitive business conditions, many business persons have
been registered as sole-proprietors or partnership corporations to run
their businesses. The Malaysian ofcial statistics also stated that 98.5
percent of rms were small and medium enterprises (SMEs). With
many of these businesses operating with only one or two persons, it was
not seen as necessary to institute any specic organizational structure,
which as caused the present inconsequential result. Moreover, the
current situation of Covid-19 has disrupted the business environment
which included aspects of work, processes, and structure. Present day
workers also have to follow various standard operating procedures
(SOP), which were in the past not experienced before. These sudden
changes have inuenced and thus resulted in different ndings which
were not expected.
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CONCLUSION, IMPLICATIONS, AND
DIRECTIONS FOR FUTURE RESEARCH
In the current study, three independent variables were studied to
determine how they impacted organizational innovation. Knowledge-
oriented leadership was found to have a positive effect and a strong
relationship with organizational innovation. Likewise, E-HRM also
positively impacted organizational innovation. By investigating the
relationship between knowledge-oriented leadership, E-HRM and
decentralized organizational structure in management practices and
determining how these variables impacted organizational innovation,
the current research has extended our knowledge on organizational
innovation in the context of the current dynamic business environment
of Industry 4.0. By testing the proposed conceptual framework, the
current study has been able to conrm the importance of certain
management practices for organizational innovation, especially with
regard to specic leadership styles and human resource practices that
are supported by online features.
The present research has added a noteworthy contribution to the
literature by lling the research gap on the identication of antecedents
to organizational innovation. The critical role of knowledge-oriented
leadership and E-HRM in organizational innovation will certainly
generate considerable interest among future researchers. Most
importantly, the insignicant results on the relationship between
decentralized organizational structure and organizational innovation
will widen the opportunity for research on the manufacturing sector.
Besides, the results of the research have multiple takeaways for the
manufacturing industry stakeholders and Malaysian ofcials. The
new Malaysian policy “Industry4wrd” which strongly emphasized
the importance of innovation for the manufacturing sector has
further underscored the valuable contributions of the present study.
The industry stakeholders must now make more serious efforts to
adopt the relevant recommended management practices to enhance
organizational innovation. Due to the fact that manufacturing
companies will always require continuous improvement in their
processes, they must also continually learn to be more careful in
choosing their leaders and the best HR practices.
In future, other management practices such as organizational culture
can be utilised to determine and enhance organizational innovation.
Moreover, a longitudinal study to analyze the covid-19 impact on
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organizational innovation is highly recommended in future studies.
The quantitative methodology used in the present study has limited
the researcher to using only closed-ended questions to obtain
information from respondents. Furthermore, the ndings are limited
to the manufacturing sector and cannot be extrapolated to other
industries. Therefore, it would be interesting to expand the scope to
other sectors by choosing different geographical research sites using a
mixed methodology to further validate the ndings in this study.
ACKNOWLEDGMENT
This research was part of the project entitled, “Fourth Industrial
Revolution Technology Disruption of the Workplace and its Societal
Challenges on Business: New Opportunities in Accelerating of a
Productive Aging Workforce Reskilling and Innovation.”, which
was funded by the Universiti Tunku Abdul Rahman Research Fund
(UTARRF) 6200/CE3.
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