Content uploaded by Norsiah Hami
Author content
All content in this area was uploaded by Norsiah Hami on Dec 14, 2015
Content may be subject to copyright.
77:4 (2015) 57–68 | www.jurnalteknologi.utm.my | eISSN 2180–3722 |
Jurnal
Teknologi
Full Paper
AN EMPIRICAL STUDY ON THE IMPACT OF SUSTAINABLE
MANUFACTURING PRACTICES AND INNOVATION
PERFORMANCE ON ENVIRONMENTAL SUSTAINABILITY
N. Hamia*, M.R. Muhammadb, Z. Ebrahimb
aSchool of Technology Management and Logistics, College of
Business, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
bFaculty of Manufacturing Engineering, Universiti Teknikal Malaysia
Melaka, Malaysia
Article history
Received
02 June 2015
Received in revised form
09 August 2015
Accepted
1 September 2015
*Corresponding author
norsiahami@uum.edu.my
Abstract
This study analyzes the causal relationship between sustainable manufacturing practice (SMP) and environmental sustainability
as well as determines the mediating effect of innovation performance (IP) on the relationship between SMP and environmental
sustainability. Adaptation from the changing business environment, manufacturing firms are facing great challenge on
producing more products with less resource consumption, pollution emitted and waste generated. Using structural equation
modeling, the survey data collected from 150 Malaysian manufacturing firms has been analyzed in this study. The empirical
results show that both types of SMP have a positive and significant impact on environmental sustainability with external SMP is
greater than internal SMP. However, there is no significant evidence to prove IP as a mediator for SMP -environmental
sustainability linkage. The findings of this paper have important implication in both theoretical and practical perspectives. While
provide better understanding of the phenomena by simultaneously analyzing a series of dependence relationships among SMP,
IP and environmental sustainability, these results could help managers to understand the types of practices that would improve
their environmental performance.
Keywords: Sustainable manufacturing, sustainable manufacturing practice, innovation performance, environmental
sustainability
© 2015 Penerbit UTM Press. All rights reserved
1.0 INTRODUCTION
Sustainability becomes a part of the national
agenda which is highlighted in the 11th Malaysia
Plan. The efforts towards environmental sustainability
dramatically widened the responsibilities of the
manufacturing firms in doing business. Besides
producing products for fulfilling economic demands
and needs, they need to become a driving force for
the creation of sustainable society by designing and
implementing sustainable practices that allow them
to eliminate or significantly reduced their
environmental impacts as well as they can produce
products that contribute to better environmental
performance in other sectors [1]. With the growing
global concerns in the issues of sustainability such as
scarcity of natural resources and rapid environmental
degradation, sustainable manufacturing (SM)
strategies have drawn attention. Various studies from
different countries were conducted to define
sustainability (including environmental sustainability)
and SM, and to identify the variables that contribute
to the achievement of environmental sustainability in
a manufacturing context.
Through a literature review, a series of sustainable
practices in manufacturing industries that possibly
contribute to the greater level of environmental
sustainability are identified such as cleaner
production, eco-efficiency, green supply chain
management, corporate social responsibility, closed-
58 N. Hami, M.R. Muhammad & Z. Ebrahim / Jurnal Teknologi (Sciences & Engineering) 77:4 (2015) 57-68
loop production and industrial ecology. While some
studies found a positive relationship between such
practices and environmental sustainability, others
have found no relationship at all. The mixed results
might be due to the differences in operationalizing
the variable (i.e. sustainable manufacturing practice)
across studies. Majority of the studies tend to focus on
the specific context of sustainable manufacturing
practice (SMP), either environmentally friendly
practices (also called green practices) or socially
responsible practices (also called corporate social
responsibility practices). Studies in the wider context
of SMP to cover both environmentally friendly and
socially responsible practices are very scarce in the
literature.
Another imperative indicative of the mixed results
of the previous studies is that, there are more
complex relationship between SMP and
environmental sustainability. Many of the past studies
focused on the
direct effect of SMP on environmental sustainability
but overlooked the importance of indirect effect in
that relationship. The statistical association between
SMP and environmental sustainability needs to be
explained. There are possibilities that the other
variables mediate the relationship between these
two variables. Since the significant relationships of
innovation performance (IP) with SMP and
environmental sustainability were found in some
previous studies [2,3,4], there is a possibility that IP
mediates the relationship between SMP and
environmental sustainability. Therefore, the lack of
studies in investigating whether the achievement of
firms in introducing a new or significantly improved
product, or a new or improved way in making
product, a new marketing method, or a new
organizational method in business practices,
workplace organization or external relations provides
a causal link between SMP and environmental
sustainability is an important research gap.
Considering the direct and indirect effects, the
main objectives of this study are to analyze the
causal relationship between SMP and environmental
sustainability as well as to analyze the mediating
effect of SMP on environmental sustainability through
IP by using primary data collected from Malaysian
manufacturing firms.
2.0 LITERATURE REVIEW AND HYPOTHESES
2.1 Sustainability and Sustainable Manufacturing
The concept of sustainability has emerged in the
1970’s when the issue of business ethics was debated
[5]. Sustainability is not a fixed concept but it evolves
as a consequence of adaptation to changing
circumstances. In response to the issues of global
inequality, resource distribution and global
population impacts, World Commission on
Environment and Development of the United Nations
(WCED) proposed the concept called sustainable
development (SD) in 1987 which is define as
development that meets the needs of the present
without compromising the ability of future
generations to meet their own needs. Although it is
quite broad, this definition is the most extensively
adopted to describe sustainability and SD in various
discipline of studies.
Sustainability is complex and multi-faceted which
recognizes the interdependence of the three pillars
(i.e. economic, environmental, and social) that
frequently referred to as the Triple Bottom Line (TBL).
The TBL approach suggests that apart from
concentrating on economic goals, organizations
necessitate to engage in activities that positively
affect the environment and social performance [6].
While economic sustainability refers to the extent to
which a firm improves operational and business
performance, social sustainability widen the
corporate responsibilities beyond the boundaries of
the firm and normally address the demands and
needs of other key stakeholders such as
governments, suppliers, customers, local communities
and non-government organizations [7,8]. With regard
to cover “green” issues from natural environment
conservation to energy consumption, environmental
sustainability refers to the ability of firms in reducing
the level of resource usage, pollution emitted and
waste generated [7,8]. Reduced the level of
resources consumption such as water, energy, non-
renewable resources and hazardous inputs as well as
the creation of wastes and polluting emissions are
indicators of environmental performance of a firm.
The three pillars of sustainability create a balance in
the organizations that makes their operations and
actions become sustainable.
Considering the wider context of sustainability, in
this study, SM is viewed as a broad notion which is
developed through the integration of sustainability
concepts into the manufacturing system with an aim
to achieve sustainability in industrial production.
2.2 Sustainable Manufacturing Practice
Since the last decades, the concept of
manufacturing has been evolved from the
substitution-based of traditional manufacturing to a
lean manufacturing which focus on waste reduction,
environmentally-benign of green manufacturing, and
sustainable manufacturing [9]. The growing concern
about the impact of manufacturing operations on
environmental and social performance has given rise
to a series of sustainable practices in manufacturing
industries, from the application of technology for the
treatment of pollution at the end of the pipe to more
integrated systems of production.
Generally, the development of sustainable
practices in manufacturing industries can be seen at
the three levels encompassing product, process and
system [10]. At the product level, the traditional 3R
concept (reduce, reuse, recycle), promoting the
adoption of green manufacturing, is expanded to a
59 N. Hami, M.R. Muhammad & Z. Ebrahim / Jurnal Teknologi (Sciences & Engineering) 77:4 (2015) 57-68
more sustainable 6R approach (reduce, reuse,
recycle, recover, redesign, remanufacture). The
emerging of new concept seems to enhance
potential effectiveness achieved in advancing SM.
The transformation from 3R to 6R allows for the
changing paradigm of single life cycle (open-loop
system) to multiple life cycles (closed-loop system). At
the process level, numerous efforts have been
made recently with an aim to attain sustainable
manufacturing processes. Firms bear a responsibility
to optimize their technological improvements and
process planning for reducing resource consumption,
waste generation and occupational hazards as well
as improving product life [9]. System level is the third
element that needs to be highlighted in explaining
the development of sustainable practices in
manufacturing industries. Transformation on the
orientation of sustainable practices can be seen in
recent decades, from a mere focus on
manufacturing operations and cooperation
between departments within a firm, sustainable
considerations have expanded exceeding the
conventional organizational boundaries to include
the entire supply chain and beyond the chain of
production. The need for firms to consider the
environmental impact of their activities beyond the
manufacturing facility to the entire product life cycle
or beyond the value system has laid the basis for a
range of proactive environmental initiatives and
business models such as green supply chain
management (GSCM), closed-loop production and
industrial ecology [1]. Meanwhile, the pressure for
firms to be accountable for their environmental and
social responsibilities has led to the concept and
practice of corporate social responsibility (CSR) [1].
Considering the evolution of sustainable practices in
manufacturing industries as well as the wider context
of sustainability to include economic, environmental
and social performance, sustainable manufacturing
practice (SMP) can be defined as a firm’s intra- and
inter-organizational practices that integrate
environmental, economic and social aspects into
operational and business activities. Differentiated
based on the orientation of sustainable thinking,
there are two types of SMP namely internal SMP and
external SMP. While internal SMP focuses on the
sustainable practices within a firm’s level such as
cleaner production, eco-efficiency and employee
relation, external SMP refers to the inter-
organizational practices within the value system and
beyond the chain of production to improve
economic, environmental and social sustainability
simultaneously such as supplier relation, customer
relation, community relation, industrial relation and
close-loop production.
2.3 SMP and Environmental Sustainability
Strong commitment to the social responsibility
particularly on the natural environment, reflected by
the implementation of proactive environmental
strategies such as internal SMP and external SMP,
provides significant benefits to the environment. A
number of studies, conducted in different countries
by using various types of statistical methods and
techniques, found that considering social and
environmental aspects into technical and
organizational activities undertaken by firms would
increase environmental performance
[11,12,13,14,15].
Analyzing the relationship between the three
dimensions of circular economy practices and
environmental performance among Chinese
manufacturing firms using structural equation
modeling (SEM) approach, Zhu et al. [13] found that
internal environmental management, eco-design
and corporate asset management and recovery
have direct effects on environmental performance.
Internal environmental management such as cleaner
production and eco-efficiency as well as corporate
asset management and recovery (i.e. closed loop
production) which aim for preventing or at least
minimizing pollution at source would improve
operational efficiency and environmental
sustainability compared to the traditional end-of-
pipe solutions by reducing the level of resource
usage, pollution emitted and waste generated.
In order to achieve greater environmental
sustainability, firms need to take a much broader
perspective on sustainable practices to go beyond
organizational boundaries. It appears that the best
result of environmental sustainability occurs when the
entire supply chain and industrial networks (i.e.
nearby organizations) are taken into considerations
instead of just focus on the firm itself. External SMP
such as environmental collaboration with supply
chain partners would lessen product and process
environmental burdens by reducing unnecessary
wastes and inefficiencies in performing activities
across the supply chain [16].
Extending the application of inter-organizational
environmental management cooperation beyond
the chain of production, a number of studies found
the positive relationship between external SMP (i.e.
industrial ecology) and improved environmental
performance. For example, Fichtner et al. [11]
discovered the favorable implications of inter-
company supply concepts in a network of five
energy-intensive industrial firms located in the area
near the Rhine Harbor in Karlsruhe and cooperation
between a German car manufacturer and its
disposal firm on economic and environmental
performance. Interestingly, they found that
noticeable improvements in terms of environmental
performance may attain by firms which had
adopted inter-organizational environmental
management compared to the optimal strategies
independently implemented by the individual firms
[11]. Conducting a case study on the application of
industrial ecology in Baogang Group, iron and steel
enterprise in Inner Monglia, Yongwei et al. [12]
supported this result by noting that Baogang Group
gains great achievement in energy-saving and
60 N. Hami, M.R. Muhammad & Z. Ebrahim / Jurnal Teknologi (Sciences & Engineering) 77:4 (2015) 57-68
emission reduction resulting from the inter-
organizational cooperation.
Based on the empirical evidences of the previous
studies pertaining to the significant relationship
between both internal and external SMP and
environmental sustainability, the following hypothesis
is proposed:
H1: SMP has a positive and significant impact on
environmental sustainability.
2.4 SMP, Innovation Performance and Environmental
Sustainability
Empirical evidence on the linkage between SMP and
environmental sustainability appears to be
inconclusive. While some studies found positive and
significant results, there are some other studies who
failed to prove the significant role of SMP on
predicting environmental sustainability [8,17]. The
mixed results might be due to the differences in
operationalizing the variables across studies.
Although several studies have investigated the
linkage between sustainable practices and
sustainability performance in a manufacturing firm,
the majority of the studies tend to focus on the
specific context of SMP, either green practices or
corporate social responsibility practices. Studies in
the broader context of SMP which include both
environmental friendly and socially responsible
practices are very scarce in the literature. Clearly,
operationalizing SMP in a wider context to include
economic, environmental and social aspects is
crucial to provide a clearer picture of the role of the
SMP in explaining the variability of environmental
sustainability of a firm.
In addition, insufficient statistical evidence to prove
significant causal relationship between SMP and
environmental sustainability indicates that there may
be a more complex relationship exists between these
two variables. When screened through the lens of
intra and inter-organizational collaboration within
and beyond the supply chain partners, the adoption
of SMP may lead to better innovation performance
(IP) of a firm that eventually would improve
environmental sustainability. IP thus can serve as a
mediator that explains the relationship between SMP
and environmental sustainability.
Implementing proactive environmental
management and social responsibility practices may
foster the development of innovation which forms
the basis for firm’s competitive advantage [18]. In
compliance with regulations and code of practice
set by various regulatory institutions, firms are
encouraged to implement sustainable practices in
their business operations [19,20]. Previous studies
have recognized the potential impact of such
regulations and standards on supporting and
promoting favorable innovation outcomes [21,22].
Responding to the current issues of sustainability and
increasing pressures exerted by various stakeholders
for being more responsible, the rules and standard of
practice become more stringent, stimulates the
considerable adoption of environmental and social
responsibility strategies, which in turn have a positive
effect on innovation performance [23]. Investigating
the major environmental risks through water pollution
disputes in Siaoli River, Tu and Yujung [24] argued
that current environmental standards, targeting the
traditional industrial pollutants, are too outdated to
effectively handle the high-technology pollution
problems. Although the electronics industries of high
technology have played an important role in driving
the global economy, manufacturing high-
technology products cause hundreds of chemicals
released and thousands of tons of waste water
generated per day. In this sense, SMP must be
improved continuously to be compatible as it may
have been outdated and less effective in addressing
the current problems associated with environmental
pollution and other sustainability issues. The
development of SMP to improve sustainability
performance is expected to increase R&D activities
as well as other innovative initiatives, thus leading to
improve IP of the organization.
In a different context, SMP implementation would
contribute to enhance IP through better intra- and
inter-organizational relationships [25,26]. Through SMP
which promote integration and collaboration with
various parties, organizationally relevant information,
knowledge, and expertise are spread and
exchanged among individual members or units
within and outside organization with accuracy and
efficiency. As found by Lin and Chen [27] from their
study of the relationships between internal and
external integrations, shared knowledge, innovation
capabilities and product competitive advantage
among 245 high technology firms in Taiwan, high
level of shared knowledge of internal capabilities,
customers and suppliers would create better
innovation capability. The transfer of knowledge from
external parties promotes the development of new
capabilities which may not be possible for a single
firm to achieve with their own resources [28].
Successful sharing of valuable information among
members within and outside organization could be
seen in various aspects that support innovation
success such as quick response to market changes
and technology advancements, and better
understanding of the needs of employees,
customers, suppliers, and society at large [8,29,30].
The role of innovation in promoting carbon
emissions reduction programs and mitigation of
climate change is generally acknowledged [31].
Recognizing innovation as valuable, rare, non-
substitutable and unique organizational resources,
the ability to successfully implement creative ideas
within an organization offers significant benefits for
gaining greater environmental sustainability.
Incorporating social responsibility and environmental
management principles when creating new or
improved products, production processes,
technologies and organizational systems, firms may
enhance environmental sustainability by reducing
the level of resource consumption, pollution emitted
61 N. Hami, M.R. Muhammad & Z. Ebrahim / Jurnal Teknologi (Sciences & Engineering) 77:4 (2015) 57-68
and waste generated. Based on their cause-effect
analysis between environmental performance and
changes on workplace organization, Longoni et al.
[32] provide statistical evidences indicating the
significant impact of organizational innovation on
environmental sustainability. Analyzing the effect of
eco-innovation types on firms’ ecological
performance using empirical data from 245 Chinese
firms, Dong et al. [3] found that end-of-pipe solutions,
product innovation, process innovation and
organizational innovation are significant
determinants of environmental performance with
process innovation as the strongest predictor.
Based on the extant arguments and empirical
results regarding a series of dependence
relationships among SMP, IP and environmental
sustainability, the following hypothesis is proposed:
H2: IP mediates the relationship between SMP and
environmental sustainability.
3.0 METHODOLOGY
3.1 Research Design
The population for this study consists of
manufacturing firms in Malaysia. Deriving from the
directory of Federation of Malaysian Manufacturers
(FMM), a total of 600 from 2,415 registered
manufacturing firms encompassing various industries
are randomly selected as a sample for this study [33].
Considering the issue of generalizability of the
findings, the simple random sampling procedure,
which assures that each firm has an equal chance of
being chosen as part of the sample within the
population, has been chosen in this study. Following
the Cochran [34] formula, 241 firms need to be
selected as a sample in order to represent the overall
population of 2,415 firms. However, the oversampling
approach has been applied in this study, resulting
the sample size increase by more than 145% to
account for undelivered mails and uncooperative
subjects.
The unit of analysis of this study is the individual in
which the data are gathered from each individual
firm and treating each respondent’s response as an
individual data source. In order to get valid and
accurate data, the need for choosing the right
respondent cannot be overemphasized. Considering
the level of knowledge, skills and experience with the
variables studied, the targeted respondent in this
study is personnel who holds managerial position in a
firm and involves in the operational activities.
3.2 Survey Instrument
A questionnaire survey was used to gather primary
data in this study. The questionnaire is structured into
four sections with 107 indicator variables. A five-point
scale, anchored by one for ‘strongly disagree’ and
five for ‘strongly agree’, is applied to measure the
degree of implementation of SMP within the firm. In
total, eight observed variables have been used to
measure SMP for both internal and external SMP.
Three observed variables (i.e. Int1 Cleaner
production, Int2 Eco-efficiency and Int3 Employee
relation) with 18 indicators are assigned to measure
internal SMP while external SMP is reflected in five
observed variables embracing the relations with
suppliers, customers, communities as well as closed-
loop production with 30 indicators. After reviewing
how performance is measured in different studies of
environmental sustainability, this study draw up a
scale that includes 7 indicators to access the
performance of firm in reducing the level of resource
usage, pollution emitted and waste generated in the
last three years that is considered as attributable to
the implementation of the SMP. The innovation
performance of firms normally is described in term of
the number of new products or the number of
patents. However, a broader perspective is deemed
to be more appropriate to the context of this study.
As a result, IP has been formulated into 24 indicators
in four observed variables that capture the extent to
which a firm successfully performs in product
innovation, process innovation, organizational
innovation, and marketing innovation in the last three
years. Again, a five-point scale, anchored by one for
‘strongly disagree’ and five for ‘strongly agree’ is
used to measure the firm’s performance in both
environmental sustainability and innovation.
The operationalization of SMP, environmental
sustainability and IP is based on the combination of
scales developed by previous researchers
[8,29,35,36]. However, because of the lack of
established scales, some self-administered indicators
have been undertaken for several observed
variables such as Ext5 Industrial relation and IP3
Organizational innovation. The indicators are
carefully developed based on the theoretical
definition that corresponds to the respective
observed variables. All of the observed variables and
indicators for SMP, environmental sustainability and
IP, as listed in Appendix A, were initially validated by
a panel of experts consisting of six academic
professors and senior lecturers, and two industry
professionals.
3.3 Response Analysis
Supplementing with cover letter and self-addressed,
stamp-attached envelope, a set of questionnaire
was initially mailed to 600 potential respondents. Out
of the total questionnaires sent, three were returned
as undeliverable, reducing the sampling frame to
597. A month later, a second round of questionnaire
was conducted to all non-respondents. After
screening the responses for extreme outliers and
incomplete survey forms, the survey yielded 150
usable responses, or a 25.13% response rate. Such
response rate is acceptable as greater than the
suggested cutoff of 20% [37].
62 N. Hami, M.R. Muhammad & Z. Ebrahim / Jurnal Teknologi (Sciences & Engineering) 77:4 (2015) 57-68
The responses were received from various
manufacturing industries, size of firms and
technological intensity. Most of respondents come
from four industries, encompassing electrical and
electronics (34.7%), transport equipment (19.3%),
chemical (16.0%), and metals (12.0%). The remaining
17.3% are from food products and beverages (7.3%),
machinery and equipment (4.7%), wood based
(3.3%) and textiles and apparel (2.7%). As expected,
the findings show that the majority of the responding
firms are large-sized (70.0%), while 17.3% and 12.0%
are medium and small organizations, respectively. In
the context of technological intensity, more than 40%
of the firms are classified as medium-high technology
(41.3%), whereas 28.0% are high technology, 17.3%
are medium-low technology and the remaining
13.3% being low technology.
In order to detect any potential non-response bias
that may happen when some of the targeted
respondents do not take part in the survey, the
independent groups t-test and chi-square test have
been performed in this study. Following the
recommendation by Armstrong and Overton [38]
and Lambert and Harrington [39], the 150
respondents are differentiated into two groups based
on their response time, i.e. early respondents and late
respondents. It is assumed that the late return of
surveys is similar to that of non-respondents. As a
result, the 61 responses received from the first round
of questionnaires are assigned into the former group
while the 89 responses obtained from the second
round of questionnaires reflect the latter group. The
findings of the T-test indicate that there are no
statistically significant differences between early
respondents and late respondents in each indicator
of SMP, environmental sustainability and IP, except
for the indicator of S2.2 at the 0.05 level. Similarly, the
chi-square analysis shows no significant differences
between those two groups in term of industrial
classification, size of the firm and technological
intensity. The potential of common method bias
(CMB) is the other issue that needs to be assessed in
adopting survey-based method. In this study,
Harman’s single factor test has been performed to
detect the presence of the CMB. However, the result
is not significant, confirming that CMB is not a critical
concern in this study. Finally, having confirmed the
quality of the responses through some series of
testing, the full data set of 150 responses is valid and
usable for subsequent analysis.
4.0 DATA ANALYSIS
4.1 Measurement Model Validation
The hypothesized models developed for the purpose
of this study have been tested using the SEM
approach. Following the validation guidelines for
reflective measurement model suggested by Urbach
and Ahlemann [40] and Hair et al. [41], the
measurement model of this study has been tested for
uni-dimensionality, indicator reliability, internal
consistency reliability, convergent validity and
discriminant validity. The test for uni-dimensionality is
performed to verify that a set of indicator variables,
are strongly associated with each other and
represent a single construct or observed variable.
Since PLS-SEM cannot measure the uni-dimensionality
directly, the confirmatory factor analysis (CFA) in SPSS
Statistical 19 has been applied in this study. The results
found that all set of indicator variables for each
construct of SMP, EnS and IP loaded on only one
factor except Int2 Eco-efficiency. Then, the result of
Int2 Eco-efficiency is further analyzed to check for
the indicator that has a low correlation with other
indicators and a low factor loading that provides
candidate for removal in the second run of CFA. As a
result, the indicator variable of Int2.1 was removed
from the second run of the analysis and the result is
uni-factorial. Having confirmed the uni-
dimensionality, the remaining indicators have been
tested for further validation analyses in SmartPLS. The
results are tabulated in Table 1.
Table 1 Measurement model results
Construct
Loading
CR
AVE
1st order
model
2nd
order
model
Internal SMP
Cleaner production
Eco-efficiency
Employee relation
0.55 -
0.85
0.61 -
0.88
0.72 -
0.88
0.85
0.86
0.84
0.89
0.89
0.89
0.92
0.72
0.58
0.62
0.67
External SMP
Supplier relation
Customer relation
Community relation
Closed-loop
production
Industrial relation
0.78 -
0.89
0.77 -
0.85
0.72 -
0.90
0.77 -
0.89
0.69 -
0.83
0.80
0.76
0.85
0.84
0.75
0.90
0.94
0.92
0.92
0.93
0.89
0.64
0.73
0.65
0.67
0.67
0.58
Environmental
sustainability
0.82 -
0.90
0.95
0.75
Product innovation
Process innovation
Organizational
innovation
Marketing innovation
0.78 -
0.90
0.82 -
0.89
0.83 -
0.90
0.79 -
0.88
0.93
0.95
0.95
0.94
0.71
0.74
0.75
0.73
a See Appendix A for indicator or item description
CR=Composite reliability; AVE=Average variance
extracted
63 N. Hami, M.R. Muhammad & Z. Ebrahim / Jurnal Teknologi (Sciences & Engineering) 77:4 (2015) 57-68
The indicator reliability refers to the extent to which
the indicators have consistency in measuring the
corresponding construct. Factor loadings have been
applied in assessing the indicator reliability in this
study. Referring to Table 1, all of the factor loadings in
both first- and second-order model are well above
the minimum threshold value of 0.50 [42], confirming
the indicator reliability of each construct in the
measurement model.
Composite reliability (CR) has been analyzed for all
constructs of SMP, environmental sustainability and IP
to determine the internal consistency reliability. As
presented in Table 1, the values of CR are ranging
from 0.89 to 0.95, indicating the high internal
consistency reliability of the thirteen constructs in the
first-order model and eight constructs in the second-
order model [40,41].
Convergent validity assesses the extent to which
the indicator variables reflecting a construct
converge in comparison to the indicators measuring
other constructs. It examines whether a particular
indicator exactly measures the designated construct.
In this study, the average variance extracted (AVE)
value has been used to ascertain convergent
validity. All AVE estimates shown in Table 1 are well
above the minimum required level of 0.50 [40,41],
thus proving the convergent validity of each
construct in the measurement model.
Following the Fornell-larcker criterion procedure for
establishing discriminant validity, the AVE of each
construct is compared with the inter-construct
squared correlations associated with that construct.
Discriminant validity refers to the extent to which a
construct is truly different from another constructs. In
contrast with convergent validity, discriminant validity
ensures that a construct is unique and its indicators
do not measure other construct unintentionally. The
results presented in Table 2 through Table 4
confirming the discriminant validity for all constructs
since their AVEs are greater than the corresponding
inter-construct squared correlations [40,41].
Table 2 Comparison of the AVE and squared correlation
between constructs for SMP at first-order model a
Int1
Int2
Int3
Ext1
Ext2
Ext3
Ext4
Ext5
Int1
0.58
Int2
0.44
0.62
Int3
0.27
0.32
0.67
Ext1
0.20
0.36
0.17
0.73
Ext2
0.45
0.54
0.35
0.23
0.65
Ext3
0.25
0.33
0.24
0.32
0.35
0.67
Ext4
0.21
0.38
0.23
0.31
0.32
0.37
0.67
Ext5
0.09
0.18
0.18
0.30
0.14
0.35
0.34
0.58
a Diagonal elements are Average variance extracted (AVE)
of each construct; Off diagonal elements are the squared
correlation between constructs
Int1=Cleaner production; Int2=Eco-efficiency; Int3=Employee
relation; Ext1=Supplier relation; Ext2=Customer relation;
Ext3=Community relation; Ext4=Closed-loop production;
Ext5=Industrial relation
Table 3 Comparison of the AVE and squared correlation
between constructs for SMP at second-order model
Internal SMP
External SMP
Internal SMP
0.72
External SMP
0.58
0.64
a Diagonal elements are Average variance extracted (AVE)
of each construct; Off diagonal elements are the squared
correlation between constructs
Table 4 Comparison of the AVE and squared correlation
between constructs for IP and environmental sustainability
IP1
IP2
IP3
IP4
EnS
IP1 Product innovation
0.7
1
IP2 Process innovation
0.5
0
0.7
4
IP3 Organizational
innovation
0.3
9
0.5
0
0.7
5
IP4 Marketing innovation
0.3
6
0.3
8
0.4
4
0.7
3
EnS Environmental
sustainability
0.1
7
0.1
9
0.2
4
0.1
3
0.7
5
a Diagonal elements are Average variance extracted (AVE)
of each construct; Off diagonal elements are the squared
correlation between constructs
Based on the above discussions, the five forms of
validation (i.e. unidimensionality, indicator reliability,
internal consistency reliability, convergent validity,
and discriminant validity) verify that all sets of
indicator variables for each construct of SMP,
environmental sustainability and IP are statistically
strong. It is proven that, while they are internally
consistent in their measurements, those sets of
indicators truly represent the theoretical constructs of
SMP, environmental sustainability and IP. Thus, the
validated data sets of SMP, environmental
sustainability and IP, consist of 78 indicator variables
of 150 responses, are worthy for further structural
model analysis with regard to meeting specified
objectives in this study.
4.2 Structural Model Assessment
Once the validation of measurement model in this
study is verified, the proposed structural models
indicating the interrelationships among SMP,
environmental sustainability and IP are assessed. The
assessment is based on three criteria namely the
coefficient of determination (R2), path coefficients
(β) and predictive relevance (Q2). The results of
structural model analysis are presented in Table 5
and Table 6.
64 N. Hami, M.R. Muhammad & Z. Ebrahim / Jurnal Teknologi (Sciences & Engineering) 77:4 (2015) 57-68
Table 5 Structural model of internal SMP, IP and
environmental sustainability results
Structural path
β a
R2 b
Q2 c
Internal SMP→Environmental
sustainability (path c)
0.25**
0.41
0.30
Internal SMP→IP (path a)
Outcome variable:
Product innovation
Process innovation
Organizational
innovation
Marketing
innovation
0.10
0.21
0.19*
0.16*
0.27
0.31
0.40
0.33
0.19
0.23
0.29
0.24
IP→Environmental sustainability (path
b)
Causal variable: Product innovation
Process innovation
Organizational
innovation
Marketing
innovation
0.11
0.05
0.15*
-0.13
0.41
0.30
Internal SMP→Environmental
sustainability (path )
0.22**
0.41
0.30
a * p < 0.1, ** p < 0.05, ** p < 0.01
b R2 values represents the explained variance for the
endogenous variables.
c Q2 > 0 indicates that the model has predictive relevance,
Q2 < 0 implies that the model is lacking predictive
relevance.
Table 6 Structural model of external SMP, IP and
environmental sustainability results
Structural path
β a
R2 b
Q2 c
Internal SMP→Environmental
sustainability (path c)
0.40***
0.41
0.30
Internal SMP→IP (path a)
Outcome variable:
Product innovation
Process innovation
Organizational
innovation
Marketing
innovation
0.44***
0.38***
0.47***
0.44***
0.27
0.31
0.40
0.33
0.19
0.23
0.29
0.24
IP→Environmental sustainability (path
b)
Causal variable: Product innovation
Process innovation
Organizational
innovation
Marketing
innovation
0.11
0.05
0.15*
-0.13
0.41
0.30
Internal SMP→Environmental
sustainability (path )
0.32***
0.41
0.30
a * p < 0.1, ** p < 0.05, ** p < 0.01
b R2 values represents the explained variance for the
endogenous variables.
c Q2 > 0 indicates that the model has predictive relevance,
Q2 < 0 implies that the model is lacking predictive
relevance.
As presented in Table 5 and Table 6, environmental
sustainability has been predicted quite well by
internal SMP, external SMP and IP, with R2 value of
0.41. Exceeding the recommended minimum value
of 0.1 [43], this value indicates that SMP (i.e. internal
SMP and external SMP) and IP explain almost half of
the variance of environmental sustainability,
demonstrating the considerable explanatory power
of the proposed models. The significance level of
path coefficients (β) in this study is determined by
using re-sampling bootstrap procedure with 1000
subsamples. Meanwhile, the positive values of Q2 in
all structural models in this study demonstrate good
predictive relevance of SMP and IP on environmental
sustainability.
Hypothesis 1 proposes that SMP has a positive and
significant impact on environmental sustainability.
This hypothesis attempts to test whether greater level
of implementation of both types of SMP (i.e. internal
SMP and external SMP) would lead to achieving
better performance on environmental sustainability.
As presented in Table 5 and Table 6, internal SMP (c =
0.25, p < 0.05) and external SMP (c = 0.40, p < 0.01)
have significant predictive power on environmental
sustainability. Since the total effect of both internal
SMP and external SMP on environmental sustainability
is positive and significant, the first hypothesis in this
study is supported.
Hypothesis 2 suggests that IP mediate the
relationship between SMP and environmental
sustainability. This hypothesis attempts to test whether
the four types of IP (i.e product innovation, process
innovation, organizational innovation and marketing
innovation) have a significant mediating effect on
the relationship between both types of SMP (i.e.
internal SMP and external SMP) and environmental
sustainability. Referring to Table 5, the results show
that internal SMP has significant effect only on the
three hypothesized mediating variables, i.e. process
innovation (a = 0.21, p < 0.05), organizational
innovation (a = 0.19, p < 0.1) and marketing
innovation (a = 0.16, p < 0.1). While, external SMP
significantly predicts all of the four types of IP, i.e.
product innovation (a = 0.44, p < 0.01), process
innovation (a = 0.38, p < 0.01), organizational
innovation (a = 0.47, p < 0.01) and marketing
innovation (a = 0.44, p < 0.01), as displayed in Table
6. However, when controlling the SMP, organizational
innovation is the single hypothesized mediating
variable which significantly predicts environmental
sustainability with b = 0.15, p < 0.1. The estimated
direct effect of internal SMP and external SMP on
environmental sustainability is = 0.22, p < 0.05 and
= 0.32, p < 0.01, respectively. The indirect effect (ab)
of internal SMP and external SMP on environmental
sustainability through organizational innovation is 0.03
and 0.07, respectively. For 95% bootstrapped
confidence intervals, the indirect effect of each type
of SMP on environmental sustainability through all
types of IP are include zero and thus are not
statistically significant. Accordingly, the second
hypothesis in this study, proposing the significant
mediation effect of IP on the causal relation of SMP
on environmental sustainability is rejected.
65 N. Hami, M.R. Muhammad & Z. Ebrahim / Jurnal Teknologi (Sciences & Engineering) 77:4 (2015) 57-68
5.0 DISCUSSION AND CONCLUSION
Environmental sustainability refers to the ability of
firms in reducing the level of resource usage,
pollution emitted and waste generated.
Theoretically, this study suggests that the greater the
level of implementation of both types of SMP (i.e.
internal SMP and external SMP) in a manufacturing
firm, the greater the achievement of environmental
sustainability to be achieved by the firm. The
empirical results found in this study prove the positive
impact of both internal SMP and external SMP on
environmental sustainability as proposed in
hypothesis 1. Considering a wider context of SMP to
include environmentally friendly and socially
responsible practices, the results of this study extend
the findings by previous researchers who confirmed
the significant impact of the specific context of
sustainable practices, i.e. green practices, in
improving environmental performance [13,14,15].
Implementing cleaner production and eco-
efficiency strategies in daily operations as well as
emphasizing on closed-loop production and
industrial ecology would protect the natural
environment by generating less waste, fewer
resources and energy consumption, and less
environmental pollution. While improving resource
productivity by identifying and eliminating waste
would lower the costs of productions, it is also directly
leads to reduce resource usage, pollution emitted
and waste generated. Pursuing economic and
environmental excellences, firm should move from
focusing on traditional end-of-pipe solutions to
aggressively concentrate on pollution prevention
practices (i.e. cleaner production, eco-efficiency,
closed-loop production and industrial ecology).
In order to achieve greater environmental
sustainability, firms need to take a much broader
perspective on sustainable practices to go beyond
the organizational boundaries. Supporting the finding
by Fichtner et al. [11] who conducted case studies
on industrial symbiosis, the results of this study reveal
that the best result of environmental sustainability
occurs when the entire supply chain, nearby
organizations and local communities are taken into
considerations instead of just focus on the firm itself.
The impact of external SMP on improving
environmental sustainability is greater than internal
SMP. External SMP such as environmental
collaboration with supply chain partners would
decrease product and process environmental
burdens by reducing unnecessary wastes and
inefficiencies in conducting activities across the
supply chain [16]. Extending the application of inter-
organizational environmental management
cooperation beyond the chain of production, inter-
organizational practices such as sharing inputs,
outputs and by-products among nearby and
synergistic firms would yield environmental
sustainability. The result of this study extends the
finding by Yongwei et al. [12] who discovered inter-
organizational cooperation as a source of energy-
saving and emission reduction when conducting a
case study on the application of industrial ecology in
Baogang Group.
With regard to the mediation analyses,
theoretically, it is suggested that having better
performance on product, process, organizational
and marketing innovations resulting from the
adoption of SMP would lead to improving
environmental sustainability. However, the results of
this study conclude that there is no significant
mediated effect of SMP on environmental
sustainability through all of the four types of IP. A
plausible reason for the insignificant findings is that
although the range and quality of products,
technologies, manufacturing processes, marketing
strategies as well as organizational method in
business practices, workplace organization or
external relations may have been continuously
improved but they still less effective in addressing the
current problems associated with environmental
issues. For instance, while the electronics industries of
high technology have played an important role in
economic development, manufacturing high-
technology products cause hundreds of chemicals
released and thousands of tons of waste water
generated per day [24]. Chemical compounds
released from the manufacturing firms may have
great impacts on the community and environmental
health. Complying with the current environmental
standards which target traditional industrial
pollutants, the application of new production
processes may still not be able to effectively handle
the high-technology pollution problems [24].
The findings of this study offer a number of
significant contributions and implications that are
beneficial for both academicians and practitioners.
While the study contributes to the body of
knowledge by providing statistical evidences relating
to a series of dependence relationships related to
the three different variables encompassing SMP, IP
and environmental sustainability, the ability to
simultaneously examine these relationships is
valuable for better understanding of the
phenomena. The results of this study empirically verify
the positive effect of both types of SMP on
environmental sustainability with external SMP is
greater than internal SMP. In addition, there is no
convincing evidence that IP is a mediator of the
relationship between SMP and environmental
sustainability. There may be other factors that explain
the impacts of SMP on environmental sustainability.
Through rigorous testing processes, this study
develops valid and reliable model for measuring the
extent of SMP adopted as well as organizational
performance achieved in the context of innovation
and environmental sustainability at a manufacturing
firm level. This measurement model may help
industrial practitioners in understanding the diverse
aspects of SMP implementation, identifying strengths
and weaknesses of their current practices and setting
the indicators of both innovation and environmental
66 N. Hami, M.R. Muhammad & Z. Ebrahim / Jurnal Teknologi (Sciences & Engineering) 77:4 (2015) 57-68
performance. In addition, the measurement model
which has been developed in this study is useful for
other researchers. They could extend the scope of
application of this measurement model to other
environments such as research in different countries
and further development of research in the area of
sustainable manufacturing and innovation
management.
Acknowledgement
We would like to express our gratitude to the Ministry
of Education Malaysia and Universiti Utara Malaysia
for the research funding, to Universiti Teknikal
Malaysia Melaka for facilitating the research and to
everyone who has contributed to the completion of
this study.
References
[1] OECD. 2010. Eco-innovation in Industry: Enabling Green
Growth, OECD Publishing.
[2] K.H. Lee, J.W. Kim. 2011. Integrating Suppliers into Green
Product Innovation Development: An Empirical Case
Study in the Semiconductor Industry. Bus. Stra. Env. 20: 527.
[3] Y. Dong, X. Wang, J. Jin, L. Shi. 2013. Research on Effects
of Eco-innovation Types and Regulations on Firms'
Ecological Performance: Empirical Evidence from China.
J. of Eng. and Tech. Mgt. 19.
[4] C.C.J. Cheng, C.I. Yang, C. Sheu. 2014. The Link between
Eco-innovation and Business Performance. A Taiwanese
Industry Context. J. of Cleaner Prod. 64: 81.
[5] G.M. Hall, J. Howe. 2010. Sustainability of the Chemical
Manufacturing Industry: Towards a New Paradigm? Edu.
for Chemical Engineer 5: 100.
[6] V. Dao, I. Langella, J. Carbo. 2011. From Green to
Sustainability: Information Technology and an Integrated
Sustainability Framework. J. of Strategic Info. Syst. 20: 63.
[7] N. Hami. 2015. Sustainable Manufacturing Practice and
Sustainability Performance Mediated by Innovation
Performance. Sintok: UUM.
[8] M.G. Yang. 2013. Developing a Focal Firm's Sustainable
Supply Chain Framework: Drivers, Orientation, Practices
and Performance Outcomes. University of Toledo.
[9] I.S. Jawahir, O. Dillon Jr. 2007. Sustainable Manufacturing
Processes: New Challenges for Developing Predictive
Models and Optimization Techniques. In 1st Int. Conf. on
Sustainable Mfg. Montreal, Canada.
[10] A.D. Jayal, F. Badurdeen, O.W. Dillon Jr., I.S. Jawahir. 2010.
Sustainable Manufacturing: Modeling and Optimization
Challenges at the Product, Process and System Levels.
CIRP J. of Mfg. Sci. and Tech. 2: 144.
[11] W. Fichtner, I. Tietze-Stockinger, M. Frank, O. Rentz. 2005.
Barriers of Interorganizational Environmental
Management: Two Case Studies on Industrial Symbiosis.
Prog. in Ind. Ecology - An Int. J. 2: 73.
[12] D. Yongwei, Z. Pu, R. Jie. 2011. Analysis of Energy Efficiency
in the Large Enterprises from an Industrial Ecology
Perspective: Case Study from Baogang Group. Energy
Procedia, 5: 1237.
[13] Q. Zhu, Y. Geng, K.H. Lai. 2011. Environmental Supply
Chain Cooperation and Its Effect on the Circular
Economy Practice-Performance Relationship among
Chinese Manufacturers. J. of Ind. Ecology, 15: 405.
[14] B. Sezen, S.Y.Cankaya. 2013. Effects of Green
Manufacturing and Eco-Innovation on Sustainability
Performance. Procedia – Soc. and Behavioral Sci., 99: 154.
[15] Y. Li. 2014. Environmental Innovation Practices and
Performance: Moderating Effect of Resource
Commitment. J. of Cleaner Prod. 66: 450.
[16] S. Seuring, M. Muller. 2008. From a Literature Review to a
Conceptual Framework for Sustainable Supply Chain
Management. J. of Cleaner Prod. 16: 1699.
[17] W.S. Ashton. 2011. Managing Performance Expectations
of Industrial Symbiosis. Bus. Strategy and the Env. 20: 297.
[18] L. Kuo, S.K. Huang, Y.C.J. Wu. 2010. Operational Efficiency
Integrating the Evaluation of Environmental Investment:
The Case of Japan. Mgt. Decision. 48: 1596.
[19] T.K. ElTayeb, S. Zailani, K. Jayaraman. 2010. The
Examination on the Drivers for Green Purchasing Adoption
among EMS 14001 Certified Companies in Malaysia. J. of
Mfg Technology Mgt. 21: 206.
[20] L.C. Giunipero, R.E. Hooker, D. Denslow. 2012. Purchasing
and Supply Management Sustainability: Drivers and
Barriers. J. of Purchasing and Supply Mgt. 18: 258.
[21] K. Rennings, C. Rammer. 2011. The Impact of Regulation-
Driven Environmental Innovation on Innovation Success
and Firm Performance. Ind. and Innov. 18: 255.
[22] J. Doran, G. Ryan. 2012. Regulation and Firm Perception,
Eco-Innovation and Firm Performance. European J. of
Innov. Mgt. 15: 421.
[23] Y. Eiadat, A. Kelly, F. Roche, H. Eyadat. 2008. Green and
Competitive? An Empirical Test of the Mediating Role of
Environmental Innovation Strategy. J. of World Bus. 43:
131.
[24] W. Tu, L. Yujung. 2009. Ineffective Environmental Laws in
Regulating Electronic Manufacturing Pollution: Examining
Water Pollution Disputes in Taiwan. In IEEE Int. Symp. on
Sustainable Syst. and Tech. Phoenix, AZ.
[25] D. Cetindamar, G. Ulusoy. 2008. Innovation Performance
and Partnerships in Manufacturing Firms in Turkey. J. of
Mfg. Tech. Mgt. 19: 332.
[26] Y.T.H. Chiu. 2008. How Network Competence and
Network Location Influence Innovation Performance. J. of
Bus. & Ind. Mktg. 24: 46.
[27] M.J.J. Lin, C.J. Chen. 2008. Integration and Knowledge
Sharing: Transforming to Long-term Competitive
Advantage. International J. of Org. Analysis. 16: 83.
[28] A. Idris, L.S. Tey. 2011. Exploring the Motives and
Determinants of Innovation Performance of Malaysian
Offshore International Joint Ventures. Mgt. Decision. 49:
1623.
[29] A.Y.L. Chong, F.T.S. Chan, K.B. Ooi, J.J. Sim. 2011. Can
Malaysian Firms Improve Organizational/Innovation
Performance via SCM? Ind. Mgt. & Data Syst. 111: 410.
[30] S. Petrovic-Lazarevic, A. Sohal, I. Baihaqi. 2007. Supply
Chain Management Practices and Supply Chain
Performance in the Australian Manufacturing Industry.
Working paper series 21/07 Monash University.
[31] V.A. Bakhtina. 2011. Innovation and Its Potential in the
Context of the Ecological Component of Sustainable
Development. Sustainability Accounting, Mgt. and Policy
J., 2: 248.
[32] A. Longoni, R. Golini, R. Cagliano. 2014. The Role of New
Forms of Work Organization in Developing Sustainability
Strategies in Operations. Int. J. of Prod. Econ. 147:147.
[33] FMM. 2013. Malaysian Industries: FMM Directory 2013. 44th
ed. Kuala Lumpur: Federation of Malaysian
Manufacturers.
[34] W.G. Cochran. 1977. Sampling Techniques. 3rd ed. New
York: John Wiley & Sons.
[35] K.C. Shang, C.S. Lu, S. Li. 2010. A Taxonomy of Green
Supply Chain Management Capability among
Electronics-related Manufacturing Firms in Taiwan. J. of
Env. Mgt. 91: 1218.
[36] I.S. Mijatovic, D. Stokic. 2009. The Influence of Internal and
External Codes on CSR Practice: The Case of Companies
Operating in Serbia. J. of Bus. Ethics. 94: 533.
[37] D. Ojha, R.A. Gokhale. 2009. Logistical Business Continuity
Planning: Scale Development and Validation. Int. J. of
Log. Mgt. 20: 342.
67 N. Hami, M.R. Muhammad & Z. Ebrahim / Jurnal Teknologi (Sciences & Engineering) 77:4 (2015) 57-68
[38] J.S. Armstrong, T.S. Overton. 1977. Estimating Nonresponse
Bias in Mail Surveys. J. of Mktg. Research, 14: 396.
[39] D.M. Lambert, T.C. Harrington. 1990. Measuring
Nonresponse Bias in Customer Service Mail Surveys. J. of
Bus. Log. 11: 5.
[40] N. Urbach, F. Ahlemann. 2010. Structural Equation
Modeling in Information Systems Research Using Partial
Least Squares. Journal of Info. Tech. - Theory and App. 11:
5.
[41] J.F. Hair, G.T.M. Hult, C.M. Ringle, M. Sarstedt. 2014. A
Primer on Partial Least Squares Structural Equation
Modeling (PLS-SEM). Los Angeles: Sage Publication Inc.
[42] J.F. Hair, W.C. Black, B.J. Babin, R.E. Anderson, R.L. Tatham.
2006. Multivariate Data Analysis, 6th ed., New Jersey:
Pearson Prentice Hall.
[43] R.F. Falk, N.B. Miller. 1992. A Primer for Soft Modelling. Ohio:
The University of Akron.
Appendix A. Scale And Indicators
A.1. Internal SMP
Indicate the extent to which you agree with the following
statements as they relate to current practice in your
organization on a scale from one for strongly disagree to
five for strongly agree.
Dimension 1: Int1 Cleaner Production
Int1.1
Int1.2
Int1.3
Int1.4
Int1.5
Int1.6
Substitution of non-environmental friendly materials
Optimization of manufacturing processes to
reduce solid waste and emissions
Process design focused on reducing energy and
natural resources consumption in operations
Product design focused on reducing energy and
materials consumption
Acquisition of clean technology/equipment
Good housekeeping practices
Dimension 2: Int2 Eco-efficiency
Int2.1
Int2.2
Int2.3
Int2.4
Int2.5
Int2.6
Reuse of products/components
Recycling of materials internal to the company
Cross-functional cooperation for environmental
improvements
Total quality environmental management is in
place
Environmental compliance and auditing programs
are in place
The company’s efforts in relation to the
environmental matters have exceeded the
requirements of the relevant regulations
Dimension 3: Int3 Employee Relation
Int3.1
Int3.2
Int3.3
Int3.4
Int3.5
Int3.6
Guaranteed observation of industry safety
regulations
Fair payment of employees
Care for employee’s personal development
Supporting work-life balance
Involving employees into making important
decisions
Cooperation with unions and labour
representatives
A.2 External SMP
Indicate the extent to which you agree with the following
statements as they relate to current practice in your
organization on a scale from one for strongly disagree to
five for strongly agree.
Dimension 1: Ext1 Supplier Relation
Ext1.1
Ext1.2
Ext1.3
Ext1.4
Ext1.5
Ext1.6
Choice of suppliers by environmental criteria
Guiding suppliers to set up their own environmental
programs
Bringing together suppliers in the same industry to
share their know-how and problems
Informing suppliers about the benefits of cleaner
production and technologies
Urging suppliers to take environmental actions
Sending internal auditors to appraise
environmental performance of suppliers
Dimension 2: Ext2 Customer Relation
Ext2.1
Ext2.2
Ext2.3
Ext2.4
Ext2.5
Ext2.6
Environmental friendly waste management
Environmental improvement of packaging
Eco labeling of products
Providing credible information about product
biography
Integration of customer feedback into business
activity
Prevention of products causing danger for
customers
Dimension 3: Ext3 Community Relation
Ext3.1
Ext3.2
Ext3.3
Ext3.4
Ext3.5
Ext3.6
Active involvement in the creation of better
general conditions in local community
Cooperation with third party (e.g., public
authorities, scientific institutions, NGOs) towards
environmental protection
Continuous dialogue with municipalities to know
the most important problems of the local
community
Providing information about corporate social
responsibility (CSR) projects and expected benefits
Encouraging employees to get involved in
charitable projects
Regularly providing donation or sponsorship
Dimension 4: Ext 4 Closed-loop Production
Ext4.1
Ext4.2
Ext4.3
Ext4.4
Ext4.5
Ext4.6
Increase the product’s useful life
Design the product to accommodate multiple
future uses/application
Design the product for easy material recovery
Ensure that infrastructures for product recovery
exist
Establish recycling procedures
Establish remanufacturing procedures
Dimension 5: Ext5 Industrial Relation
Ext5.1
Ext5.2
Ext5.3
Ext5.4
Ext5.5
Ext5.6
Using waste or by-products of other industrial firms
as input materials
Exchange of waste or by-products with other
industrial firms
Share in the management of utilities (e.g., energy,
water, waste treatment) with other industrial firms
Share knowledge (e.g., technological, managerial,
environmental) with other industrial firms
Share ancillary services (e.g., transportation,
landscaping, waste collection) with other industrial
firms
Cooperate with local communities towards
environmental protection
A.3. Innovation Performance
Indicate the extent to which you agree with the following
statements as they relate to innovation performance of
your organization in the last three years on a scale from one
for strongly disagree to five for strongly agree.
68 N. Hami, M.R. Muhammad & Z. Ebrahim / Jurnal Teknologi (Sciences & Engineering) 77:4 (2015) 57-68
Dimension 1: IP1 Product Innovation
IP1.1
IP1.2
IP1.3
IP1.4
IP1.5
IP1.6
Increased number of new products introduced to
the market
Increased number of new products that are first-to-
market (early market entrants)
Use the latest technology for new product
development
Increased speed of new product development
Reduced cost of new product development
Able to produce greater level of newness (novelty)
of new products
Dimension 2: IP2 Process Innovation
IP2.1
IP2.2
IP2.3
IP2.4
Increased technological competitiveness
Use up-to-date technology in manufacturing
processes
Increased speed of adoption of the latest
technological innovations in manufacturing process
Increased the number of new production methods
IP2.5
IP2.6
introduced
Able to change rapidly in manufacturing processes
Able to change rapidly in manufacturing
techniques
Dimension 3: IP3 Organizational Innovation
IP3.1
IP3.2
IP3.3
IP3.4
IP3.5
IP3.6
Better knowledge management system
Increased organizational flexibility
Stronger external relations
Increased speed of adoption of new
organizational methods
Increased the number of new organizational
systems introduced
Apply up-to-date organizational methods
Dimension 4: IP4 Marketing Innovation
IP4.1
IP4.2
IP4.3
IP4.4
IP4.5
IP4.6
New products often take us up against new
competitors
Increased the number of new marketing
methods/approaches
Products’ most recent marketing programme is
revolutionary in the market compared with
competitors
Higher success rate in new product launch
compared with competitors
Increased the number of new market entry
Often at the cutting edge of technology in new
product introductions
A.4. Environmental Sustainability
Indicate the extent to which you agree with the following
statements as they relate to both operational and business
performance of your organization in the last three years on
a scale from one for strongly disagree to five for strongly
agree.
ES1
ES2
ES3
ES4
ES5
ES6
ES7
Reduced water usage
Reduced energy consumption
Reduced non-renewable resources usage
Reduced hazardous inputs usage
Reduced solid waste
Reduced waste water emissions
Reduced emissions of polluting gases
