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Citation: Alsulamy, S.; Dawood, S.;
Rafik, M.; Mansour, M. Industrial
Sectors’ Perceptions about the
Benefits of Implementing ISO 14001
Standard: MANOVA and
Discriminant Analysis Approach.
Sustainability 2022,14, 5025. https://
doi.org/10.3390/su14095025
Academic Editors: Siu-Kit
(Eddie) Lau, Abel Tablada,
Zdravko Trivic, Vesna Kosori´c,
Miljana Horvat, Milena Vukmirovi´c,
Silvia Domingo-Irigoyen,
Marija Todorovi´c, Jérôme H. Kaempf,
Kosa Goli´c and Ana Peric
Received: 17 March 2022
Accepted: 20 April 2022
Published: 22 April 2022
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4.0/).
sustainability
Article
Industrial Sectors’ Perceptions about the Benefits of
Implementing ISO 14001 Standard: MANOVA and
Discriminant Analysis Approach
Saleh Alsulamy 1, Shaik Dawood 2, Mohamed Rafik 2and Mohamed Mansour 2, 3, *
1Architecture and Planning Engineering Department, College of Engineering, King Khalid University,
Abha 61421, Saudi Arabia; s.alsulamy@kku.edu.sa
2Industrial Engineering Department, College of Engineering, King Khalid University,
Abha 61421, Saudi Arabia; shdawood@kku.edu.sa (S.D.); mrnoor@kku.edu.sa (M.R.)
3Industrial Engineering Department, College of Engineering, Zagazig University, Zagazig 44519, Egypt
*Correspondence: momansor@kku.edu.sa; Tel.: +966-54-575-0250
Abstract:
The most frequent drawback of ISO 14001 observed in existing studies relates to the cost of
certification and implementation process. This drawback requires scaling the benefits of adopting the
standard to assign organizations limited resources based on each benefit scale. This paper reports
the first research results that scale the benefits of adopting the standard. A quantitative method was
adopted, where data were collected using a questionnaire survey. A total of
120 respondents
were
recruited from organizations operating in six industrial sectors to take part in the study. MANOVA
and discriminant analysis methodologies were used to analyze the 14 most cited benefits in the
literature on adopting the standard. A novel feature of our approach is the comprehensive statistical
analysis of the collected data, which yields robust results due to assumption satisfaction. The results
demonstrated that the mean vector of the benefits was not equal per each sector. Environmental
management and indicator dimensions can discriminate sectors more than the environmental aware-
ness dimension. This study provides insights into the necessity of assessing the benefits of ISO 14001
adaptation that helps organizations allocate their limited resources optimally and support the listing
of standard key performance indicators in ISO 14001. In addition, it calls for combining ISO 9001:2015,
ISO 14001:2015, and ISO 45001:2018 in one standard.
Keywords: environmental management systems; ISO 14001:2015; MANOVA; discriminant analysis
1. Introduction
The United Nations (UN) professed 2021 to be the commencement of the UN Decade
on Ecosystem Restoration on 1 March 2019, to promote and enhance efforts to avert, stop,
and reverse environmental deterioration and increase awareness of the necessity of effec-
tive ecosystem restoration. A total of 348,473 organizations in 195 countries globally have
certified their Environmental Management Systems (EMSs) as proof of their environmental
commitment [
1
]. ISO 14001 EMS is centered on and driven by environmental impacts,
supports the integration of environmental management and business operations, allows for
continuous development, and is verifiable through regular auditing. A number of studies
have demonstrated the advantages that firms may achieve by adopting ISO 14001; most of
them categorize the benefits as environmental management (EM), environmental indicators
(EIs), and environmental awareness and social aspects (EA) [
2
,
3
]. Unfortunately, ISO 14001
literature does not agree on the effect of adopting the standard on the environment [
4
].
Furthermore, few research works have investigated the drawbacks of implementing the
standard and showed that the cost of adopting ISO 14001 could be high [
5
]. Hence, a
considerable research area of interest arises concerning the scaling of the benefits of imple-
menting the standard to optimize the assignment of the organizations’ limited resources.
Sustainability 2022,14, 5025. https://doi.org/10.3390/su14095025 https://www.mdpi.com/journal/sustainability
Sustainability 2022,14, 5025 2 of 19
The purpose of this paper was to investigate whether the mean vectors representing the
benefits from implementing the standard are equal or not among six industrial sectors, in
addition to defining the discriminating benefits that may differ from one sector to another.
While some researchers view a positive relationship between adopting ISO 14001 and
business EIs, others argue that there is no effect between ISO 14001 certification and some
EIs [
4
]. Regarding the EM dimension, it includes four benefits, rigor and effectiveness
of practices (EM01), regulatory compliance (EM02), greener supply chain (EM03), and
documentation control (EM04) [
3
]. Higher rigor for EM01 is generally associated with the
implementation of purported best environmental practices, improved employee commit-
ment, and improved management system follow-up through frequent audits [
6
,
7
]. All
studies on EM02 have demonstrated positive effects, such as increased compliance with
environmental regulations and the avoidance of fines for noncompliance [
8
–
10
]. In studies
that examined this element, enhancements in the greening of supply chain management
(EM03) were also identified [
11
–
13
]. Other researchers have established that ISO 14001
positively impacts the documenting of environmental practices (EM04), particularly in
terms of environmental control [
14
]. Nonetheless, several investigations showed that the
reported improvements were dubious, or the purpose of documenting ISO was frequently
misinterpreted within organizations [13,15].
Concerning the environmental performance indicators dimension, it includes six
benefits such as reduction and management of waste (EI01), air pollution (EI02), general
environmental performance (EI03), consumption of energy and resources (EI04), issues
related to environmental risks and safety (EI05), and water contamination (EI06) [
3
]. Re-
searchers have established that adopting ISO 14001 has a favorable effect on the general
reduction and management of waste (EI01) [
15
–
17
]. Conversely, some scholars established
that the standard has no substantial influence on this issue [
18
,
19
]. According to the
studies [
17
,
18
,
20
], the use of ISO 14001 reduces pollution of air as well as atmospheric emis-
sions (EI02). Contrary, other research found this relationship to be insignificant [
19
,
21
,
22
].
Furthermore, the findings show somewhat mixed results concerning the EIs dimension:
Some scholars established that ISO 14001 positively impacts general environmental per-
formance (EI03) [
6
,
10
,
23
], while other studies found insignificant improvements related
to the standard [
7
,
11
,
19
]. Concerning (IE04) some researchers established that using ISO
14001 improved the effectiveness of consumption of energy and resources [
15
–
17
], while
two papers by Zobel [
19
,
24
] found that noncertified organizations performed better in this
area. The decline of environmental risk and safety issues (EI05) were discussed in some
studies [
15
,
25
,
26
]. Except for Mohammed [
27
], all these studies established improvements
related to the standard. Except [
27
,
28
], scholars that have examined how the standard
influences water contamination (EI06) [
18
,
19
,
21
] have found insignificant improvements
associated with the implementation of ISO 14001.
The social effect of ISO 14001, especially the development of environmental awareness,
was discussed in the literature. According to the literature reviewed, the most common
benefits of implementing ISO 14001 relate to the effect on organizational image, reputation,
and stakeholder relationships (EA01). Apart from [
29
], all other studies that were reviewed
indicated a positive effect of ISO 14001 implementation [
15
–
17
,
30
,
31
]. According to [
26
,
32
],
reputation and image improvements are the most significant benefits observed. The effect
of ISO 14001 implementation on employee commitment and environmental awareness
(EA02) observed improvements [
33
,
34
]. Several studies have also found benefits in environ-
mental awareness, communication, and workplace culture [
12
,
29
]. However, some studies
found no significant improvements in employee commitment and awareness following
the implementation of ISO 14001 [
35
,
36
]. In relation to the employee competencies and
training related to the environment (EA03), some scholars [
35
,
37
] established positive
effects of ISO 14001 implementation or observed notable actions. However, Concepción
López-Fernández and Serrano-Bedia [
14
] found insignificant change in this area. Some
researchers also found that implementing ISO 14001 improves managers’ involvement and
Sustainability 2022,14, 5025 3 of 19
support (EA04) [
8
,
29
]. These findings were inconsistent with those of [
35
], who found that
ISO 14001 implementation has an insignificant relationship with managers’ commitment.
Research on the effect of adopting ISO 14001 on businesses has mostly been restricted
to assessing if there is a positive/no significant impact on business environmental perfor-
mance without comparing the effect of implementing the standard on the various business
sectors, which distinguishes our study. This study aimed to explore the association between
ISO 14001 implementation and environmental performance among different industrial
sectors. This paper sought to show no difference among sectors on the benefits scale based
on the views and opinions of environmental department managers and to test if there
are any discriminant functions for defining promising discriminant benefits. Thus, the
following research questions were formulated: “Is there a statistically significant difference
at 0.05 level of significance between mean vectors of ISO 14001 benefits evaluated based upon the
perceptions of environmental department managers due to the difference in the industrial sector
or not?”; and “ Is there is a discriminant effect for benefits of ISO 14001 per sector or not.” We
assumed that participants would answer honestly and have a high level of perception
about ISO 14001 and environmental management, responses were taken to protect the
confidentiality of the information provided by the respondents, involvement in the research
was free and voluntary, and respondents would withdraw from the study at any time
without any ramifications. For each response, the 14 benefit variables were independent
for an organization. In general, 14 benefits of ISO 14001 were focused on in a literature
review. Furthermore, the study had three delimitations that restricted the findings. First,
the study was delimited to six industrial sectors as the target population in Saudi Arabia
(SA). The results may or may not be generally applicable to other sectors or geographic
regions. The main reason for choosing these sectors is the largest number of ISO 14001
certified Saudi organizations belong to these sectors [
1
]. Secondly, the study delimited
itself to using a convenience sample from a target population of 255 organizations. All
population was contacted and included in the study. Lastly, the study used data collected
data from employees working in EM high leadership positions within the organization to
minimize the delimitation of the employees.
This study tested whether the mean vector of 14 benefits of adopting ISO 14001
was equal in importance as evaluated by environmental managers in Saudi Arabia by
using MANOVA. Furthermore, the discriminant analysis technique was used to define the
discriminating benefits per sector. The remaining parts of this research paper are organized
as follows: Section 2outlines the methodological stance adopted to test the benefits of
the mean vectors’ equivalence and define the discriminating ones; Section 3presents the
results of MANOVA and discriminant analysis methodologies. Section 4presents the
discussion of the study findings in relation to the existing literature. Lastly, Section 5covers
the conclusions drawn from the study and practical applications of the study findings. It
also presents the study limitations and recommendations for future research. Moreover,
the paper includes an Appendix A.
2. Methods
Since our topic has not been well-researched in the Arab Gulf countries, we adopted
the quantitative design to investigate the difference in 6 sectors’ perceptions of the benefits
of implementing ISO 14001 [
38
]. The latest results of the International Organization for Stan-
dardization (ISO) Survey are for 2020, which showed an approximation of the total number
of valid certificates as of 31 December 2020. In Saudi Arabia, there were
515 certifications
for 718 sites [
1
]. Organizations working in 6 economic activities out of 35 were included in
the study due to a large number of ISO 14001 certified organizations belonging to these
6 activities
compared with the other 29 activities. These activities were; G1: Chemicals,
chemical products, and fibers, G2: Plastic and rubber products, G3: Fabricated metal and
basic metal products, G4: Construction, G5: Wholesale and retail trade, repairs of motorcy-
cles, motor vehicles, and household and personal goods, and G6: Engineering services. The
economic activities were listed on the Saudi national grouping of economic activities based
Sustainability 2022,14, 5025 4 of 19
on the International Standard Industrial Classification (ISIC) of all economic activities [
39
].
Organization sizes included in the study ranged from low, medium, and large. Minimum 2
years of certification were adopted as inclusion criteria for the participating organizations
in the study. These inclusion criteria satisfied that organizations were able to return to their
records and judge the questions of the study. The minimum requirements for participants’
age, years of experience, and position were 35 years, 2 years, and a manager for the envi-
ronmental department, respectively. A minimum bachelor’s degree is a requirement to
participate in the survey. Each organization would be presented if 4 participants working
in EM and related departments were shared in the survey. The representative scale of an
organization will be the average for the 4 responses.
Non-random sampling is one of the techniques for selecting samples that is based on
the research’s subjective judgment [
40
]. Due to the varying company sizes, the data were
collected from four employees among top management who are related to ISO 14001. This
is because they are central in management and ISO 14001 certification and know the most
about environmental management. The interview questions were sent to all interviewers
in advance. The main language that was used during interview sessions was Arabic and
English. A hundred and fifty organizations approached and participated in the study out of
255 organizations representing approximately 58.82% of the population. A comprehensive
research proposal was sent by fax to organizations clarifying the study objectives and
expected outcomes in addition to the requirements for valid participation in the survey.
Organizations and authors decide together the interview members and sessions dates.
The interviews were conducted at the organization’s sites from April to December 2020.
The face-to-face interviews were conducted with the CEO, President, Vice President, and
Manager for each organization for 20 to 30 min.
The sessions took place at the participant’s office. The study was approved by our
University Internal Review Board to ensure compliance with the University Declaration
of King Khalid University. Participants signed a consent to participate in research form
indicating the freedom to withdraw at any time, refuse to answer any questions, confidential
use of collected data, no direct benefit from participation, agreement for audio-recording
for the interview, anonymous identity, retaining the original data with authors, access to
collected data at any time, and freedom to contact any participant. Using Pillai’s V, the
number of groups and the number of variables are equal to 0.4, 6, and 14, respectively, the
effect size f
2
(V) value based on Muller and Peterson algorithm is equaled to 0.086, leading
to a total sample size of 108 achieving an actual f
2
(V) of 0.832 [
41
]. Thus, the minimum
number of intended observations per group equals 18. A sample of 120 observations was
included in the study to achieve reliable f2(V) with 20 observations per group.
A literature survey revealed that the benefits most often mentioned may be grouped
into three broad categories, which are summarized and reviewed in the introduction sec-
tion as depicted in Table 1. A questionnaire composed of the items in Table 1was used to
measure the benefit of implementing ISO 14001:2015 in organizations. The questionnaire
consists of 14 Likert scale importance values represented for each benefit. The participants
indicated their evaluation of the level of importance for each benefit on a 9-point scale,
which ranged from “extremely unimportant” to “extremely unimportant”. The question-
naire was depicted in Appendix A. Interviews were conducted with four representatives
per organization by the research team; collecting information in e-documents and EMS
annual reports and comparing interview results with retrieved data could increase the
construct validity and improve the accuracy of the study’s findings and conclusions [
42
]. To
increase the internal validity of this study, we compared the data collected from interviews
between researchers and between recorded notes [
43
]. The generalizability of the research’s
findings corresponds to the external validity quality of the research [
44
]. In this study, the
external validity can be generalized to Saudi Arabia’s concerning 6 sectors, but it has a
limited generalization ability to the global organizations working in the same activities due
to the difference in culture, a type developed or developing countries, or even organization
size. In this study, an audio recorder and note-taking are used during the interview to
Sustainability 2022,14, 5025 5 of 19
increase the study reliability of data collection [
45
]. The interview questions were sent to
interviewees in advance to allow them to know the interview’s approach. On top of that,
we do respect the interviewees if they do not feel free to answer some questions. The inter-
viewees were carefully chosen based on the related responsibility to ISO 14001, ensuring
that job positioning and personal relationships are not factors when
choosing interviewees
.
Table 1. Summary of benefits of obtaining ISO 14000 certification documented in the literature.
Category (Code) Dependent Variable Title (code) References
Positive Impact No Significant Impact
EM
Rigour and effectiveness of practices (EM01) [7,8,34] –
Regulatory compliance (EM02) [9–11] –
Greener supply chain (EM03) [12,13] –
Documentation control (EM04) [15] [13,14]
EI
Waste minimization and management (EI01) [16,17,20] [18,21]
Air pollution (EI02) [20–22] [18,23,24]
Environmental performance in general (EI03)
[7,11,25] [8,12,18]
Energy and resources consumption (EI04) [16,17,20] [18,19]
Environmental risks and safety issues (EI05) [13,16,26,27] [28]
Water contamination (EI06) [28,29] [18,22,23]
EA
Image and stakeholders (EA01) [16,17,20,31,32] –
Employee’s involvement (EA02) [34,35] [36,37]
Employee’s training and knowledge (EA03) [36,38] [15]
Manager involvement (EA04) [9,30] –
A MANOVA was undertaken to examine if there exists a notable difference in the
linear combination of the fourteen ISO 14001
0
benefits between the levels of group sectors.
Before conducting the MANOVA, collected data were checked to ensure that there was
a moderate correlation between dependent variables, multivariate normality, absence of
multicollinearity, and the homogeneity of the covariance matrices [
46
]. Pearson correlation
was utilized to evaluate the moderate correlation range between 0.3 and 0.7 [
46
], and
multivariate normality was tested by Henze–Zirkler’s test developed by Henze and Zirkler
as cited in [
47
]. There exists no known uniformly strongest test; thus, it is recommended
that different tests be performed to evaluate multivariate normality. The Henze and Zirkler
test has been shown to have good overall strength over alternatives to normality. This test
has desirable characteristics such as affine invariance, symptotic power against contiguous
alternatives of order n−1/2, consistency against any fixed non-normal alternative distribu-
tion, and any dimension’s and sample size’s feasibility. The absence of multicollinearity
was tested against a Variance inflation factor (VIF) value to be less than 5 [
48
]. Box’s M test
was utilized to test the homogeneity of covariance matrices [
49
]. Statistical tests were based
on the level of significance
α
= 0.05. The relationship between the standard benefits and
economic activity level was further analyzed using ANOVA.
3. Results
MANOVA was undertaken to examine if there exists a notable difference in the linear
combination of EM01, EM02, EM03, EM04, EI01, EI02, EI03, EI04, EI05, EI06, EA01, EA02,
EA03, and EA04 between six Saudi industrial sectors. Furthermore, discriminant analysis
was utilized to define the variables that have a significant discrimination effect on the sector
type. In the following, we will discuss how these results might be important for shedding
light on the development of the international standard ISO 14001. A minimal data set can
be accessed on the Figshare website [50].
(a)
Descriptive statistics
Summary statistics were calculated for EM01, EM02, EM03, EM04, EI01, EI02, EI03,
EI04, EI05, EI06, EA01, EA02, EA03, and EA04. Table 2includes the descriptive statistics for
Sustainability 2022,14, 5025 6 of 19
the dependent variables disaggregated by the independent variables for a sample of 120
and a group size of 20.
Table 2.
Mean and standard deviation for EM01, EM02, EM03, EM04, EI01, EI02, EI03, EI04, EI05,
EI06, EA01, EA02, EA03, and EA04 by sector.
Sector G1 (n= 20) G2 (n= 20) G3 (n= 20) G4 (n= 20) G5 (n= 20) G6 (n= 20) Total (n= 120)
DV
Statistic MSDMSDMSDMSDMSDMSDMSD
EM01 7.750 0.416
80.183
0.613 8.229 0.492 7.733 0.488 8.246 0.504 7.733 0.518 7.979 0.553
EM02 4.587 0.561
40.643
0.479
40.678
0.452 4.538 0.605
40.651
0.573
40.499
0.528 4.599 0.528
EM03
50.324
0.503 5.267 0.537 5.767 0.439 5.292 0.478 5.826 0.487
50.308
0.522
50.464
0.540
EM04 6.295 0.483 5.943 0.567 6.527 0.512
60.027
0.604 6.531 0.510 6.212 0.443 6.256 0.559
EI01 1.266 0.533 1.275 0.505
10.162
0.501 1.211 0.578
10.377
0.628 1.217 0.391 1.251 0.521
EI02 7.220 0.533
70.344
0.611
70.184
0.562
70.176
0.514 7.288 0.580 7.255 0.598 7.245 0.558
EI03 2.915 0.505 3.271 0.439
20.678
0.362
20.680
0.484 3.283 0.506
30.082
0.490 2.985 0.521
EI04
20.424
0.610
20.465
0.565 1.951 0.538 1.992 0.564 2.513 0.395
20.409
0.508 2.292 0.571
EI05 6.836 0.487 6.859 0.502
60.645
0.379
60.663
0.478
70.079
0.394
60.652
0.484 6.789 0.474
EI06
20.063
0.474 1.963 0.523
10.464
0.572
10.452
0.578
20.028
0.553
10.458
0.443 1.738 0.588
EA01
50.694
0.520
50.647
0.535
50.632
0.614 5.221 0.448 5.542 0.565
50.638
0.612 5.562 0.563
EA02 3.773 0.570 3.725 0.529 3.746 0.542
30.690
0.481
30.639
0.499 3.719 0.526 3.715 0.516
EA03 8.218 0.392
80.166
0.407
80.187
0.375
80.185
0.438
80.195
0.325 8.243 0.470
80.199
0.396
EA04
40.111
0.525
40.062
0.500
40.145
0.554
30.652
0.448 3.837 0.462
40.104
0.569 3.985 0.532
(b)
Sample profile
The profile of respondents: 100% of the participants were males because of the so-
cietal nature of the working environment in SA. Descriptive statistics for the age of the
120 respondents
reveal an overall mean score of 47.53 years (SD = 50.64). This shows that
the sample age is concentrated near the center point of the interval, ranging from 35 to
60 years, indicating some homogeneity type. These results are due to most of the sample
ages being located in the interval of 46–50 years with a percentage of 440.17. The overall
average of respondents’ years of experience was 90.45 years (SD = 3.91). This indicates that
the respondents have sufficient experience to judge the questionnaire’s questions and the
questions they answered, which is reinforced by the fact that most of them (480.33%) work
in CEO positions.
Profile of responses by subsector, firm size, year of ISO 14001 certification: The number
of respondents in the population representing the economic subsectors of fibers, chemicals,
and chemical products, plastic and rubber products, fabricated metal and basic metal
products, construction, retail and wholesale trade, repairs of motorcycles, motor vehicles
and household and personal goods, and engineering services of 20, 23, 27, 28, 25, and 27
from populations of 20, 23, 61, 77, 30, and 44 respectively. A total of 150 organizations
participated in the survey, of which 130.33% were chemicals, chemical products, and fibers
organizations, 150.33% were rubber and plastic products organizations, 180.00% were basic
metal and fabricated metal products organizations, 180.67% were construction organiza-
tions, 160.67% were wholesale and retail trade, repairs of motorcycles, motor vehicles
and household and personal goods organizations, and 180.00% representing engineering
services organizations. A total of 440.67% of organizations were large enterprises, 250.33%
were medium-sized, while 300.00% of the organizations were small size. All certified orga-
nizations [
18
] working in the chemicals, chemical products, and fibers sector responded
to the questionnaire 10 of 20 organizations certified or renewed certification after 2009,
3 organizations in the period of 2008–2009, 4 organizations in the period of 2006–2007,
and 3 organizations are certified in 2006. It is noticeable that 50% of organizations were
certified after 2009. The sample covered a variety of respondents concerning age, years of
experience, respondent position, six industrial sectors, firm size, and year of certification,
which reflects that the most sample opinions were built on the environmental respondents’
perceptions which gives confidence in the result of the analysis. Out of 150 responses,
30 responses were excluded from analysis due to the existence of outliers.
Sustainability 2022,14, 5025 7 of 19
(c)
MANOVA results
MANOVA assumptions check: For one-way MANOVA, preliminary assumptions test-
ing was conducted. Interval/ratio level-dependent variables: The organizations’ responses
were summarized as the average of four responses from managers who work in managing
the EMS satisfying the continuous dependent variables condition. Unrelated categorical in-
dependent variable: The economic activity that organizations belong to includes six groups
(fibers, chemical, and chemical products, plastic and rubber products, fabricated metal
and basic metal products, construction, retail, and wholesale trade, repairs of motorcycles,
motor vehicles and household and personal goods, and Engineering services).
Independence of observations: There exists no significant relationship between the
observations within every group or between the groups themselves. Data collection was
performed to guarantee that different research subjects were in every group, with no
research subject being in more than one group. Adequate sample size: Utilizing Pillai’s V,
the number of groups, and the number of variables equivalent to 0.4, 6, and 14, respectively,
the effect size f
2
(V) value based on Muller and Peterson algorithm is equaled to 0.086,
leading to a total sample size of 108 accomplishing an actual f
2
(V) of 0.832 [
41
]. Thus, the
minimum number of intended observations per group equals 18. A sample of 120 non-
outlier perceptions was included in the study to achieve reliable f
2
(V) with 20 perceptions
per group.
Absence of univariate or multivariate outliers: Outliers per group were identified if
a point’s value was more than three standard deviations from the group’s mean. Outlier
points per group were removed from the dataset before performing MANOVA. Multivariate
outliers were detected based on the Wilks method developed in 1963 for detecting a
single outlier from a normal multivariate sample and approaching the maximum squared
Mahalanobis distance to an F distribution function by the Yang and Lee 1987 formulation.
There are no outliers in the validated sample data set used in the analysis. Multivariate
normality: Henze–Zirkler ’s test [
47
] was used to test the multivariate normality. Results
indicated that the Henze–Zirkler statistic = 0.998, associated p-value = 0.084, hence, data
are multivariate normal (p= 0.05). Linear relationship of dependent variables: The R
function ggpairs() [GGally package] lists the Pearson product correlation (r) among ISO
14001 benefits. The values of r
s
represent the pairwise relationship between the outcome
variables for each group and indicate a significant linear relationship for EMs variables at
p= 0.01,0.05, or 0.001.
Homogeneity of variance-covariance matrices: Box’s M test of equality of covariance
was performed to examine the homogeneity of variance-covariance matrices across sector
levels. The results were significant based on
α
= 0.05. Box’s M = 631.264, F = 0.814,
df1 = 525
, df2 = 19212.882, and p= 0.999, that is greater than 0.05 indicating that the
covariance matrices for each sector level were significantly not different from one another
and that the assumption was met.
Absence of multicollinearity: Calculating the linear regression model of EM01 as
dependent variable and other benefits as independent variables (EM01 ~ constant + EM02
+ EM03 + EM04 + EI01 + EI02 + EI03 + EI04 + EI05 + EI06 + EA01 + EA02 + EA03 + EA04)
results in collinearity statistics in terms of tolerances and VIFs for independent variables.
The maximum calculated VIF equals 2.985, which is less than 5, and the minimum tolerance
equals 0.335, which is greater than 0.1, indicating that there is no multicollinearity among
outcome variables. The correlation coefficients of dependent variables range from 0.3 to 0.7,
indicating a moderate correlation and that there is no singularity among dependent vari-
ables as depicted in Table 3, which provides a Pearson correlation coefficients matrix among
variables. Univariate normality assumption: The Shapiro–Wilk test function shapiro_test()
in the R package “rstatix” was used to assess normality for multiple variables by groups.
Results indicated that variables are normally distributed for each sector group (p> 0.05).
However, the MANOVA is practically strong to modest defilements of normality when the
same size is at least 20 in each cell [51].
Sustainability 2022,14, 5025 8 of 19
Table 3. Pearson correlation matrix.
INDVs EM01 EM02 EM03 EM04 EI01 EI02 EI03 EI04 EI05 EI06 EA01 EA02 EA03 EA04
EM01 1 0.633 ** 0.695 ** 0.634 ** 0.387 ** 0.410 ** 0.429 ** 0.402 ** 0.413 ** 0.416 ** 0.438 ** 0.412 ** 0.398 ** 0.399 **
EM02 0.633 ** 1 0.683 ** 0.665 ** 0.444 ** 0.422 ** 0.389 ** 0.425 ** 0.412 ** 0.394 ** 0.392 ** 0.428 ** 0.421 ** 0.417 **
EM03 0.695 ** 0.683 ** 1 0.687 ** 0.420 ** 0.376 ** 0.383 ** 0.363 ** 0.437 ** 0.398 ** 0.358 ** 0.394 ** 0.398 ** 0.375 **
EM04 0.634 ** 0.665 ** 0.687 ** 1 0.428 ** 0.412 ** 0.376 ** 0.425 ** 0.433 ** 0.412 ** 0.400 ** 0.386 ** 0.426 ** 0.412 **
EI01 0.387 ** 0.444 ** 0.420 ** 0.428 ** 1 0.632 ** 0.645 ** 0.644 ** 0.674 ** 0.673 ** 0.406 ** 0.423 ** 0.436 ** 0.434 **
EI02 0.410 ** 0.422 ** 0.376 ** 0.412 ** 0.632 ** 1 0.660 ** 0.655 ** 0.669 ** 0.615 ** 0.427 ** 0.446 ** 0.425 ** 0.357 **
EI03 0.429 ** 0.389 ** 0.383 ** 0.376 ** 0.645 ** 0.660 ** 1 .728 ** .723 ** 0.642 ** 0.398 ** 0.420 ** 0.412 ** 0.439 **
EI04 0.402 ** 0.425 ** 0.363 ** 0.425 ** 0.644 ** 0.655 ** .728 ** 1 0.678 ** 0.699 ** 0.420 ** 0.416 ** 0.411 ** 0.389 **
EI05 0.413 ** 0.412 ** 0.437 ** 0.433 ** 0.674 ** 0.669 ** .723 ** 0.678 ** 1 0.695 ** 0.392 ** 0.417 ** 0.405 ** 0.374 **
EI06 0.416 ** 0.394 ** 0.398 ** 0.412 ** 0.673 ** 0.615 ** 0.642 ** 0.699 ** 0.695 ** 1 0.452 ** 0.424 ** 0.380 ** 0.403 **
EA01 0.438 ** 0.392 ** 0.358 ** 0.400 ** 0.406 ** 0.427 ** 0.398 ** 0.420 ** 0.392 ** 0.452 ** 1 0.626 ** 0.666 ** 0.684 **
EA02 0.412 ** 0.428 ** 0.394 ** 0.386 ** 0.423 ** 0.446 ** 0.420 ** 0.416 ** 0.417 ** 0.424 ** 0.626 ** 1 0.680 ** 0.666 **
EA03 0.398 ** 0.421 ** 0.398 ** 0.426 ** 0.436 ** 0.425 ** 0.412 ** 0.411 ** 0.405 ** 0.380 ** 0.666 ** 0.680 ** 1 0.643 **
EA04 0.399 ** 0.417 ** 0.375 ** 0.412 ** 0.434 ** 0.357 ** 0.439 ** 0.389 ** 0.374 ** 0.403 ** 0.684 ** 0.666 ** 0.643 ** 1
** Correlation is significant at the 0.01 level (2-tailed).
MANOVA’ results: The main effect for industrial sector was significant, Wilks’
Λ= 0.102
, F(70, 484) = 4.265, p< 0.001, partial
η2
= 0.367, and observed power = 10.00, sug-
gesting the linear combination of ISO 14001 benefit variables (EM01, EM02, EM03, EM04,
EI01, EI02, EI03, EI04, EI05, EI06, EA01, EA02, EA03, and EA04) was significantly different
among the levels of industrial sector. Furthermore, the effect size is large. The observed
power was 10.00, which indicates that there was a 100% likelihood that the findings could
be significant. The MANOVA results are shown in Table 4.
Table 4. MANOVA results for ISO 14001 benefits by the industrial sector.
Effect Wilks’ Lambda F Hypothesis df Error df pPartial η2Noncent. Parameter Observed Power
Sector
0.102
4.265
70.000 484.944
0.000
0.367 280.790 1.000
To further examine the effects of sectors on EM01, EM02, EM03, EM04, EI01, EI02,
EI03, EI04, EI05, EI06, EA01, EA02, EA03, and EA04, an Analysis of Variance (ANOVA)
was performed for each dependent variable to assess if there were significant differences
in ISO 14001 benefits by sectors (Table 5). Using the Bonferroni method based on an
α
= 0.003 (0.05/14), ANOVAs were significant and indicated that there were significant
differences in EM01, EM03, EM04, EI03, EI04, and EI06 among the sector levels. Considering
EM variables, initially, EM01 has F(5, 114) = 50.402, p= 0.000, indicating that there were
significant differences in EM01 among sector’ levels. The Partial
η2
was 0.192, indicating
the sector explains approximately 19.2% of the variance in EM01. Secondly, EM02 has
F(5, 114) =0.345
,p= 0.884, which indicated that there were insignificant differences in EM02
among sector’ levels. The Partial
η2
was 0.015, indicating the sector explains approximately
1.5% of the variance in EM02. Thirdly, EM03 has F(5, 114) = 50.469, p= 0.000, indicating that
there were significant differences in EM03 among sector’ levels. The Partial
η2
was 0.193,
indicating the sector explains approximately 190.3% of the variance in EM03. Last EM04 has
F(5, 114) = 40.445, p= 0.001, which revealed that there were significant differences in EM04
among sector’ levels. The Partial
η2
was 0.163 indicating the sector explains approximately
160.3% of the variance in EM04.
Concerning the EI variables, Initially, EI01 has F(5, 114) =0.391, p= 0.854, implying
that there were insignificant differences in EI01 among sector’ levels. The Partial
η2
was
0.017, which indicated that the sector explains approximately 1.7% of the variance in EI01.
Secondly, EI02 has F(5, 114) = 0.259, p= 0.934, indicating that there were no significant
differences in EI02 among sector’ levels. The Partial
η2
was 0.011, indicating the sector
explains approximately 10.1% of the variance in EI02. Thirdly, EI03 has F(5, 114) = 6.813,
p= 0.000
, indicating that there were significant differences in EI03 among sector levels. The
Partial
η2
was 0.230, indicating the sector explains approximately 230.0% of the variance in
EI03. Fourthly, EI04 has F(5, 114) = 40.433, p= 0.001, indicating that there were significant
differences in EI04 among sector levels. The Partial
η2
was 0.163, implying that the sector
explains approximately 160.3% of the variance in EI04. Fifthly, EI05 has F(5, 114) = 2.806,
Sustainability 2022,14, 5025 9 of 19
p= 0.020, which indicated that there were insignificant differences in EI05 among sector’
levels. The Partial
η2
was 0.110, indicating the sector explains approximately 110.0% of
the variance in EI05. Last, EI06 has F(5, 114) = 6.875, p= 0.000, indicating that there were
significant differences in EI06 among sector levels. The Partial
η2
was 0.232, indicating the
sector explains approximately 23.2% of the variance in EI06.
Regarding EA variables, Firstly, EA01 has F(5, 114) = 1.997, p= 0.084, which indicated
that there were insignificant differences in EA01 among sector levels. The Partial
η2
was
0.081, indicating the sector explains approximately 80.1% of the variance in EA01. Secondly,
EA02 has F(5, 114) = 0.156, p= 0.978, implying that there were insignificant differences
in EA02 among sector’ levels. The Partial
η2
was 0.007, indicating the sector explains
approximately 0.7% of the variance in EA02. Thirdly, EA03 has F(5, 114) = 0.092, p= 0.993,
indicating that there were no significant differences in EA03 among sector’ levels. The
Partial
η2
was 0.004, indicating the sector explains approximately 0.4% of the variance in
EA03. Last, EA04 has F(5, 114) = 2.976, p= 0.015, which meant that there were insignificant
differences in EA04 among sector’ levels. The Partial
η2
was 0.115, indicating that the sector
explains approximately 11.5% of the variance in EA04.
Table 5.
ANOVA table for EM01, EM02, EM03, EM04, EI01, EI02, EI03, EI04, EI05, EI06, EA01, EA02,
EA03, and EA04 by sectors.
Variable SS df F pPartial η2Observed
Power
EM01 6.977 5 5.402 0.000 0.192 0.987
EM02 0.495 5 0.345 0.884 0.015 0.135
EM03 6.708 5 5.469 0.000 0.193 0.988
EM04 6.062 5 4.445 0.001 0.163 0.963
EI01 0.545 5 0.391 0.854 0.017 0.149
EI02 0.417 5 0.259 0.934 0.011 0.112
EI03 7.441 5 6.813 0.000 0.230 0.998
EI04 6.327 5 4.433 0.001 0.163 0.963
EI05 2.926 5 2.806 0.020 0.110 0.819
EI06 9.518 5 6.875 0.000 0.232 0.998
EA01 3.043 5 1.997 0.084 0.081 0.652
EA02 0.215 5 0.156 0.978 0.007 0.085
EA03 0.075 5 0.092 0.993 0.004 0.070
EA04 3.893 5 2.976 0.015 0.115 0.844
Table 6shows the Bonferroni multiple comparisons in relation to the observed means.
The means difference is significant at the
α
= 0.05 for all comparisons in the table. For
example, the benefit variable EI06 located in the cell corresponding to G1 and G3 implies
that there exists a significant difference in the mean of the variable between G1 and G3
equal to 0.599 for G1. The means for variables EM01, EM03, EM04, EI03, EI04, and EI06
between G4 and G5 are equal to
−
0.512,
−
0.535,
−
0.504,
−
0.603,
−
0.522, and
−
0.576,
respectively. Furthermore, it is noticed that the industrial sectors pairs of (G1, G2), (G3, G6),
and (G4, G6) do not contain any variables, whereas sector pairs of (G1, G3), (G1, G4), and
(G1, G6) includes one variable. Sector pairs of (G1, G5) and (G2, G6) include two variables.
Sector pairs of (G2, G4), (G3, G4), and (G5, G6) include three variables. Sector pairs of (G2,
G3) and (G3, G5) include five variables, while the pair of (G4, G5) includes six variables.
All Gs pairwise comparisons were significantly different for each of the outcome variables.
Sustainability 2022,14, 5025 10 of 19
Table 6.
Bonferroni multiple comparisons based on observed means for EM01, EM02, EM03, EM04,
EI01, EI02, EI03, EI04, EI05, EI06, EA01, EA02, EA03, and EA04 by sectors.
G1 G2 G3 G4 G5 G6
Benefit Mean
diff.
Benefit Mean
diff.
Benefit Mean
diff.
Benefit Mean
diff.
Benefit Mean
diff.
Benefit Mean
diff.
G1 – – – – EI06 0.599 EI06 0.612 EM01
EM03
−0.496
−0.502
EI06 0.605
G2 – – EM03
EM04
EI03
EI04
EI06
−0.499
−0.584
0.592
0.514
0.499
EM01
EI03
EI06
0.496
0.591
0.511
EM03
EM04
−0.559
−0.588
EM01
EI06
0.497
0.505
G3 – – EM03
EM04
EA04
0.475
0.500
0.494
EM03
EI03
EI04
EI05
EI06
−0.535
−0.605
−0.562
−0.433
−0.564
– –
G4 – – EM01
EM03
EM04
EI03
EI04
EI06
−0.512
−0.535
−0.504
−0.603
−0.522
−0.576
– –
G5 – – EM01
EM03
EI06
0.513
0.519
0.570
(d)
Discriminant analysis results
The discriminant command in SPSS does a stepwise linear discriminant analysis,
which is the most used type of discriminant analysis. The command is adjusted to use
stepwise variable selection, Wilks’ Lambda method, 0.1 probability of F entry, and 0.2
probability of F removal. At every step of the solution, a variable that reduces the overall
Wilks’ Lambda is introduced. Table 7shows that ten ISO 14001 benefits were entered into
the analysis: EI06, EM03, EI03, EA04, EM01, EM04, EM02, EI02, EI01, and EI04 as a result
of applying the discriminant analysis algorithm (Sig. < 0.05). These variables participate in
classifying the industrial sectors in groups and have a significant statistical effect of these
variables on classifying industrial sectors. EI05, EA01, EA02, and EA03 were removed from
the analysis by the discriminant analysis algorithm due to (Sig. > 0.05).
Table 7. Variables in the analysis.
Variable
Wilks’ Lambda
Statistic df1 df2 df3 Exact F Approximate F
Statistic df1 df2 Sig. Statistic df1 df2 Sig.
EI06 0.768 1 5
114.000
6.875 5
114.000
0.000 – – – –
EM03 0.561 2 5
114.000
7.585 10
226.000
0.000 – – – –
EI03 0.419 3 5
114.000
– – – – 7.639 15
309.584
0.000
EA04 0.336 4 5
114.000
– – – – 7.189 20
369.095
0.000
EM01 0.281 5 5
114.000
– – – – 6.686 25
410.134
0.000
EM04 0.228 6 5
114.000
– – – – 6.522 30
438.000
0.000
EM02 0.191 7 5
114.000
– – – – 6.290 35
456.745
0.000
EI02 0.162 8 5
114.000
– – – – 6.078 40
469.197
0.000
EI01 0.147 9 5
114.000
– – – – 5.684 45
477.267
0.000
EI04 0.132 10 5
114.000
– – – – 5.387 50
482.238
0.000
Sustainability 2022,14, 5025 11 of 19
Five discriminant functions were found to be statistically significant as shown in
Tables 8and 9. Wilks’
Λ
= 0.132, Chi-square = 2240.651, and Sig = 0.000 for discriminant
function 1 through 5. Wilks’
Λ
= 0.289, Chi-square = 137.806, and Sig = 0.000 for discrimi-
nant function 2 through 5. Wilks’
Λ
= 0.448, Chi-square = 890.175, and
Sig = 0.000
for dis-
criminant function 3 through 5. Wilks’
Λ
= 0.631, Chi-square = 510.106, and
Sig = 0.000
for
discriminant function 4 through 5. Wilks’
Λ
= 0.833, Chi-square = 200.322, and
Sig = 0.002
for discriminant function 5. The five discriminant functions explain 44.5%, 200.6%, 150.3%,
120.0%, and 7.5% of the variance. Canonical correlations are 0.737, 0.596, 0.539, 0.492,
and 0.409 for discriminant functions, indicating that 540.3%, 35.5%, 290.1%, 24.2%, and
16.7% of variances were explained by the association between explanatory variables and
group membership by the five discriminant functions, respectively. The first discriminant
function had the largest relationship with EI01, followed by EI03, EI04, EM04, EI06, EI02,
EM02, EM03, EM01, and EA04. The second discriminant function had the most significant
relationship with EM04, followed by EM02, EI06, EA04, EI01, EI03, EI04, EM03, EI02, and
EM01. Discriminant function 3 has the largest relationship with EM03, followed by EI04,
EM01, EI03, EI06, EI02, EM02, EA04, EI01, and EM04. Discriminant function 4 has the
largest relationship with EI03, followed by EI01, EM01, EM02, EM03, EM04, EI04, EI06,
EA04, and EI02.
Table 8. Eigenvalues for canonical discriminant functions.
Function Eigenvalue % of Variance Cumulative % Canonical
Correlation
1 10.187 44.5 44.5 0.737
2 0.550 200.6 650.1 0.596
3 0.409 150.3 80.5 0.539
4 0.320 120.0 92.5 0.492
5 0.201 7.5 1000.0 0.409
Table 9. Wilks’ Lambda for canonical discriminant functions.
Test of
Function(s) Wilks’ Lambda Chi-Square df Sig.
1 through 5 0.132 2240.651 50 0.000
2 through 5 0.289 137.806 36 0.000
3 through 5 0.448 890.175 24 0.000
4 through 5 0.631 510.106 14 0.000
5 0.833 200.322 6 0.002
Discriminant function 5 has the largest relationship with EA04, followed by EI02,
EM03, EM02, EM04, EI01, EI04, EI03, EM01, and EI06. These relationships were deduced
using data given in the standardized Canonical Discriminant Function (CDF) coefficient
Table 10. Table 11 presents the classification results for original and cross-validated cases.
Cross-validation is performed only for the cases included in the analysis. During cross-
validation, every case is grouped by the functions generated from all other cases other than
that specific case. The table below indicates that 13 G1 observations remained in the same
group by the classifier, 2 cases classified in G4, 2 cases classified in G5, and 3 cases were
classified in G6, representing 65%,10%,10%, and 15% from a sample size of 20 cases. A total
of 69.2% of originally classified cases were correctly grouped, and 550.0% of cross-validated
grouped cases were correctly classified based on the data given in Table 11.
Sustainability 2022,14, 5025 12 of 19
Table 10. Standardized canonical discriminant function coefficient.
Variable Function
12345
EM01 0.381 0.386 −1.134 −0.226 0.484
EM02 0.527 −0.792 −0.214 −0.385 −0.306
EM03 −0.734 0.806 0.123 0.213 −0.168
EM04 −0.756 0.411 0.859 0.205 0.085
EI01 −0.575 −0.188 −0.326 −0.032 −0.607
EI02 −0.604 −0.525 −0.384 −0.096 −0.002
EI03 0.884 0.487 −0.193 0.890 −0.129
EI04 0.342 −0.184 0.576 0.620 0.062
EI06 0.819 0.438 0.537 −1.229 0.083
EA04 −0.197 −0.522 0.199 0.074 1.018
Table 11. Classification results.
Sector
Predicted Group Membership
Count Total %
Total
G1 G2 G3 G4 G5 G6 G1 G2 G3 G4 G5 G6
Original
G1 13 0 0 2 2 3 20 65 0 0 10 10 15 100
G2 3 12 2 1 1 1 20 15.0 60.0 10.0 5.0 5.0 5.0 100
G3 1 0 15 3 0 1 20 5.0 0.0 75.0 15.0 0.0 5.0 100
G4 2 0 1 15 1 1 20 10.0 0.0 5.0 75.0 5.0 5.0 100
G5 1 2 2 0 14 1 20 5.0 10.0 10.0 0.0 70.0 5.0 100
G6 0 1 1 3 1 14 20 0.0 5.0 5.0 15.0 5.0 70.0 100
Cross-validated
G1 11 0 1 3 2 3 20 55 0 5 15 10 15 100
G2 3 10 2 2 2 1 20 15.0 50.0 10.0 10.0 10.0 5.0 100
G3 1 1 12 4 0 2 20 5.0 5.0 60.0 20.0 0.0 10.0 100
G4 4 0 3 9 1 3 20 20.0 0.0 15.0 45.0 5.0 15.0 100
G5 1 2 3 0 13 1 20 5.0 10.0 15.0 0 65.0 5.0 100
G6 1 1 2 4 1 11 20 5.0 5.0 10.0 20.0 5.0 55.0 100
4. Discussion
The results presented here provide two main findings that enhance our understanding
of the 14 cited benefits of adopting ISO 14001 based on environmental managers’ percep-
tions working in six industrial sectors located in Saudi Arabia. First, the MANOVA results
show that ISO 14001 mean benefits, as measured by the 9-Likert scale, are significantly
different among the six industry types. Second, the discriminant analysis results show that
10 of the 14 benefits discriminate between sectors. In the following, we will discuss how
these results might be important for shedding light on the development of the international
standard ISO 14001. To the best of our knowledge, this study’s objective was not covered in
the literature. Because obtaining the ISO 14001 certificate is very expensive, it is necessary
to plan well to assign organizations’ resources to obtain the greatest benefits from the
certificate. A sample of 120 environmental managers working in six sectors in Saudi Arabia
was analyzed using MANOVA and discriminant analysis to investigate the benefits scale.
As presented in Table 4, MANOVA results revealed that the linear combination of EM01,
EM02, EM03, EM04, EI01, EI02, EI03, EI04, EI05, EI06, EA01, EA02, EA03, and EA04 was
significantly different among sectors. It seems likely that these results are, in fact, due to
the noticeable variation of the impact of the standard on the 14 benefits. Though some
studies observed improvements in benefits, some studies did not observe a substantial
change. This is in line with the work performed by Boiral and Guillaumie [
3
] concerning
the disagreement from researchers about the effect of ISO 14001 implementation and the
firm’s benefits.
ANOVAs were significant, implying that there were significant differences in EM01,
EM03, EM04, EI03, EI04, and EI06 among sectors. These results are in line with the opinions
calling for a positive impact of ISO 14001 adoption on EM01 [
6
,
7
,
33
], a positive impact
Sustainability 2022,14, 5025 13 of 19
of EM03 [
11
,
12
], a positive impact of EM04 [
14
], and disagree with the opinions calling
for no impact mentioned by [
12
,
13
] regarding EM04. We can conclude from the conflict
of opinions regarding EM04 that organizations, in general, find ISO 14001’s adoption as
an additional administrative burden on employees due to the use of an environmental
documentation system in addition to the traditional administrative documentation system
used in it, but our results confirm that applying the standard increases the ability of
organizations to control its documents, especially those concerned with environmental
management. To reduce the documentation effort, we propose combining ISO 9001:2015,
ISO 14001:2015, and ISO 45001:2018 in one standard concerning quality, environment,
and safety management in organizations. Our results are consistent with many studies
supporting a positive impact between EM03 and adoption of the standard as [
6
,
10
,
23
] and
conflicts with no impact opinions concluded by [
7
,
11
,
19
]. This conflict in results may be
explained by the differences that may exist in the implementation of the ISO 14001 system
among organizations. Evaluation of researchers about ISO 14001
0
s adoption impact on EI04
came in conflict, while their evaluation was similar to our evaluation [
15
–
17
,
31
], except
the work performed by [
19
,
24
] came with an evaluation of no significant impact. This
can be explained by some organizations were able to maintain the same performance for
EI04, while others were able to achieve a tangible positive effect, which does not conflict
with the application of the ISO standard. Concerning water contamination, our results are
consistent with the opinions of a positive effect between EI06 and ISO 14001 adoption and
in line with the results of [
27
,
28
] and opposite to the opinions of no effect for [
18
,
19
,
21
]. This
can be explained by the fact that references [
27
,
28
] evaluate the relationship in 19 and five
industrial sectors while [
18
,
19
,
21
] evaluate the relationship in manufacturing organizations
only. Consequently, our results came consistent with opinions that considered multiple
industrial sectors in their evaluation. This supports that the sector type is an influencing
factor in evaluating the effect of implementing the standard on EI06.
ANOVAs were significant, indicating that there were no significant differences in
EA04, EI05, EA01, EI01, EM02, EI02, EA02, and EA03 among sectors, as shown in Table 5.
For example, the EM01 scale resulted in F(5, 114) = 50.402, p< 0.000, partial
η2
= 0.192,
and observed power = 10.00. The effect size was large for ANOVAs (partial
η2
> 0.14) [
52
].
The strength of the relationship between the type of industrial sector and EM01, EM03,
EM04, EI03, EI04, or EI06 was strong, the type of group accounting for 19.2 %, 190.3 %,
160.3 %, 230.0 %, 160.3 %, 23.2 % respectively of the variance of the outcome variable. The
observed powers of 0.987, 0.988, 0.963, 0.998, 0.963, and 0.998 indicated that there was a
high possibility that the results could have come out for analysis. These results are in line
with {[
14
], [
12
,
15
,
25
,
26
], [
15
–
17
,
30
,
31
], [
15
–
17
], [
8
–
10
], [
17
,
18
,
20
], [
33
,
34
], [
33
,
34
], [
35
,
37
]} for
a positive impact for benefits and contrary to the opinions that claim that there is no impact
of {–, [
29
], –, [
19
,
24
], –, [
19
,
21
,
22
], [
35
,
36
], [
16
]} respectively as shown in Table 1. The lack of
difference between the six sectors in the evaluation of these benefits can be explained by the
fact that they are direct benefits that are achieved after the implementation of the system,
such as regulatory compliance, manager’s involvement, etc. The partial
η2
, Table 5, for
EI05, EA01, and EA04 belongs to the interval [0.06, 0.14], indicating a medium effect size for
ANOVAs. The observed powers of these variables are 0.819, 0.652, and 0.844, respectively.
The strength of the relationship between the type of industrial sector and EI05, EA01, or
EA04 was medium, the type of group accounting for 110.0%, 80.1%, and 11.5%, respectively
of the variance of the dependent variable. The observed powers of 0.819, 0.070, and 0.844
indicated that there was a medium likelihood that the findings could have come out for
analysis. The effect size was small for ANOVAs of EM02, EI01, EI02, EA02, and EA03
(partial
η2
< 0.06). The observed powers of these variables are 0.135, 0.149, 0.112, 0.085, and
0.070 respectively. The strength of the relationship between the type of industrial sector
and EM02, EI01, EI02, EA02, or EA03 was small, the type of group accounting for 1.5%,
1.7%, 10.0%, 0.7%, and 0.4% respectively of the variance of the dependent variable. The
observed powers of 0.135, 0.149, 0.112, 0.085, and 0.070, which indicated that there was a
small likelihood that findings could have come out for analysis.
Sustainability 2022,14, 5025 14 of 19
As shown in Table 6, Bonferroni’s multiple comparisons results showed that there
is no difference in ISO 14001 benefit evaluation between sector pairs of (G1, G2), (G3,
G6), and (G4, G6). By comparing the benefits of ISO 14001 certification according to the
perceptions of environmental managers for the six sectors, it was shown that G1 evaluated
EI01 greater than G3, G4, and G6 with significant mean differences of 0.599, 0.612, and
0.605, respectively, while G1 evaluated EM01 and EM03 with mean significant differences
of 0.599 and 0.612 less than their counterparts for sector G5. By comparing G2 with G3,
it was found that it assesses ISO 14001 benefits with significant differences mean greater
than G3 for EI03, EI04, and EI06 with values of 0.592, 0.514, and 0.499, respectively, while it
assesses EM03 and EM04 with mean significant differences of 0.499 and 0.584, as shown in
Table 6. G2 assessed EM01, EI03, and EI06 with mean significant differences of 0.496, 0.591,
and 0.511, respectively, more than G4. While G2 assessed EM03 and EM04 less than G5 with
significant mean differences of 0.559 and 0.588, it assessed EM01 and EM06 with significant
mean differences of 0.497 and 0.505 more than the G6 assessment. Considering G3, Table 6
shows that it is more concerned with EM03, EM04, and EA04 than G4, with significant
mean differences of 0.475, 0.500, and 0.494. By comparing G3 with G5, we found that G3
evaluated the benefits of implementing ISO 14001 with a lower significant mean difference
for five discriminating benefits (EM03, EI03, EI04, EI05, and EI06) with significant mean
differences of 0.535, 0.605, 0.562, 0.433, and 0.564 respectively. According to this study’s
results, it was found that sector four does not differ from other sectors except for sector
five; it assessed the benefits EM01, EM03, EM04, EI03, EI04, and EI06 with significant mean
differences of 0.512, 0.535, 0.504, 0.603, 0.522, and 0.576 less than G5. Concerning G5, it
has significant differences for benefits more than G6 by mean of 0.513, 0.519, and 0.570, as
shown in Table 6.
As shown in Table 7, discriminant analysis results implied that EI06, EM03, EI03,
EA04, EM01, EM04, EM02, EI02, EI01, and EI04 are listed to discriminate sectors and have a
significant statistical effect. Additionally, EI05, EA01, EA02, and EA03 were removed from
the analysis. The results implied that 10 benefits out of the 14 that discriminated against
sector five are EIs, 4 EMs, and one EA. The results show that 5 EIs (water contamination,
general environmental performance, pollution of air, waste reduction and management,
and energy and resources consumption) have a significant discriminant effect on classifying
the six sectors. It seems likely that these results are, in fact, due to the importance of EIs
for organizations in different sectors varies, as organizations focus on using indicators that
directly reflect their activities and have direct effects on their cost and competitiveness.
Furthermore, results show that the four EM benefits, EM01, EM02, EM03, and EM04, have
a significant discriminant effect on classifying the six sectors. It seems likely that these
results are, in fact, due to the variation in management procedures and administrative
efforts adopted by organizations working in different sectors. Regarding the EA dimension,
results show that managers’ involvement benefit has a significant discriminant effect on
classifying the six sectors. It seems likely that these results are, in fact, due to ISO 14001 in
clause 50.1 restricts that management should demonstrate leadership and commitment to
the EMS [
53
]. Thus, this benefit varies from one sector to another based on the manager’s
effort to reduce the effect of their processes on the environment.
There may be some possible limitations in this study. The first is that possible method-
ological limitations of the study were a lack of prior research studies on the topic due to the
difficulty in collecting reliable data from organizations in different countries. This allows
researchers to develop an entirely new research typology in comparing ISO 14001 benefits
based upon robust statistical techniques such as N-ways MANOVA and profile analysis as
a need for further development in the area of study. The second limitation concerns the
perception scale assumed that the variables are independent and may affect the study’s
results. This opens a chance for making pairwise comparisons among benefits pairs and
the use of analytical hierarchal process methodologies to further investigate the effects of
implementing the standard. The third limitation concerns the long period of sampling that
may affect the results of the study and open a research direction for monitoring the per-
Sustainability 2022,14, 5025 15 of 19
ceptions of environmental managers towards the standard implementation by increasing
the years of receiving the ISO 14001 certificate. Finally, a possible cultural limitation of
contacting environmental managers of females in Saudi Arabia due to the religious nature
of the country leads to a lack of females who works as environmental managers.
5. Conclusions
In this study, we examined the industrial sectors’ perceptions of the benefits of im-
plementing the ISO 14001 standard in Saudi Arabia using MANOVA-DA methodologies.
The benefits were categorized into three main categories: environmental management,
environmental indicators, and environmental awareness and social aspects. The envi-
ronmental management category includes rigor and effectiveness of practices, regulatory
compliance, greener supply chain, and documentation control. Environmental indicators
include waste minimization and management, air pollution, environmental performance
in general, energy and resources consumption, environmental risks and safety issues, and
water contamination. Environmental awareness and social aspects benefits include image
and stakeholders, employee involvement, employee training and knowledge, and manager
involvement. We compared the mean vectors of environmental managers’ perceptions
of implementing the standard for 120 organizations belonging to six industrial sectors:
fibers and chemicals, plastic and rubber products, fabricated metal products, construction,
wholesale and retail trade, and engineering services fields. MANOVA results showed that
the mean vector representing the evaluations of environmental managers was not equal to
the benefits of implementing ISO 14001. Results of the discriminant analysis showed that
10 of 14 benefits could be considered discriminant factors for sectors, where the benefits
of environmental management and environmental indicator dimensions were more able
to discriminate sectors than the benefits of EA dimensions. Although the previous results
indicated that there is a discrepancy in the effect of adopting ISO 14001 in general on the
dimensions of environmental management, environmental performance indicators, and
environmental awareness, from a positive effect to no effect, our study proved a positive
relationship between the ISO 14001 adoption and the 14 environmental benefits mentioned
in this study.
The results may differ if measured for other industries not covered in this study.
Furthermore, results may vary according to the geographical scope of data collection on
a global scale. In addition, the study’s results can vary according to the company’s size
and the number of years of ISO 14001 certification. Regardless, our results indicate the
need for practitioners and ISO 14001
0
implementers to reconsider determining the relative
benefit importance and allocating their resources to achieve the greatest benefits levels at
the lowest costs, with priority given to environmental performance indicators that directly
affect the environment. Our results open a new avenue of study that focuses on studying
the disparity between the benefits of implementing ISO 14001 on a global scale, which
will provide basic information and data sources that can be used to identify EIs for each
industry that can be integrated into the development of the international standard. If
the benefits vary on a global scale, it is possible to make a kind of normalization of these
benefits for ease of comparing the benefits of organizations in different sectors and linking
this to the allocated funds of the organizations to monitor and improve the implementation
of ISO 14001 standard. Finally, a natural expansion of this study might be the use of other
discriminant analysis methodologies. Furthermore, there is an urgent need to investigate
combining ISO 9001:2015, ISO 14001:2015, and ISO 45001:2018 in one standard that has a
significant impact on reducing the administrative efforts made by institutions to maintain
quality, environment, and safety for their work.
Author Contributions:
Conceptualization, M.M. and S.D.; methodology, M.M.; software, S.A.; vali-
dation, M.R., S.A. and M.M.; formal analysis, S.D.; investigation, M.M.; resources, S.A.; data curation,
S.A.; writing—original draft preparation, M.M.; writing—review and editing, S.A.; visualization,
M.R.; supervision, M.M.; project administration, S.A.; funding acquisition, M.M. All authors have
read and agreed to the published version of the manuscript.
Sustainability 2022,14, 5025 16 of 19
Funding:
We would like to thank King Khalid University’s deanship of scientific affairs and the
Ministry of Education in Saudi (Asser Saudi Arabia) for their help with communicating with indus-
trial organizations during the data gathering process. This research was financed by King Khalid
University through its general research program funds [grant number R.G.P.1/220/41]. The au-
thors were solely responsible for the content, and it does not represent the official opinions of King
Khalid University.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement:
Data used during the study are available in a repository online in
accordance with funder data retention policies at Figshare at: https://doi.org/100.6084/m9.figshare0
.19322177.v1, accessed on 16 March 2022.
Acknowledgments:
We take this opportunity to pass our sincere gratitude to the anonymous review-
ers for their thorough reading of our manuscript, as well as their insightful remarks and suggestions.
We also appreciate the deanship of scientific affairs of King Khalid University, Saudi Ministry of
Education (Asser, Saudi Arabia), for their help with communicating with industrial organizations
during the data collection phase.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A
Table A1. Perceptions about the Benefits of Implementing ISO 14001 Standard Questionnaire.
A 9-Point Likert Scale Questionnaire
Importance Evaluation of ISO 14001:2015 Benefits
Organization official name:
Organization’s economic activity: please, select one economic activity for your organization.
(a) Chemicals, chemical products &
fibers #(b) Construction #
(c) Rubber and plastic products #(d) Wholesale & retail trade, repairs of motor vehicles, motorcycles & personal &
household goods #
(e) Basic metal & fabricated metal
products #(f) Engineering services #
Organization
size: low #Medium #Large #
ISO 14001 year of certification:
Before
2006
#2006–2007 #2008–2009 #After 2009 #
Sex: Male #Female #
Age: 35–45 years #46–50 years #Above 50 years #
Position:
CEO #President #Vice President #Manger #
Years of experience in current position:
2–5 years #6–10 years #Above 10 years #
For the next 14 questionnaire items, please choose a number from 1–9 and mark the appropriate importance below to indicate how much you agree with this
statement.
Extremely
Unimportant
Very
Unimportant Unimportant Maybe
Unimportant Unsure Maybe
Important Important Very
Important
Extremely
Important
1 2 3 4 5 6 7 8 9
1. Please rate the importance of “Rigour and effectiveness of practices” benefit from implementing ISO 14001:2015 standard in your organization.
# # # # # # # # #
2. Please rate the importance of “Regulatory compliance” benefit from implementing ISO 14001:2015 standard in your organization as a 9-point scale.
# # # # # # # # #
3. Please rate the importance of the “Greener supply chain” benefit from implementing ISO 14001:2015 standard in your organization.
# # # # # # # # #
4. Please rate the importance of “Documentation control” benefit from implementing ISO 14001:2015 standard in your organization.
Sustainability 2022,14, 5025 17 of 19
Table A1. Cont.
A 9-Point Likert Scale Questionnaire
Importance Evaluation of ISO 14001:2015 Benefits
# # # # # # # # #
5. Please rate the importance of “Waste minimization and management” benefit from implementing ISO 14001:2015 standard in your organization.
# # # # # # # # #
6. Please rate the importance of “Air pollution” benefit from implementing ISO 14001:2015 standard in your organization.
# # # # # # # # #
7. Please rate the importance of “Environmental performance in general” benefit from implementing ISO 14001:2015 standard in your organization.
# # # # # # # # #
8. Please rate the importance of “Energy and resources consumption” benefit from implementing ISO 14001:2015 standard in your organization.
# # # # # # # # #
9. Please rate the importance of “Environmental risks and safety issues” benefit from implementing ISO 14001:2015 standard in your organization.
# # # # # # # # #
10. Please rate the importance of “Water contamination” benefit from implementing ISO 14001:2015 standard in your organization.
# # # # # # # # #
11. Please rate the importance of “Image and stakeholders” benefit from implementing ISO 14001:2015 standard in your organization.
# # # # # # # # #
12. Please rate the importance of “Employee’s involvement” benefit from implementing ISO 14001:2015 standard in your organization.
# # # # # # # # #
13. Please rate the importance of “Employee’s training and knowledge” benefit from implementing ISO 14001:2015 standard in your organization as a 9-point scale.
# # # # # # # # #
14. Please rate the importance of “Manager involvement” benefit from implementing ISO 14001:2015 standard in your organization.
# # # # # # # # #
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