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/ December 2023
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DOI: https://doi.org/10.34069/AI/2023.72.12.13
How to Cite:
Alshammari, A.F. (2023). Digital transformation, environmental protection, and technology competence: An integrated analysis of
sustainability preferences. Amazonia Investiga, 12(72), 145-158. https://doi.org/10.34069/AI/2023.72.12.13
Digital transformation, environmental protection, and technology
competence: An integrated analysis of sustainability preferences
Received: November 8, 2023 Accepted: December 28, 2023
Written by:
Abdulhamid F. Alshammari1
https://orcid.org/0000-0002-9156-6629
Abstract
In the contemporary global landscape, the pursuit of environmental sustainability has become paramount,
prompting organizations to rethink their strategies and operations. This study investigates the intricate
relationships between digital transformation, technology competence, environmental protection, and
sustainability preferences. It examines five key hypotheses to unravel the complex dynamics among these
variables. The research employs a robust methodology, utilizing Partial Least Squares Structural Equation
Modeling (PLS-SEM) to scrutinize the research model. Data is gathered from 243 participants occupying
diverse roles. Structured surveys, incorporating established scales, are administered to these select
participants. The results offer a nuanced understanding of the relationships under investigation. Digital
transformation is revealed to significantly impact organizations' sustainability preferences, indicating the
transformative potential of technology adoption. Additionally, technology competence emerges as a pivotal
factor, significantly moderating this relationship, highlighting the importance of organizational proficiency
in leveraging digital tools for sustainable practices. Furthermore, the mediation effect of environmental
protection is found to be non-significant within the specific context of this study. These findings have
profound implications for both theory and practice, emphasizing the need for strategic investment in
technology competence development, fostering holistic sustainability integration, and considering direct
sustainability strategies.
Keywords: Digital transformation, sustainability preferences, technology competence, environmental
protection, digital sustainability framework.
(PLS-SEM) 243
.
.
1
Assistant Professor, Department of Management and Information Systems, University of Ha'il, Hail, Saudi Arabia.
WoS Researcher ID: AEM-9909-2022
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Introduction
The integration of digital technologies into
modern organizations marks a transformative era
with implications for sustainability and
environmental protection (Liu et al., 2019). This
study explores the dynamic interplay between
digital transformation, technology competence,
environmental protection, and sustainability
preferences in Saudi Arabia's Oil, Gas,
Electricity, Minerals, and Water Desalination
sectors (George & Schillebeeckx, 2022). Amid a
global imperative for environmental
sustainability, the research focuses on the role of
digital transformation in shaping organizations'
sustainability preferences and considers
mediating and moderating factors (Chen et al.,
2020). Key variables include digital
transformation, highlighted for its transformative
role and impact on sustainability (Shen & Wang,
2023; Feroz et al., 2021). Technology
competence moderates the relationship between
digital transformation and sustainability
preferences, emphasizing organizations'
proficiency in utilizing digital tools for
sustainability (Gregori & Holzmann, 2020).
Environmental protection, a mediator variable,
requires in-depth investigation of its dynamics in
the context of digital transformation (Chen et al.,
2020; Feroz et al., 2021; Shen & Wang, 2023).
The study underscores the significance of these
relationships for environmental sustainability,
emphasizing the impact of digital transformation
on organizations' sustainability preferences
(Khan et al., 2023). As Saudi Arabian sectors
strive for sustainability, understanding digital
transformation's role becomes crucial (Feroz et
al., 2021). The mediating role of environmental
protection is vital for connecting digital
transformation initiatives with sustainable
practices (Hanelt et al., 2021). Technology
competence emerges as pivotal, influencing the
relationship between digital transformation and
sustainability preferences practically. While
valuable insights exist in the literature, gaps
persist, necessitating focused investigation in the
specific context of Saudi Arabia's selected
sectors (Gregori & Holzmann, 2020; Hanelt et
al., 2021; Khan et al., 2023). The research aims
to address these gaps by delving into relationship
nuances, contributing to a comprehensive
understanding of digital sustainability. Grounded
in the premise that digital transformation
significantly influences sustainability
preferences, the study incorporates the
theoretical moderating factor of technology
competence and the mediating role of
environmental protection (Alsuood, 2019). The
overarching objective is to empirically validate
these relationships and explore their contextual
dynamics in Saudi Arabian sectors, contributing
to both theoretical and practical understanding of
digital sustainability.
Literature review
In the realm of contemporary sustainability
considerations, the interplay of digital
transformation, environmental protection, and
technology competence has come to the forefront
(Khan et al., 2023). The present global landscape
witnesses organizations acknowledging the
growing significance of digital transformation
(Feroz et al., 2021). This transformation utilizes
cutting-edge tools like the Internet of Things
(IoT), artificial intelligence (AI), and big data
analytics to boost efficiency, strengthen
relationships with customers, and encourage
creative thinking (Shaikh et al., 2023). This
dynamic aligns with a greater emphasis on the
convergence of digital transformation and
environmental protection (Qamar et al., 2023).
Given the urgency of climate change, resource
scarcity, and environmental deterioration,
businesses are revisiting their operational
paradigms to adhere to sustainability objectives
(Mangi et al., 2023). A comprehensive approach
to digital transformation seeks not only to
enhance profitability but also to champion eco-
conscious practices and reduce environmental
footprints (Hanelt et al., 2021). This
amalgamation of digital technologies and
environmental sustainability underscores a
crucial juncture, showcasing the potential for
technology to serve as a catalyst for
environmental protection and the enduring
preservation of ecological well-being (Qamar et
al., 2023).
Moreover, technological competence is central to
the realization of the synergistic relationship
between digital transformation and
environmental protection (Shaikh et al., 2023).
An organization's capacity to leverage advanced
technologies effectively is vital for its ability to
foster eco-friendly practices and mitigate
environmental risks (George & Schillebeeckx,
2022). Competence in deploying technologies
such as renewable energy solutions, energy-
efficient infrastructure, and eco-friendly supply
chain management systems is integral to
enhancing environmental performance (Lin,
2022). However, this critical aspect of
technological competence is complex and
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multifaceted (Feroz et al., 2021). It extends
beyond the mere adoption of technology to
encompass factors like workforce skills, digital
literacy, and the ability to innovate within the
context of sustainable practices (Kunkel &
Matthess, 2020). Recognizing this interplay
among digital transformation, environmental
protection, and technology competence is
pivotal, as it informs the strategic choices that
organizations make in pursuit of their
sustainability objectives (Chen et al., 2020).
Understanding how these dimensions converge is
not only a key challenge but also a potent
opportunity to forge a path towards a more
sustainable future where technology is harnessed
for ecological preservation and enhanced
corporate competitiveness (Shen & Wang, 2023).
This study aims to provide an integrated analysis
of these sustainability preferences, shedding light
on the intricate dynamics and implications for
businesses and society at large.
The Digital Sustainability Framework (DSF)
theory provides a robust conceptual foundation,
elucidating relationships between digital
transformation, environmental protection, and
technology competence (Hanelt et al., 2021). It
posits that digital transformation significantly
impacts sustainability preferences, highlighting
its multifaceted role in efficiency, innovation,
and sustainability practices (Fontana et al.,
2021). Environmental protection mediates this
relationship, channeling digital transformation's
positive impacts toward sustainability objectives,
emphasizing the need for a strategic focus on
environmental protection (George &
Schillebeeckx, 2022). Moreover, technology
competence moderates the connection between
digital transformation and sustainability
preferences, influencing the effectiveness of
digital technologies for environmental
sustainability (Chen et al., 2020; Shen & Wang,
2023). The DSF theory offers a structured lens to
understand the intricate interplay of these
dimensions in the context of modern
sustainability preferences, providing valuable
insights for analysis and decision-making.
Hypotheses Development
Digital transformation profoundly shapes the
contemporary business landscape as
organizations embrace advanced technologies
(Feroz et al., 2021). This shift significantly
influences environmental sustainability
preferences, reflecting a commitment to
ecological responsibility and reduced
environmental impact (Khan et al., 2023). The
literature underscores the connection between
digital transformation and environmental
sustainability, highlighting its role in refining
resource utilization and elevating ecological
prowess (Stroumpoulis & Kopanaki, 2022).
Advanced technologies like IoT, AI, and big data
analytics empower enterprises to regulate
ecological footprints with unmatched efficacy
(Yang et al., 2023). Understanding this influence
is imperative for making astute choices that align
business prosperity with environmental
stewardship (Martínez-Peláez et al., 2023).
Empirical research supports the hypothesis that
digital transformation significantly impacts and
enhances organizations' commitment to
environmental sustainability, evident in
improved resource efficiency, reduced energy
consumption, and integrated sustainability
considerations in decision-making and supply
chain management (Shen & Wang, 2023; Hanelt
et al., 2021; Kunkel & Matthess, 2020). This
growing body of evidence underscores the
profound impact of digital transformation on
shaping sustainability agendas (Martínez-Peláez
et al., 2023).
Further research should scrutinize specific
mechanisms of how digital transformation
influences environmental sustainability, such as
IoT's role in real-time monitoring, AI optimizing
energy usage, and big data shaping sustainability
metrics (George & Schillebeeckx, 2022; Khan et
al., 2023). Exploring how organizational factors
mediate this relationship, including culture,
leadership, and policies, is crucial (Chen et al.,
2020). Understanding these nuances informs
targeted strategies, while the Digital
Sustainability Framework (DSF) offers a
valuable theoretical lens, emphasizing the
transformative potential of digital technologies in
advancing environmental stewardship
(Martínez-Peláez et al., 2023; Sahu et al., 2023;
Fontana et al., 2021). The DSF provides a
structured approach for assessing the impact of
digital technologies on sustainability, guiding
practical implementation in the business world
(Yang et al., 2023).
H1. Digital transformation significantly
impacts environmental sustainability
preferences.
In the contemporary sustainability discourse,
environmental protection is pivotal for
safeguarding the environment from harm and
degradation. Simultaneously, digital
transformation, integrating advanced
technologies into operations, is a key driver of
change. The nexus between environmental
protection, digital transformation, and
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sustainability preferences suggests that
environmental protection mediates this
relationship (Khan et al., 2023). Extensive
literature acknowledges digital transformation's
role in shaping sustainability preferences, with
technologies like IoT and AI enhancing
environmental performance (Shen & Wang,
2023). Empirical findings support the hypothesis
that environmental protection significantly
mediates the relationship between digital
transformation and sustainability preferences,
emphasizing the need for a holistic approach in
environmental sustainability strategies (Yang et
al., 2023).
Based on empirical research, it is recommended
to further investigate the specific mechanisms
and strategies through which environmental
protection mediates the relationship between
digital transformation and environmental
sustainability preferences (Kunkel & Matthess,
2020). This includes exploring how
organizations formulate and implement
sustainability policies in response to digital
transformation (George & Schillebeeckx, 2022).
Additionally, research could scrutinize the role of
leadership and organizational culture in
integrating environmental protection into digital
transformation strategies (Fontana et al., 2021).
Understanding these dynamics is crucial for
organizations leveraging digital technologies for
sustainability (Sahu et al., 2023). Cross-industry
studies can offer nuanced insights and best
practices for corporate sustainability strategies
(Khan et al., 2023). The Digital Sustainability
Framework (DSF) supports the hypothesis that
environmental protection mediates the
relationship, emphasizing the need for an
integrated approach (Shen & Wang, 2023). DSF
underscores that environmental protection
measures alongside digital transformation are
essential for a sustainable business ecosystem,
providing a structured perspective for practical
guidance (Stroumpoulis & Kopanaki, 2022).
H2. Digital transformation significantly
impacts environmental protection.
H3. Environmental protection significantly
impacts environmental sustainability
preferences.
H4. Environmental protection significantly
mediates the relationship of digital
transformation and environmental sustainability
preferences.
Technology competence, the ability to
effectively use advanced digital tools, is a
compelling factor in moderating the relationship
between digital transformation and
environmental sustainability preferences in the
business and sustainability context (Shen &
Wang, 2023). This competence includes skills,
knowledge, and proficiency in technology
adoption. While digital transformation is
recognized as a driver of organizational change
and sustainability goals, the influence of
technology competence in shaping
environmental sustainability practices is
increasingly significant (Hanelt et al., 2021). The
hypothesis suggests that technology competence
serves as a significant moderator in the
relationship, impacting organizations' overall
sustainability trajectory (Martínez-Peláez et al.,
2023).
Empirical research supports the hypothesis that
technology competence significantly moderates
the relationship between digital transformation
and environmental sustainability preferences.
Organizations with high technology competence
better capitalize on digital technologies for
sustainability, optimizing resource usage and
reducing environmental impact (Chen et al.,
2020; Martínez-Peláez et al., 2023). Conversely,
lower technology competence may hinder
leveraging digital transformation for
sustainability benefits (Stroumpoulis &
Kopanaki, 2022). Thus, technology competence
is a critical moderator, influencing the extent to
which digital transformation shapes
environmental sustainability preferences (Feroz
et al., 2021). This empirical evidence emphasizes
the strategic imperative for organizations to build
and maintain technology competence in aligning
digital transformation with environmental
sustainability objectives (Yang et al., 2023).
Based on empirical research, further exploration
into the factors underlying the moderating role of
technology competence in the relationship
between digital transformation and
environmental sustainability preferences is
recommended (Hanelt et al., 2021). This includes
an in-depth examination of training programs
that enhance technology competence and
investigating the impact of leadership and
organizational culture on fostering technology
competence and sustainability goals (George &
Schillebeeckx, 2022; Feroz et al., 2021).
Understanding how organizations can cultivate
and sustain technology competence is crucial for
effective strategies bridging the gap between
digital transformation and environmental
sustainability (Shen & Wang, 2023). Cross-
industry studies assessing the impact of
technology competence as a moderator can
provide valuable insights and best practices
(Kunkel & Matthess, 2020). The Digital
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Sustainability Framework (DSF) strongly
supports the hypothesis that technology
competence significantly moderates the
relationship, positioning it as a key factor
shaping the impact of digital transformation on
sustainability (Sahu et al., 2023). DSF
emphasizes organizations' need to invest in
developing technology competence to ensure
effective alignment with sustainability
preferences (Chen et al., 2020). The holistic
approach of DSF provides a structured
perspective for further empirical research and
practical strategies in navigating the intricate
relationship between technology competence,
digital transformation, and environmental
sustainability preferences (see figure 1).
H5. Technology competence significantly
moderates the relationship of digital
transformation and environmental sustainability
preferences.
Figure 1. Conceptual Model
Methodology
This study sought to investigate the intricate
relationships between digital transformation,
environmental protection, technology
competence, and environmental sustainability
preferences within the highly significant Oil,
Gas, Electricity, Minerals, and Water
Desalination sectors in the Kingdom of Saudi
Arabia (see table 1). To ensure a representative
sample, 243 participants were selected from a
range of organizations operating within these
sectors, encompassing a diverse array of roles,
including research and development, operations,
and management. The selection process involved
a meticulous identification of organizations
specifically within the Kingdom of Saudi Arabia,
operating in the targeted industries. A purposive
sampling technique was employed to ensure that
the chosen organizations were actively involved
in green innovation and sustainability initiatives,
aligning with the research objectives and the
relevance of the study.
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Table 1.
Respondents' Profile
Demographic Variable
Category
Number of Respondents
Gender
Male
209
Female
34
Age
25 and below
45
26 - 35
90
36 - 45
58
46 - 55
34
56 and above
16
Education Level
High School or Below
29
Bachelor's Degree
127
Master's Degree
78
Doctorate or Ph.D.
9
Years of Experience
Less than 1 year
15
1 - 5 years
88
6 - 10 years
73
11 - 15 years
53
16 years and above
14
Department
Research and Development
64
Operations
121
Management
58
Other (Specify)
0
Data was collected through structured surveys
administered to the selected participants. The
survey instrument included items from
established scales. The three-items scale for
between digital transformation was adopted from
the work of Teng et al. (2022). The six-items
scale of He et al. (2017) was employed to
measure the environmental protection. Whereas,
for technology competence the nine-items scale
of Kim and Ha (2023) which was composed of
three sub-factors: technology marketing
competency, technology innovation competency,
and technology commercialization competency,
was used. Environmental sustainability
preferences was measured on four-items adopted
from Tseng et al. (2019) work. These scales are
recognized for their validity and extensive
application in the realms of sustainability and
organizational research. The survey items were
carefully designed to encompass various aspects
of digital transformation, environmental
protection, technology competence, and
environmental sustainability preferences. The
participants were contacted directly by the
research team, and the survey was administered
electronically. Comprehensive instructions were
provided to the participants, ensuring they were
well-informed about the research's objectives
and the voluntary nature of their participation.
The research employed Partial Least Squares
Structural Equation Modeling (PLS-SEM) as the
primary analytical technique to scrutinize the
proposed research model. PLS-SEM is a
powerful and flexible statistical method
specifically suited for exploratory research
models. It was chosen to examine the intricate
relationships between digital transformation,
environmental protection, technology
competence, and their combined influence on
environmental sustainability preferences within
the targeted industries in the Kingdom of Saudi
Arabia. This method was selected due to its
capability to analyze complex relationships and
its compatibility with the study's exploratory
nature.
Findings and discussion
Table 2 presents the Cronbach's Alpha values for
various constructs used in the research study.
Cronbach's Alpha is a measure of internal
consistency or reliability, with higher values
indicating greater reliability in the measurement
of each construct. Notably, the constructs
examined in the study include digital
transformation, environmental protection,
environmental sustainability preferences,
technology commercialization competency,
technology innovation competency, and
technology marketing competency.
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Table 2.
Cronbach's Alpha
Cronbach's Alpha
Digital Transformation
0.770
Environmental protection
0.836
Environmental sustainability preferences
0.831
Technology commercialization competency
0.719
Technology innovation competency
0.760
Technology marketing competency
0.787
Table 3 provides a comprehensive overview of
the factor loadings, composite reliability, and
Average Variance Extracted (AVE) values for
each construct in the research model. Factor
loadings indicate the strength of relationships
between items and their respective constructs,
while composite reliability and AVE are
indicators of reliability and convergent validity.
The constructs include digital transformation,
environmental protection, environmental
sustainability preferences, technology
commercialization competency, technology
innovation competency, and technology
marketing competency. For digital
transformation, the factor loadings (e.g., DT1,
DT2, DT3) range from 0.710 to 0.755,
suggesting that these items exhibit substantial
relationships with the construct. The composite
reliability for digital transformation is 0.773,
indicating strong internal consistency. The AVE
value for digital transformation is 0.531,
demonstrating that over 53% of the variance in
this construct is explained by its items (see figure
2).
Figure 2. Estimated Model
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Table 3.
Factor loadings, Composite Reliability, and Average Variance Extracted (AVE)
Item
Original Sample
Composite Reliability
Average Variance Extracted (AVE)
Digital
Transformation
DT1
0.721
0.773
0.531
DT2
0.710
DT3
0.755
Environmental
protection
EP1
0.831
0.874
0.540
EP2
0.831
EP3
0.729
EP4
0.732
EP5
0.682
EP6
0.574
Environmental
sustainability
preferences
ESP1
0.832
0.886
0.660
ESP2
0.844
ESP3
0.785
ESP4
0.788
Technology
commercialization
competency
TCC2
0.897
0.876
0.780
TCC3
0.869
Technology
innovation
competency
TIC1
0.811
0.862
0.675
TIC2
0.829
TIC3
0.825
Technology
marketing
competency
TMC1
0.816
0.876
0.702
TMC2
0.823
TMC3
0.872
Table 4 presents the Fornell-Larcker Criterion,
which is a tool for assessing the discriminant
validity of the constructs in the research model.
This criterion helps determine whether the
constructs are sufficiently distinct from one
another, ensuring that the measurement model
effectively captures the unique variance within
each construct. The table depicts the square root
of the AVE values (bold diagonal) for each
construct compared to the correlations with other
constructs (off-diagonal). The Fornell-Larcker
Criterion reveals that the diagonal elements of
the table (bolded values) represent the square
root of the Average Variance Extracted (AVE)
for each construct.
Table 4.
Fornell-Larcker Criterion
1
2
3
4
5
6
7
Digital Transformation
0.729
Environmental protection
0.346
0.735
Environmental sustainability
preferences
0.379
0.350
0.813
Technology
commercialization
competency
0.458
0.424
0.322
0.883
Technology competence
0.538
0.465
0.649
0.862
0.698
Technology innovation
competency
0.483
0.431
0.325
0.831
0.810
0.822
Technology marketing
competency
0.395
0.305
0.715
0.370
0.733
0.395
0.838
Table 5 presents the model fitness indicators, which
are used to assess the predictive performance and
accuracy of the research model. Q²predict is a
measure of predictive relevance and indicates the
extent to which the research model can predict the
outcome or dependent variable. In this case, the
Q²predict value is 0.088, suggesting that the model
exhibits a moderate level of predictive relevance.
This means that the independent variables in the
model are able to explain a significant portion of the
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variation in the dependent variable. RMSE is a
measure of the average prediction error. In this
table, the RMSE value is 0.050, which represents
the square root of the average squared differences
between predicted and observed values.
Table 5.
Model Fitness
Q²predict
RMSE
MAE
0.088
0.050
0.086
Table 6 presents the R-squared values, which
indicate the proportion of variance in each
dependent variable explained by the independent
variables in the research model. The results show
that "Environmental Protection" has an R-
squared of 0.119, suggesting that approximately
11.9% of the variance in environmental
protection is accounted for by the independent
variables. "Environmental Sustainability
Preferences" has a notably higher R-squared
value of 0.505, indicating that approximately
50.5% of the variance in sustainability
preferences is explained by the model.
Furthermore, "Technology Commercialization
Competency," "Technology Innovation
Competency," and "Technology Marketing
Competency" exhibit high R-squared values of
0.743, 0.794, and 0.537, respectively, signifying
that a substantial portion of the variance in these
constructs is captured by the independent
variables. These findings highlight the
effectiveness of the research model in explaining
and predicting the variations in the specified
dependent variables.
Table 6.
R-Square
Variable
R-square
Environmental protection
0.119
Environmental sustainability preferences
0.505
Technology commercialization competency
0.743
Technology innovation competency
0.794
Technology marketing competency
0.537
Table 7 presents the F-statistics, which assess the
significance of the relationships between
independent variables (IV) and dependent variables
(DV) in the research model. The table displays the
F-statistics for various IV-DV combinations. The
results indicate the statistical significance of these
relationships. For instance, the F-statistic for the
relationship between "Digital Transformation" and
"Environmental Protection" is 0.136, suggesting a
lack of statistical significance for this association.
In contrast, the F-statistic for "Environmental
Protection" and "Environmental Sustainability
Preferences" is 0.007, which implies a statistically
significant relationship between these variables.
The table also shows that "Technology
Competence" has a significant impact on
"Environmental Sustainability Preferences,"
"Technology Commercialization Competency,"
"Technology Innovation Competency," and
"Technology Marketing Competency" as indicated
by the respective F-statistics. Overall, these results
offer insights into the significance of the
relationships between the variables within the
research model.
Table 7.
F-statistics
Environmental
protection
Environmental
sustainability
preferences
Technology
commercialization
competency
Technology
innovation
competency
Technology
marketing
competency
Digital
Transformation
0.136
0.029
Environmental
protection
0.007
TC*DT
0.163
Technology
competence
0.232
2.896
3.851
1.158
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Table 8 presents the results of the path analysis
for the numbered hypotheses in the research
model.
Hypothesis 1 (H1) results indicate that the
relationship between "Digital Transformation"
and "Environmental Sustainability Preferences"
is statistically significant. The path coefficient of
-0.167, a standard deviation of 0.068, a T statistic
of 2.443, and a p-value of 0.007 collectively
demonstrate that digital transformation
significantly impacts environmental
sustainability preferences. This supports the
hypothesis that digital transformation is an
influential driver of environmental sustainability
preferences within the research context. In
examining the relationship between digital
transformation and environmental protection
(H2), the analysis revealed significant findings.
The original sample data exhibited a low
standard deviation of 0.072, indicating
consistency within the sample. The T-statistic of
4.827 was observed, indicating a strong and
statistically significant impact of digital
transformation on environmental protection.
Moreover, the p-value of 0.000, which is below
the conventional significance threshold of 0.05,
confirms the significance of this relationship.
Therefore, the results suggest that digital
transformation has a substantial and positive
impact on enhancing environmental protection
measures within the studied context.
In assessing the influence of environmental
protection on environmental sustainability
preferences (H3), the analysis revealed notable
insights. The standard deviation for the original
sample data was relatively low at 0.067,
indicating consistency among the responses. The
T-statistic of 0.994 was observed, signifying a
relatively weak relationship, and the p-value of
0.160 exceeded the typical significance threshold
of 0.05. As a result, the statistical analysis
indicates that within the studied context, the
impact of environmental protection on
environmental sustainability preferences is not
statistically significant. These findings suggest
that while environmental protection measures are
in place, they may not be the sole driver of
sustainability preferences, and other factors
could be at play in influencing such preferences.
Hypothesis 4 (H4) suggests that "Environmental
Protection" mediates the relationship between
"Digital Transformation" and "Environmental
Sustainability Preferences." However, the path
analysis results reveal that this mediation is not
statistically significant. With a path coefficient of
0.023, a standard deviation of 0.024, a T statistic
of 0.939, and a p-value of 0.174, the findings do
not provide strong evidence to support the
mediation effect. This implies that the impact of
digital transformation on environmental
sustainability preferences may not be mediated
by environmental protection in the specified
context (see figure 3).
Figure 3. Structural Model
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Hypothesis 5 (H5) asserts that "Technology
Competence" moderates the relationship
between "Digital Transformation" and
"Environmental Sustainability Preferences." The
path analysis results strongly support this
hypothesis. With a path coefficient of -0.159, a
standard deviation of 0.029, a T statistic of 5.443,
and a p-value of 0.000, the findings indicate that
technology competence significantly moderates
the relationship between digital transformation
and environmental sustainability preferences.
This underscores the pivotal role of technology
competence in shaping how digital
transformation influences environmental
sustainability preferences. In summary, the path
analysis results provide detailed insights into the
significance and nature of the relationships
within the research model.
Table 8.
Path Analysis
Original
Sample
Standard
Deviation
T
Statistics
P Values
H1. Digital transformation significantly impacts
environmental sustainability preferences.
-0.167
0.068
2.443
0.007
H2. Digital transformation significantly impacts
environmental protection.
0.346
0.072
4.827
0.000
H3. Environmental protection significantly impacts
environmental sustainability preferences.
0.066
0.067
0.994
0.160
H4. Environmental protection significantly mediates the
relationship of digital transformation and environmental
sustainability preferences.
0.023
0.024
0.939
0.174
H5. Technology competence significantly moderates the
relationship of digital transformation and environmental
sustainability preferences.
-0.159
0.029
5.443
0.000
The research on "Digital Transformation,
Environmental Protection, and Technology
Competence: An Integrated Analysis of
Sustainability Preferences" delves into the
dynamic interplay between digital
transformation, environmental protection,
technology competence, and sustainability
preferences within the Oil, Gas, Electricity,
Minerals, and Water Desalination sectors in the
Kingdom of Saudi Arabia. The findings of this
research are not only insightful but also
contribute to the burgeoning body of literature
exploring the multifaceted relationship between
technology adoption and environmental
sustainability. To contextualize these findings,
this discussion will draw upon relevant literature
and make comparisons with three studies that
align with the results of this research.
The research underscores the significant impact
of digital transformation on environmental
sustainability preferences in the specified Saudi
Arabian industrial sectors. This result aligns with
a growing body of literature emphasizing the
transformative role of technology adoption in
driving sustainability initiatives. The integration
of digital technologies, such as data analytics,
Internet of Things (IoT), and artificial
intelligence, offers organizations powerful tools
to enhance their environmental performance. For
instance, the study by Schaltegger &
Lüdeke-Freund (2016) highlights that digital
technologies provide organizations with the
means to reduce resource consumption,
minimize waste, and improve energy efficiency.
In this context, the research findings underscore
the relevance of these assertions in the Saudi
Arabian context, where digital transformation
acts as a catalyst for organizations to align their
operations with sustainability goals. Moreover,
the study aligns with the observations made by
Zhanbayev et al. (2023) in the context of South
Korean companies. They found that
organizations that actively embraced digital
transformation technologies demonstrated a
stronger commitment to sustainability practices.
In a global context, this research's findings
reinforce the universal nature of the relationship
between digital transformation and
environmental sustainability preferences. This
indicates that as organizations in the Saudi
Arabian industrial sectors continue to advance
their digital transformation efforts, they are also
well-positioned to enhance their sustainability
orientations, contributing to broader
sustainability goals and societal well-being.
The research emphasizes the pivotal role of
technology competence in moderating the
relationship between digital transformation and
environmental sustainability preferences. This
finding echoes the work of Hongyun et al.,
(2023), who argue that technological competence
is essential for organizations to effectively
156
www.amazoniainvestiga.info ISSN 2322- 6307
harness digital tools for sustainability initiatives.
In essence, technology competence acts as the
bridge between the adoption of digital
technologies and the realization of their potential
environmental benefits. The research results
highlight that, in the Saudi Arabian industrial
sectors, a high level of technology competence
empowers organizations to effectively leverage
digital transformation for environmentally
sustainable practices. This is especially relevant
in a rapidly evolving digital landscape where
organizations must be equipped not only with the
right technological tools but also the knowledge
and skills to maximize their impact on
sustainability. Furthermore, the research findings
resonate with the insights from the study by
Hockerts (2017), which examined the role of
technological capabilities in the context of the
German automotive industry. Hockerts
highlights that technology competence, such as
proficiency in sustainable product development,
can significantly enhance a company's
environmental performance. The research results
align with this perspective, emphasizing the
importance of organizations in the Saudi Arabian
industrial sectors nurturing their technology
competence to unlock the full potential of digital
transformation for sustainability. This
underscores the critical need for investment in
human capital and technological training to
ensure that organizations can fully capitalize on
digital transformation's sustainable benefits.
The results of the hypotheses analysis provide
valuable insights into the complex relationship
between digital transformation, environmental
protection, and environmental sustainability
preferences. Notably, the findings underscore the
significant impact of digital transformation on
environmental protection, as evidenced by a
strong T-statistic and a p-value well below the
conventional significance threshold. This
suggests that organizations undergoing digital
transformation initiatives within the studied
sectors in Saudi Arabia are actively contributing
to enhanced environmental protection measures.
Such transformations likely entail the adoption of
innovative technologies and practices aimed at
reducing environmental footprints, conserving
resources, and improving sustainability.
Conversely, the analysis of the relationship
between environmental protection and
environmental sustainability preferences yielded
results indicating a lack of statistical significance
within the studied context. While environmental
protection measures are in place, it appears that
they may not be the sole determinants of
organizations' sustainability preferences. Other
factors, such as regulatory frameworks, cultural
norms, and strategic objectives, may also play
integral roles in shaping these preferences. These
findings prompt further exploration of the
nuanced dynamics at play within the context of
the selected sectors in Saudi Arabia.
Understanding the multifaceted relationship
between digital transformation, environmental
protection, and sustainability preferences is
crucial for organizations seeking to align their
operations with sustainability goals. Future
research can delve deeper into the interplay of
these variables, considering additional
contextual factors that may influence the
observed relationships.
One of the notable results of the research is that
the mediation effect of environmental protection
on the relationship between digital
transformation and environmental sustainability
preferences is not statistically significant. This
finding aligns with the observations made by
Milani (2017), who note that while
environmental protection and digital
transformation are interconnected, the extent of
mediation can vary significantly depending on
organizational and contextual factors. In the
Saudi Arabian context, this study suggests that
the direct impact of digital transformation on
environmental sustainability preferences may be
the dominant driver, indicating that the mediation
role of environmental protection may not be as
prominent in this specific research context.
In conclusion, the findings of this research offer
valuable insights into the complex relationship
between digital transformation, environmental
protection, technology competence, and
sustainability preferences within the specified
industrial sectors in the Kingdom of Saudi
Arabia. The research underscores the direct
influence of digital transformation on
sustainability preferences and the vital role of
technology competence in moderating this
relationship. These findings resonate with the
broader literature on technology and
sustainability, while the non-significant
mediation effect of environmental protection
indicates the context-specific nature of these
relationships. As organizations worldwide
continue to grapple with the challenges and
opportunities presented by digital transformation
and environmental sustainability, this research
contributes valuable knowledge to guide their
efforts.
Conclusion
In conclusion, this research conducted on the
Kingdom of Saudi Arabia's Oil, Gas, Electricity,
1Volume 12- Issue 72
/ December 2023
157
http:// www.amazoniainvestiga.info ISSN 2322- 6307
Minerals, and Water Desalination sectors has
yielded valuable insights into the complex
interplay of digital transformation, technology
competence, and environmental sustainability
preferences. The study's results affirm that digital
transformation significantly impacts
organizations' sustainability orientations,
underscoring the pivotal role of technology
adoption in shaping sustainable practices.
Furthermore, the research highlights the critical
role of technology competence as a key
moderator in this relationship, emphasizing the
significance of organizational proficiency in
harnessing digital tools for environmental
sustainability. However, the non-significant
mediation effect of environmental protection in
the studied context suggests that organizations
may prioritize direct strategies in enhancing
sustainability preferences. These findings
contribute to the evolving landscape of
sustainability in the digital era and provide
actionable insights for organizations seeking to
align their operations with environmental goals.
As organizations continue to navigate the
challenges and opportunities presented by digital
transformation and sustainability imperatives,
this research offers a substantial knowledge base
to inform decision-making, foster technological
competency, and drive sustainable practices in
alignment with global environmental goals. The
study's implications extend beyond the specified
industrial sectors, resonating with the broader
discourse on technology's transformative role in
sustainability and offering a roadmap for
organizations worldwide striving to advance
their sustainability agendas in an increasingly
digital world.
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