Assessing Strategic Business and IT Alignment:
Validation of a Novel Model across Moroccan Enterprises
AOUATIF BENKHAYAT
Laboratory of Studies and Research in Applied Mathematics,
Mohammadia School of Engineering, Mohamed V,
University of Rabat,
MOROCCO
Abstract: - Strategic alignment between Business and IT remains a critical factor for organizational
effectiveness, but measuring it often presents a complex challenge. This paper evaluates the model we proposed
in previous work to measure the degree of alignment between Business strategy and IT initiatives. We applied
the model to a selection of Moroccan companies. We compared the alignment scores obtained with those from
the established Strategic Alignment Maturity Model (SAMM) using Cohen's Kappa and simple linear
regression for comparative analysis. This study demonstrates our model's effectiveness in evaluating
continuous scores and provides substantial concordance in categorical maturity assessments. Our validation
confirms that our model can apply to various business contexts, paving the way for further refinement to
evaluate business-IT alignment strategies.
Key-Words: - Business-IT alignment, strategic alignment, Business strategy, IT strategy, strategic alignment,
business performance, strategic alignment maturity.
Received: May 6, 2023. Revised: February 22, 2024. Accepted: March 13, 2024. Published: April 12, 2024.
1 Introduction
Since the 1980s, Business and IT alignment has
been a significant topic of concern. In our current
digital environment, the need for this alignment is
imperative. Raza Ur Rehman Qazi, in his 2018
study, notes that companies that fail to align their
Business strategies and infrastructures with
technological advancements tend to struggle, [1].
Tarafdar and colleagues, in 2020, highlighted the
importance of IT alignment for organizations'
abilities to innovate and adapt in the digital age, [2].
The IBM Global CEO Study of CEOs explains that
companies have to deal with a gap in integrating
Business and technology, which could lead to lower
customer satisfaction, slower adaptation speed, and
less process flexibility.
Following Gao and Sarwar, we argue that a lack
of strategic alignment is the primary reason for these
failures, where managers need to leverage the
alignment of vision, mission, and objectives with
the information systems, [3]. Strategic alignment is
about harmonizing information system strategies
with Business strategies, [4], [5], to serve
productivity, performance, and success, [6], [7], [8].
This should be management’s top priority, and we
strive to find its potential antecedents, which
subsequently facilitate greater competitiveness, [9],
and performance, [10].
The importance of strategic alignment is well
established. Still, there is a need for up-to-date
instruments tailored explicitly for measuring
business-IT alignment in the context of
contemporary challenges. A recent review by
Martinez and Turner, in 2021, illustrates this gap,
noting the changes in the Business environment due
to the rise of artificial intelligence, machine
learning, and other advanced technologies, [11].
In the literature, many approaches have been
proposed to address strategic alignment. For
instance, in requirement engineering, there is a push
to represent the organization’s strategic orientations,
objectives, activities, and the process used to
achieve these objectives in the same model.
Frameworks like B-SCP, [12], Zachman, and
TOGAF, [13], while valuable, do not offer a
dedicated methodology to formalize strategic
alignment, which would support systematic
reasoning about the synergy between organizations'
strategies and IT, [14].
Our proposed model, [15], addresses this gap
by explicitly focusing on the synergy between
Business and IT strategies, offering a more
structured and comprehensive framework for
measuring the strategic alignment in organizations.
This paper aims to validate our model, based on
the strategic frameworks of Miles and Snow, [16],
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[17]. We employ a comprehensive questionnaire
disseminated among leading Moroccan companies
to test our model. The goal is to evaluate the
alignment between IT and Business. By comparing
our results with the Strategic Alignment Maturity
(SAMM) framework, inspired by Henderson and
Venkatraman’s SAM model, [18], we add depth to
our analysis. The SAMM framework includes five
levels of strategic alignment maturity and six
maturity factors, [19]. Our study seeks to support
the hypothesis that a mature strategic alignment
arises from the parallel alignment of Business and
IT orientations. We use Cohen’s Kappa and linear
regression analysis as our verification methods to
confirm this hypothesis.
2 Theoretical Background
2.1 Business-IT Alignment
A large number of researchers have proposed
various concepts related to strategic alignment.
Achieving alignment requires an ongoing effort of
strategic planning, goal realignment, and
implementation of best practices in supporting and
shaping Business strategies. Through strategic
alignment, the aim of IT now is not only to improve
efficiency but also to improve Business
effectiveness and manage organizations more
strategically.
The importance of alignment has been widely
recognized and well documented; however, many
companies still need to be aligned. This is due to the
need for a practical model to identify the degree of
alignment and how to maintain it.
Luftman and BRIER propose a framework to
measure the strategic alignment maturity, [20],
based on the model SAM. This model provides a
tool to evaluate the maturity of their strategic
choices and alignment activities and identify areas
where they can achieve a higher level of alignment,
[18].
In [21], it is created an instrument to measure
the maturity of business-IT alignment based on
SAM. They use the six categories in Table 1
(Appendix), which contains 39 items, for assessing
alignment. For each item, the manager answers five
choice scales, representing a different level of
maturity. An answer of one indicated the lowest
level of maturity, and an answer of five showed the
highest.
Depending on how an organization scores the
components of each factor, one of the five levels of
strategic alignment maturity is assigned to the
organization. The five process levels are:
1) Initial/Ad Hoc Process – Business and IT
are not aligned or harmonized;
2) Committed Process – the organization has
committed to becoming aligned;
3) Established Focused Process – Strategic
Alignment Maturity established and focused
on Business objectives;
4) Improved/Managed Process – Reinforcing
the concept of IT as a Value Centre;
5) Optimized Process – Integrated and co-
adaptive Business and IT strategic planning.
2.2 Proposed Model
Our study adopted the Miles and Snow typology for
categorizing organizational strategies into distinct
types. Although traditionally, this typology includes
four categories—Prospector, Defender, Analyzer,
and Reactor, we have chosen to focus on three:
Prospector, Defender, and Reactor. We have made
this decision because the Analyzer category
represents a blend of Prospector and Defender
characteristics, which could potentially obscure the
distinct impacts of each strategy on IT alignment.
Excluding the Analyzer ensures a more precise and
robust analysis.
Prospectors are characterized by their
innovation and pursuit of new market opportunities.
Defenders focus on operational efficiency and
market share protection. Reactors, by contrast, lack
a consistent strategic orientation, reacting to
external pressures rather than following a proactive
strategy.
In our previous research, we developed distinct
metrics for each strategy type, [15]. For the
Business prospector strategy, we focus on exploring
new opportunities, market position over immediate
profitability, and reducing prices to gain market
share. The defender strategy emphasizes stability,
control, and quality improvement. Reactor strategy
metrics concentrate on cost efficiency and market
responsiveness; they include protecting market
share by adjusting product quality and pricing and
investing in new technologies to keep up with
market trends. These customized metrics showed
how each strategy type has a different approach.
We developed distinct metrics for each IT
strategy type, [15]. The IT Prospector strategy,
driven by innovation and market dominance,
identified indicators like using competitive
intelligence systems, employing IT for marketing
and promotions, and relying on IT to manage
customer feedback and service delivery. For the IT
Defender strategy, the metrics include using IT to
optimize Business processes and support R&D.
Finally, the IT Reactor strategy, emphasizes agility
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and cost-efficiency, leverages IT to safeguard
market share, track market trends, and cut
production and market costs. These metrics
complement those established for the Business
strategy types, offering a comprehensive view of
strategic alignment as presented in Figure 1.
Fig. 1: Representation of Business and IT strategy
according to Miles and Snow, [15]
We used a comprehensive questionnaire
completed by IT and Business management
representatives within the organizations to measure
the alignment between IT and Business strategies.
Responses were based on a 1 to 9 scale, with 1
representing equal importance, indicating that both
factors contribute equally to the objective, and 9
representing extreme importance of one activity
over the other, [15].
This approach produced two distinct matrices,
which specifically reflect the perspectives of IT and
Business see Table 2 (Appendix). By employing the
Analytic Hierarchy Process (AHP) method, [22], we
normalized the data within these matrices, deriving
a priority vector for each strategy. The extent of
alignment is then determined by assessing the
congruence between these vectors, effectively
quantifying the degree to which IT and Business
strategies are synchronized.
VB= is the Business matrix priority
And VIT= is the IT matrix priority.
Alignment is measured using the formula K, as
detailed in our previous work, [15], which calculates
the difference between the Business and IT strategy
priority matrices. A perfect alignment of 100% is
indicated when VB and VIT are equal.
K= 100-[(xp1+ xp2+ xp3) - (yp1+ yp2+ yp3)
+ (xd1+ xd2+ xd3) - (yd1+ yd2+ yd3)) + (xr1+ xr2+ xr3) -
(yr1+ yr2+ yr3) ].
(1)
3 Validation of the Proposal Model
To ensure the reliability and applicability of our
model, [15], we tested it on 13 Moroccan
companies. These same companies had previously
been assessed using the SAMM model, as presented
in [19]. This choice was deliberate; the SAMM
model is widely recognized in strategic alignment
and serves as a comparison benchmark. After
obtaining the results from both models, we did a
comprehensive statistical analysis. We utilized
correlation analysis to ascertain the linear
relationship between our model's outcomes and
those from the SAMM model. To further
substantiate the validity of our findings, we also
applied Cohen's Kappa coefficient, which provided
an additional layer of validation by measuring the
level of agreement between the categorical
assessments of both models.
3.1 IT Issues in Morocco
Morocco's economy is on the upswing, prompting
companies to invest more in technology. This
investment aims to make tasks easier and help
employees work more efficiently. However, many
managers, especially in the industrial production
sectors, still need to give it the importance it
deserves. They may need to recognize the potential
benefits technology fully can bring to their
Business, how to structure their IT teams
effectively, or how to maximize the return on their
tech investments.
Yet, it is clear that things are changing. Instead
of just sticking to basic computer tasks, many
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Moroccan businesses are venturing into advanced
systems. They are exploring tools like ERP, which
helps manage different parts of a Business, and new
methods to keep track of their products and
deliveries, known as supply chain management.
Nevertheless, these tools are not plug-and-play; they
need proper setup and maintenance. It means the IT
department has to collaborate with other teams in
the Business more than ever before.
This trend emphasizes the need for a strong
partnership between tech experts and other
departments in a company. As Businesses in
Morocco continue to evolve, having everyone on the
same page will ensure they get the most out of their
tech investments.
3.2 Instrument Used
A comprehensive survey was administered to 39
executives, spanning IT and Business roles, from 26
distinct Business units within 13 companies. The
survey consisted of two separate questionnaires: one
designed for IT and the other for Business strategy.
Each executive was tasked with expressing their
preference between two options using a nine-point
scale, [15].
To guarantee the accuracy and relevance of the
questionnaire content, it was critically examined by
two scholars specializing in business-IT alignment.
Their insights were solicited for potential
augmentations, omissions, or adjustments to the
content. Based on their feedback, minor alterations
were made. Subsequently, a pilot test of the
questionnaire was conducted to ensure its clarity
and comprehensibility.
3.3 Data Collection
Thirteen Moroccan companies participated in our
study, offering a diverse snapshot of the nation's
industrial landscape. Participants included the
country's primary telecommunication operator, the
national railway and highway companies, and the
official post office. Additionally, the study
encompassed three manufacturing entities and six
enterprises from the financial, insurance, and service
sectors, further details of which can be found in
Table 3.
These companies vary significantly in size. The
most prominent employed approximately 9,000
people, while the smallest employed about 500. It is
important to note that five of the thirteen were
publicly traded companies. With total revenues
ranging from an astounding 6.5 billion Dirhams to
1.2 million Dirhams, their financial imprint was as
varied. This range emphasizes the diverse scale and
size of the study’s entities and offers a
comprehensive view of IT and business alignment
across Morocco’s different industries and firm sizes.
Table 3. Interviewed companies
Company
Area of operation
Souriau Esterline
Connection technology producer
Maroc Telecom
Telecommunication operator
ONCF
Moroccan railway company
Sofac
Credit institution
Capgemini
IT service company
Barid Al Maghrib
Letters and parcel delivery
company
Nexans
Manufacture of industrial wires
and cables and
fiber optic cables
Metallurgy anonym
A company in the metallurgy
sector which preferred to remain
anonymous
SGMB
Bank
RMA Assurance
Insurance company
GROUPE AFMA
Insurance broker
ADM
National company in charge of
building,
maintaining and operating the
motorway network
A-SIS
Publisher and integrator of
complete solutions
for logistics
The questionnaire was given to managers
through Google Forms. After gathering all the
responses, we structured and processed the data
using the Analytic Hierarchy Process (AHP)
technique [22]. We determined the Business and IT
direction vectors for every participating
organization. The degree of alignment, as shown in
Table 4, varied from 4% to 77%. This considerable
variation indicates that many Moroccan businesses
have a big chance to improve alignment. Prioritizing
this alignment will help the Business reach.
We utilized the SAMM assessment tools to
confirm the validity and reliability of our model and
its capacity to yield a precise alignment measure.
These tools are based on best practices for strategic
alignment between IT and business, derived from
extensive literature examinations carried out by
academic experts, [23]. Table 5 (Appendix) provides
the alignment maturity levels of the participating
companies as evaluated using the SAMM tools. This
comparative analysis provides a clear benchmark,
ensuring that the results of our model correspond
with accepted practices.
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Table 4. Alignment degree using the Benkhayat
model
Compagnie
Souriau Esterline
Maroc Telecom
ONCF
Sofac
Capgemini
Barid Al Maghrib
Nexans
Metallurgie
SGMB
RMA Assurance
GROUPE AFMA
ADM
A-SIS
Based on this evaluation, the degree of
alignment maturity ranges from level 2 to level 4. In
all SAMM model categories, companies scored at
level three on average. This suggests that most
organizations that participated in the survey have a
well-established alignment procedure that closely
corresponds with their business objectives. We used
the following formula to get the percentage
representation for each level:
P=Level*100/5 (2)
3.4 Data Analysis
3.4.1 Analysis using Linear Regression
We employed a simple linear regression analysis to
cross-validate the degree of alignment determined
by our model. Linear regression was selected for its
simplicity and effectiveness in clarifying the
relationship between variables. This analytical
approach facilitates quantifying the strength and
nature of the correlation between the results of our
model and the SAMM model's 'P' values. A
significant correlation between the two would
validate the efficacy of our instrument. Our
regression analysis yielded an R² value of 0.787,
which is statistically significant with a p-value less
than 0.01 (refer to Table 7 for details). The derived
regression equation from this analysis (details in
Table 6) is as follows:
Benkhayat Model[t] = -0.460831 + 1.54919SAMM[t] +
e[t]
Table 6. Multiple Linear Regression - Ordinary
Least Squares
Table 7. Multiple Linear Regression - Regression
and Residual Statistics
Multiple Linear Regression - Regression Statistics
Multiple R
0.8717
R-squared
0.7598
Adjusted R-squared
0.738
F-TEST (value)
34.8
F-TEST (DF numerator)
1
F-TEST (DF denominator)
11
p-value
0.0001033
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation
0.1435
Sum Squared Residuals
0.2266
The computed value of R stands at 0.8717.
Based on Pearson’s correlation coefficient
interpretation, this denotes a strong positive
correlation. In practical terms, this suggests that
when our model indicates a high degree of
alignment, it is likely that the SAMM model will
also show a high degree of alignment maturity, and
vice versa.
Furthermore, the R² value, which represents the
coefficient of determination, is 0.7598. This implies
that our model can explain approximately 75.98% of
the variation in the SAMM alignment maturity.
Essentially, this means that our model can largely
predict the outcomes of the SAMM model.
3.4.2 Analysis using Cohen's Kappa
To further validate and crosscheck the results of our
model, beyond the insights provided by the simple
linear regression, we incorporated Cohen's Kappa
methodology. This statistical technique is renowned
for quantifying the degree of agreement between
two raters or classifications, making it apt to
compare our model (the Benkhayat Model), [15],
and the established SAMM model.
Variable
Param
eter
S.D.
T-STAT
2-tail p-
value
1-tail p-
value
H0:
parameter
= 0
(Intercep
t)
-
0.4608
0.1475
-
3.1240e+0
0
0.00967
4
0.004837
SAMM
+1.54
9
0.2626
+5.8990e+
00
0.00010
33
5.165e-05
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Harmonizing the Models:
Given the SAMM model's inherent 5-level structure,
we needed to recalibrate the Benkhayat Model, [10],
to a comparable format. Accordingly, we demarcated
five levels based on percentage scores:
Level 1 (0-20%)
Level 2 (21-40%)
Level 3 (41-60%)
Level 4 (61-80%)
Level 5 (81-100%)
Following this alignment, the comparative data
for both models is presented in Table 8:
Table 8. Alignment Level Comparisons between
Benkhayat and SAMM Model
Compagnie
Benkhayat
Model
SAMM Model
Souriau
Esterline
Level 1
Level 2
Maroc Telecom
Level 2
Level 3
ONCF
Level 1
Level 1
Sofac
Level 1
Level 2
Capgemini
Level 4
Level 4
Barid Al
Maghrib
Level 2
Level 2
Nexans
Level 4
Level 4
Metallurgie
Level 3
Level 3
SGMB
Level 2
Level 2
RMA
Assurance
Level 4
Level 4
GROUPE
AFMA
Level 2
Level 2
ADM
Level 4
Level 4
a-SIS
Level 3
Level 3
Cohen's Kappa Calculation:
The foundation of Cohen's Kappa involves two
principal probabilities:
po: Observed Proportion of Agreement: This is
the actual frequency of agreement observed
between the two models. In our dataset, 8 out
of 13 companies had a consensus between both
models, giving us the following:
po= 8/13 or roughly 0.6154
pe: Expected Proportion of Agreement by
Chance: This denotes the likelihood of random
agreement. A 4x4 contingency table aids in
determining this, factoring in the frequency
distribution of the two model's classifications.
Table 9. Frequency Distribution for the Benkhayat
and SAMM Model Classifications
Summing the products of the frequencies (see
Table 9) provides an expected agreement of 47.
When normalized by the total number of companies,
the expected agreement is 47/ (13*13) =47/169
pe ≈ 0.2781
Now, using the formula for KAPA
K= ( po- pe)/(1- pe) (3)
This calculation yields a Kappa value close to 0.468.
Interpretation:
A Kappa value of 0.468 suggests a moderate
agreement between the Benkhayat Model, [15] and
the SAMM Model. This indicates that the two
models often concur on the alignment level of a
company, but discrepancies exist. This moderate
agreement suggests that while both models aim to
measure alignment, they prioritize or weigh specific
criteria differently.
4 Discussion
Our analysis indicated that the proposed model has
strengths and opportunities for improvement.
The regression analysis showed that our model is
good at predicting continuous scores, similar to
SAMM. However, transitioning from continuous
scores to maturity levels presents difficulties. The
application of Cohen’s Kappa analysis revealed a
moderate agreement between our model and SAMM,
highlighting the essential requirement to examine the
criteria and thresholds used in grading maturity. This
brings us back to the question of the classification
used: is it too strict or too lenient? On the other hand,
our model could ignore essential SAMM criteria.
Ultimately, the benchmarks or standards
employed in our model to classify maturity levels
should be revised to refine the proposed model. A
comprehensive review of industry standards and
regular stakeholder feedback can improve the
reflection of our model of real-world scenarios.
A thorough examination of SAMM and maybe
other models can also help to understand the
Level
Benkhayat
Model
SAMM
Model
Product of
Frequencies
1
3
2
3 * 2 = 6
2
5
5
5 * 5 = 25
3
2
2
2 *2 = 4
4
3
4
3 * 4 = 12
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complexity of the classification and achieve better
harmony. This implicates the establishment of new
criteria, whether included or not in SAMM.
Considering the dynamic nature of strategic
alignment, our model should be flexible to pursue
future industry changes and market trends. Regular
updates to our model may also guarantee its ongoing
relevance.
5 Conclusion
Our model is based on a matrix representation of
Business and IT strategies. To determine the
alignment, we suggest comparing the priority vectors
within these matrices. The degree of alignment is
equal to the difference between these two priority
matrices.
The model applies to many industries, making it
a valuable tool for any firm seeking to evaluate the
alignment between their business and IT strategies.
Our real-world case studies confirmed this.
The application and validation of our model
produced informative results. It showed remarkable
accuracy in continuous alignment scores, closely
matching the SAMM model’s criteria. This
performance underlines the model’s strong capability
in evaluating alignment from a straight metric
perspective.
However, after moving to assess discrete
maturity levels, specific differences occurred. The
moderate agreement found in Cohen’s Kappa
analysis highlights the differences between our
model and the SAMM model when interpreting and
categorizing alignment maturity. These variances
highlight further areas for improvement,
emphasizing the significance of continuously
evaluating our model’s parameters for maturity level
categorization.
Looking ahead, we intend to include additional
factors that may influence the company's
performance, such as the market tendency, the
workforce, or other parameters. Our adventure has
only begun, and we are excited to refine and expand
this tool to unlock the full potential of efficient
strategic alignment across varied industries.
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[23] Philip G. Bergeron, & Louis Raymond.
Strategic alignment: A process model for
integrating information technology and
business strategies. Journal of Computer
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WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2024.21.78
Aouatif Benkhayat
E-ISSN: 2224-2899
941
Volume 21, 2024
APPENDIX
Table 1. Criteria of alignment maturity [19]
Factor
Components
Communication
Com1: The degree of understanding of Business by the IT functions
Com2: The degree of understanding IT by Business
Com3: The degree of richness of the methods used for the organizational learning
Com4: The style of communication used in the organization
Com5: The degree of knowledge sharing throughout the organization
Com6: The use of IT Business liaisons
Competency
Comp1: Focus on the metrics and processes used to measure the contribution of the IT
Comp2: Focus on the metrics and processes used to measure the Business contribution
Comp3: Degree and the orientation of integrated IT and Business measures
Comp4: Degree of service level agreements
Comp5: Frequency and formality of benchmarking practices
Comp6: Frequency and formality of IT assessments and reviews
Comp7: Degree of continuous improvement practices
Comp8: Contribution of IT in strategic objectives.
Governance
Gov1: The degree of Business strategic planning with IT involvement
Gov2: The degree of IT strategic planning with Business Involvement
Gov3: Basis of budgeting IT resources
Gov4: Basis of IT investment decision
Gov5: Frequency, formality, and effectiveness of IT steering committees
Gov6: Integration of IT projects prioritization
Gov7: responsiveness of IT functions to changing Business needs
Partnership
Part1: The Business’ perception of the role of IT
Part2: The role of IT in strategic Business planning
Part3: Integrated shared risks and rewards
Part4: Formality and effectiveness of partnership program
Part5: Perception of trust and value
Part6: Reporting level of Business sponsor/champion
Technology scope maturity (SCOPE)
SCOPE1: Technological and strategic sophistication of primary systems/ applications
SCOPE2: IT standards articulation and compliance
SCOPE3: Degree of architectural integration
SCOPE4: Degree of infrastructure transparency
SCOPE5: Degree of infrastructure flexibility
Skills maturity
Skills1: Degree of cultural innovation
Skills2: Degree of integrated locus of power in IT-based decisions
Skills3: Degree of a change readiness culture
Skills4: Degree of opportunity for skills enrichment through job transfer
Skills5: Degree of opportunity for skills enrichment through cross-training or job rotation
Skills6: Degree of interpersonal interaction across IT and Business
Skills7: Ability to attract and retain IT staff with technical and Business skills
Table 2. Business/It Strategy Matrix
Business Strategy
Prospector
Defender
Reactor
P1
P 2
P 3
D1
D2
D3
R1
R2
R3
P 1
1
A12
A13
A14
A15
A16
A17
A18
A19
P 2
10-A12
1
A23
A24
A25
A26
A27
A28
A29
P 3
10- A13
10- A23
1
A34
A35
A36
A37
A38
A39
D1
10- A14
10- A24
10- A34
1
A45
A46
A47
A48
A49
D2
10- A15
10- A25
10- A35
10- A45
1
A56
A57
A58
A59
D3
10- A16
10- A26
10- A36
10- A46
10- A56
1
A67
A68
A69
R1
10- A17
10- A27
10- A37
10- A47
10- A57
10- A67
1
A78
A79
R2
10- A18
10- A28
10- A38
10- A48
10- A58
10- A68
10- A78
1
A89
R3
10- A19
10- A29
10- A39
10- A49
10- A59
10- A68
10- A79
10- A89
1
Total
X1
X2
X3
X4
X5
X6
X7
X8
X9
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Volume 21, 2024
Table 5. Companies' Maturity Assessments
Communication
Competency/Value
Governance
Partnership
Scope &
Architecture
Skills
Overall
Maturity
Souriau Esterline
2,2
2,1
2,3
1,5
2,4
2,7
Level 2
Maroc Telecom
3,5
2,8
2,7
2,8
4,0
2,6
Level 3
ONCF
1,3
1,4
1,1
1,8
1,4
1,7
Level 1
Sofac
3,0
2,3
3,9
3,0
2,6
2,4
Level 2
Capgemini
3,5
4,4
5,0
4,5
4,8
4,1
Level 4
Barid Al Maghrib
3,5
3,3
3,6
2,8
2,2
2,3
Level 2
Nexans
4,0
4,3
4,4
4,3
4,0
4,7
Level 4
Metallurgy
anonym
3,8
3,5
2,9
3,2
2,6
2,3
Level 3
SGMB
3,5
3,1
2,3
2,5
2,8
2,6
Level 2
RMA Assurance
4,2
4,4
4,3
4,2
4,2
3,6
Level 4
GROUPEAFMA
2,0
2,1
2,0
1,7
2,8
2,3
Level 2
ADM
4,7
3,9
3,7
4,5
4,2
4,4
Level 4
A-SIS
3,7
3,4
2,9
3,7
3,6
3,6
Level 3
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2024.21.78
Aouatif Benkhayat
E-ISSN: 2224-2899
943
Volume 21, 2024