A Model for Implementing Enterprise Resource Planning Systems in
Small and Medium-sized Enterprises
Daniela Tapia
, Paola Vintimilla
, Ximena Alvarez
, Juan Llivisaca
, Mario Peña
Rodrigo Guamán
, Lorena Siguenza-Guzman
and Diana Jadan-Aviles
Universidad de Cuenca, Ecuador
Department of Applied Chemistry and Systems of Production, Faculty of Chemical Sciences,
Universidad de Cuenca, Cuenca, Ecuador
Research Department (DIUC,) Universidad de Cuenca, Cuenca, Ecuador
Department of Computer Sciences. Faculty of Engineering. Universidad de Cuenca, Cuenca, Ecuador
{estefania.tapia, paola.vintimilla, ximena.alvarez, juan.llivisaca, mario.penao, rodrigo.guaman, lorena.siguenza,
Keywords: SMEs, Enterprise Resource Planning, Interpretive Structural Model.
Abstract: Small and medium-sized enterprises (SMEs) are considered dynamic agents within the business environment.
Currently, SMEs have great potential for strong growth and great profit. However, their growth is restricted
by the lack of systems that would allow integrating their data and activities. One possible solution is the
implementation of Enterprise Resource Planning (ERP) systems to increase the company’s level of efficiency,
effectiveness, and productivity. However, implementation processes require investing resources and bring
certain problems, e.g., the difficulty to fully adapt to the organization’s accounting and management
procedures, and lack of experience of end-users in handling ERP systems. The aim of this study is focused on
constructing a model for successfully implementing ERP systems into SMEs. This model used a group of
critical success factors (CSF) to analyze empirical evidence in organizations. To its development, the
interpretive structural modeling methodology was used, and it was validated in a focus group of experts in
implementing and using ERP systems. The results show that the model is adequate for a successful
implementation in SMEs engaged in sales, production, or service activities.
Currently, enterprises face new challenges in
changing markets. For them, it is essential to improve
internal processes to obtain greater profits and
benefits. A factor frequently used to improve
productivity and business competitiveness is
technological innovation. Companies are more likely
to succeed when they make use of technological
advances (Guerrero, Marín, and Bonilla, 2018).
One technological tool for managing the activities
and resources of a production system is Enterprise
Resource Planning (ERP). An ERP system is
designed to integrate all the information coming from
the material flow, workers, and financial resources of
an organization through a common database. These
systems allow efficient and automated management
of manufacturing and production, finance and
accounting, sales and marketing, and human
resources processes (Laudon and Laudon, 2012;
Sánchez, García, and Ortiz, 2017). Several authors
Tapia, D., Vintimilla, P., Alvarez, X., Llivisaca, J., Peña, M., Guamán, R., Siguenza-Guzman, L. and Jadan-Aviles, D.
A Model for Implementing Enterprise Resource Planning Systems in Small and Medium-sized Enterprises.
DOI: 10.5220/0010483200950104
In Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021) - Volume 1, pages 95-104
ISBN: 978-989-758-509-8
2021 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
like Villacreses and Cedeño (2017), Deshmukh,
Thampi, and Kalamkar (2015), and Grandón,
Ramírez, and Rojas (2018) show that implementing
an ERP system benefits companies and achieves
expected results. However, the process of
implementing an ERP system is not always
successful. Rivera, Reyes, and Arévalo (2018) state
that a third of the implementation projects are
unsuccessful; and about 65% of the application cases
fail for several reasons.
It is complex to describe advantages and
disadvantages of ERP systems and their
implementation. Many authors present important
facts that should be taken into account. For example
EL Mrini et al. (2014) state that implementing an ERP
provides a structural change on all the company's
bricks: operational, organizational and cultural. These
authors also mention that the ERP implementation
projects can paralyze the company if they are not
properly implemented. Abugabah (2017) specifies
that ERP systems are viewed as powerful solutions
that help improve productivity, performance and
overall quality; however, the effective use and the
beneficial outcomes from the systems are not
guaranteed nor recognized by many organizations.
In small and medium-sized enterprises (SMEs),
the case of ERP systems implementation projects is
studied in different papers. For instance, Rivera and
Pérez (2013) indicate that some critical factors can
augur success or failure in the ERP implementation,
such as the type of system selected based on the
marketing, production, or service activities. These
challenges appear at internal and external
organization levels. At the internal level, these
systems help maintain control; at the external level,
they can-not be manipulated or changed by the
company (Palomo, 2005). Kauffman (2001) points
out that the limitations for ERP implementation in
SMEs at an internal level are: 1) a lack of efficient
systems of planning, organization, administration,
and control, and 2) insufficient technologies for
managing and developing production. Similarly,
Artola and Artieda (2014) conclude that the SMEs'
weaknesses to automate for their business through an
ERP include: 1) difficulty in accessing credits due to
their high cost, and 2) insufficient financial resources
to support the use of technology.
Besides, ERP requires a high degree of
integration. However, most organizations do not have
defined processes or an appropriate organizational
structure to fully integrate the ERP into their systems.
The idea of solving business integration problems
through ERP systems is attractive; however, the
benefits price is high. Implementing ERP systems
requires high capital investments and considerable
time. The latter influences the organizational culture
of the company. Extensive training, temporary
productivity drops, and slower delivery of orders to
customers during the ERP transition alter the quality
of the enterprise service (EJ Umble and Umble,
In the Ecuadorian context, SMEs are
characterized by their familiar and traditional
structure, often built on the empiricism basis and with
strong change resistance. Nevertheless, this sector has
been really important for boosting local economies
and generating employment.
The objective of the current paper is to establish a
successful ERP implementation model for
Ecuadorian SMEs. To this end, several studies have
been taken as a reference to identify the critical
factors and keys for the implementation success of an
ERP system. In particular, the study by Bernal (2019)
focuses on the Austral business environment in
Ecuador. This study has contributed with a valuable
list of 31 critical success factors (CSF) for the
successful ERP implementation in SMEs. These
factors have been considered from a business
perspective in order to structure and integrate them
into the implementation model.
The purpose of this study is to find a successful model
for ERP implementation in SMEs. The 31 CSF
proposed by Bernal, (2019) were used in the
interpretative structural model.
2.1 Interpretative Structural Model
The interpretive structural model (ISM) complies
with the necessary parameters for its construction,
adapts to the context of the study, and considers a
series of CSF. ISM identifies the relationships among
the components facing the same complex situation.
These relationships are given among factors directly
or indirectly.
Thus, the final model is based on the construction
of three sequential matrices: 1) the structural self-
interaction matrix (SSIM), which is responsible for
establishing the contextual relationship among
factors; 2) then, SSIM becomes a reachability matrix
(binary) where its transitivity is verified; and finally,
3) a multilevel model is obtained which expresses
through a graph the direct and indirect relationships
among analyzed factors.
ICEIS 2021 - 23rd International Conference on Enterprise Information Systems
2.2 Study Sample
A non-probabilistic convenience sampling technique
was used with a focus group of experts in ERP
systems implementations and uses. This process
helped to determine the model’s validity.
2.3 Methodology
The proposed methodology required a previous
literature review regarding fundamental concepts for
its application. The methodology developed during
this investigation is summarized in Figure 1.
Figure 1: Research methodology (Raj, Shankar, and Suhaib,
Step 1: A literature review of topic related factors.
This bibliographic review was considered from two
approaches: Critical factors established from business
experience (16 factors) and Critical factors
established from the personal perception of experts
(22 factors). However, this paper only presents the
business experience approach, because ERP systems
have been used mainly in this sector. In addition, due
to the complexity in the communication that it has in
companies it is very important.
In this step a principal component analysis (PCA)
was performed. According to López and Fachelli
(2015), the criteria to determine the PCA approach
are the following:
1) Consider all factors with an eigenvalue greater
than 1 in terms of the total variance. 2) Consider the
number of axes that accumulates around 70% of the
total variance, however, lower values have been
considered due to their importance. 3) Represent the
factors and the associated eigenvalues graphically, by
observing the behaviour of the resulting curve
through the sedimentation graph.
In this way, necessary components and integrating
factors were determined. The factors of PCA are
detailed in Table 1.
Table 1: Critical Success Factors (Bernal, 2019).
CSF for ERP successful
1 2
CSF: Strategic
Support from Senior
0,912 0,255
x2 Project Management 0,867 0,122
x3 Use of a Steering Committee 0,593 0,398
Business Process
Reengineering BPR
0,114 0,922
x5 Goals and Objectives 0,410 0,831
CSF: Support
Participation of the change
0,854 0,148
x7 Interdepartmental Cooperation 0,805 0,153
x8 Communication -0,002 0,854
Relationship with suppliers and
0,505 0,678
x10 External Consultants 0,523 0,623
CSF: Operational
x11 ERP System Configuration 0,881 0,204
IT Structure and Legacy
0,821 0,095
Skills, Knowledge and
0,776 0,159
ERP System Acceptance /
0,666 0,385
ERP System Organizational
0,088 0,903
Participation of End Users and
0,317 0,830
Step 2: SSIM elaboration with the CSF of Bernal
The SSIM matrix was created using the relationships
proposed by Routroy and Kumar (2014), presented in
Table 2.
As an example, for factor x7, the lower diagonal
indicates that position i influenced the factor x2 that
is in the position j. Then, in the box (7,2), the symbol
"V" was located (Table 3).
A Model for Implementing Enterprise Resource Planning Systems in Small and Medium-sized Enterprises
Table 3: Structural self-interaction matrix.
x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14 x15 x16
x1 -
x2 A -
x3 X A -
x4 A A A -
x5 A X A V -
x6 A X A V A -
x7 A V X V X V -
x8 X X A X A V V -
x9 X A X V A O O X -
x10 X O X V A O O O X -
x11 A A A A A A O O A A -
x12 A A A A A V O O X O X -
x13 A V V V V V V A V V V V -
x14 A A A O A X V A X A A X A -
x15 A A A A A A O A O A A A V O -
x16 A A A X A A X A A A A A A V V -
Table 2: Symbology for the SSIM matrix (Routroy &
Kumar, 2014).
Symbology Description
V Factor i influences or is driven to factor
A Factor
influences or is driven to factor i
X Factor i and factor j are related in both directions
O There is no relationship between factor i and factor
Step 3: Initial (RM) and final (FRM) reachability
matrices elaboration.
First, an isomorphic transformation was made. This
means that the symbol matrix (VAXO) was
transformed into a binary matrix called the initial
reachability matrix (RM). For this, the rules proposed
by Raj, Shankar, and Suhaib (2008), shown in Table
4, were used.
Table 4: Symbology for the RM matrix (Raj, Shankar, and
Suhaib, 2008).
Input (i, j) 1 0 1 0
Input (j, i) 0 1 1 0
Second, the concept of transitivity was
introduced, used to elaborate the final reachability
matrix (FRM). The transitivity rule, given by Rajesh
et al. (2008), consists of relating the factors of the RM
matrix whose value inside its box is zero. In other
words, the transitivity in this study has been
established by constructing the matrix graph (RM).
A brief example of this graph construction can be
seen in Figure 2. Note how a direct relationship
originates from node x2 towards x16 and the same
occurs from node x16 to node x7. Thus, it is
ICEIS 2021 - 23rd International Conference on Enterprise Information Systems
concluded that there is transitivity (dashed line)
between box x2 (i) and x7 (j) which was replaced by
“1a” in the FRM matrix.
Figure 2: Example of transitivity.
The comparisons between the nodes were made in
pairs or by inferences to fill each box where there is a
crossover of matrix variables. Thus, pairwise
comparisons were reduced by 50% to 80%. It is also
an advantage that many relationships in the system
were transitive (Watson, 1978).
Step 4: Conic matrix elaboration to distribute the
CSF by levels.
The conic matrix was prepared based on the matrix
(FRM), and from it, the levels for the location of each
factor within the models were defined.
Step 5: Classification of CSF in the power of
influence and dependence diagram.
For this, factors have been classified into
autonomous, dependent, independent, and linked
clusters. Each cluster measures dependency and
influence on a scale.
Step 6: Extracting the graph.
Considered the results of Step 4 and presents the
relationships existing among the CSF.
Table 5: Initial reachability matrix.
x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14 x15 x16
x1 - 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
x2 0 - 1 1 1 1 0 1 1 0 1 1 0 1 1 1
x3 1 0 - 1 1 1 1 1 1 1 1 1 0 1 1 1
x4 0 0 0 - 0 0 0 1 0 0 1 1 0 0 1 1
x5 0 1 0 1 - 1 1 1 1 1 1 1 0 1 1 1
x6 0 1 0 1 0 - 0 0 0 0 1 0 0 1 1 1
x7 0 1 1 1 1 1 - 0 0 0 0 0 0 0 0 1
x8 1 1 0 1 0 1 1 - 1 0 0 0 1 1 1 1
x9 1 0 1 1 0 0 0 1 - 1 1 1 0 1 0 1
x10 1 0 1 1 0 0 0 0 1 - 1 0 0 1 1 1
x11 0 0 0 0 0 0 0 0 0 0 - 1 0 1 1 1
x12 0 0 0 0 0 1 0 0 1 0 1 - 0 1 1 1
x13 0 1 1 1 1 1 1 0 1 1 1 1 - 1 0 1
x14 0 0 0 0 0 1 1 0 1 0 0 1 0 - 0 0
x15 0 0 0 0 0 0 0 0 0 0 0 0 1 0 - 0
x16 0 0 0 1 0 0 1 0 0 0 0 0 0 1 1 -
A Model for Implementing Enterprise Resource Planning Systems in Small and Medium-sized Enterprises
Table 6: Final reachability matrix.
x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14 x15 x16
Power of
x1 - 1 1 1 1 1 111111111 1 15
x2 1a - 1 1 1 1 1a111111a11 1 15
x3 1 1a - 1 1 1 1111111a11 1 15
x4 1a 1a 0 - 0 1a 1a 1 1a 0 1 1 1a 1a 1 1 12
x5 1a 1 1a 1 - 1 1111111a11 1 15
x6 0 1 1a 1 1a - 1a 1a 0 0 1 1a 1a 1 1 1 12
x7 1a 1 1 1 1 1 - 1a 1a 1a 1a 1a 0 1a 1a 1 14
x8 1 1 1a 1 1a 1 1 - 1 1a 1a 1a 1 1 1 1 14
x9 1 1a 1 1 1a 1a 1a 1 - 1 1 1 1a 1 1a 1 15
x10 1 1a 1 1 1a 1a 1a 1a 1 - 1 1a 1a 1 1 1 15
x11 0 0 0 1a 0 1a 1a 0 1a 0 - 1 1a 1 1 1 9
x12 1a 1a 1a 1a 0 1 1a 1a 1 1a 1 - 1a 1 1 1 14
x13 1a 1 1 1 1 1 11a1111-11a 1 13
x14 1a 1a 1a 1a 1a 1 1 1a 1 1a 1a 1 0 - 1a 1a 14
x15 0 1a 1a 1a 1a 0 1a 0 1a 1a 1a 1a 1 1a - 1a 12
x16 0 1a 1a 1 1a 1a 1 1a 1a 0 1a 1a 1a 1 1 - 13
cy power
11 14 13 15 12 14 15 13 14 11 15 15 13 15 15 14
Step 7: Model proposal for the implementation of
ERP systems.
Based on Step 6, a model was built that allowed
visualizing the relationships of the factors.
Step 8: Validation of the proposed model through a
focus group.
Step 7 was validated using a focus group, with experts
who have several years of experience in the ERPs
implementation. This validation followed the
recommendations of Mendoza, González, and Pino
(2013) for panel structure and data treatment.
When implementing an ERP system, the importance
of certain factors is crucial to guarantee success in the
company. In this sense, the presence of CSF in the
implementation model obtained is exposed. And, the
impact they will have at the time of implementation
can be seen, corroborating the hypothesis for this
According to experts' opinion, the contextual
relationships established in the lower diagonal of the
SSIM matrix mostly indicate an influence between
the critical factors from position i to position j, as can
be seen in Table 3. These results were crucial for the
development of the following matrices since the
model’s success depends on these relationships.
Then, the VAXO symbol matrix became a
completely binary matrix, both for the upper and
lower diagonal. Table 5 shows the initial RM in
which the cells are mostly occupied by the number
one, this means that the presence of transitivity in this
matrix will be very significant.
ICEIS 2021 - 23rd International Conference on Enterprise Information Systems
In the FRM, a matrix with a great presence of
transitivity was obtained. By adding these transitive
cells, i.e., cells having the reference "1a", together
with the cells occupied by the numbers one both in
the rows and in the columns, the power of influence
and dependence for each factor were obtained. These
values were proportional to each other, being very
important data for the analysis when validating the
model. The detail of this matrix is found in Table
6.The conic matrix indicates the distribution of each
factor in its respective level, obtaining a total of 16
iterations, 7 iterations corresponding to level 1, 6
iterations for level 2, and 3 iterations for level 3. Each
iteration means an assigned factor at a level. These
iterations allowed diagraming the final model with
the relationships established between each critical
factor according to the level at which they are located.
By clustering CSF (Figure 3), it is observed that
the first three quadrants do not have the presence of
any factor. However, for quadrant IV, the 16 factors
are present with a strong influence of each factor on
the other according to the literature established by
Routroy and Kumar (2014). And so, these factors
required feedback for the structuring of the model,
where their relationships were based mainly on
influence and dependence.
Finally, the model obtained is made up of three
levels, where the third “strategic” level was placed at
the bottom as the base of the model. The name
assigned to this level is because the factors located are
responsible for making the decisions of the entire
project and will have a significant impact on the
performance of the following levels. The factors at
this level begin to be directly and indirectly related to
the factors located in the second level, also called the
internal level, since the factors located have functions
that only involve the organization and its personnel.
These factors are related in the same manner to
factors located at level 1, the operational level
containing the factors responsible for finalizing the
implementation and supervising the operation of the
ERP system in SMEs. The final model can be
observed in Figure 4.
Once the model was formulated and validated, a more
precise relationship was established between the
critical factors within the context of SMEs. The
results obtained in the model are discussed from the
application of the ISM methodology and its
respective validation. According to the model
generated, the results obtained have been given in
three levels, starting from the bottom or base, towards
the top of the model. The validated model is shown in
Figure 5.
4.1 Strategic Level (Level 3)
In level 3, three key factors can be observed: 1)
Support from Senior Management (x1), 2)
Relationship with Suppliers and Support (x9), and 3)
External Consultants (x10). At this level, the
implementation of an ERP begins, due to strategic
decisions about the implementation and the assurance
of success. This is corroborated with the results
obtained in the power of influence and dependence
diagram concerning the factors x1 and x10 of support
for senior management, that is, based on the
dependence that exists between them.
Despite the fact that, a transitive relationship
(dashed line) between External Consultants (x10) and
Change Management (x6) can be observed, in the
validation processes, this transitivity has been
eliminated. The experts have stated that change
management involves decisions purely internal to the
company without having any kind of contact with
external consultants. Likewise, based on the relation
between Communication (x8) and the Relationship
with Suppliers and Support (x9), it is established that
communication is a strategy that should only occur
within the organization.
4.2 Internal Level (Level 2)
At this level, six internal factors of the organization
are included: Change Management (x6), Project
Management (x2), Use of a Steering Committee (x3),
Skills, Knowledge, and Experience (x13), Clear
Goals and Objectives (x5) and Communication (x8).
Within the influence and dependency diagram, it is
observed that the participation of the Change
management (x6) is a factor highly dependent on the
factors of the same level, being essential within the
decision making processes in the organization.
Likewise, the clear Goals and Objectives (x5)
presents low dependency; thus, when validating this
relationship, the experts have decided to maintain the
transitivity towards level 1. In other words, to reach
these factors, it is necessary to make decisions at the
strategic level (level 3). Regarding Skills,
Knowledge, and Experiences (x13), despite being an
influential factor and at the same time dependent on
the use of a Steering committee (x3), the experts
suggested eliminating this relationship. The
reasoning behind this is that it presents a greater
weight with external consultants and vendors that are
A Model for Implementing Enterprise Resource Planning Systems in Small and Medium-sized Enterprises
Figure 3: Diagram of power of influence and dependence of critical success factors.
Figure 4: Structural model of critical success factors for implementation in SMEs.
Figure 5: Validated structural model of critical success factors for implementation in SMEs.
factors that help ensure a successful implementation.
At this internal level, communication and
information and knowledge exchange strategies have
been established. These will help project management
and change within the organization, by integrating all
areas affected during implementation.
4.3 Operational Level (Level 1)
This level has seven factors: IT Structure and Legacy
Systems (x12), Business Process Reengineering BPR
(x4), ERP System Acceptance / Resistance (x14),
ERP System Configuration (x11), ERP System
Organizational Adjustment (x15), Participation of
End Users and Stakeholders (x16), Interdepartmental
Cooperation (x7). It has been named at this level as
operational because it contains factors responsible for
the implementation of the ERP system. The ERP
System Configuration (x11) within the influence and
dependency diagram has been estimated as a highly
dependent operating factor because its configuration
must be processed in parallel with the activities of the
ICEIS 2021 - 23rd International Conference on Enterprise Information Systems
factors of its same level. Nevertheless, this factor is
key for implementation at the operational level. In
fact, standard ERP systems are unable to fully adapt
to a company's processes (Gool and Seymour, 2018).
This dependence can be observed in the diagram of
power of influence and dependence of CSF in Figure
The IT Structure and Legacy Systems (x12), even
though it has been observed to be a highly dependent
factor, it was discarded by the experts based on their
knowledge and expertise. They argued that the
presence of this factor does not
have a major influence on the final stage of
implementation of this ERP system in SMEs, since
this kind of organization does not necessarily have a
structured database.
It has been initially observed that the ERP System
Configuration (x11) together with the ERP System
Acceptance (x14) are highly dependent factors within
the implementation and maintaining a bidirectional
relationship. However, during the validation, this
relationship was null because their dependence does
not add a weighted value when performing the
A key part of the model validation carried out by
the experts is the fact that SMEs have adequate
implementation strategies. According to this,
interdepartmental cooperation, process
reengineering, and acceptance of the ERP system are
essential since, at the end of the implementation
process, the system operation must be corroborated.
The current results were contrasted with other
similar cases, such as the study carried out by Pinto,
Ramírez, and Grandón (2017), who investigated the
antecedents of success in implementations of ERP
systems. This work reduced all factors to three
dimensions such as the organization, the project, and
the people. These dimensions include the critical
factors most valued by companies, which are
favorably complemented by the current factors
involved in this study, as well as, their approaches to
the project, the development of the organization in the
face of the implementation of an ERP, and its staff.
This indicates that by taking into account these
three aspects, the estimation of the implementation
time will be shorter and able to better adapt to the
business processes to which any organization is
The most relevant resources of the experts' validation
show that SMEs need the participation and
commitment of the top management, a good
relationship with the service providers and the
external consultants.
The participation and commitment of top
management are essential for the implementation of
this type of system, especially when it depends on the
resource allocation and the possible process changes.
The model obtained in the present investigation
places the greatest emphasis on the importance of top
management in the search and selection phases of the
system to be implemented.
In addition, the model presented allows greater
attention to the top management in the enterprise
preparation while implementing the ERP system
because it increases the probability of achieving
Another fundamental pillar to achieve success in
the implementation of ERP systems is effective
communication between the different actors. It is
achieved when the value-adding processes are known
by all the stakeholders of the implementation, and the
origin and reliability of the information are known for
It is relevant to establish a partner relationship
with the suppliers of the system. Such suppliers must
respect business decisions and ethically indicate to
their customers all possible advantages and
disadvantages of their product. Besides, to allow easy
implementation and accessibility for SMEs, suppliers
can provide ERP in the cloud, offered as: IaaS
(infrastructure as a service) SaaS (software as a
service) and PaaS (platform as a service).
It is important to highlight the participation of the
end-user in all implementation phases (Abugabah,
2017) the organization must seek strategies to reduce
the change resistance to the sustainability of the
implemented system over time.
There are some limitations to this investigation
due to the number of samples used to generalize the
results. Likewise, most of the data was taken from
manufacturing companies due to its high percentage
in the Austral zone of Ecuador.
As future work, at a research-level, the ISM
methodology can be integrated with Fuzzy
relationships to quantitatively show the existing
connections between levels of the model. In addition,
this work could guide SMEs to build a set of
indicators while they implement an ERP system.
This study is part of the research project “Analysis
and definition of strategies and scenarios for the
A Model for Implementing Enterprise Resource Planning Systems in Small and Medium-sized Enterprises
successful implementation of Enterprises Resources
Planning systems in the south of Ecuador” supported
by the Research Department of the University of
Cuenca (DIUC).
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