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.

1 INTRODUCTION

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).

https://orcid.org/0000-0002-2331-0939

https://orcid.org/0000-0002-8194-6054

https://orcid.org/0000-0001-6724-7997

https://orcid.org/0000-0003-2154-3277

https://orcid.org/0000-0002-3986-7707

https://orcid.org/0000-0002-9577-0264

https://orcid.org/0000-0003-1367-5288

https://orcid.org/0000-0002-7264-5188

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

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,

2002).

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.

2 METHODS

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,

2008).

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).

Code

CSF for ERP successful

implementation

Component

1 2

CSF: Strategic

Support from Senior

Management

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

management

0,854 0,148

x7 Interdepartmental Cooperation 0,805 0,153

x8 Communication -0,002 0,854

Relationship with suppliers and

support

0,505 0,678

x10 External Consultants 0,523 0,623

CSF: Operational

x11 ERP System Configuration 0,881 0,204

x12

IT Structure and Legacy

Systems

0,821 0,095

x13

Skills, Knowledge and

Experience

0,776 0,159

x14

ERP System Acceptance /

Resistance

0,666 0,385

x15

ERP System Organizational

Adjustmen

0,088 0,903

x16

Participation of End Users and

Stakeholders

0,317 0,830

Step 2: SSIM elaboration with the CSF of Bernal

(2019).

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.

N° 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).

V A X O

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.

N° 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.

N° x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14 x15 x16

Power of

Influence

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

Dependen

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.

3 RESULTS

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

research.

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.

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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.

4 DISCUSSION

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

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101

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

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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

implementation.

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

dedicated.

5 CONCLUSIONS

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

success.

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

sure.

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.

ACKNOWLEDGEMENTS

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

103

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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