Key Drivers of ERP Implementation in Digital Transformation: Evidence from Austro-Ecuadorian

Abstract

This study identifies key drivers for ERP implementation in small- and medium-sized enterprises (SMEs) in Austro–Ecuador and examines their impact on operational efficiency, strategic adaptability, and digital transformation. Motivated by the limited empirical evidence on ERP adoption in Latin American SMEs, this research aims to provide Austro–Ecuadorian insights that contribute to innovation management practices in emerging economies. To identify the critical success factors (CSFs) influencing ERP implementation, a four-phase methodology was employed, encompassing a CSF literature review, data collection and case analysis from 55 SMEs, multiple correspondence analysis (MCA), and descriptive ERP analysis. Statistical analysis of the surveyed SMEs, primarily from manufacturing sectors, revealed that while a significant portion (37%) lacked ERP experience, 22.9% were in the process of implementing or actively using systems such as Oracle’s J.D. Edwards Enterprise One and SAP. The MCA highlighted ERP system configuration, vendor relationships, and user training as significant factors for successful ERP implementation, reported by 54.5% of the companies. Quadrant analysis further emphasized the influence of IT structure and legacy systems on implementation characteristics, with cluster analysis identifying three distinct groups of companies based on their ERP strategies. The findings underscore the importance of top management support, business process re-engineering, and external consultants for successful ERP adoption in SMEs, providing practical insights for optimizing innovation management in the digital era. Future research should investigate the long-term impacts of ERP systems on organizational performance and innovation sustainability.

1. Introduction

In the contemporary business landscape, organizations are compelled to continuously enhance their operational processes and strategic decision-making to optimize profitability (Archana et al., 2022). This imperative is driven by the rapid pace of technological advancements and the concomitant need for technological transformation within organizational structures. Consequently, enterprises, particularly small- and medium-sized enterprises (SMEs) in Latin America, must adapt to technological innovations that significantly impact business operations by implementing systems that bolster productivity and competitive market positioning (Pino et al., 2021).

Innovation management within organizations has evolved considerably, with the digital age presenting unique challenges and opportunities that necessitate a re-evaluation of traditional frameworks and methodologies (Asprion et al., 2018). The advent of digital technologies such as Ind 4.0 (smart industries), Big Data, or Internet of Things (Iot) has fundamentally altered the mechanisms through which innovation is conceived, developed, and implemented (Kaufmann, 2015). These technologies have enabled organizations to leverage data-driven insights, optimize decision-making processes, and foster collaborative ecosystems that transcend geographical and organizational boundaries. Consequently, the digital age demands a nuanced understanding of innovation management, one that integrates technological advancements with strategic foresight to navigate the complexities of contemporary organizational environments (Menz et al., 2021).

Enterprise resource planning (ERP) systems have emerged to provide technological solutions, offering an integrative framework that consolidates diverse organizational information—spanning material, human, and financial resources—into a unified database. This integration facilitates improved productivity and operational efficiency (Greenwood et al., 2019). ERP systems are comprehensive business solutions encompassing a broad spectrum of functions and processes designed to enable organizations to manage their resources effectively (Guerrero Luzuriaga et al., 2018; Vicedo et al., 2020). By optimizing information flow and automating business processes, ERP systems eliminate redundant operations, thereby allowing personnel to shift focus from routine tasks to strategic decision-making (El Sawah et al., 2008).

The implementation of ERP systems is typically structured into three distinct phases: pre-implementation, implementation, and post-implementation (Hasibuan & Dantes, 2012). This study concentrates on the pre-implementation and implementation phases, which are characterized by significant challenges, including complexity, stringent time constraints, and limited resource allocation (Xie et al., 2022). The successful application of ERP systems has occurred not only in large and complex companies but also in SMEs, as demonstrated in the work of López Rivas et al. (2021), who analyzed the use of ERP in small companies, such as franchises, and demonstrated that these programs are used to maintain a competitive advantage (Raharjo & Perdhana, 2015). For SMEs, ERP systems can substantially enhance operational efficiency and market competitiveness. Moreover, integrating ERP systems with an organization’s operational strategies can yield synergistic outcomes. For example, in the study of Zabala et al. (2021), the integration of ERP systems with corporate social responsibility (CSR) indicators was shown to improve stakeholder relations, demonstrating the adaptability of ERP systems to align with existing business frameworks. ERP systems further support sustainable business practices and public initiatives by enhancing information flow, improving operational efficiency, and facilitating informed decision-making (Zhou et al., 2015). Alba and Rojas (2020) emphasize that a meticulously designed ERP implementation methodology for SMEs can streamline processes, integrate organizational areas, provide real-time data access, and reduce operational costs. The involvement of high- and mid-level stakeholders is crucial for the successful implementation of ERP systems (Nikitović, 2012).

Despite their benefits, SMEs face challenges such as high costs, system integration difficulties, inadequate planning, and slow implementation (Faizan & Mehmood, 2022; Syaifuddin et al., 2024). These factors can lead to reduced implementation efficiency and effectiveness. Organizational culture and behavioral dynamics further complicate ERP adoption (Gomes Ferri, 2024; Rahayu & Juliana Dillak, 2018). Additionally, recent global events, such as the COVID-19 pandemic, geopolitical conflicts, and border closures, have exacerbated these challenges by impeding technological adaptation in SMEs. Nevertheless, the emergence of Industry 4.0 tools, such as cloud technologies, presents opportunities to mitigate these challenges by reducing costs and enhancing technological integration (Gessa et al., 2023).

In summary, this research underscores the importance of ERP systems in augmenting the operational capabilities of SMEs, providing a strategic roadmap for ERP adoption, and fostering a competitive edge in challenging market conditions. The empirical results of this study indicate that successful ERP implementation in SMEs from the Austro region of Ecuador depends on a set of interrelated factors. These factors include the configuration of the ERP system, the strength of supplier relationship management, the availability of technical support, and the presence of structured change management strategies. Enterprises that had a high level of top management involvement and invested in user training reported significantly better integration outcomes. The analysis, based on multiple correspondence analysis (MCA), also shows that professional experience in the position—used as a supplementary variable—correlates with higher implementation success. In order to assess the long-term benefits of ERP, future research should examine post-implementation performance metrics. Given these challenges, identifying the critical success factors (CSFs) that influence ERP implementation outcomes is critical. The following section reviews existing research on CSFs and their role in ensuring ERP-implementation success in SMEs.

2. Literature Review

2.1. Critical Success Factors (CSFs) for the Implementation of ERP in SMEs

ERP implementation can be approached from two perspectives: the user’s perspective and the company’s management perspective. On this basis, research indicates that the main people affected by the implemented ERP system are the users who actively use it (Kodithuwakku & Madhavika, 2023), whereas management is affected when projects do not result in planned objectives (Anaya et al., 2023). Some external factors affect ERP implementation; for example, the COVID-19 pandemic has complicated implementation, and ERP software vendors have moved to remote implementations, as well as wars and blockades, which have made this activity more challenging (Harun et al., 2022).

There are several studies on the identification of critical success factors (CSFs) in ERP implementation, and the literature shows that trust between organizations and suppliers of ERP systems is the first step in ensuring the correct implementation of these programs (Li et al., 2024). In addition, insufficient research has been conducted on the identification of CSF in remote implementation (Kodithuwakku & Madhavika, 2023). The adoption of these integrated business management solutions can generate significant benefits, but it also introduces a set of challenges and critical factors that determine the success of the implementation.

Table 1. Critical factors for ERP implementation.

Factor	Sources	Perspective	Category
Knowledge management	(Françoise et al., 2009)	U	O
Top management support	(Al-Fawaz et al., 2008; Juniawan et al., 2022; Kautsar & Budi, 2020; Lara-Pérez et al., 2024; Malik & Khan, 2021; Panji Wicaksono et al., 2022; Rahayu & Juliana Dillak, 2018)	E	O
Education and training	(Al-Fawaz et al., 2008; Panji Wicaksono et al., 2022; Rahayu & Juliana Dillak, 2018)	E	O
Organizational culture	(Kautsar & Budi, 2020; Malik & Khan, 2021)	E	O
ERP implementation team characteristics	(Kautsar & Budi, 2020)	E	O
Project team competence	(Juniawan et al., 2022; Nagpal et al., 2017)	E	O
Team composition	(Juniawan et al., 2022; Kronbichler et al., 2009)	E	O
Organizational change management	(Juniawan et al., 2022; Malik & Khan, 2021; Panji Wicaksono et al., 2022)	E	O
Cooperation between team members	(Juniawan et al., 2022)	E	O
Organizational impact	(Aini et al., 2020)	E	O
Information quality	(Aini et al., 2020)	E	O
Individual impact	(Aini et al., 2020)	E	O
Workgroup impact	(Aini et al., 2020)	E	O
System quality	(Aini et al., 2020)	E	O
ERP fit	(Aini et al., 2020; Al-Fawaz et al., 2008; Kautsar & Budi, 2020; Kronbichler et al., 2009; Panji Wicaksono et al., 2022)	E	O
Communication	(Chen et al., 2009; Dezdar & Ainin, 2011; Saade & Nijher, 2016)	U	O
User training and education	(Noudoostbeni et al., 2010; Shaul & Tauber, 2013)	U	O
Project management	(Dezdar & Ainin, 2011; Ranjan et al., 2018; Saade & Nijher, 2016; Shaul & Tauber, 2013)	U	O
User participation and involvement	(Françoise et al., 2009; Nah et al., 2003; Shaul & Tauber, 2013)	U	O
External consultants	(Motwani et al., 2005)	U	O
ERP system configuration	(Esteves & Pastor, 2000)	U	O
Vendor support and relationship	(Leyh, 2014; Somers & Nelson, 2004)	U	O
Project champion (mediator)	(Somers & Nelson, 2004)	U	O
Available resources	(Achanga et al., 2006; Reel, 1999; Remus, 2007)	U	O
Monitoring/performance measurement	(Al-Mudimigh et al., 2001; Fui-Hoon Nah et al., 2001)	U	O
ERP system acceptance/resistance	(Al-Mudimigh et al., 2001; Fui-Hoon Nah et al., 2001)	U	O
Vendor tools and implementation methods	(Somers & Nelson, 2004)	U	O
Data accuracy	(Somers & Nelson, 2004)	U	O
Organizational culture	(Nah et al., 2003)	U	O
Problem-solving	(Esteves & Pastor, 2000; Gunasekaran et al., 2001; Loh & Koh, 2004; Nah et al., 2003)	U	O
Organizational structure	(Françoise et al., 2009)	U	O
Interdepartmental cooperation	(Somers & Nelson, 2004)	U	O
Use of steering committee	(Somers & Nelson, 2004)	U	O
Effective project management	(Al-Fawaz et al., 2008; Kronbichler et al., 2009; Rahayu & Juliana Dillak, 2018)	E	S
Business process re-engineering	(Aini et al., 2020; Al-Fawaz et al., 2008; Malik & Khan, 2021; Rahayu & Juliana Dillak, 2018)	E	S
Implementation process	(Kautsar & Budi, 2020)	E	S
Clear goals and objectives	(Juniawan et al., 2022; Panji Wicaksono et al., 2022)	E	S
The effectiveness of project leader	(Govea Souza, 2021)	E	S
End-user involvement	(Al-Fawaz et al., 2008; Juniawan et al., 2022; Kronbichler et al., 2009; Panji Wicaksono et al., 2022)	E	S
Vendor and consultant quality	(Aini et al., 2020; Kronbichler et al., 2009; Malik & Khan, 2021)	E	S
Top management commitment	(Ranjan et al., 2018; Saade & Nijher, 2016; Shaul & Tauber, 2013)	U	S
Change management	(Nah et al., 2003; Saade & Nijher, 2016; Shaul & Tauber, 2013)	U	S
Implementation strategy	(Dezdar & Ainin, 2011; Saade & Nijher, 2016; Saini et al., 2013; Scott, 2000)	U	S
Skills, knowledge, and experience	(Somers & Nelson, 2004)	U	S
Project team leadership/takeover	(Esteves & Pastor, 2000)	U	S
Corporate strategy/business strategy	(Nah et al., 2003)	U	S
Hardware and software selection	(Kautsar & Budi, 2020; Rahayu & Juliana Dillak, 2018)	E	T
Testing and start-up of the system	(Juniawan et al., 2022)	E	T
IT infrastructure and legacy systems	(Ranjan et al., 2018; Ribbers & Schoo, 2002)	U	T
ERP system testing	(Nah et al., 2003)	U	T
Environment (national culture and language)	(Françoise et al., 2009)	U	T

Note: E = enterprise, O = organizational, S = strategic, T = technical, U = user.

lists some of the research on ERP implementation and elaborates on which critical success factors were covered (Alba & Rojas, 2020; Bernal & Jadan, 2020; Kodithuwakku & Madhavika, 2023; Kusumawardhana et al., 2024; Lara-Pérez et al., 2024; Rodríguez Aldana & Fong Reynoso, 2020).

The factors shown above were compiled from only some of the articles available, and only those factors that are more adapted to SMEs were considered. Some of the points to highlight are as follows:

• Top management support: The active backing and support of an organization’s top management for the implementation of an ERP system or project (Rahayu & Juliana Dillak, 2018).
• Effective project management: It involves the application of techniques, tools, and skills to plan, execute, and control projects efficiently to achieve their ERP objectives (Al-Fawaz et al., 2008).
• Change management: Any ERP implementation process requires managing and controlling organizational changes in a planned and structured way to minimize resistance and maximize adoption (Shaul & Tauber, 2013).
• Communication: It consists of the effective transmission of information, ideas, and opinions among the different stakeholders of a project or system (Dezdar & Ainin, 2011).
• Implementation strategy: A detailed plan that guides the implementation of a system or project, including the necessary activities, resources, and timelines (Saade & Nijher, 2016).
• User training and education: In the end, end-users can be provided with the training and education necessary to effectively use a new system or technology (Shaul & Tauber, 2013).

The successful implementation of an ERP system in a small business requires not only top management support, effective project management, change management, communication, implementation strategies, and user training and education, but also a change in the mindset and way processes are managed (Grandón et al., 2018). Small companies can be better prepared to face the challenges of today’s market and improve their competitiveness by following these key points and taking advantage of the success stories mentioned above (Table 1). The main idea is to obtain the maximum benefits offered by an ERP system to understand the successful practices of many organizations, as summarized in

Table 2. Research variables.

Variable	Description
x1	Support and involvement of top management
x2	Project management
x3	User training
x4	Change management
x5	Balanced project team
x6	Communication
x7	Clear goals and objectives
x8	Business process re-engineering (BPR)
x9	ERP organizational fit
x10	End user and stakeholder involvement
x11	External consultants
x12	ERP system configuration
x13	Relationship with vendors and support
x14	IT structure and legacy systems
x15	Project champion (mediator)
x16	Skills, knowledge, and experience
x17	Project team leadership/empowered decision-makers
x18	Available resources
x19	Monitoring/performance measurement
x20	ERP system acceptance/resistance
x21	Vendor tools and implementation methods
x22	Data accuracy
x23	Organizational culture
x24	ERP system testing
x25	Environment (national culture and language)
x26	Problem-solving
x27	Organizational structure
x28	Interdepartmental cooperation
x29	Knowledge management
x30	Company strategy/adjustment strategy
x31	Use of steering committee

.

2.2. Highlights for Implementing ERP in SMEs

In the process of implementing an ERP system, it is essential to have a solid strategy that guides all the steps of the implementation with the objective of integrating the company’s data (Haddara, 2022). The identification and clear definition of the company’s objectives and goals with the implementation of the ERP system should be included in the ERP implementation strategy (Vera, 2006). The implementation of ERP systems in SMEs is a complicated process that requires careful planning and effective strategies to be successful. According to the articles by Govea Souza (2021), Alsharari et al. (2020), and Zamzeer et al. (2020), the strategies that can be implemented are summarized as follows: Establish an implementation committee: In this way, efforts are made to form an implementation committee that is composed of members from different areas of the company. This committee will be responsible for overseeing the entire implementation process, ensuring that the needs of all departments are taken into account. Assess business needs and objectives: Before selecting an ERP system, it is essential to conduct a thorough assessment of the company’s needs and objectives. This involves identifying critical areas for improvement, inefficient processes, and the strategic objectives to be achieved with the ERP. Selecting the right ERP: Many systems have advantages and disadvantages; a prior investigation of the ERP system that suits the needs and size of the SME is necessary.

Despite a general consensus on the benefits of structured planning and stakeholder engagement; the prioritization and mechanisms of specific strategies at play; the formation and operation of lean and mean ERP adoption committees (Govea Souza, 2021); and the importance of linking ERP functionalities to the company’s strategic goals from the outset (Alsharari et al., 2020), not everyone agrees on the inclination toward the technical or organizational components of the game; the adaptation of the software to the constraints of resource-poor SMEs (Haddara, 2022); or the human side of it, such as internal communication or change management (Vera, 2006). The implication is that the success of ERP adoption is likely to be highly contingent, particularly among SMEs in developing countries. However, little is known about how these strategies interact and are put into practice, and how they are perceived and used among SMEs or in some countries with specific regional characteristics. In addition, the supplier must be reliable and offer adequate support. Implementation planning: A detailed implementation plan, including definitions of goals, timelines, budgets, resource allocation, and risk management, is recommended.

There has been a lot of research focused on what determines the success of ERP implementation, but most of this research has dealt with large companies, and much of the work has been extracted from the operational and strategic differences of SMEs in emerging markets. In addition, the relationship between ERP adoption and digital technology transformation in low-resource environments has not been adequately addressed. This research fills these gaps by examining the way ERP is implemented in Austro–Ecuadorian SMEs, trying to identify the factors that influence its success, which are organizational, technical, and contextual under the conditions commonly found in developing countries. In addition, the research provides original empirical knowledge in the field of innovation and digital product-scale practices in small-business environments.

The present study aims to provide guidance on critical factors influencing ERP implementation in SMEs, with the following objectives: RO1 is to identify commonalities among SMEs that have implemented ERP systems. RO2 is to explore the relationships between success factors and firm-specific variables. By leveraging the experiential insights of other SMEs, this research seeks to furnish a practical framework that guides SMEs in ERP implementation, thereby reducing resource expenditure, mitigating risks, and enhancing competitiveness. In addition to the SME sector, this study contributes to broader business competitiveness and economic growth. In the context of an ever-evolving business environment, the effective implementation of ERP systems is a vital catalyst for organizational advancement and adaptability. This study distinguishes itself by providing a contextualized understanding of ERP implementation within the under-researched setting of Ecuadorian small- and medium-sized enterprises (SMEs). By offering empirical evidence from this unique geographical and business context, the research illuminates potential variations in implementation strategies and success factors compared to those in developed economies. The findings identify region-specific challenges and priorities, such as limited prior ERP experience and platform preferences, offering actionable insights for practitioners operating in Ecuador’s Austro region. Ultimately, this research establishes a foundation for future research into the long-term impacts of ERP systems on organizational performance and sustainable innovation within developing economies.

Building on these findings, this study employs a structured methodology to examine ERP implementation in SMEs. The next section outlines the research design, data-collection process, and analytical techniques used to investigate ERP-adoption patterns.

3. Materials and Methods

This study follows a mixed-methods approach, combining surveys and multiple correspondence analysis (MCA) to examine ERP implementation in SMEs. The authors emphasized a series of steps that are summarized in Figure 1, which outlines the research methodology, including a literature review, data collection, and MCA analysis. The first phase involved identifying critical success factors (CSFs) through an extensive literature review, while subsequent phases applied statistical analysis and clustering techniques to categorize SMEs. The first phase was a review of the implementation of the CSFs. A review of the specialized literature is needed to gather the necessary information to understand the implementation strategies of an ERP system in small companies (Kalling, 2003). The results included 31 unique CSFs, which were based on different works, such as (Bernal & Jadan, 2020; Kodithuwakku & Madhavika, 2023; Kusumawardhana et al., 2024; Vicedo et al., 2020; Rivera et al., 2018; Schniederjans & Yadav, 2014; Velastegui, 2021). The next phase involved a combination of interviews and structured surveys. These were carried out across a range of industries, including a targeted group of SMEs. The questionnaire instrument was validated through a pilot study with 13 companies (Cronbach’s alpha, 0.904), allowing for a comprehensive assessment of item clarity and internal coherence. After having been refined, the final version of the questionnaire was distributed electronically to SMEs located in the Austro region of Ecuador. In particular, the experiences of companies that had successfully implemented ERP were included as empirical references to support and illustrate the strategic proposals made in this study. The exhaustive analysis of cases was performed through a survey, and the evaluation of business strategies and the consideration of management practices were the methods used in this research to address the proposed ORs. In the next phase, data collection was carried out in an instrument created to measure the success of ERP systems where their competitiveness has improved. These findings will be discussed in depth. The implications for business management will be examined, and practical suggestions will be made on the basis of case studies. The next stage involved a study of MCA, a statistical technique for reducing and visualizing information about categorical variables, i.e., summarizing data in a reduced number of dimensions without losing information. The aim of this method is to study the relationships among the different CSFs identified. Finally, companies were clustered to group them so that they could share the lessons learned in the implementation of ERP, and by discussing them, the findings were validated through discussion.

3.1. Phase 1: CSF Review

The key variables of ERP implementation are determined as the key areas of activity where everything must be properly accommodated so that the company progresses and, in general, achieves the goals set. The advantage of these key implementation variables lies in providing a clear guide to centralize energy, resources, and all the care in the planning of an implementation plan. Therefore, if these factors or variables are not visibly distinguished, they can lead to the failure of a system’s implementation (Schniederjans & Yadav, 2014). There are several proposals of critical success factors that can be assigned depending on the company in which they are applied.

According to Schniederjans and Yadav (2014), in one of his research projects regarding the implementation of ERP systems in SMEs, there is a lack of comprehensive order of critical factors that are indispensable in the application of this system. In the proposed research, revision of the CSFs in Table 1 and Table 2 was taken into account. Both business and user perspectives were considered for the latter CSFs. Thirty-one factors, presented in Table 2, were used for the following phase. CSFs were used to determine the similarities that exist between the different companies studied. Moreover, we determined which factors or variables are independent and which factors have a dependency relationship on the basis of the critical factors proposed by Bernal and Jadan (2020). In this case, a covariate of study was also considered, which is the experience in the position of the respondents and the experience implementing ERP.

3.2. Phase 2: Data Collection and Case Analysis

SMEs were sought by considering secondary sources, such as records in company superintendencies or in the tax office. A probabilistic approach was used to select the sample. The final number of valid responses was 55 small businesses out of approximately 200 businesses between June and October 2020. Similar studies have compared the changes in post-covid strategies, and the case of the authors of Kusumawardhana et al. (2024) was considered so that we have an updated conceptual framework. Then, semi-structured interviews and surveys with representatives of companies in the sector were used to collect data.

The data presented in this study are based on surveys developed and validated in collaboration with a focus group composed of six experts with more than 10 years of experience in the field of supply chain-integration projects using enterprise software tools. These experts, who have been directly involved in ERP implementation and post-implementation phases, provided key insights that helped ensure the relevance and technical depth of the tool. The surveys sought detailed information on the ERP implementation strategies used and the challenges faced during and after the implementation process. This research tool allows for the collection of both qualitative and quantitative data on the implementation strategies of different companies. These surveys were conducted via three approaches: The first approach consisted of sociodemographic questions. The second approach consisted of questions focused on the CSF, with a Likert-scale model with which they rated their range of agreement or disagreement, with 1 being less representative and 5 being more representative. Finally, the third approach consisted of closed questions related to business characteristics for the correct application of ERP systems.

3.3. Phase 3: Multiple Correspondence Analysis (MCA)

In 60 s, the first works on the MCA were established. At that time, this technique was understood as a set of tools aimed at examining and interpreting the information of a set of variables, without losing information, and showing the relationships between variables (Greenacre, 2008). The relationship uses graphs to show a few variables and their relationships. The MCA in this research aims to indicate similar characteristics that the companies that participated in the study have (Baki et al., 2022). The interpretation of the results of the MCA can be considered to be similar to a principal component analysis (PCA) since it is summarized by a contingency table (Chen et al., 2009). Importantly, the percentages of inertia or variance are limited in our research. The selection and interpretation of the factorial axes will be carried out mainly with the help of the contributions of the active variables and the test values related to an additional variable (year of experience in the position). We consider that the interpretation of the CSF axes is carried out crosswise: a contrast is sought between what is similar between all items to the right of the origin of the axis and everything that is placed to the left of the origin (Chen et al., 2009).

In the CSF, the contribution of the components (Contrib) relates the distance from the point of origin and the weight of the point (Saade & Nijher, 2016; Saini et al., 2013). The contribution is visualized for each category in which the questions of the questionnaire were rated (Figure 2), where it can be seen how each point, which represents a company, contributes with its variability to the CSF. To make sense of the results, they were validated with experts in ERP implementation (Nagpal et al., 2017). Regarding the interpretation of the results, as mentioned in Chen et al. (2009), the contribution of the variable must be significant and validated with the figures that can be made. On the other hand, the supplementary variables that will be used are years of experience in the position (on-the-job experience) and whether it has been successful in implementing ERP. This promotes the interpretation of the results, as it provides an idea of whether experience in the position is indispensable for an ERP implementation study. Finally, MCA was carried out with the R packages FactoMineR and Factoshiny in R (version 4.3.2), using all the variables of the questionnaire (Françoise et al., 2009; Noudoostbeni et al., 2010).

3.4. Phase 4: Descriptive ERP in Ecuadorian SMEs

In the fourth phase, the results are discussed, considering the similarities of Ecuadorian SMEs in implementing ERP systems, as well as whether the covariates (experience in the workplace and experience in implementing ERP) have been determinants of the results obtained. The clustering carried out in this research aims to form homogeneous groups of companies that have similar characteristics in terms of ERP system implementation. Hierarchical clustering was considered because of the nature of the data. The ward method is used because of its consistency in performing the sum of squares. It also allows us to control the groups that can be formed. Finally, the Dunn index was calculated in order to know the efficiency of the clustering.

4. Results

4.1. Statistical Analysis of the Samples

The population of this study is composed of SMEs in the Austro region in Ecuador, which are grouped out of 130 companies. A sample of 55 companies was selected from the Superintendence of Companies, Securities and Insurance of Ecuador (SUPERCIAS). According to a study by Bernal and Jadan (2020), 22.9% of the companies in the province of Azuay are engaged in the manufacture of textile products; 14.6% of the manufacturing companies are engaged in the manufacture of food products; 8.3% of the manufacturing companies are engaged in the manufacture and processing of food; and 8.3% of the manufacturing companies are engaged in the manufacture of substances and chemical products, the manufacture and processing of processed metal products, and the manufacture of leather and related products. The companies engaged in the manufacture of electrical equipment; manufacture of furniture; manufacture of nonmetallic mineral products; manufacture of computer, electronic, and optical products; and repair and installation of machinery and equipment constitute 4.2% of all companies. At the end of the list, we have the manufacture of household appliances, the manufacture of jewelry, the costume of jewelry and related items, the manufacture of machinery, and the printing and reproduction of engravings, with shares of 2.1% each.

Considering the number of employees per company, the following distribution was obtained: small businesses with 1 to 9 employees represent 22.9%, those with 10 to 49 employees account for 50%, medium-sized firms with 50 to 199 employees make up 16.7%, and large companies with 200 or more employees constitute 10.4%. With respect to ERP systems, 37% of respondents lack experience or practice in their use, whereas 22.9% are implementing or actively using them. The most common ERP systems among SMEs in Azuay include Oracle’s J.D. Edwards Enterprise One, which is implemented by 27.3% of businesses. Moreover, SAP, MS dynamics (AX, GP, NAV, and SL), and DataShoes (used in footwear production) each constitute an 18.2% share. In terms of ERP effectiveness, 54.5% of companies reported successful implementation, 36.4% achieved partial success, and 9.1% considered implementation unsuccessful.

4.2. Development of the MCA Method

MCA is a technique that helps to reduce and visualize information on categorical variables, that is, to summarize data in a reduced number of dimensions, with no possible loss of information. The descriptive analyses of the Likert-scale levels, which contained the majority of the survey questions asked, were named variables, and the results were as follows: VL = very low (5.4%), L = low (9.4%), N = neutral (21.3%), H = high (33.5%), and VH = very high (30.3%). Notably, the majority of the respondents agreed that the indicators are highly important for implementation. Notably, ERP applications had the greatest impact on companies’ IT structure and legacy systems, as well as on the use of companies’ board of directors’ committees (Figure 3). On the other hand, the organizational culture and knowledge management variables had a negative effect on ERP applications. Most of the variables that contribute to Dim1—such as interdepartmental cooperation, and end-user and stakeholder involvement—are organizational factors. Meanwhile, Dim2 is influenced by x23, x25, project team leadership, and available resources, which are strategic factors (Figure 2).

Figure 2 shows that key factors in ERP implementation, including x12 = (ERP system configuration), x13 (relationship with vendors and support), x11 (external consultants), and x3 (user training), are important variables when implementing ERP systems and contribute to the two levels of MCA analysis. The last categories, such as “knowledge management low” and “balanced project team low”, are less relevant than the initial categories in dimensions 1 and 2. In this descriptive analysis, the main variables that were analyzed in the different companies show that the support and participation of the top management result as follows: of the 55 companies in total, 26 responded to this variable as very high, meaning that they consider this variable very important within the application of the ERP system; 18 responded high, meaning that they consider it important; and 7 companies consider it neutral.

Quadrant Analysis

On the other hand, Figure 3 shows the appearance of the cloud of individuals, representing companies. From the surveys conducted, the results were applied to the MCA. For this purpose, two components were chosen (>32% of the variability contribution), and the crossing of these two components shows different quadrants, where each individual, or variable, is placed in each quadrant according to its level of contribution to the technique. The contribution was collated by cosine quadratic distances, which indicate the quality of the information provided by the companies in this study. Figure 3 shows the result of the MCA defined by the coordinates and the main dimensions of the method. The biplot of the 55 companies can be seen, with each point representing one of them; in the same way, the separation indicates the similarities of each company in comparison with the 31 variables taken into account. Similarly, companies that are far away from the coordinates (0, 0) have little or no similarity compared with those located farther from the center of the graph. The clustering of firms near the origin (near the (0,0) coordinates in Dim1 and Dim2) suggests that these firms share similar characteristics or have similar responses on the variables in the analysis, whereas unique firms are those that are far from the central cluster, such as Companies 52 and 26. For example, Company 26 is ranked higher in Dim2, suggesting that it has different characteristics or responses than the firms clustered at the bottom of the graph. To perform a specific analysis of the similarities between the companies participating in the study, a quadrant study was carried out (Figure 3). The blue dots represent the companies, whereas the green dots represent the years in the office. It is better to perform the study in parts because it is easier to interpret (Baki et al., 2022).

Quadrant I, horizontal axis (Dim1), represents the net intensity of the implementation of the ERP best practices (from low embracing and application on the left to high on the right). The vertical (Dim2) distances show different styles of implementation of EPR projects. The different level of emphasis on the strategy, the organization, or a combination of both, a vertical distance implies a very different approach to and emphasis on an ERP project. Company 26 (11 years old) was associated with topics such as strong top management support (x1.H), low use of external consultants (x11.L), and very limited available resources (x18.VL). Company 26 is joined by Company 8. This portrait appears when firms are able to have adopted this best practice with a very low level of resources (economic, human, etc.), and also by having their top management being highly supportive and committed, that is, to do it with them and not to mainly delegate its development to the IT Department. Companies such as 51, 43, 23, and 13 are companies associated with the challenges of poorly defined goals (x7.L), lack of organizational fit (x9.L), low skills (x16.L), and high user resistance against ERP (x20.H). Their presence in these squares hints at a more difficult implementation journey, which may require coping mechanisms and that was not caught by the current set of factors. Companies such as 13, 23, and 51 have greater affinity among all the variables taken into account in the ERP application, with project management, relationship with suppliers and support, and IT structure and legacy systems being the characteristics represented in this quadrant. With respect to the time in the job-handling ERP systems, it can be said that, on average, it was 5 to 9 years. Unlike companies such as 1, 16, and 52, which are located farther from the origin, the environment variable (national culture and language) and problem-solving are the least interesting for this group of companies. Notably, the variables change management, communication, clear goals and objectives, adjustment, and organization are considered irrelevant in relation to the ERP (Figure 3a).

Quadrant II contains the majority of companies. Company 54 seems to stem from its high operational capabilities in project management (x2.L) and problem resolution (x26.L). The upward positioning along Dim2 might demonstrate effects from additional organizational enablers, including change management or user training, when these factors align in the same direction. Furthermore, this quadrant consists of companies such as 42, 32, and 12, which are close to categories revealing neutral project management (x2.N), limited organizational structure support (x27.VL/L), and low communication (x6.L). This could be the segment where companies are very stringent on the organization’s scaffolding or rely on its informal and adaptive strategies. In this quadrant, the predominant variable is IT structure and legacy systems, with Companies 7, 21, and 54 having the greatest weight in regard to this variable. Relationships with suppliers, and support and communication have a medium relationship, with Companies 42, 29, and 48 being the closest. Therefore, in this quadrant, contrast with Quadrant I is observed. The average time in the position of this group is 15 years (Figure 3b). The biplot reveals that none of the firms situated within this quadrant carries an identifiable age designation. This implementation profile yields no conclusive information about the importance of firm maturity. The position of Company 54 demonstrates that internal capabilities such as agile project management and issue resolution can lead to successful implementation in the absence of strong structural support elements.

In Quadrant III, there are companies whose axes have negative scores for both dimensions, suggesting that they lack the positive characteristics or factors defined by Dimension 1 and Dimension 2. This group includes traditional companies whose average time in the position of the respondents is 9.5 years (Figure 3c). In the quadrant where Dim1 is negative and Dim2 is positive, Company 3 is located near the variable types x29_H (knowledge management) and x12_VH (ERP system configuration). The firm’s position reveals a success formula based on exceptional ERP system design and powerful knowledge management capabilities. Despite the firm’s negative Dim1 positioning, indicating uneven high rankings on best-practice indicators, its system-customization abilities and internal knowledge-flow strengths effectively compensated for these deficiencies. This analysis suggests that successful ERP deployment means different things and achieving success depends on matching organizational capabilities with system setup, as is especially important for SMEs.

Quadrant IV comprises 12 companies, and the predominant variables are the IT structure and legacy system. Dim2 indicated the presence of a number of good things in the companies, such as a company culture that is very flexible and conducive to continuous improvement, a management team or a unifying operative staff that is well-liked and respected, or very strong user training programs. Thus, even if Companies 36 and 49 did not have all of the classical ERP success factors mentioned above at a high level, their high performance might also be explained by the fact that they were also leveraging other organizational capabilities just as critical to the success of the project, but less visible. There is likely a relationship between a company’s age and its reliance on informal, culture-based facilitators as opposed to codified, best formal practices (13 years). This is why it is so important to understand that ERP success is not a one-dimensional concept, but rather, that it is a success that is both multifaceted and only relevant within a specific situation, specific only to the company in question—giving rise to there being as many different dimensions of success as there are companies you have studied. Companies 2, 5, and 7, in this case, have the highest affinity among them with respect to all the ERP application variables, thus explaining the closeness of their coordinates represented for this quadrant. Unlike Companies 49, 16, and 36, which lack or give very little importance to the variables of project team leadership/empowered decision-makers, organizational culture and available resources are among the most prominent. The number of years in the position in this quadrant is 13.2.

The different quadrants contribute to the implementation of ERP. Each quadrant has characteristic companies that define the way to implement these systems. The years of experience in a position are an important variable for each quadrant and increase in each quadrant. Therefore, the study is complemented with a supplementary variable, the years in the position of the people who responded to the survey. We also add the variable of whether the person who answered the survey has been successful in implementing ERP or similar systems. This is because it is not the same to implement an ERP when starting in the position or not knowing the company as it is for someone who already knows the company and the position he/she holds; likewise, there is a marked difference between being successful in implementing an ERP system and not.

4.3. Analysis of the CSF with Supplementary Variables

The supplementary variable year in the position is added within the variables of an ERP of the dataset (Figure 4). In this analysis, the descriptive statistics of the variable years in position are evident, yielding an average of 8 years. The point statistics are similar in magnitude: the distribution of the data is concentrated around the average in the highest percentage of the companies. As seen, job experience and success in ERP implementation are two variables that are relative for Companies 1, 13, and 28. Companies 3, 7, and 21 are marked by the few years of job experience of those in charge of implementing ERP systems; however, it should be noted that they have been successful in the implementation of ERP systems. This leads us to consider that experience helps greatly in the implementation of ERP systems, but it is not the only thing that should be considered to guarantee the success of adequate implementation. In the case of Company 3, top management support and participation, business process re-engineering (BPR), and external consultants are variables that are considered important for guaranteeing success.

Cluster Analysis

According to the study conducted by Govea Souza (2021), the clustering analysis of companies that have implemented ERP systems in the small-business sector makes it possible to obtain homogeneous groups of successful companies in the implementation. For this clustering, the companies in the study were used, and different hierarchical and non-hierarchical methods were analyzed (

Table 3. Indicators to cluster.

Method	Dunn’s Indicator
Hierarchical	0.5372
CLARA	0.2040
PAM	0.2040

). In the first group, the Clustering Large Applications (CLARA) and Partitioning Around Medoids (PAM) methods were evaluated; in the second group, hierarchical clustering with the dendrogram method was considered (Wendt & Weinrich, 2023). The clustering analysis allowed for visualization of the companies in different categories according to their ERP implementation strategies and, according to their importance, project management, supplier relationships, support and IT structure and legacy systems, ERP system configuration, and top management support and involvement (Figure 5). These results show that small businesses have different approaches and priorities when implementing an ERP system. Even ERP implementers are multidisciplinary, including professionals in areas such as information technology, project management and senior management, which motivates a difference in implementation.

In the quality analysis of the clustering, hierarchical clustering was performed via the average linkage method since it yielded the best results (Milligan & Cooper, 1987; Mojena, 1977). On the basis of the clustering performed, four main groups of companies that have implemented ERP systems were identified.

Three groups were formed that differ mainly in their focus and priorities during the implementation of the system. Cluster 1, starting with a group of four companies, is high only in the area of the management team because of the proper involvement of the top-level decision-makers and strategic control. In addition to having the relevant members, these companies possess strong project-governance structures that have made use of the implementation committees, and the organizational alignment that followed happened due to a clear configuration of ERP systems and participation mechanisms. Furthermore, their ERP implementations reflect the decentralized decision-making process and informal leadership engagement, showing a relatively unsophisticated and leadership-based approach. These companies are quite particular in that they emphasize top management support and participation through adequate project management. Cluster 2 is a group of 24 companies. These companies belong to various industries, such as wood processing, ceramics making, and textile manufacturing. What makes them similar is that they all give high priority to system configuration and its integration with the existing IT and legacy systems. For many of these corporations, the use of ERP only came after the re-engineering of BPR, meaning that a lot of effort was put into the process of harmonizing system functionality with the workflow redefinition. Though there is top management support, the focus of this group lies more in the areas of technical capability and ERP–platform fit. In some companies, business process re-engineering (BPR) has been the first step in the implementation of some process improvements and is always supported by top management. The last group, composed of 27 companies, is characterized by high importance given to the formation of a balanced project team and communication. This is reflected in the relationship with suppliers and support. In the project team, it is possible to have multifunctional employees who promote the implementation and various areas of the ERP, as well as the empowerment of the team in regard to decision-making (Saini et al., 2013). In the analyzed group, these companies demonstrate a marked way of working and an organizational culture oriented toward communication. For this group, top management support and participation are just as important as they are for the other groups.

5. Discussion

5.1. Common Patterns and Strategic Differences

The common patterns indicate that they have effectively integrated ERP into their business processes, thus allowing them to improve efficiency in areas such as accounting, inventory management, and sales operations, among other variables. Some companies are strongly aligned with some basic, standardized ERP principles, such as the successful implementation of key processes in the company, such as accounting, inventory management, and sales, which may be a clear sign that the ERP is effectively integrated into daily processes. The ERP system has the ability to streamline activities and enable intelligent decision-making (Alba & Rojas, 2020; Greenwood et al., 2019). The central role of top management’s support and structured project governance are common denominators of successful ERP adoption. This aligns with what Rahayu and Juliana Dillak (2018) and Juniawan et al. (2022) emphasized regarding the need for high-level involvement during all implementation phases. However, this study challenges this view by demonstrating that collegial involvement can compensate for financial or human resource scarcity, a crucial point among SMEs, and that not only is that factor important, but so is the experience of the individuals who put the ERP in place. Common to many organizations that emphasize top management support and participation is business process re-engineering (BPR), which aligns with the findings of Vrecl and Sternad Zabukovšek (2022), who highlighted that ERP implementation requires top management support, a business plan and user participation. On the other hand, the BPR allows the company to have the flexibility to adapt to new processes, which an ERP requires, and thus to carry out the implementation successfully. But this requirement is only the beginning, and it is a requirement that every company must have. Many companies focus better on other aspects

There are examples of the deviation of the specific organizational culture, sourced configurations, or sectoral requirements of companies (e.g., 1, 8, 24, 26, 48, and 52). In those cases, the inventory system is an example of a solution that is in line with the realities of the operations, as suggested by Zabala et al. (2021). The authors thus propose that ERP could be applied across a broad spectrum of activities, and the results would still be successful. The most recent findings, those by Zabala et al., suggest that by tailoring their ERP systems to their specific needs, these firms were able to do just that, which confirms the point made in the opening. In many productive sectors, systems and productive relationships can be very different. However, the strategy for innovation is common due to organizations having multiple ERP strategies that do not only interplay with each other but can also help to build the whole picture of the stage they are now in (Raharjo & Perdhana, 2015). This coincides with the work of Archana et al. (2022), who indicate that the ERP methodology is crucial for the successful implementation of the project since an incorrect choice causes delays and poor decision-making. This makes it possible to work with an innovation-oriented business strategy using ERP systems.

On the other hand, the professional experience of managers is not only one of the crucial components of ERP success, as Françoise et al. (2009) propose, but it is not the key factor in all the cases. SMEs with younger or less experienced leaders took the lead and still managed to succeed when they had a very clear implementation plan, additional expertise from the outside, or strong vendor relationships (Leyh, 2014; Somers & Nelson, 2004). Thus, the involvement of thematic experts highlights the complexity of human capital in ERP projects, where structured assistance can compensate for lack of internal experience. A common practice among companies is to have a balanced team of experienced and proactive team members to ensure that projects achieve their planned objectives. However, there are cases where on-the-job experience is not relevant (Company 3). Technical and organizational factors are relevant and common in companies with this situation. This is because, in SMEs, these factors are limited due to limited resources. A lack of resources is a common issue among SMEs in Latin American countries. It can thus be concluded that resilience constitutes a factor in such cases. It is a phenomenon observed among prosperous enterprises that they are not always in sufficient possession of the resources required to undertake projects, including the expertise of their managerial staff. This is consistent with the findings of Kautsar and Budi (2020), who emphasized the importance of ERP–organization fit, especially in environments with legacy systems. Strategic factors are important, and organizational factors are mostly not considered.

This research explores how different strategies in ERP implementation and underlying innovation strategies may have led to the variations observed for different companies. For example, companies in highly regulated sectors (food and metallurgy) show distinct patterns because of their need to comply with specific regulations through ERP. The relationship between the position of companies on the graph and the reported benefits of ERP in the literature could provide different perspectives on best practices and areas of improvement for ERP implementation in SMEs. According to the study conducted, the companies that are positively associated with characteristics and factors that are defined as positive (Quadrant I) have younger or less experienced leaders; provided they are supported by strong implementation strategies, external expertise, or good relationships with vendors, they can be successful (Leyh, 2014; Somers & Nelson, 2004). Regarding the experience in the position and the success of implementing the person in charge of these systems, there is a clear idea of how there is a relationship, but there are cases in which this is not fulfilled. This discovery hints at a more comprehensive comprehension of human capital in ERP projects, as, in this case, the part of structured support may optionally alleviate the lack of experience from within the company.

In summary, we can assert that the innovation strategy of ERP implementation is a matter with many sides to it, and professional experience is an important requirement for the implementation of an ERP; however, it is ultimately the companies’ readiness, infrastructure, and leadership commitment that should determine the specific direction of the strategy application.

5.2. ERP Implementation Profiles

The identification of patterns exhibited by successful companies through the utilization of statistical tools (i.e., clusters) proves advantageous across numerous industrial sectors (Chabert, 2018). It allows us to understand the theories of Vrecl and Sternad Zabukovšek (2022) and Katerattanakul et al. (2014), who suggested that the success of ERP is related to the level of readiness of the company and a proper alignment of innovation strategy. ERP implementation has different effects on different groups of companies (Katerattanakul et al., 2014). By comparing the similarities of the companies, common characteristics handled by these companies can be counted. The relationships they have when implementing ERP were taken. It is evident that a proportion of SMEs adopt a radical approach to business operations, underpinned by a commitment to process re-engineering as a fundamental component of their strategic framework. Re-engineering was one of the first actions to implement this type of software, with a group of SMEs using the IT structure and systems that the organization already had. This finding reaffirms the opinion that ERP does not have only one set of factors that contribute to success; instead, it has many sets of factors that are mutually dependent and must be aligned with the factors of each company (Hasibuan & Dantes, 2012; Zabala et al., 2021).

A comprehensive body of knowledge is to be derived from the companies within the scope of this research. Regardless of the industry sector, the profile of an SME seeking success in ERP implementation necessitates the balancing of three fundamental factors, strategic, organizational, and technical. Moreover, it should be noted that the possession of relevant professional experience does not necessarily guarantee a successful implementation, a notion which coincides with López Rivas et al. (2021) and Xie et al. (2022). ERP implementation is a complex process, but success stories can be achieved by considering experience and time as the main factors. This allows us to consider experience and time in terms of importance for these projects.

6. Conclusions

The RO1 on the search for similarities between companies was obtained through the identification of key elements that contribute to the success of this process in SMEs. This work aims to enrich the understanding of ERP implementation in SMEs by exploring the organizational factors considered crucial to success. The success with ERP is not about any single factor but very much about properly sewing together project management, executive support, change readiness, and technical infrastructure. Furthermore, beyond the identification of CSFs, these works evidence instances where SMEs that overcame the obstacles to their success were albeit devoid of resources, experience, or formal arrangements, implying that success with ERP is a multi-factorial and situational feat. The analysis revealed that change management, the IT structure and legacy systems, communication, and clear goals and objectives are essential components that influence the success of the implementation and are related to each other, with these variables having a very high impact on SMEs that have successfully implemented ERP. In addition, the time in the position of the people who manage an ERP system, together with the experience in successful implementations, has been considered a fundamental contribution since these two issues are always considered related, but some companies can reach successful objectives without the combination of these two factors. RO2, which looks for the relationship between CSFs and company practices, can be answered by clustering companies. Here, the relationship between groups of companies and success factors for ERP implementation can be noted. This finding shows that the sector of activity to which the enterprises belong is not an important factor for the implementation of an ERP project.

In essence, from a theoretical viewpoint, this work contributes to the body of knowledge on the use of ERPs in less researched regions such as the Austro region of Ecuador. From a practical point of view, it provides SME managers with a flexible model that can be adjusted to their peculiar capabilities and constraints. And, from a strategic point of view, the work serves as a reminder of the harmony that needs to be established between the ERP objectives and the stage of preparedness of the organizations.

There are limitations to the study, however. First, the research is cross-sectional, meaning that it cannot capture the long-term benefits of ERP implementation. In addition, the context of the data may limit the generalizability of the findings. Future research could benefit from the use of longitudinal data; comparative studies across regions and countries; and the integration of other methodologies, such as structural equation modeling and case-based inference/reasoning. Exploring the role of a firm’s organizational culture or leadership style could also help uncover deeper causal relationships that may influence ERP performance.

In summary, the study confirms that despite the challenges SMEs face in implementing ERP, it is possible to successfully practice ERP as long as a company strategically aligns technical, organizational, and managerial considerations with its own business environment.