Exploring the Determinants of Digital Transformation Adoption for SMEs in an Emerging Economy

Abstract

In the fourth industrial revolution age, digital transformation is crucial to the sustainable development of small- and medium-sized businesses (SMEs). This study suggests a hierarchical model based on the Technology–Organization–Environment (TOE) model with three main dimensions and nine sub-dimensions for SMEs that implemented digital transformation in the emerging economy. The fuzzy analytic hierarchical process methodology (Fuzzy AHP) was used to explore and rank determinants of the digital transformation adoption for SMEs. Data were collected by the questionnaires from 72 respondents, who were the leaders of SMEs in Vietnam. The results revealed that the environmental factor was ranked the most important factor in the pairwise comparisons of the hierarchical structure, and the sub-dimension of the customer experience was at the highest ranking of the relative pairwise comparisons of the digital transformation adoption for SMEs, followed by technological compatibility, government support, organizational support, and human resources. This research makes contributions to the topic of digital transformation from both theoretical and practical implications. The result stresses the critical significance of environmental factors in the successful adoption of digital technologies in SMEs, which adds to the perspective in the context of a growing nation.

1. Introduction

The adoption of digital transformation is crucial for SMEs to grow sustainably and is a key driving force behind expanding businesses in the fourth industrial revolution [1]. In order to improve an enterprise’s operational effectiveness, digital technologies are being used in the business process of enterprises in a series of ways, such as digitization, digitalization, and digital transformation [2]. Adoption of digital technologies can help enterprises more quickly create sustainable products and services, promoting innovation culture, increasing experience and connecting with customers, improving capital efficiency, and market expansion [3,4,5]. SMEs managers who want their businesses to survive and thrive in comparative competitive circumstances have an ideal choice to adopt digital transformation to all aspects of business operations [6]. Therefore, adopting digital transformation in SMEs can bring opportunities for businesses to develop sustainability [4].

Additionally, the COVID-19 pandemic, a historically unprecedented disease, has had an impact on all areas of the economy. The crisis epidemic changed the demand, behavior, and consumer culture from onside to online customers [4]. All companies, including SMEs, have forced the adaptation to survival and development in the business operation process [7]. The adoption of digital transformation in the COVID-19 condition setting was driven by pressure to increase the sustainability of SMEs [4].

Businesses that apply digital transformation can gain many benefits such as reshaping organizational structure, enhancing operational efficiency, improving customer experience, enhancing competitiveness, building innovative business models, and saving operating costs [8]. These benefits help SMEs to successfully adopt digital transformation, improve management efficiency, and provide goods and services to customers. As opposed to that, SMEs have many limitations such as lack of capital, lack of highly skilled human resources, few skilled workers in information communication technology, lack of digital infrastructure platforms, and lack of digital standards [9]. In general, the benefits of adopting digital transformation for SMEs bring good conditions to build an innovative culture, improve corporate governance, and effectively use the support of the government and partnerships. These are favorable conditions for SMEs to clearly identify the determinant factors to applying digital transformation.

Up to now, numerous studies have shown that SMEs need to adopt digital transformation in a highly competitive environment [10]. Using the TOE model, scholars have pointed out the elements impacting SMEs’ adoption of digital transformation [11,12,13]. Relative advantage, compatibility, complexity, perceived usefulness, and trialability are technological variables that are important for SMEs to adopt digital transformation [14,15,16]. Organizational variables impact the adoption of digitalization of SMEs through organizational culture, innovativeness, firm sizes, top management support, and human resources [14,15,17,18]. Furthermore, environmental factors consist of government support, market uncertainty, competitive pressure, customer experience, and competitive industry, which are important roles in implementing digital transformation in SMEs [16,19,20]. Previous studies used the TOE model to indicate the significant factors to influence the digital transformation process of SMEs but a lack of studies to rank the most important factors that determine the digitalization of SMEs.

The main barriers to SMEs implementing digital transformation are a lack of digital human resources, information technology platforms, financial resources for technology investment, and independent digital transformation capabilities [21]. Therefore, SMEs need to prioritize ranking the necessary factors to use limited resources in applying digital transformation. However, there has not been much research on how ranking important different elements are for SMEs implementing digital transformation. This study used the Fuzzy AHP technique to rank the critical elements of the TOE framework in the adoption of digital transformation by SMEs in Vietnam, filling a research gap and completing the theory and practice of digital transformation.

The weight-calculated approach known as the fuzzy AHP is used in circumstances of multi-criteria decision-making (MCDM) to select the criterion with the highest weight. The resulting fuzzy AHP approach uses fuzzy numbers because of their ability to accurately express subjective preferences in pair-wise AHP comparisons based on SME managers’ opinions [22]. The prioritization ranking is based on a way of comparing pairwise critical criteria to help SMEs choose the appropriate investment strategy with limited resources to successfully adopt the digital transformation. The technology factors are technological compatibility, technology complexity, and relative advantage [19]. Organizational factors are necessary for transforming enterprises’ business models with key factors, including organizational support, human resources, and innovation culture [11,12]. Environmental factors of the customer’s experience, government support, and environmental uncertainty are considered to influence the digital transformation adoption of SMEs [23]. Consequently, the research question aims to investigate the key variables influencing SMEs in emerging nations to adopt digital transformation.

The introduction part is the first section of the paper’s structure, which is followed by a research framework. Our presentation of the Fuzzy AHP approach is in the third section. The study’s findings are presented in the fourth section, which is followed by discussions. Finally, the last section concludes with conclusions.

2. Research Framework

The key theory to investigate the factors influencing SMEs in emerging countries to adopt digital transformation is the TOE framework [24]. Therefore, this study explores how technological, organizational, and environmental variables affect SMEs in Vietnam, an emerging country adopting digital transformation. Figure 1 demonstrates the research model, technology factors including relative advantage, compatibility, and complexity, as well as organizational elements such as organizational support, human resources, and innovation culture; unpredictability, customer experience, and government support are examples of environmental factors.

2.1. Technological Factors

2.1.1. Relative Advantage

Greater market penetration, lower operating costs, and simpler implementation of new business models are the relative advantages of SMEs adopting digital transformation [25]. If SME owners believe new technology will help them execute their tasks better, they are more inclined to adopt and use them [26]. In addition, the relative advantages of innovation are the magnitude perceived as better than other alternative ideas [27]. The benefits of developing innovation for a business are referred to as relative advantages [28]. The relative advantage focuses on the technology’s advantages and downsides [29].

2.1.2. Technological Compatibility

Technological compatibility is an essential factor when a company adopts innovative technologies, and it is the degree of organizational innovation that adapts to the business culture, business models, and core values of the company [30]. Technological compatibility has been illustrated through its important role in developing business models [31]. For SMEs, it is crucial that the adjustments must be compatible with the organizational culture [32]. Researchers underline that digital technologies should compete with current systems in the digital transformation era [19].

2.1.3. Technological Complexity

Technological complexity measures how widely an innovative technology is adopted and implemented within a company [33]. It is perceived as a shared problem when it comes to digital transformation. A company launching digital transformation has a lot of trouble with technological changes, customer behaviors, and other digitalization challenges [34].

Due to the complexity of technology, SMEs frequently find it challenging to use it. In addition, a lack of knowledge and skills might hinder the deployment of new digital technologies and digital transformation [32,35]. The adoption of digital technologies by SMEs will be negatively correlated with the level of technical difficulty [32].

2.2. Organizational Factors

2.2.1. Organizational Support

The vision of digital technology determines the direct development of the company by building the idea of applying digital transformation to create an advantage competition in the transformation process. Digital transformation requires the company to build the development of fundamental platforms and motivate stakeholders’ actions. In addition, companies need to prepare and mobilize essential financial resources and facilities for the digital transformation process [36]. Furthermore, organizational support is assessed based on the extent to which company leadership allocates and supports resources to employees to carry out business operations. The provision of modern information technology platforms plays an important role in encouraging productivity improvement [37]. For SMEs with limited resources, leaders will find appropriate methods to support employees in implementing the process of applying digital transformation toward business performance [36].

2.2.2. Human Resources

One of the main directions deploys successful digitalization is “personnel for the digital transformation”. Skills in the digital technologies of employees is a crucial role during the digital transformation processes of a firm [38]. Digital transformation not only depends on the employees but also on the managers who use digital technologies [39]. Human resources play a central and pivotal role in business operations and are an important factor in developing solutions for business development [40]. Enterprises must always identify human resources as a strategic asset to determine the company’s competitive advantage. Additionally, the process of digital transformation has a significant impact on the function of human resource management in businesses by showcasing and assessing the abilities and responsibilities of managers who execute human resource management [41].

The performance of businesses and the rate at which digital transformation is taking place are closely related. Kmecová [42] pointed out that the innovative implementation of SMEs, despite having high requirements for digital transformation in terms of human resource management, is currently lagging behind due to the limited digital transformation skills of the SMEs’ workforce.

2.2.3. Innovation Culture

Innovation culture has a significant role in the relationship between technological knowledge and the innovative manufacturing process [43]. Managers and staff of the enterprises should be trained to develop innovative products and services to enhance the companies’ innovative culture [44]. Innovation culture has impacted managerial knowledge, regarded innovative performance, supported employees’ inventive competence, tolerated risk, and developed individual growth [45].

Innovation is a trend that businesses must embrace, but SMEs have a difficult time developing an operational innovation plan. Since SMEs have constrained financial and human resources for development, decisions about innovative activities must be made with greater attention [46]. Very few SMEs can afford to set up an independent management innovation department; thus, building an innovation culture and establishing innovation systems is a key factor in their competitive condition [47].

2.3. Environmental Factors

2.3.1. Customer Experience

Customer experience, which is directly tied to an enterprise’s profitability and even existence, is greatly impacted by digital transformation [48]. Improving customer experience is a significant motivation and role of a business and the implementation of digital transformation [49,50]. A company can adopt digital transformation to improve customer experience by understanding customer information, enhancing business models, and integrating technologies. In addition, changing customers’ behavior or understanding customers’ needs can progress customer experience [51]. Adopting digital transformation for SMEs can increase customers’ experience when focusing on creating new distribution channels and operating effective digital technologies [52].

2.3.2. Government Support

In general, SMEs have a significant role in developing the national economy. However, SMEs still lack technical and managerial skills and have limited access to finance, technology, market, and effective business structures. Thus, governments can provide budgets, information infrastructures, and technical support for managerial training technology programs for SMEs [53].

The government supports and accelerates the digital transformation of SMEs through the deployment, provision, and support of basic platforms such as platforms-as-a-service, infrastructure-as-a-service, and software-as-a-service [54]. Governments deliver services through innovative technologies that will help SMEs increase their competitiveness, cut their operating costs, have easy access to customers, and advance their technology.

2.3.3. Environmental Uncertainty

Environmental uncertainty is the level of unpredictable changes in an economy [55]. It reflects unanticipated changing customer behavior and technological innovation. Technological uncertainty is caused by the development of technological innovation. Under high technological uncertainty, companies tend to rapidly adopt innovative technologies to develop competitive business [56]. The adoption of digital transformation can be considered a technology innovation process that can progress a firm’s competitive capability [57].

Small firms are particularly exposed to environmental uncertainties because of resource limitations [58]. However, with the advantage of being small scale, SMEs have a high degree of flexibility in applying and navigating market fluctuations. Furthermore, Didonet [59] pointed out that the constant changes and developments of technology create opportunities for SMEs to compete and develop new business models.

3. Research Methodology

3.1. Research Framework

The objective of this study was to assess the relative significance of the TOE model using the Fuzzy AHP methodology. The AHP questionnaire was designed into a three-layer hierarchical structure, as shown in Figure 1. Level 1 illustrated how important SMEs were in adopting digital transformation. The TOE model’s dimension, which was made up of sub-dimensions, was the second level. Each layer’s factors were compared pair by pair. The adoption of digital transformation in Vietnamese businesses was the main topic of this study.

3.2. The Fuzzy Analytical Hierarchy Process (AHP)

AHP, proposed by Saaty [60], is a process designed to identify complex decisions where multiple criteria need to be considered. For MCDM instances, the weight-calculated procedures are used to select the criterion with the highest weight [61]. Due to the usage of fuzzy numbers’ capacity to faithfully reflect subjective preferences in pair-wise AHP comparisons, the resulting fuzzy AHP method is well suited to handling uncertainty in subjectivity-based decision-making situations. Based on the unbalanced judgment scales and the uncertainty associated with the experts’ opinions, the Fuzzy AHP technique, developed by Chang [62], uses triangular fuzzy integers to compare pairwise.

When SMEs adopt digital transformation, fuzzy AHP is utilized to rank key criteria. The criteria are assessed using pairwise comparison matrices. The following procedures are used to create the Fuzzy AHP model.

• Step 1: Build a hierarchical structure diagram; level 1 is the general research goal, level 2 is the evaluation criteria, and level 3 is the options, as shown in Figure 1.

• Step 2: Build a pairwise comparison scale matrix.

This study used a weighted rating scale of triangular fuzzy number (TFN). The TFN had a developed scale from 1 to 9 [60], and the transformation process is described in Table 1. The change was represented as a triple value as a = (l, m, u) [61], where l and u are a’s lower and upper bounds, and m is the method a’s evaluation value.

${\mu }_{{\tilde{A}}_{\left(x\right)}}=\left\{\begin{array}{c}\frac{x}{m-l}-\frac{l}{m-l},\hspace{1em}\hspace{1em} \hspace{1em}l\le x\le m\hfill \\ \frac{u}{u-m}-\frac{x}{u-m},\hspace{1em}\hspace{1em}\hspace{1em}m\le x\le u\hfill \\ 0,\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}otherwise\hfill \end{array}\right.$

• 3.. Step 3: Based on pairwise comparison from experts’ opinions to build a fuzzy comparison matrix (Ã) in Table 1.

$\tilde{A}=\left[\begin{array}{cc}\begin{array}{cc}1& {\tilde{a}}_{12}\\ {\tilde{a}}_{21}& 1\end{array}& \begin{array}{cc}\dots & {\tilde{a}}_{1n}\\ \dots & {\tilde{a}}_{2n}\end{array}\\ \begin{array}{cc}\dots & \dots \\ {\tilde{a}}_{n1}& {\tilde{a}}_{n2}\end{array}& \begin{array}{cc}\dots & \dots \\ \dots & 1\end{array}\end{array}\right]$

where if i = j then ã_ij = 1; if i ≠ j then ã_ij = 3, 5, 7, 9; and ã_ji = 1/3, 1/5, 1/7, 1/9.

To perform the pairwise comparison between fuzzy parameters, the linguistic variable was defined corresponding to the evaluation levels according to the table.

• 4.. Step 4: Calculate the sum of each row in the ã_ij matching matrix, then normalize those values according to the formula [61]

$S_i=\sum _{j=1}^m{\tilde{a}}_{ij}\times {\left[\sum _{i=1}^n\sum _{j=1}^m{\tilde{a}}_{ij}\right]}^{-1}$

The weights in each condition are represented by triangle-shaped fuzzy numbers, which are regarded as correlation weights for each alternative.

• 5.. Step 5: Finding the minimum value for each pairwise of fuzzy numbers.

$V\left(S_i>S_j\right)={sup}_{x\ge y}\left[min\left({\mu }_{S_i}\left(x\right),{\mu }_{S_j}\left(y\right)\right)\right]$

The above formula can be expressed as

$V\left(S_i\ge S_j\right)=\left\{\begin{array}{c}1,m_i\ge m_j\\ 0,l_j\ge u_i\\ other,\frac{l_j-u_i}{{(m}_i-u_i)-{(m}_j-j_j)}\end{array}\right.$

• 6.. Step 6: Calculate the weight vector by normalizing the matrix.

$W_i=\frac{\min V(S_i\ge S_j)}{{\sum }_{k=1}^n\min V(S_k\ge S_j)}$

In there

$$\begin{gathered} \min V\left(S_i\ge S_j\right) j=1,\dots .,n\left(j\ne i\right); \\ i=1,\dots ..,n \end{gathered}$$

• 7.. Step 7: Check the sustainability through the Consistency Ratio (CR) index.

$$\begin{gathered} CR=\frac{CI}{RI} \\ CI=\frac{{\mathsf{\lambda }}_{max}-n}{n-1} \end{gathered}$$

The Random Index (RI) is for the randomness index; the Consistency Index (CI) is for consistency; and n is for the number of criteria [60]. The DMs’ evaluations and judgments are consistent when the CR. is less than 0.1; otherwise, the evaluations are inconsistent and must be corrected.

• 8.. Step 8: Calculate the weighted value of each factor.

3.3. Data Collection

The information for this study was gathered via a questionnaire survey of SMEs in Vietnam. SMEs work in many different sectors, including manufacturing, construction, trade, services, agriculture, and more. For this study, a questionnaire survey was carried out in Vietnam from north to south. The adoption of digital transformation in SMEs was the study’s main focus.

The building of the questionnaire was divided into three steps to ensure accuracy and objectivity. In addition, to design the questionnaire and collect answers, the sample must be valid and reliable. First, the main contents of the study were discussed with leaders of SMEs applying digital transformation and scholars studying digital transformation, and three main dimensions and nine sub-dimensions were chosen in this step. Secondly, on the basis of the opinions of experts, the authors built a complete questionnaire and translated it into Vietnamese. Then, a sample survey of 8 SME leaders was carried out. They had rich experience in adopting digital transformation in their companies, and, in addition, the respondents had been working for at least 10 years in their fields, which were the commercial industry, manufacturing industry, and service industry. The owners and managers commented on the ease of understanding the pilot questionnaires and made a relative pairwise comparison between three main factors and nine sub-factors on a nine-point scale in the questionnaires. Third, from the comments of the respondents about the need to clarify the contents of the questionnaire, the authors built a complete questionnaire.

Based on the data of the Vietnam Association of Small and Medium Enterprises (VINASME), 150 samples were randomly collected from North to South Vietnam, and the proportion of SMEs selected for the survey corresponded to the proportion of SME enterprises operating in each region. The southern region had the largest number of SMEs; thus, the sample selection rate was 39%, followed by the northern region with the second largest number of SMEs with a selected sample rate of 36% and the lowest in the central region with a sample rate of 25%. SME leaders were contacted by phone, and 112 managers agreed to participate in the investigation. The questionnaire was sent to SME leaders by email with a 10-day response time, accompanied by a thank you letter for participating in the interview. After the announcement period, there were 86 emails responding to the questionnaire from SME leaders. A total of 112 managers was contacted through email, and 72 answers were used to analyze via the Fuzzy AHP methodology.

3.4. Data Analysis

These sectors included the commercial service industry (37.5% of the sample), the manufacturing industry (25%), the construction industry (18.1%), and the agriculture industry (19.4%). The SMEs were located in all regions of Vietnam: the north (34.7 of the sample), center (27.7%), and south (37.6%).

4. Results and Discussions

4.1. Research Results

The fuzzy AHP methodology analyzed a comprehensive and systematic way to adopt priority among the digital transformation of SMEs. All paired comparison matrices had consistency ratios (CR) that were less than 0.1, the maximum permitted value [60], indicating that the consistency and reliability of all the pairwise matrices were acceptable.

The environment was ranked first in the pairwise comparisons’ second-level hierarchical structure, and the relative importance of the environment was 0.525, respectively. Environmental factors influenced the adoption of digital transformation within small businesses, which included customer experience, government support, and environmental uncertainty. The relative importance of technology was 0.243, followed by the organization at 0.232 (in Table 2).

Sub-dimensions of the third level had been ranked according to their global weights. The sub-dimension of customer experience was the top priority to accept digital transformation in small firms, and the relative importance of global weight was 0.38. Technological compatibility was the second position to come with the adoption of digital transformation (a global weight of 0.124). The third location was government support, which had a value of relative comparison of global weight that was 0.118, followed by organizational support and human resources (global weight of 0.113 and 0.092), respectively. Finally, the innovative culture of small companies was ranked in the last position (global weight of 0.026).

4.2. Discussion

Previous research has shown that the number of key factors suitable for analysis in a field was between the top two and six factors [62], and the analysis results of the Fuzzy AHP methodology indicated that there was a large gap between the fifth factor, human resources (0.092), and the sixth factor, technological complexity (0.064).

The study focused on discussing five important elements that may help SMEs decide whether to undertake digital transformation, including customer experience, technological compatibility, government support, organizational support, and human resources.

4.2.1. Customer Experience

The study’s findings were that improving customer experience was the most important factor in digital transformation adoption by SMEs. Therefore, SMEs must center their strategies around the customer journey by creating a positive, powerful experience to increase customers’ loyalty and moving toward the goal of improving efficient business activities [49]. Enterprises need to improve their business models to meet the needs of customer experience by applying digital technology through the enhanced interaction and personalization of products and services for customers [50]. SMEs utilize cutting-edge technological platforms that are crucial for achieving client satisfaction. While social networks offer excellent opportunities for customers to share their experiences with products and services with businesses and others, chatbots are utilized to connect directly with customers. To boost customer satisfaction, these apps produce new experiences and values. These applications also improved our capacity to need the appropriate goods for consumers’ demands. The adoption of digital transformation by SMEs strengthens the relationship between suppliers and consumers, helps customers have interesting experiences, and promotes engagement with businesses.

4.2.2. Technological Compatibility

Our findings confirmed and supported earlier research showing that technology compatibility had a favorable impact on SMEs’ digital transformation. The result confirmed that technology compatibility was the appropriateness and consistency factor between new technology and the SMEs’ existing technology platforms to implement digital transformation [35]. To improve SMEs’ advantages, they need to build a based framework with a flexible model, small scale, easy deployment, easy configuration, and reasonable cost when applying their digital transformation. In addition, if SMEs can integrate digital technologies with present practices platforms, they stand to benefit greatly [19]. Small enterprises must ensure that the adoption of innovations must be compatible with the organizational culture [32]. Otherwise, due to limited capital, SMEs may find it challenging to synchronize and integrate compatibility between outdated and cutting-edge technologies during the innovation investment processes [19].

4.2.3. Government Support

SMEs lack the capital to make large-scale investments in digital technologies during digital transformation; thus, government support is essential for firms, including SMEs, to develop into digital enterprises [53]. The government develops and promulgates policies and strategies on applying digital transformation as well as providing capital for investment in information technology infrastructures for SMEs and connecting agents and providers of digital platforms for business activities of enterprises. In Vietnam, the SMEdx program is a special government program aimed at accelerating digital transformation in small and medium enterprises through the use of government-provided digital platforms. When SMEs have participated in this program, they simply have to pay monthly rent digital platform, saving money on the expense of investing in a digital investment, while still assuring operational effectiveness and data security. The government’s support enhances SMEs, which accesses markets, improves sustainable business development, and contributes important resources to promoting the nation’s economy [63].

4.2.4. Organizational Support

Employees’ skills and willingness to apply digital technology to business operations are important factors of organizational support [64]. Based on the organizational support, managers allocate to and support the use of successful digital technologies for employees’ missions. Furthermore, when leaders build close relationships and appropriate support in their organizations, they are ready to apply digital technologies in their digital transformation journey, which not only improve business efficiency but also are an opportunity to improve and develop employees’ personal capabilities [65,66]. The result of organizational support is to emphasize the role of management in the adoption plan for the digital transformation strategy and the willingness of employees to embrace technology to increase efficient business [64].

4.2.5. Human Resources

In order to fulfill the requirements of the digital era, the inevitable requirement is that enterprises must have high-quality human resources in line with the digital transformation strategy. Modern digital technologies such as AI, big data analytics, automation, machine learning, data mining, and robotics have been used as tools to improve efficiency in the field of human resource management [67]. Many businesses, including small and medium-sized businesses, are implementing technological advancements in their human resource management functions. Due to this, businesses are being forced to adjust their policies, especially operations from hiring to onboarding, training, evaluating, and rewarding performance to match the online workforce. When the COVID-19 pandemic broke out and spread, these were heavily implemented. To achieve these goals effectively, SMEs need to build a human-resources-focused digital transformation such as digitizing human resource processes, digitizing business analysis, digitizing recruitment processes, digitizing training management, and digitizing business performance management [68].

5. Conclusions

In order to investigate the elements that affected SMEs’ adoption of digital transformation, Vietnamese SMEs were utilized as an example in this study. This research will be an important reference for SMEs in developing countries trying to implement digital transformation. Using the Fuzzy AHP technique, the factors that influenced SMEs’ adoption of digital transformation were examined. The study employed the TOE model, which had three main dimensions and nine significant sub-dimensions to measure. The authors conducted interviews with SME leaders using a questionnaire. The relative pairwise comparison results of the Fuzzy AHP method showed that environmental factors had the most important roles in applying digital transformations, followed by technological factors and organizational factors. The top five important factors that determined the adoption of digital transformation were shown as follows: customer experience, technology compatibility, government support, organizational support, and human resources.

This research made contributions to the topic of digital transformation from both a theoretical and practical standpoint. This study stressed the critical significance of environmental factors in the successful adoption of digital technologies in SMEs, which added to the theoretical perspective in the context of a growing nation. Specifically, SMEs must concentrate on implementing new technology solutions to enrich and enhance the journey of improving customer experience. Additionally, the study added to the literature on government support, and the findings highlighted that government plays a significant role in helping SMEs implement digital transformation by providing funding for digital platforms.

The study’s findings could have practical implications. An SMEs’ internal factors, such as organizational support and human resources, present an important role for managers who utilize and deploy digital technologies in business processes. In addition, managers could enhance and support their staff to conduct digital activities in SMEs through digital human resource management. SMEs are successfully assessed to apply digital transformation when the managers are always willing to invest in effective digital platforms and employees are ready to use new technologies in their business activities.

The research had some limitations, and, accordingly, led to some suggestions for future research. First, future research could segment SMEs by the industries in which they operate in, provide a precise assessment of the application of digital transformation for a given industry, or compare the level of digital transformation adoption among SMEs across industries. Second, expanding the scope of research in developing economies is necessary to keep up with the trend in global digital transformation. These research findings will provide scientific evidence to assess which factors influence determining factors in the adoption of digital transformation by SMEs in those countries. Third, one perspective of future work, which is the combination of Fuzzy AHP with other ranking methods, belongs to the MCDM methodology to improve the accuracy of the analysis.

Author Contributions

Conceptualization, V.A.T. and C.-Y.L.; data collection, V.A.T.; validation, V.A.T. and C.-Y.L.; formal analysis, V.A.T. and C.-Y.L.; writing—original draft preparation, V.A.T. and C.-Y.L.; writing—review and editing, V.A.T. and C.-Y.L. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from Viet Anh Ta upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figure and Tables

Figure 1. Research framework.

Table 1

The criteria of fuzzy AHP.

Linguistic Variables	Intensity of Importance	TNF Assigned
Equal	1	(1, 1, 1)
Weakly More Important	3	(2, 3, 4)
Significantly More Important	5	(4, 5, 6)
Very Strongly More Important	7	(6, 7, 8)
Extremely More Important	9	(9, 9, 9)
Between two adjacent scales’ values	2, 4, 6, 8

Table 2

The relative ranking comparison.

Main Dimensions	Weights (Rank)	Sub-Dimensions	Local Weight	Global Weight (Rank)	CR
Technology	0.243 (2)	Relative Advantage	0.228	0.056(7)	0.033
		Technological Compatibility	0.511	0.124(2)
		Technological Complexity	0.261	0.064(6)
Organization	0.232 (3)	Organizational Support	0.489	0.113(4)	0.001
		Human Resources	0.399	0.092(5)
		Innovative Culture	0.112	0.026(9)
Environment	0.525 (1)	Customer Experience	0.725	0.380(1)	0.007
		Government Support	0.225	0.118(3)
		Environmental Uncertainty	0.050	0.026(8)

References

1. Philbin, S.; Viswanathan, R.; Telukdarie, A. Understanding how digital transformation can enable SMEs to achieve sustainable development: A systematic literature review. Int. Small Bus. J.; 2022; 6, 473. [DOI: https://dx.doi.org/10.26784/sbir.v6i1.473]

2. Schallmo, A.; Daniel, R. Digital Transformation Now! Guiding the Successful Digitalization of Your Business Model; Springer Science and Business Media, LLC.: Berlin, Germany, 2018.

3. Šimberová, I.; Korauš, A.; Schüller, D.; Smolíkova, L.; Straková, J.; Váchal, J. Threats and Opportunities in Digital Transformation in SMEs from the Perspective of Sustainability: A Case Study in the Czech Republic. Sustainability; 2022; 14, 3628. [DOI: https://dx.doi.org/10.3390/su14063628]

4. Chen, C.L.; Lin, Y.C.; Chen, W.H.; Chao, C.F.; Pandia, H. Role of government to enhance digital transformation in small service business. Sustainability; 2021; 13, 1028. [DOI: https://dx.doi.org/10.3390/su13031028]

5. Bui, M.L. A journey of digital transformation of small and medium-sized enterprises in Vietnam: Insights from multiple cases. J. Asian Econ.; 2021; 8, pp. 77-85.

6. Fachrunnisa, O.; Adhiatma, A.; Lukman, N.; Ab Majid, M.N. Towards SMEs’ digital transformation: The role of agile leadership and strategic flexibility. J. Small Bus. Strategy; 2020; 30, pp. 65-85.

7. Baryshnikova, N.; Kiriliuk, O.; Klimecka-Tatar, D. Enterprises’ strategies transformation in the real sector of the economy in the context of the COVID-19 pandemic. Prod. Eng.; 2021; 27, pp. 8-15. [DOI: https://dx.doi.org/10.30657/pea.2021.27.2]

8. Garzoni, A.; De Turi, I.; Secundo, G.; Del Vecchio, P. Fostering digital transformation of SMEs: A four levels approach. Decis. Sci.; 2020; 58, pp. 1543-1562. [DOI: https://dx.doi.org/10.1108/MD-07-2019-0939]

9. Amaral, A.; Peças, P. SMEs and Industry 4.0: Two case studies of digitalization for a smoother integration. Comput. Ind.; 2021; 125, 103333. [DOI: https://dx.doi.org/10.1016/j.compind.2020.103333]

10. Eller, R.; Alford, P.; Kallmünzer, A.; Peters, M. Antecedents, consequences, and challenges of small and medium-sized enterprise digitalization. J. Bus. Res.; 2020; 112, pp. 119-127. [DOI: https://dx.doi.org/10.1016/j.jbusres.2020.03.004]

11. Reis, J.; Amorim, M.; Melão, N.; Matos, P. Digital transformation: A literature review and guidelines for future research. World Conference on Information Systems and Technologies; Springer: Cham, Switzerland, 2018; pp. 411-421.

12. Bin, M.; Hui, G. A systematic review of factors influencing digital transformation of SMEs. Turk. J. Comp. Math. Educ.; 2021; 12, pp. 1673-1686.

13. Nguyen, T.H.; Le, X.C.; Vu, T.H.L. An Extended Technology-Organization-Environment (TOE) Framework for Online Retailing Utilization in Digital Transformation: Empirical Evidence from Vietnam. J. Open Innov. Technol. Mark. Complex.; 2022; 8, 200. [DOI: https://dx.doi.org/10.3390/joitmc8040200]

14. Alshamaila, Y.; Papagiannidis, S.; Li, F. Cloud computing adoption by SMEs in the north east of England: A multi-perspective framework. J. Enterp. Inf. Manag.; 2013; 26, pp. 250-275. [DOI: https://dx.doi.org/10.1108/17410391311325225]

15. AlBar, A.M.; Hoque, M.R. Factors affecting the adoption of information and communication technology in small and medium enterprises: A perspective from rural Saudi Arabia. Inf. Technol. Dev.; 2019; 25, pp. 715-738. [DOI: https://dx.doi.org/10.1080/02681102.2017.1390437]

16. Wong, L.W.; Leong, L.Y.; Hew, J.J.; Tan, G.W.H.; Ooi, K.B. Time to seize the digital evolution: Adoption of blockchain in operations and supply chain management among Malaysian SMEs. Int. J. Inf. Manag.; 2020; 52, 1997. [DOI: https://dx.doi.org/10.1016/j.ijinfomgt.2019.08.005]

17. Abed, S.S. Social commerce adoption using TOE framework: An empirical investigation of Saudi Arabian SMEs. Int. J. Inf. Manag.; 2020; 53, 102118. [DOI: https://dx.doi.org/10.1016/j.ijinfomgt.2020.102118]

18. Pathan, Z.H.; Zeng, J.; Akram, U.; Latif, Z.; Khan, M.K.; Tunio, M.Z. Essential factors in cloud-computing adoption by SMEs. Hum. Syst. Manag.; 2017; 36, pp. 261-275. [DOI: https://dx.doi.org/10.3233/HSM-17133]

19. Prause, M. Challenges of industry 4.0 technology adoption for SMEs: The case of Japan. Sustainability; 2019; 11, 5807. [DOI: https://dx.doi.org/10.3390/su11205807]

20. Idris, K.M.; Mohamad, R. The influence of technological, organizational and environmental factors on accounting information system usage among Jordanian small and medium-sized enterprises. Int. J. Econ. Financ. Issues; 2016; 6, pp. 240-248.

21. Álvarez, J.J.; Zartha, S.J.W.; Orozco, M.G.L. Barriers to sustainability for small and medium enterprises in the framework of sustainable development—A Literature review. Bus. Strategy Environ.; 2019; 28, pp. 512-524.

22. Calabrese, A.; Costa, R.; Levialdi, N.; Menichini, T. Integrating sustainability into strategic decision-making: A fuzzy AHP method for the selection of relevant sustainability issues. Technol. Forecast. Soc. Change; 2019; 139, pp. 155-168. [DOI: https://dx.doi.org/10.1016/j.techfore.2018.11.005]

23. Alraja, M.N.; Hussein, M.A.; Ahmed, H.M.S. What affects digitalization process in developing economies? An evidence from SMEs sector in Oman. Bull. Electr. Eng. Inform.; 2021; 10, pp. 441-448. [DOI: https://dx.doi.org/10.11591/eei.v10i1.2033]

24. Qalati, S.A.; Yuan, L.W.; Khan, M.A.S.; Anwar, F. A mediated model on the adoption of social media and SMEs’ performance in developing countries. Technol. Soc.; 2021; 64, 101513. [DOI: https://dx.doi.org/10.1016/j.techsoc.2020.101513]

25. Kendall, J.D.; Tung, L.L.; Chua, K.H.; Ng, C.H.D.; Tan, S.M. Receptivity of Singapore’s SMEs to electronic commerce adoption. J. Strateg. Inf. Syst.; 2001; 10, pp. 223-242. [DOI: https://dx.doi.org/10.1016/S0963-8687(01)00048-8]

26. Moghavvemi, S.; Hakimian, F.; Tengk Feissal, T.M.F. Competitive advantages through IT innovation adoption by SMEs. Soc. Technol.; 2012; 2, pp. 24-39.

27. Rogers, E.M. Diffusion of Innovations; Universität Hohenheim: Stuttgart, Germany, 2010.

28. Moore, G.C.; Benbasat, I. Development of an instrument to measure the perceptions of adopting an information technology innovation. Inf. Syst. Res.; 1991; 2, pp. 192-222. [DOI: https://dx.doi.org/10.1287/isre.2.3.192]

29. Chen, H.M.; Kazman, R.; Matthes, F. Demystifying big data adoption: Beyond IT fashion and relative advantage. 2015; Available online: https://aisel.aisnet.org/digit2015/?utm_source=aisel.aisnet.org%2Fdigit2015%2F4&utm_medium=PDF&utm_campaign=PDFCoverPages (accessed on 1 March 2023).

30. Jaklič, J.; Grublješič, T.; Popovič, A. The role of compatibility in predicting business intelligence and analytics use intentions. Int. J. Inf. Manag.; 2018; 43, pp. 305-318. [DOI: https://dx.doi.org/10.1016/j.ijinfomgt.2018.08.017]

31. Ortega, B.H.; Martínez, J.J.; De Hoyos, M.J.M. Influence of the business technological compatibility on the acceptance of innovations. Eur. J. Innov. Manag.; 2007; 10, pp. 7-24. [DOI: https://dx.doi.org/10.1108/14601060710720528]

32. Premkumar, G.; Roberts, M. Adoption of new information technologies in rural small businesses. Omega; 1999; 27, pp. 467-484. [DOI: https://dx.doi.org/10.1016/S0305-0483(98)00071-1]

33. Feeny, S.; Rogers, M. Innovation and performance: Benchmarking Australian firms. Aust. Econ. Rev.; 2003; 36, pp. 253-264. [DOI: https://dx.doi.org/10.1111/1467-8462.00285]

34. Jöhnk, J.; Ollig, P.; Oesterle, S.; Riedel, L.N. The Complexity of Digital Transformation-Conceptualizing Multiple Concurrent Initiatives. Wirtschaftsinformatik (Zentrale Tracks); GITO Verlag: Berlin, Germany, 2020; pp. 1051-1066.

35. Orr, G. Diffusion of innovations, by Everett Rogers 1995. Retrieved Jan.; 2003; 21, 2005.

36. Schwarzmüller, T.; Brosi, P.; Duman, D.; Welpe, I.M. How does the digital transformation affect organizations? Key themes of change in work design and leadership. Manag. Rev.; 2018; 29, pp. 114-138. [DOI: https://dx.doi.org/10.5771/0935-9915-2018-2-114]

37. AlNasrallah, W.; Saleem, F. Determinants of the Digitalization of Accounting in an Emerging Market: The Roles of Organizational Support and Job Relevance. Sustainability; 2022; 14, 6483. [DOI: https://dx.doi.org/10.3390/su14116483]

38. Kozanoglu, D.C.; Abedin, B. Understanding the role of employees in digital transformation: Conceptualization of digital literacy of employees as a multi-dimensional organizational affordance. J. Enterp. Inf. Manag.; 2021; 34, pp. 1649-1672. [DOI: https://dx.doi.org/10.1108/JEIM-01-2020-0010]

39. Smirnova, A.M.; Zaychenko, I.M.; Bagaeva, I.V. Formation of requirements for human resources in the conditions of digital transformation of business. International Conference on Digital Technologies in Logistics and Infrastructure; Atlantis Press: Amsterdam, The Netherlands, 2019; pp. 280-285.

40. Becker, B.E.; Huselid, M.A. Strategic human resources management: Where do we go from here?. J. Manag.; 2006; 32, pp. 898-925. [DOI: https://dx.doi.org/10.1177/0149206306293668]

41. Bell, B.S.; Lee, S.W.; Yeung, S.K. The impact of e-HR on professional competence in HRM: Implications for the development of HR professionals. Hum. Resour. Manag. J.; 2006; 45, pp. 295-308. [DOI: https://dx.doi.org/10.1002/hrm.20113]

42. Kmecová, I.; Stuchlý, J.; Sagapova, N.; Tlustý, M. SME human resource management digitization: Evaluation of the level of digitization and estimation of future developments. Polish J. Manag. Stud.; 2021; 23, 232. [DOI: https://dx.doi.org/10.17512/pjms.2021.23.2.14]

43. Grace Chen, Y.; Chen, Z.H.; Ho, J.C.; Lee, C.S. In-depth tourism’s influences on service innovation. Int. J. Cult. Tour. Hosp. Res.; 2009; 3, pp. 326-336. [DOI: https://dx.doi.org/10.1108/17506180910994541]

44. Škerlavaj, M.; Song, J.H.; Lee, Y. Organizational learning culture, innovative culture and innovations in South Korean firms. Expert Syst. Appl.; 2010; 37, pp. 6390-6403. [DOI: https://dx.doi.org/10.1016/j.eswa.2010.02.080]

45. Martín-de Castro, G.; Delgado-Verde, M.; Navas-López, J.E.; Cruz-González, J. The moderating role of innovation culture in the relationship between knowledge assets and product innovation. Technol. Forecast. Soc. Change; 2013; 80, pp. 351-363. [DOI: https://dx.doi.org/10.1016/j.techfore.2012.08.012]

46. Niewöhner, N.; Asmar, L.; Wortmann, F.; Röltgen, D.; Kühn, A.; Dumitrescu, R. Design fields of agile innovation management in small and medium sized enterprises. Procedia CIRP; 2019; 84, pp. 826-831. [DOI: https://dx.doi.org/10.1016/j.procir.2019.04.295]

47. Isensee, C.; Teuteberg, F.; Griese, K.M.; Topi, C. The relationship between organizational culture, sustainability, and digitalization in SMEs: A systematic review. J. Clean. Prod.; 2020; 275, 122944. [DOI: https://dx.doi.org/10.1016/j.jclepro.2020.122944]

48. Sahu, N.; Deng, H.; Mollah, A. Investigating the critical success factors of digital transformation for improving customer experience. 2018; Available online: https://aisel.aisnet.org/confirm2018/18/ (accessed on 1 March 2023).

49. Setia, P.; Setia, P.; Venkatesh, V.; Joglekar, S. Leveraging digital technologies: How information quality leads to localized capabilities and customer service performance. MIS. Q.; 2013; 37, pp. 565-590. [DOI: https://dx.doi.org/10.25300/MISQ/2013/37.2.11]

50. Fitzgerald, M.; Kruschwitz, N.; Bonnet, D.; Welch, M. Embracing digital technology: A new strategic imperative. MIT Sloan Manag. Rev.; 2014; 55, 1.

51. Westerman, G.; Bonnet, D. Revamping your business through digital transformation. MIT Sloan Manag. Rev.; 2015; 56, 10.

52. Matarazzo, M.; Penco, L.; Profumo, G.; Quaglia, R. Digital transformation and customer value creation in Made in Italy SMEs: A dynamic capabilities perspective. J. Bus. Res.; 2021; 123, pp. 642-656. [DOI: https://dx.doi.org/10.1016/j.jbusres.2020.10.033]

53. Doh, S.; Kim, B. Government support for SME innovations in the regional industries: The case of government financial support program in South Korea. Res. Policy; 2014; 43, pp. 1557-1569. [DOI: https://dx.doi.org/10.1016/j.respol.2014.05.001]

54. Setiyani, L.; Makluf, L.; Suherman, Y. Utilization Analysis of Cloud Computing on SMEs: Systematic Review. Int. J. Appl. Inf. Syst.; 2020; 4, pp. 93-99.

55. Achrol, R.S.; Stern, L.W. Environmental determinants of decision-making uncertainty in marketing channels. J. Mark. Res.; 1988; 25, pp. 36-50. [DOI: https://dx.doi.org/10.1177/002224378802500104]

56. Zhu, K.; Weyant, J.P. Strategic decisions of new technology adoption under asymmetric information: A game-theoretic model. Decis. Sci.; 2003; 34, pp. 643-675. [DOI: https://dx.doi.org/10.1111/j.1540-5414.2003.02460.x]

57. Mensah, E.K.; Asamoah, L.A.; Jafari-Sadeghi, V. Entrepreneurial opportunity decisions under uncertainty: Recognizing the complementing role of personality traits and cognitive skills. J. Entrep. Manag. Innov.; 2021; 17, pp. 25-55.

58. Yoo, J.; Kim, J. The effects of entrepreneurial orientation and environmental uncertainty on Korean technology firms’ R&D investment. J. Open Innov. Technol. Mark. Complex.; 2019; 5, 29.

59. Didonet, S.; Simmons, G.; Díaz-Villavicencio, G.; Palmer, M. The relationship between small business market orientation and environmental uncertainty. Mark. Intell. Plan.; 2012; 30, pp. 757-779. [DOI: https://dx.doi.org/10.1108/02634501211273841]

60. Saaty, T.L. Homogeneity and clustering in AHP ensure the validity of the scale. Eur. J. Oper. Res.; 1994; 72, pp. 598-601. [DOI: https://dx.doi.org/10.1016/0377-2217(94)90426-X]

61. Chang, D.Y. Applications of the extent analysis method on fuzzy AHP. Eur. J. Oper. Res.; 1996; 95, pp. 649-655. [DOI: https://dx.doi.org/10.1016/0377-2217(95)00300-2]

62. Liang, T.C.; Peng, S.H. Using Analytic Hierarchy Process to examine the success factors of autonomous landscape development in rural communities. Sustainability; 2017; 9, 729. [DOI: https://dx.doi.org/10.3390/su9050729]

63. Hansen, H.; Rand, J.; Tarp, F. Enterprise growth and survival in Vietnam: Does government support matter?. J. Dev. Stud.; 2009; 45, pp. 1048-1069. [DOI: https://dx.doi.org/10.1080/00220380902811025]

64. Kim, S.; Lee, H. The impact of organizational context and information technology on employee knowledge-sharing capabilities. Public Adm. Rev.; 2006; 66, pp. 370-385. [DOI: https://dx.doi.org/10.1111/j.1540-6210.2006.00595.x]

65. Baccarella, C.V.; Maier, L.; Meinel, M.; Wagner, T.F.; Voigt, K.I. The effect of organizational support for creativity on innovation and market performance: The moderating role of market dynamism. J. Manuf. Technol. Manag.; 2022; 33, pp. 827-849. [DOI: https://dx.doi.org/10.1108/JMTM-10-2020-0423]

66. Wang, Y.S.; Li, H.T.; Li, C.R.; Zhang, D.Z. Factors affecting hotels’ adoption of mobile reservation systems: A technology-organization-environment framework. Tour. Manag.; 2016; 53, pp. 163-172. [DOI: https://dx.doi.org/10.1016/j.tourman.2015.09.021]

67. Vardarlier, P. Digital transformation of human resource management: Digital applications and strategic tools in HRM. Digital Business Strategies in Blockchain Ecosystems. Contributions to Management Science; Springer: Cham, Switzerland, 2020; pp. 239-264.

68. Bansal, A.; Panchal, T.; Jabeen, F.; Mangla, S.K.; Singh, G. A study of human resource digital transformation (HRDT): A phenomenon of innovation capability led by digital and individual factors. J. Bus. Res.; 2023; 157, 113611. [DOI: https://dx.doi.org/10.1016/j.jbusres.2022.113611]