Key Success Factors and Barriers for Implementation of Information Communication Technology (ICT) In Small and Medium Enterprises (SMEs): Evidence from Developing Nation Download PDF

Journal Name : SunText Review of Economics & Business

DOI : 10.51737/2766-4775.2024.100

Article Type : Research Article

Authors : Acharya SH, Khanal K and Kadariya MI

Keywords : IT Implementation; CSF; ICT factors; ICT barriers; SME; ICT; PCA


Based on a survey conducted among 221 participants representing medium sized enterprises in Kathmandu this study reveals important findings, about the challenges and opportunities faced by these businesses. The analysis, which was supported by reliability tests highlights "Internal Readiness/Trainings" as the factor for successful implementation of information and communication technology (ICT) while "External Barriers" are identified as significant obstacles. To identify the components Principal Component Analysis (PCA) was utilized. These components serve as the foundation for a framework aimed at improving ICT implementation in SMEs. The main factors contributing to success include support, from top level management incentives for team members training for IT workforce effective change management practices and thorough software testing. On the hand barriers include awareness of ICT benefits and concerns related to data security.


Enterprises are often categorized based on factors such as the number of employees, annual sales, assets, or a combination of these criteria [1]. Within this categorization, Small and Medium-sized Enterprises (SMEs) hold a significant role and are widely recognized as vital contributors to a nation's economic growth and stability [2]. Unfortunately, many SMEs face the risk of failure, often attributed to a lack of timely and accurate data and information [3]. However, the adoption of Information and Communication Technology (ICT) can play a pivotal role in increasing the success rate of these enterprises [4]. SMEs play a crucial role in generating employment opportunities, thereby contributing to the overall economic growth of a nation [5]. They also foster a more competitive market environment [6]. To ensure the success of SMEs, it is essential to identify and prioritize Critical Success Factors (CSFs), which can vary depending on the type of enterprise and the specific regulations and policies of each country [7]. These CSFs encompass a wide range of factors, including those related to the enterprise itself, its business operations, and the entrepreneurial spirit behind it [8]. The presence and utilization of accurate and comprehensive data and information are fundamental to the survival and prosperity of organizations [9]. The rapid evolution of ICT has had a profound impact on organizations, catalyzing their growth [10]. However, even the most well-designed and rigorously tested IT tools may fall short of meeting an organization's actual requirements [11]. Therefore, the successful implementation of IT systems within an organization necessitates careful consideration of all factors and conditions that may influence both the implementation process and the system's effectiveness during its operational phase [12]. It is noteworthy that the success rate of IT system implementation, particularly in terms of executing a well- devised plan, tends to be low [13]. This can be attributed to a multitude of factors, encompassing technical, economic, organizational, behavioural, and psychological aspects. The complexity of IT system implementation arises from the collaboration between two distinct entities: the service provider and the service recipient [14]. Consequently, it becomes imperative to identify and understand the various factors that impact the effectiveness of IT system implementation. Enterprises are often classified based on factors such as number of employees, annual sales, assets, or a combination of these criteria. In this classification, small and medium enterprises (SMEs) play a significant role and are widely recognized as significant contributors to the economic growth and stability of the country. Unfortunately, many SMEs face the risk of failure, which is often attributed to a lack of timely and accurate information and information. However, the adoption of Information and Communication Technology (ICT) plays an important role in increasing the success of these projects.

SMEs play an important role in creating employment opportunities, thus contributing to the overall economic development of the country. They also create a more competitive market environment. In order for SMEs to succeed, it is important to identify and prioritize critical success factors (CSFs), which may vary depending on the type of company and the specific laws and regulations of each country. These CSFs include a wide range of factors related to the firm itself, its business activities and the entrepreneurial spirit behind it Sun. The availability and use of accurate and comprehensive information and information is fundamental to the survival and success of organizations. The rapidly developing information technology has had a tremendous impact on organizations and has acted as a catalyst for their growth. However, even well-designed and well-tested IT tools may not meet the real needs of an organization. Hence the perfect implementation. While Nepal’s small and medium enterprises (SMEs) sector has grown tremendously in recent years, the challenge of organizing these projects and ensuring their long-term success remains daunting [15]. The high failure rate of Nepali SMEs may be partly due to the struggle to adapt to the local business environment and effectively implement Information Technology (ICT) systems, the challenges and opportunities have not been adequately explored. There is a crucial need to identify and understand the key success factors that can lead to sustainable development of Nepali SMEs through ICT implementation. Furthermore, it is important to highlight the key barriers that hinder the effective use of ICT in these sectors. This study aims to address this gap by exploring the complex contextual and emotional interactions that affect ICT use in Nepalese SMEs. The overall objective is to develop a customized framework that can guide these companies towards better adoption of ICT, enabling them to overcome their challenges and understand the opportunities in the dynamic business environment of Nepal.

Literature Review

Research pertaining to the adoption of Information and Communication Technology (ICT) has consistently demonstrated that Small and Medium-sized Enterprises (SMEs) in developing countries face challenges in fully leveraging technological advancements to expand their business operations [16-19]. Consequently, there exists a compelling need for a deeper comprehension of the determinants influencing ICT adoption and the factors that propel or inhibit its implementation and utilization [20]. As early as 1996, scholars acknowledged that ICT integration within organizations had evolved from being optional to becoming an imperative for survival, underscoring the urgency and significance of adopting novel technologies [21]. Information and Communication Technology (ICT) stands as a key catalyst for business performance and directly shapes the success of enterprises [22]. It exerts a positive influence on economic growth and development by enhancing operational efficiency and productivity. ICT is instrumental in optimizing resource allocation, mitigating transaction costs, and fostering technological advancements [23]. SMEs in developing countries face unique challenges in ICT integration, ranging from suboptimal management practices and limited technology access to constrained credit facilities, educational gaps, unemployment, and obstacles like ICT infrastructure limitations and slow internet connectivity [24]. Encouraging SMEs to integrate ICT into their operations for more sophisticated applications presents intricate challenges, including the imperative for technical prowess, substantial investments, and organizational adjustments, which can pose financial burdens for these enterprises [25]. The adoption of ICT unfolds in three distinct stages: pre-adoption, adoption, and post-adoption [26]. During the pre-adoption phase, novel technologies are evaluated, with a focus on immediate benefits. The adoption phase involves meticulous planning for technology acquisition and utilization. In the post- adoption phase, the continuous utilization or potential abandonment of the technology is considered. Various ICT tools, including email, websites, e-commerce platforms, e-business models, and innovative organizational structures, come into play across these stages.

Research Methods

The main objective of this study is to explore the key success factors and barriers to ICT adoption in SMEs through a quantitative descriptive research approach. The research design is organized, starting from the identification and formulation of research problems hypothesis through an extensive review of existing literature, by organizations such as government agencies, NGOs, software companies, insurers, and academic institutions, by employees, managers, owners, and debtors’ involvement. Next, data analysis is an important process in which various statistical tools are used to summarize and organize the data. The descriptive analysis includes such factors as the mean and standard deviation, while the chi-square tests examine the relationship between the independent variables and the dependent variable, "Use of ICT in SMEs" They walk Cronbach alpha analysis so ensured reliability and validity. Factor analysis is performed to find patterns and underlying relationships in data, with Kaiser-Meyer-Olkin (KMO) and Bartlett tests assessing the suitability of data for factor analysis. Principal Component Analysis (PCA) is used for dimension reduction with data exploration, and Rotated Component Matrix Variance (RCMV) describe relationships among variables.

Analysis and Findings

The data collected from the questionnaire survey were analyzed using Excel and IBM SPSS Statistics version 25.0. Descriptive statistics were employed to gain insights from the responses. In terms of respondent gender distribution, the majority (82.8%) were male, with female respondents accounting for 17.2%. Regarding the distribution of respondents based on their organizations, the largest group (39.4%) represented academic institutions, while the smallest group (1.4%) was associated with the automobile sector. These descriptive statistics provide a clear picture of the gender and organizational diversity among the survey participants.

Variables and components codes

All the variables and their components considered are coded for the computational easiness. The codes and its meaning are as per the following (Table 1).

Reliability analysis

For the reliability analysis, the Cranach’s alpha value is calculated. The overall Cronbach’s alpha value is summarized in table below (Table 2). Factors are acceptable if the value of alpha is greater than 0.7. Here, in the above table, we see that the Cronbach’s alpha calculated is 0.864. It means, all the factors are acceptable. The result shows that the internal uniformity of questionnaire is good and strength of association is also good. The reliability test is done for each variable also. The Cronbach’s alpha value for each variable is summarized in below table. From the above table, the alpha value of each variable is greater than 0.7 which means that all the factors are acceptable. Similarly, the alpha value for all items is 0.921 (greater than 0.7), hence all the items considered are consistent and acceptable (Table 3).

Kaiser-Meyer-Olkin measure of sampling adequacy for acceptance of parameters

This measure varies between 0 and 1, and values closer to 1 are better. A value of 0.6 is suggested minimum. For this research value obtained is 0.909 as shown in table below (see table 9) which is closer to 1 i.e. the research accepts entire success factors and barriers for the study (Table 4).

Bartlett’s test of sphericity

This tests the null hypothesis that the correlation matrix is an identity matrix. An identity matrix is matrix in which all of the diagonal elements are 1 and all off diagonal elements are 0. Small values less than 0.05 of the significance level indicate factor analysis is useful for the collected data. From the table 9, the significance level has low value than 0.005 and the factor analysis is useful for the collected data. The p-value is 0.000 (less than 0.05) which indicates that the factor loading is justified.

Principal component analysis for categorization of factors

PCA is used as a data analysis tool for making predictive models. It visualizes genetic distance and relatedness between populations. PCA can be done by eigen value decomposition of a data covariance (or correlation) matrix. Principal Component Analysis (PCA) is the process of data reduction or dimension reduction. For this research PCA is done through SPSS. From the factor analysis the data is converted into six principal components as shown in below (Table 5). The different factors are categorized in same components (factor loading) for those factors having significant factor loading value greater than 0.3 (Table 6).

Total variance explained (TVE)

The % of Variance column gives the ratio, expressed as a percentage, of the variance accounted for each component to the total variance in all of the variables. The first component will always have the highest variance (and hence have the highest eigenvalue), and the next component will have as much of the left over variance as it can, and so on. Hence, each successive component will account for less and less variance. The result obtained for this study can be seen in table 6 below:

Varimax rotation

A varimax rotation simplifies the expression of a particular sub-space in terms of few major items. The actual coordinate system is unchanged. The alignment is on the basis of orthogonally. Varimax maximizes the sum of the variances of the squared loadings (squared correlations between variables and factors). All the coefficient will be either large or near zero, with few intermediate values.

Naming of components

Looking for similarity between items that load on a factor, the first component is named as “Component Related to Management and Leadership” that contributes about 33.52 % of the total variance explained. The second component is named as “Component Related to Internal Barriers” that contributes about 9.39% of the total variance explained. The third component is “Component Related to Security Concern” that contributes about 4.33% of TVE. The fourth component is “Component Related to External Barrier” that contributes about 3.93% of TVE. The fifth component is “Component Related to Cost” which contributes about 3.81% of TVE. Lastly, the sixth component is “Component Related to Policy” which contributes about 3.57% (Table 7) of TVE. The Eigen value of the six different components categorized using PCA and Varimax are seen to be greater than 1 (Table 8). It describes that all these components or factors are highly reliable. Moreover, the different factors are categorized in same components (factor loading) for those factors having significant factor loading value greater than 0.3.

Reliability Analysis of Identified Components

Reliability test for the six grouped components is performed using SPSS. Cronbach’s alpha test value is presented in (Table 9) below. The Cronbach’s alpha value of all the components concludes the acceptance and reliability of components. Reliability of the four components is seen to be accepted (greater than 0.7) and for two components, the alpha value is greater than 0.6 which is questionable but can be used. Now, the implementation model that can be used to judge the success of ICT Implementation in SMEs can be developed on the basis of results obtained from the above analysis.


The findings of this research, based on the analysis of responses from 221 participants representing various SMEs in Kathmandu, reveal several key insights. It is noteworthy that a majority of the respondents (82.8%) were male, and the most represented sectors among respondents were academic institutions (39.4%) and software and hardware industries (22.6%). The reliability test, assessed using Cronbach's Alpha, indicated good internal consistency among the survey questions. Standardized values pointed to "Internal Readiness/Trainings" as the most critical success factor for ICT implementation, while "External Barriers" emerged as the most formidable obstacle. Further statistical tests, such as the Kaiser-Meyer-Olkin (KMO) and Bartlett's tests, affirmed the suitability of the data for factor analysis. Principal Component Analysis (PCA) was employed to extract six components, with the Total Variance Explained (TVE) computed for each. The reliability of these items, as measured by Cronbach's alpha, was found to be acceptable. Ultimately, these factors form the basis for developing models to enhance the effective use of IT in SMEs. Key success factors identified included top management support, team member motivation, IT staff training, change management, and software testing, while barriers included lack of IT benefits and data lack of security concerns (Figure 1).

Conceptual Model

The conceptual model developed according to the factors identified and using the new collection of factors is as follows:

Through rigorous research, this study has identified several key success factors and barriers for ICT adoption in SMEs. Importantly, success factors include top management support, motivating team members, IT staff training, re-engineering departments, thorough software testing these factors is key to successful adoption of IT and contributes significantly to SME success in this regard.

Figure 1: Conceptual model developed by researchers.

In contrast, lack of staff supports in markings, lack of knowledge, infrastructure constraints, low staffing, safety concerns, inadequate product/vendor support, information insufficient inclusion and penetration of information technology. They can fail. In addition, factors classified through principal component analysis (PCA) include management and leadership dimensions, internal barriers, security concerns, external barriers, cost considerations, and process factors.


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