Perceived Motivators and Barriers for Entrepreneurship: An Empirical Study of SMEs in Oman

Abstract

The main goal of this research is to understand how small and medium enterprises (SMEs) owners in Oman perceive the factors that drive or impede their growth and sustainability. Based on survey data of 395 SMEs in Oman, factor analysis was conducted to check if all the items load as one factor in each of the constructs. The results show that all the items measuring motivators and barriers loaded significantly for the respective scales, with high reliability (Cronbach alpha for Motivators = 0.991 and Barriers = 0.995). Relationships between the demographic factors of entrepreneurs and firm characteristics were tested and it was found that all the four variables: age of the entrepreneur (p = 0.00), qualification of the entrepreneur (p = 0.00), SME sector (p = 0.00), and age of the firm (p = 0.00) have a significant relationship with both the Motivators and the Barriers. The findings of this study could have significant implications for policymakers in Oman and other Middle Eastern countries. Since SMEs face similar problems and are given priority around the world, the findings could be applicable to other countries, as well. The findings also add important results to the empirical literature on SMEs.

1. Introduction

Small and medium enterprises (SMEs) have gained prominence for their possible role in the economic growth and industrial development in both developing as well as developed countries. SMEs play a major role in most economies, particularly in developing countries. SMEs account for the majority of businesses worldwide and are important contributors to job creation and global economic development. They represent about 90% of businesses and more than 50% of employment worldwide (World Bank, 2020). They also support large corporates by integrating into their operations. These enterprises undertake activities that allow the public sector and the government undertakings to avoid entering multiple new projects. They also cater to the needs of the local as well as international markets.

There is no standardized or universal definition of SMEs. They are classified or recognized based on the number of workers or by the size and turnover of their total assets. Further, these standards vary in different countries. They may also be recognized by their size of the investment. The Ministry of Commerce and Industry of Oman defines SMEs based on the number of workers and annual sales. SMEs form an enormous part of the total businesses in Oman. It is reported that they contribute about 70% of the total jobs in the country (Christina et al., 2014). The government of Oman has launched several initiatives like “the Youth Fund, Sanad Program Fund, incubators, and support from Oman Development Bank”. Various government ministries and departments namely the “Ministry of Commerce and Industry (Business Diagnostic Center), Ministry of Manpower (Sanad Programme), Ministry of Social Development (Livelihood (RizGH) Resources Projects), Public Establishment for Industrial Estate (Knowledge Oasis Muscat), Oman Development Bank, Omani Center for Investment Promotion & Export Development (OCIPED) have supported various programs for youth entrepreneurship development” (Alfoqahaa, 2018).

The biggest challenge of all for any SME is ensuring that your business remains successful and stands out from its competition. The issues and challenges in the growth and sustainability of SMEs have been focused on in several studies. There are factors ranging from access to finance, competitiveness, and government support to their own internal weaknesses that affect them. Researchers are also still debating whether SMEs result in economic development, implying that policymakers might be wary about supporting these SMEs. Compared to mainstream businesses, SMEs find more constraints in upscaling and growth. These constraints, as well as enablers, may be general as well as country-specific. A report of IMF on the challenges faced by SMEs in Oman provides a thorough insight into the country-related challenges (Stepanyan et al., 2019). Like the rest of the world, Oman too is trying to create an enabling environment for the SMEs on various factors. It is therefore important to understand the perceptions of SME owners regarding the motivators or enablers and barriers or challenges in Oman. A study of perceptions will help in better execution of the existing facilities to SMEs as well as creating new ones to support their success and sustainability. With this broad objective, the current study aims to answer the following research questions.

RQ1. What are the perceived motivators and barriers for SMEs in Oman?

RQ2. Do these perceptions relate to the demographic profile of the SME owners?

RQ3. Do these perceptions relate to the profile of the SME?

The organization of the rest of the paper is as follows. The second section discusses the extant literature related to the research questions. Research methodology and results are discussed in Sections 3 and 4 respectively. The last section presents the Discussions and Conclusions.

2. Literature Review

Studies pertaining to the factors affecting the success or failure of SMEs are plenty (Brouthers et al., 2015; Kwon et al., 2020; Prasanna et al., 2019; Sardo et al., 2018). Many of these studies try to identify the critical success factors for SMEs. A study by Pansiri and Temtime (2010) classified the critical factors for SMEs into “external issues, internal organizational and managerial issues; market and marketing issues; and finance and financing issues”. There are internal factors like “marketing practices, management, and person characteristics” and “the demand for human capital, funding problems, competition, economic conditions, and managerial preparation” as external factors that affect them (Hoda et al., 2020; Yarahmadi & Magd, 2016). Sadeghi (2018) mentioned that environmental factors like “social and political systems, legislation, technological trends, infrastructure factors, environmental dynamism, and competitive intensity” significantly influence the success or failure of companies. Chong et al (2011) listed several environmental factors focusing on SMEs in the information technology sector. These are “customer relationships, supply chain facilities, global competition, infrastructure and efficiency of information system/information technology, information visibility, support and commitment to top management, government encouragement and commitment, security and confidence, and cultural consideration”.

Christina et al. (2014) categorized the factors into three namely “psychological and personal skills, management skills and training, and external environment”. Further, they suggested that the possible barriers for SMEs are “credit rationing, high loan and lease finance costs, high enforcement costs, low infrastructure, poor skills and training, business transaction costs, judicial restrictions”. The role of infrastructure has been emphasized in studies as well (Abboud. 2018) Pramono et al. (2021) stated that SMEs play a decisive role in any developing economy. Although there is an increase in the SMEs there are also innumerable challenges associated with the growth Furthermore, SMEs face challenges in the form of policy and administrative challenges followed by marketing and financial issues.

Hundera (2014) attempted to identify the challenges and opportunities attached to Ethiopian women engaged in the SME sector. Based on a focused interview they identified the main factors as, “securing finances for establishing and running SMEs, lack of entrepreneurial and management competence and exposure, problems in finding the markets and distribution networks; limited opportunities for promotion and participation; a limited amount of government and institutional support; absence of technological knowhow and integration mechanism; and rampant corruption in an undisguised or disguised form”.

Brouthers et al. (2015) categorized the motivators or barriers into, “geographical, legal, and political factors”. Schilirò (2015) found access to finance as the critical factor affecting SMEs. Ghosh et al. (2001) opined that operational cost also affects the sustenance of SMEs. Technology and innovation have also been included as important factors (Ashrafi & Murtaza, 2008; Ibrahim Gumel, 2017; Meher & Ajibie, 2018). Khalique et al. (2011) studied the challenges faced by SMEs in Malaysia. They reported that half of the SMEs collapse within the first five years of commencement. They pointed to the lack of intellectual capital as the reason for the failure of SMEs. Tarling et al. (2016) found that mentorship and support to SMEs help in their survival.

Few studies focused on SMEs in Oman (Al Badi, 2018, 2019; Al Balushiet al., 2019; Al Buraiki & Rahman Khan, 2018; Christina et al., 2014). The main factors identified in these studies are, “bureaucracy, access to finance, high taxes, and government funding”. Ghosh et al. (2001) studied the factors in Singapore and reported “the operational cost, competition, size of market and management style, limitation in human capital” as critical factors. Al-Hyari et al. (2012) studied SMEs engaged in the garment industry in Jordan. They added infrastructure and government regulations to be the main factors affecting the success of SMEs. Business experience, access to resources, networking, help from family members, knowing the customer’s needs, and imposing long hours at work as an influence on performance (Ng & Kee, 2012a).

Alani Lawal et al., (2016) studied SMEs in Nigeria and listed the critical success factors as, “corruption and access to finance. infrastructure, institutions, financial market development, goods market efficiency, macroeconomic environment, labor market efficiency, health, and primary education, higher education and training, technological readiness, labor market efficiency, business sophistication, market size, and innovation of existing policies”. Hussain Naqvi (2011) pointed to the regulatory factors as critical to SME success.

Chong et al. (2011) suggest the importance of marketing as critical to the success of SMEs. (Feindt et al., 2002) listed eleven factors that may affect the success of SMEs. These are, “content, convenience, control, interaction, community, price sensitivity, brand image, commitment, partnership, process improvement, and integration”. Ramukumba (2014) identified three main factors namely, “the existence of a real business opportunity, access to capital, management capability, business methods”. Ng & Kee (2012) listed “management, intellectual capital, entrepreneurial competence, entrepreneurial characteristics, human resources, motivation, and market orientation” as important factors.

The items derived from the literature review are presented in Table 1. The items have been grouped as motivators and barriers.

Table 1: List of Motivators and Barriers

3. Research Methods and Materials

3.1. Data Collection

For the purpose of the study, primary data was collected through a structured questionnaire published on Google Forms. The questionnaire included items pertaining to motivators and barriers. The reliability analysis of this instrument shows that all the items have Cronbach’s alpha above 0.7 (Table 3). The SMEs in Oman constituted the population. Non-probability convenience sampling method was used to determine the respondents. Nonprobability sampling involves non-random selection based on convenience or other criteria, allowing you to easily collect data. Convenience sampling is a non-probability sampling technique where samples are selected from the population only because they are conveniently available to the researcher. The survey was conducted in the months of August-September 2020 at Muscat, Sohar, Sur, Salalah, and Buraimi. The managers or the representatives of SMEs were first contacted through phone. The contact details of the SME owners were obtained from industrial directories. Thereafter, the link to the questionnaire was shared with them. A total valid response of 395 respondents was received.

Table 3: Factor Analysis of Perceived Barriers

3.2. Descriptive Statistics

The descriptive statistics presented show that the SME owners are mainly males (97%), in the age group of 30–40 (41.5%), and with high school qualification (77.0%). The majority of the SMEs covered in the study belong to the manufacturing sector (73.7%) and have been operational for the last 10–20 years (56.7%).

3.3. Analytical Methods

The statistical analyses were done in SPSS 20.0. In the first step, a reliability analysis of the instruments was conducted. Reliability refers to the degree to which an instrument yields consistent results. Cronbach›s alpha is one of the most common methods for checking internal consistency reliability. Cronbach’s alpha values were calculated for each scale. Then, Factor Analysis was performed separately for the two scales. The components were extracted by using the Principal Component Analysis method. To answer the research questions RQ2 and RQ3, one-way ANOVA and Mann-Whitney U Test were applied.

4. Results

4.1. Reliability Analysis

The motivators scale included 15 items and the barriers scale included 22 items. Cronbach’s alpha values for both the scales were 0.991 and 0.995 respectively. Item-wise values of Cronbach’s alpha for both the scales were also above the required values of 0.7 (Taber, 2018).

4.2. Factor Analysis Factor analysis

is a technique that is used to reduce a large number of variables into fewer numbers of factors. This technique extracts maximum common variance from all variables and puts them into a common score. As an index of all variables, we can use this score for further analysis. The factorability of both motivators and barriers was examined. The results are discussed as follows.

4.2.1. Factor analysis of perceived motivators

First, the factor analysis of the 15 items pertaining to motivators was performed (See Table 2). The Kaiser-MeyerOlkin value was found to be 0.946 which is well above the required value. Bartlett’s test of sphericity show that the it is significant (dF = 105, p = 0.00). The communalities were found to be much above the required values. Principal component analysis was used to check if all the items explain the construct and it was found that all the 15 items formed one factor.

Table 2: Factor Analysis of Perceived Motivators

Extraction Method: Principal Component Analysis.

4.2.2. Factor Analysis of Perceived Barriers

Another factor analysis of the 22 items pertaining to barriers was performed (Table 3). The Kaiser-MeyerOlkin value was found to be 0.947 which is well above the required value. Bartlett’s test of sphericity show that the it is significant (dF = 231, p = 0.00). The communalities were found to be much above the required values. Principal component analysis was used to check if all the items explain the construct and it was found that all the 22 items formed one factor.

4.3. Relationship Between Demographics and Perceived Motivators/Barriers

After examining the two constructs, we conducted further investigated the relationships between demographic variables related to the SME owners and their perceived motivators and barriers. The two variables related to demographics are the age and qualification of SME owners. Statistical tests were performed to test if there is a significant relationship between these demographic variables and what the SME owners perceive regarding motivators and barriers. The results are discussed as follows.

4.3.1. Age

Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the “variation” among and between groups) used to analyze the differences among means. A one-way ANOVA was conducted to test the relationship between age and perceived motivators. We find that the relationship is statistically significant (p < 0.05) for both perceived motivators and barriers (Table 4). Therefore, it may be inferred that the age of SME owners significantly affects the perception regarding perceived motivators and barriers.

Table 4: Age and Perceived Motivators/Barriers

4.3.2. Qualification

A one-way ANOVA was conducted to test the relationship between the educational qualification of SME owners and perceived motivators (Table 5). We find that the relationship is statistically significant (p < 0.05) for both perceived motivators and barriers. Therefore, it may be inferred that the qualification of SME owners also significantly affects the perception regarding perceived motivators and barriers.

Table 5: Qualification and Perceived Motivators/Barriers

4.4. Relationship Between SME Profile and Perceived Motivators/Barriers

The profile of SME as assessed in terms of the sector it belongs to and year of operations (its age) are also important factors that may affect the SME owners’ perception regarding motivators and barriers. The results are discussed below.

4.4.1. SME Sector

The Mann-Whitney U test is used to compare whether there is a difference in the dependent variable for two independent groups. It compares whether the distribution of the dependent variable is the same for the two groups and therefore from the same population. Independent sample Mann Whitney U test was used to test if there is a significant relationship between the SME sector and the perception of the owners regarding motivators and barriers. The results show that there is indeed a significant relationship between the SME sector and perceived motivators as well as barriers (p < 0.05).

4.4.2. Age of SME

The age of SME was grouped into three. A one-way ANOVA was conducted to test if there is a significant relationship between the age of SME (years of operation) and perceived motivators and barriers. We find that the relationship is statistically significant (p < 0.05) for both perceived motivators and barriers (Table 6). Therefore, it may be inferred that the age of SMEs significantly affects the perception regarding perceived motivators and barriers.

Table 6: Age of SME and Perceived Motivators/Barriers

5. Discussion and Conclusion

Based on the literature review, we were able to identify a list of items that were grouped into motivators and barriers for SMEs. These items were then used in the questionnaire to measure the perception of SME owners regarding their agreement or disagreement. The factor analysis performed for the two constructs namely motivators and barriers shows that all the items sufficiently explain the two constructs respectively.

Subsequent analyses were performed to test the relationships between two demographic factors related to SME owners and two factors related to the enterprise. We found that both age and qualification of SME owners significantly affect the perceptions regarding motivator and barrier to SME success and sustenance. In terms of the SME profile, we found that the SME sector as well as its age significantly affects the perception regarding motivators and barriers.

These results all point to the need for a better understanding of the perception of SMEs and helping them in a more focused manner. The schemes, incentives, support systems should all be developed in a way to address the different needs that exist based on the above factors. Appropriate training and skill development programs would help improve the confidence of SME owners. Support in terms of technology and infrastructure is also required to be improved. In fact, one of the items in barriers is the lack of knowledge. This indicates that the owners of SMEs are unaware of the numerous facilities available to them. As a result, information about government assistance in terms of facilities, technology, and procedures should be widely disseminated.

The results suggest that the government must develop a framework to ensure that the SME owners perceive the motivators in a better way and find the barriers to be removed. Government regulations and infrastructure are very important factors as identified in this study. As suggested by Christina et al. (2014), a directorate to address the various needs of SMEs should be established. Access to finance forms an important item among the barriers. Further the recommendations by Ghosh et al (2001) for “liberalized credit facility, factoring services and tax benefits for SME lending” should boost the growth in the sector.

The findings of this study should be useful for better understanding the factors that affect SMEs. The research on critical success factors of SMEs will also be benefited as we have considered a more expanded list of motivators and barriers. We have further explored the relationships between the various variables with perceived motivators and barriers.

One of the main limitations of the study is that the questionnaire was self-answered which might have added biasness. Another limitation is the sampling method. A convenience sampling method limits the generalizability of the findings. We, therefore, recommend that our results should be interpreted considering these limitations.