Developing a model to predict the performance of small and medium-sized enterprises: the case of the kingdom of Saudi Arabia

Al Saleh, Ahmed Youssef (2016) Developing a model to predict the performance of small and medium-sized enterprises: the case of the kingdom of Saudi Arabia. Doctoral thesis (PhD), Manchester Metropolitan University.

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Abstract

The small and medium-sized enterprise (SME) sector is becoming increasingly important in the economic and social development of nations. In view of the essential nature of SME activity, the overall aim of the present research is to develop a model that is able to predict SME performance in the Saudi context. One of the reasons for embarking upon this study is that the number of SMEs that have ceased to operate in the Saudi context has recently increased, and their contribution to the economy has been reported to be low. Therefore, it is an essential to increase these SMEs’ contributions, thus enabling them to play a more central role in the Saudi Arabian economy. This can be done by identifying the factors most closely associated with their performance in order to increase their probability of success and decrease their failure rate. The research’s aim has been reached through focusing on the various different factors, produced both from inside businesses and in the external environment, which are associated with SMEs’ performance in the Saudi context. Success and failure definitions were then used to measure SMEs’ performance based on their profits. Data were collected using a quantitative method. Questionnaires were distributed to SMEs in the Eastern Province of Saudi Arabia, and the responses were analysed. First, a descriptive analysis was conducted to identify the owners/managers and their businesses’ characteristics. Second, an exploratory factor analysis was performed to find relationships in which variables were maximally correlated with one another and minimally correlated with other variables, and the variables were then grouped accordingly. Third, the results of a logit regression analysis were examined in order to predict SMEs’ performance and classify it as successful or not in the Saudi context. The main findings of the present research indicate that the full model containing all the predictors is statistically significant. Looking at the individual factors, it found that five factors add a unique, statistically significant contribution to the model; these are: owner/managers’ experience, planning, intensity of competition, the regulatory environment, and terrorism risk. The present research is among only a few researches focusing on the Eastern Province of the Kingdom of Saudi Arabia that have provided a study relating to SME performance from the perspectives of the owner/managers themselves. The findings of the present research could also be applied in other, similar contexts, such as other Gulf Cooperation Countries (GCC).