engleski

Modeling and Predicting the Growth of SME

Small and medium enterprise growth has recently become one of the central issues of entrepreneurship research. Understanding how SMEs grow is especially important since it is the small and medium sized, growth oriented enterprises that make most tangible contribution to economic growth. Therefore, numerous research studies are devoted to investigating factors related to growth. They have usually been understood in terms of three main categories: the entrepreneur, the enterprise and the environment. However, studies on SME growth are fragmented and there is a lack of conceptual framework which could integrate and explain the SME growth complexity. One way of dealing with this issue is to develop an empirical model that connects all factors related to growth. With such an approach knowledge from different studies is assembled in one model and also contribution of each factor on SME growth is identified and measured. In such a way the understanding the complexity of SME growth is risen. In line with that, the aim of this research is to develop growth model for SME. In addition to giving insight into variables related to growth, the model specificity is its ability to predict growth. Factor analysis and logistic regression are used for developing the growth prediction model. Data set for this research consists of 265 SMEs from Croatia. The data covers the period 2010-2015. SME is defined as growing if it has an average annualized growth in sales greater than 20% a year, over a three-year period. Independent variables combine financial data and survey data collected through questionnaire. Variables are related to the entrepreneur, the SME and the environment. The results show that variables important for prediction the growth of SMEs are: high tech level, age of the SME, resources - human capital, network and financial resources, growth attitude and barriers to growth. Implications of this study are of value to SME owners, managers as well as policy makers.

entrepreneurship, SMEs growth, factor analysis, logistic regression, prediction model, growth potential

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