A MULTILAYER PERCEPTRON NETWORK–BASED ANALYSIS TO CONFIGURE SMES STRATEGIC ENTREPRENEURSHIP FOR SUSTAINABLE GROWTH

10.17708DRMJ.2020.v09n02a03 (Clanek 3)

DOI:

10.17708/DRMJ.2020.v09n02a03

Excerpt:

 This study analyzed the close interaction among organizational networking and financial mechanisms of growth and sustainable growth of SMEs operating in Albania. Data on 120 SMEs for 2017–2018 were analyzed using multivariate regressions and multilayer perceptron artificial neural networks. Initially, the data were analyzed using multivariate regression analyses to find the correlation between firms’ growth measured by three different indicators: return on equity, return on assets and business size. In this approach, growth takes into consideration a firm’s liquidity, its operational efficiency, and leverage indicators in addition to organizational characteristics. The results obtained during the initial phase were fed to the multilayer perceptron artificial neural networks model to evaluate SMEs growth and further their sustainable growth process by using the age of the firm, classified into start‐up, grown, and matured stages. The model results showed that SMEs in the start‐up stage assume a risk‐taker approach toward sustainable growth. In the grown stage, they implement a market‐timing strategy in selecting investments toward a sustainable growth perspective. Those in matured stage replicate the liberal managerial style of the SMEs in start‐up stage, but employ a less aggressive strategy. 

Pages:

37-50