Performance factors of software firms in developing economies: a hybrid structural and artificial neural network model

Abstract

The research paper presented in this project report focuses on the comparative performance of software companies in developing countries concerning product radicalness, new product advantages, customer unfamiliarity, and industry differences. It is based on SEM-PLS and ANN methodologies and therefore adopts a sophisticated approach to the study of these variables and their relationships. As a result of the outcome SEM-PLS, it was established that product radicalness relates positively to firm performance through new product advantages, while customer unfamiliarity has a negative impact. To further enhance predictive accuracy, we applied the ANN model, which accommodates non-linear relationships and non-normal data distribution. Based on the results, the ANN model revealed an 86.2% prediction accuracy and ranked product radicalness as the first key contributor to firm performance. In addition, industry differences were also represented when the different trends were discovered; for example, there was a higher sensitivity to customer unfamiliarity in the manufacturing industry than in the service industry.