Spurring competitiveness, social and economic performance of family-owned SMEs through social entrepreneurship; a multi-analytical SEM & ANN perspective

Abstract

Social enterprises have become a nascent concept in academia and have grabbed the attention of research scholars. They are deemed as an important predictor of economic growth, poverty alleviation, and solving social and economic issues. In the COVID-19 pandemic, many developed and developing economies accounted for a negative change in unemployment, health, education, and other social issues. Consequently, researchers realized that social enterprises are an important predictor to overcome many issues during the pandemic. Hence, the current study contributes to the body of knowledge by investigating the influence of social entrepreneurial orientation on social and economic performance through a mediating role of competitive advantage. The data were collected from the top management of family-owned manufacturing firms operating in Pakistan. The current study executed a dual-stage analysis involving Smart-PLS and artificial intelligence (AI) named Artificial Neurons Networks (ANN). The SEM model shows that social entrepreneurial orientation has a negative impact on economic performance (profit maximization) but a positive effect on social performance. ANN architecture explains the 78 % accuracy of the proposed model. Considering the results, we recommend firms emphasize social entrepreneurial orientation to configure their competitive advantage and performance in the pandemic.