MACHINE AND DEEP LEARNING MODELING OF UNIVERSITY BUSINESS INCUBATORS(UBI) DYNAMIC CAPABILITIES WITH THEIR ENTREPRENEURIAL ACTIVITIES AND VALUE CREATION : A MIXED METHOD STUDY

Abstract

This study investigates how UniversityBusiness Incubators(UBIs) align their capabilities (substantive and dynamic) to their entrepreneurial activities in creating value within the ecosystem. The study is based on an aggregation of a doctoral research project and a research review article on UBIs capabilities.This study further develops a conceptual framework that integrates UBI based capabilities studies with their entrepreneurial activities and a statistical model with machine and deep learning in predicting how UBIs can align their innovation and market strategies with their capabilities in fostering startups and incubators survivability, sustainability and developing a high level of adaptation to challenges and crisis during the process of incubation. This study adopts a sequential exploratory mixed method approach based on exploratory and predictive research objective with a pragmatic paradigm or worldview.The study contributes to UBI study by developing an integrated framework that encapsulates UBIs dynamic capabilities, venture survivability and sustainability with UBIs socio-human structures and relationships with entrepreneurial activities studies which had been a major gap in literatures. This study further enhances the adoption of mixed method research design in UBI studies by combining the benefits of qualitative exploratory cases (studies) with statistical predictive modeling. Based on selected cases using purposive and nested sampling design and scheme, this research study would further apply the conceptual framework to UBIs in different regional contexts.