Developing an Initial Predictive Model for Screening Potential Entrepreneurs in the B40 for Targeting Assistance

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Sagaran Gopal
Sulochana Nair

Abstract

Over the years, government through its agencies has provided various forms of assistance under numerous entrepreneurship development policies and programs to encourage and help the development of entrepreneurship. These programs / assistances however have not brought out the desired results to the programs. Many of the recipients of the assistance remain at the same stage of entrepreneurship even after receiving assistance and that is, there is lack of movement upward of the entrepreneurs to a higher level from being just micro entrepreneurs. Others have not used the assistance given for entrepreneurship but have used it for consumption purposes. In addition, the assistances / program given may not have reached the right target group of deserving entrepreneurs who have all the necessary attributes of being an entrepreneur, such as being innovative and creative, forward looking, higher need for achievement, not afraid of failure and willingness to take calculated risks. The research objectives are (1) to identify the indicators that can be used to screen the potential entrepreneurs in the B40 category; (2) to ascertain the benefits of screening potential entrepreneurs in the B40 category to its stakeholders; (3) to develop a case-based reasoning artificial intelligence system based on the predictive the model. Both primary and secondary data will be used for this research. For the data collection of the primary data, the researchers will use a quantitative research approach to screen the entrepreneurs from the B40 group. This research is an exploratory design in nature as it aimed at the entrepreneurs in the B40, and intends to screen the potential one for further targeting assistance. In here, the researchers will develop indicators that can be used as a tool to screen the potential entrepreneurs. Eventually, a case-based reasoning artificial intelligence system for predictive the model will be developed.

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