Development of an expert system to evaluate risks of launching a startup

Absztrakt (kivonat)

Launching a startup involves significant risk, and accurately assessing these risks is crucial to the success of the venture. This thesis aims to address this challenge by developing a unified expert system for risk evaluation specifically designed for startups in the IT industry in the European region. The proposed expert system employs various pre-money evaluation methods to determine a value of a startup and associated risk value. Qualitative methods, including the Berkus, Risk Factor Summation, and Scorecard methods, are used to evaluate key factors that contribute to startup success. Fuzzy logic is employed to estimate the qualitative risk factors in light of the uncertain nature of the startup environment. The expert system is developed as a Java web application to automate the assessment process. To validate the developed expert system, several methods were used, resulting in a precise calculation logic with an accuracy rate of 1, and both its precision and recall are 100%. Comparison with other existing solutions demonstrates that the proposed expert system possesses some competitive advantages. Moreover, the expert system has the potential to be further improved as development continues. The expert system for the risk evaluation for startup launching presented in this thesis is expected to help entrepreneurs make informed decisions when launching a startup by providing a reliable and accurate assessment of the risks involved. Future research could focus on providing more detailed descriptions of the output data generated by the expert system, developing new methods for calculating risks, and expanding the scope of the system to other industries and geographical regions. This expert system has practical applications in enabling entrepreneurs to better understand the risks involved in launching a startup, thereby improving their chances of success.