Development of an early-stage startup valuation model using fuzzy logic method

Early-stage startups are recognized as high-potential investment channels; however, the absence of financial data at this stage makes their valuation challenging and a commonly encountered issue. The lack of financial data and the difficulty in traceability often deter investors from engaging in this field. Nevertheless, early-stage startups that are well-supported in areas such as education, mentorship, business plan validation, intellectual property, and financial planning tend to have stronger foundations, which can enhance their valuation and commercialization potential. The objective of this study is to evaluate the valuations and commercialization potential of early-stage startups using fuzzy logic and to develop a model addressing the gap in this domain. As part of this study, a comprehensive literature review on startup valuation was conducted, and valuation methods were examined to identify criteria specific to early-stage startups. The research data were analyzed using the fuzzy logic methodology, and the valuation and commercialization potential of early-stage startups operating across Turkey during 2022–2023 were measured. The findings were compared with the initial investment valuations of these startups post-incorporation. The results indicate that non-financial data can serve as a robust reference for final valuation and that early-stage startups possess distinct advantages, particularly in their commercialization processes.