Group Decision Support Model for Tech-Based Startup Funding using Multistage Fuzzy Logic

Muhammad Donny Devanda, Ditdit Nugeraha Utama

Abstract


The startup business model has grown rapidly in the last few years. However, giving investment or funding to a startup, especially in its early stages, is not easy because the risk is higher than a conventional company. This paper proposes a group decision support model (GDSM) that can help both government venture capital (GVC) and private venture capital (PVC) make the right funding decision. The model was built using a simple mathematics method (SMM) and multistage fuzzy logic (MFL) to examine twenty-two parameters in the form of fuzzy and nonfuzzy values. Two experts from GVC and PVC were interviewed to weigh all the parameters. The model is implemented and tested using three real-world data. Ultimately, the model can help decision-makers in GVC and PVC to decide the most optimum funding for startups.


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References


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DOI: https://doi.org/10.31449/inf.v47i6.4569

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