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 difficult 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 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.
Read PublicationThe previous study of the Butterfly Life Cycle Algorithm (BLCA) has been technically realized in two stages of BLCA in measuring a company's growth performance. It was based on a combined method of the Balanced Scorecard (BSC) and Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis. This paper aims to continue the BLCA implementation by performing five stages of BLCA and then improve the algorithm by implementing the Fuzzy Logic (FL) conception into BSC. The implementation of the FL method transforms the bias values in four BSC parameters into a precise value to make the model more precise. A complete BLCA algorithm combined with FL is used to accurately assess companies' growth performance. By doing some corrections to the preceding study's data of contribution value, the simulation result shows the difference in the performance value of 0.0026 with the previous one.
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