| Autor: |
Tomy, Sarath, Pardede, Eric |
| Předmět: |
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| Zdroj: |
Proceedings of the International Conference on Innovation & Entrepreneurship; 2017, p161-169, 9p |
| Abstrakt: |
Uncertainties exist in business environment pose challenges for new start-ups. Knowledge of these uncertainties influences the success and growth of a firm, which is important in the pre-start-up phase of the entrepreneurial process. Entrepreneurs need support when making decisions and the decisions have to be made swiftly, with sufficient and reliable data. The purpose of the study is to examine how the analysis and evaluation of uncertainty factors with the help of data can predict the future of an organization success. The research adopts a mixed methods approach incorporating both qualitative and quantitative techniques, building a robust technique to investigate complex cognitive phenomena in entrepreneurial contexts. In the first phase the main uncertainty factors influence the success or failure of a firm are identified and categorized using existing literatures. In the second phase a success prediction model is implemented using machine learning techniques and trained it with survey information collected from the ICT companies operating in Victoria, Australia and data from GEM consortium. The approach here is to apply machine learning algorithm to train the model and to predict the success or failure depends on the input values. The model is trained in such a way that when new data comes in, the qualitative data is transformed into quantitative data and the probability of success or failure is calculated as the result output in the pre-start-up phase. This allows nascent entrepreneurs to make likelihood predictions on the basis of data. The model is implemented as a web interface and the accuracy of the prediction model is evaluated using Confusion Matrix. The model is used to uncover the frequency of the relations that links the input uncertainty factors with the success or failure of a firm. The particular strength of this method is to evaluate the opportunity based on unrelated factors and identify the patterns by the exploration of relations between them. The method and findings would be relevant for nascent entrepreneurs and researchers focusing on entrepreneurship. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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