Designing an optimal model for choosing real options in knowledge-based companies (content analysis approach and Black-Scholes model)

Real option is a systematic approach in which economic modeling can be done using financial theories, economic analysis, operations research, decision theory, and statistics. The aim of this study is to design an optimal model for selecting real  options in knowledge-based companies. This research is conducted with a mixed approach in two parts: qualitative and quantitative. In the qualitative section, by interviewing tools and qualitative content analysis method, the components of real option selection in knowledge-based companies are identified. The statistical population in this section includes university specialists and experts, managers of knowledge-based companies and competent individuals with executive positions in these companies who have executive backgrounds at decision-making levels. The sample size is obtained by purposive sampling equal to 12 people. Based on the results of the qualitative section, 11 main components and 103 sub-components are identified to select real options in knowledge-based companies. After identifying the components of real options’ valuation in knowledge-based companies, the obtained qualitative model is tested by the Black-Scholes method. To this end, the qualitative section variables are converted to computable data for knowledge-based companies and then, the relevant statistical data are collected for 50 knowledge-based companies. Quantitative section variables include operating profit, depreciation, capital expenditures, working capital and, finally, the free cash flow of knowledge-based companies. The results show that the Black-Scholes method has more valuation than the traditional method.