Evaluating the performance of biotechnology companies by causal recipes

This study empirically investigates six variables and their combinations that may affect revenues of Taiwan's biotechnology industry. Examine variables include annual government investment, annual private investment, number of national biotechnology incubator yearly, number of manufacturers that biotechnology incubators foster yearly, number of patents that listed companies own yearly, and listed companies' annual R&D expenses. Using original and incremental Taiwanese data, this study contrasts conventional multiple regression analysis (MRA) of net effects and fuzzy-set qualitative comparative analysis (fsQCA) of causal complexities. Results indicate that fsQCA outperforms MRA and successfully models both types of data with causal complexities.