Uncertainty is inherent in the process of entrepreneurial activities and has caused a high failure rate of startups. In fact, 46% of new ventures run out of business within 4 years of operation, according to Statistic Brain Research Institute. On the other hand, a type of uncertainty that entrepreneurs need to prioritize varies depending on the industry. In high technology industries, severe problems are frequently caused especially by market uncertainty due to continuous technological developments and industries’ volatile characteristic. In entrepreneurship research, Sarasvathy introduced the concept of effectuation in 2001. Since then, the theory of effectuation has been studied by a number of researchers, as successful entrepreneurs have incorporated this theory. However, empirical evidence of effectual processes covering the applicability in high technology industries has not been testified yet. Therefore, the main purpose of this research is to fill this gap and find an answer to our research question, how do entrepreneurs effectuate in decision-making to respond to market uncertainty in high technology industries? We implemented a quantitative investigation by conducting an online survey of entrepreneurs in high-technology industries. The main findings and conclusions are that entrepreneurs in high-technology industries apply both causation and effectuation. However, causation is slightly more implemented than effectuation. Additionally, we found that experimentation-driven approach helps entrepreneurs in high-technology industries deal with market uncertainty as supplementation of effectuation.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-325029 |
| Date | January 2017 |
| Creators | Quiroga Fernandez, Ingrid Nataly, Hohyama, Tadayuki, Tran, Loi |
| Publisher | Uppsala universitet, Företagsekonomiska institutionen, Uppsala universitet, Företagsekonomiska institutionen, Uppsala universitet, Företagsekonomiska institutionen |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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