Abstract
In order to make positive socio-economic transformations, the concept of the sustainable development was proposed and it can be implemented through the innovation. And startups are among the modern innovation drivers. So, the aim of the research was to identify the key startup success factors and to develop an instrument for startup success evaluation in order to minimize the loss of time and resources and partly overcome the high uncertainty rates, specific to the startup industry, using multidisciplinary approach and, in turn, contribute to the sustainable development implementation. It was found that there are three main constituents which influence the startup success – an external environment, startup activity and an internal startup environment. The determined success factors were analyzed according to the groups which correspond to these constituents. The mathematical model in the form of the Bayesian network for evaluation and prediction of the startup success was developed. It was found that the modeled startup success probability is most likely to be of a low or an average level. The conditional probabilities distribution for the startup success was also analyzed. The developed model can be used for the startups success levels determination in a particular country, specific market, etc.
Highlights
In order to make positive socio-economic transformations, the concept of the sustainable development was proposed and it can be implemented through the innovation
The determined success factors were analyzed according to the groups which correspond to these constituents
It was determined that there are three main constituents which influence the success of the projects – an external environment, startup activity and an internal startup environment
Summary
A lot of scientific papers are devoted to the study of the features of innovative projects, many researchers try to figure out how this phenomenon affects the development of specific countries and the world as a whole and try to determine the factors that influence startup success. They apply both qualitative and quantitative methods and mathematical modeling is one of the key tools in their investigations. They were used for credit risks assessment (Leong, 2016) and in the marketing sphere (Reyes-Castro & Abad, 2016); for modeling processes that occur in the environment (Aguilera, Fernández, Fernández, Rumí & Salmerón, 2011); cyber security analysis (Peng, Li, Xinming, Peng & Levy, 2010); for the evaluation of risks arising during the software projects implementation (Hu, Zhang, Ngai, Cai & Liu, 2013), etc
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International and Multidisciplinary Journal of Social Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
