A study on the effect of successful factors of establishment on business performance and youth start-upfirms' competence

Abstract

Background/Objectives: This study is to investigate the competence and success factors of entrepreneurs who have influence on business performance for young entrepreneurs and provide factors that increase the business success rate. Methods/Statistical analysis: The survey was conducted by CEO of technology-based young entrepreneurs who were under 39 years old. The number of people surveyed was 330, and the number of questionnaires was 205, which was 62.1%. The collected data were analyzed using SPSS 22 and Smart PLS 3.0. The measurement and the structural model were analyzed to evaluate the significance and suitability of the path coefficients between the variables. Findings: We analyzed the internal consistency reliability, intensive validity and discriminant validity by analyzing the measurement model and analyzed the structural model to evaluate the significance and suitability of the decision factor (R2) effect size (f2), multicollinearity (VIF) and path coefficient. The results of the hypothesis tests on the results of the estimation of the path coefficients (Mean, STDEV, T-Value, P-Value) show that EX-S → NPF, NW-C → TECH-P, TECH-C → NPF, TECH-C → TECH-P, TIC-A → FP hypotheses were adopted to meet the significance and conformity criteria. In this paper, we can confirm that technological commercialization ability and technological innovation capacity, which are sub-factors of technological entrepreneurial capacity, which is a parameter of the core differentiating research model with the previous research, also have an important influence on business performance and creation. In conclusion, the effect of technology start-up success of technology start-up firms on the impact of technology start-up capacity and business success is confirmed through structural modeling and the result is provided to contribute to the formulation of national policy. Improvements/Applications: It is necessary to perform further research by expanding the technology field into manufacturing, non-manufacturing, IT, AI, Big Data companies and to carry out further research as a follow-up topic.