The entrepreneurial journey is not short of challenges, and about 90% + tech start-ups experience failure (Startup Genome, 2019). The magnitude of the challenges varies across the tech start-up lifecycle stages, namely emergence, stability, and growth. This opens the research question, do the profiles of a start-up and its co-founder impact start-up success or failure across its lifecycle stages? This study aims to understand and identify the profiles of tech start-ups and their co-founders. We gathered primary data from 151 start-ups (Status: 101 failed and 50 successful ones), and they are across different lifecycle stages and represent six major start-up hubs in India. The chi-square test on status and start-up's lifecycle stage indicates a noticeable correlation, and they are not independent. The Kruskal Wallis test was used to distinguish statistically significant profile attributes. The parameters distinguishing success and failure are identified, and the need to deliver customer experience is emphasized by the start-up profile attributes: Product/service, high-tech nature of a start-up, investor fund availed, co-founder experience, and employee count. The importance of entrepreneurial experience is ascertained with entrepreneur profile attributes: Entrepreneurial expertise, the number of prior and current start-ups, their willingness to start again in the event of failure, and age of co-founder, which is a proxy to learning and experience. This study has implications for entrepreneurs, investors, and policymakers.
There are many studies on spin-offs from college, but there is little concern on start-ups, which are set up by college and operated by professors. We call this type of start-up as college start-up. We check the problems and solutions of this type of start-ups. We propose three factors for success; prior checking of profitability of the business, preparation of relevant school policies and profit sharing with school and professors participated.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.15
no.1
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pp.59-70
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2020
This study was proceeded to empirically identify the start-up support policy as an element that affects the performance of the early start-ups and measure the effectiveness of the current start-up support policy, in order to suggest the direction future policies according to the study. To accomplish this the influence of the start-up support policy on the early start-ups was analyzed, and the differences according to the industry and growth stage of the start-ups, as the characteristics of the start-ups, were identified. The research subjects collected real data of 297 start-ups of the past three years that were selected for the Initial Start-Up Package project, and performed multiple regression analysis on the influence between variables, and hierarchical regression analysis on moderating effects. The summary of the study is as follows. First, as a result of identifying the influential relationship between the start-up support policy and the performance of the start-up, sales had made a significant impact on the start-up fund, start-up mentoring, and start-up infrastructure(space), while start-up education failed to show a significant effect on the increase in sales. In terms of employment, start-up mentoring was the only field that showed a significant influential relationship. Second, as a result of identifying the moderating effect of the start-up's industry and growth stage, the industry did not have a statistically significant influence, but the interactive effect was seen in start-up education. To be more specific in terms of the sales relationship of each industry, knowledge services turned out to be helpful in improving sales, while manufacturing turned out to be effective in improving sales regardless of being supported with start-up mentoring and start-up infrastructure (space). The sales relationship regarding the start-up growth stage was identified to be statistically significant. The preliminary stage was not statistically significant, while providing start-up mentoring and start-up funding were effective for start-up stage and growing stage, respectively. On the other hand, employment did not perform a significant influence on the start-up growth stage. This study analyzes the effectiveness the start-up support policy for early start-ups, identifies the need in differentiated support policies according to the characteristics of the start-ups, and suggests implications for the direction in which future policies should be made towards.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.16
no.6
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pp.57-68
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2021
The purpose of this study is to investigate the effect of location satisfaction of innovative start-ups, located in capital and non-capital areas, on the intention of relocation. The analysis was based on the data of a survey of 231 innovative start-ups that were founded less than 7 years ago. 10 factors related to the aspects of business management, network building, and business environment were considered as location satisfaction of start-ups. The dependent variable was whether innovative start-ups plan to relocate. First, it was confirmed that in the case of innovative start-ups in capital area, the intention to relocate was found to decrease when the location satisfactions related to the promptly provision of products and services to consumers and ease of supplying labor were increased. Second, in the case of innovative start-ups in non-capital area, it was found that the intention to relocate was found to decrease when the location satisfactions related to creating a network, convenient transportation and free and creative start-up environment were increased. In addition, it was found that the higher the sales of start-ups in non-capital area, the lower their intention to relocate while the higher firm age of start-ups in non-capital area, the higher their intention to relocate. This study has an academic contribution to examining the relationship between between the location satisfactions of start-ups and the intention to relocate, which has been rarely addressed in Korea, and to shedding light on the difference in capital and non-capital areas. Furthermore, this study has policy implications since it suggests factors that the government should consider for geographical agglomeration of start-ups.
Purpose - This study aims to advance our knowledge about factors influencing technical startup performance through analysing technical startup process empirically. This study was conducted to focus on industry structure(industry growth rate, competitive intensity, and enter barriers), technology characteristics(technical excellence and wide range of technical application), and the performance in the technology-based start-ups. Specifically, analyzing moderating effect of technology-marketing strategy, this studied how moderating variables affect technical startup performance under industry structure. Research design, data, and methodology - The subject of this study was technology-based start-ups company that received technology transfer from public organization. The development of the paper model is based on the literature of the preceding research analysis in technology commercialization, performance of technology-based start-ups, and marketing strategy. This study has a construct that was defined in the previous studies, such that technology marketing strategy was defined into the two ways of being broad or narrow in strategic application. From November 3. 2015 to December 22, 220 questionnaires were distributed with targeting to start-up companies in technology-based. 188 responses were collected for empirical analysis except the missing and wrong value responses. This data were used for structural equation modeling and regression analysis. Results - The results of this study are as follows. First, as industry structure variables influencing on performance(technical, financial) of technology-based start-ups, industry growth rate, competitive intensity and enter barriers of variables were verified; high growth rate has more positive effect on performance than low growth rate, competitive low intensity has more positive effect on performance than competitive high intensity, low enter barriers have more positive effect on performance than high enter barriers. Second, as technology characteristics variables influences on the performance(technical, financial) of technology-based start-ups, technical excellence and wide range of technical application of variables were verified ; technical high-excellence has more positive effect on performance than technology low-excellence, wide range of technical application has more positive effect on performance than narrow range of technical application. We also find that technology marketing strategy(broad/narrow) in moderating factors on performance (technical, financial) is as follows. Analyzing the moderating effect depending on technology marketing strategy(broad/narrow), application of technology, and the types of technology strategy(broad/narrow) were revealed that broad marketing strategy had a more significant effect on performance of technology-based start-ups. With AMOS, the relevancy of the study model revealed higher for broad technology-marketing strategy than narrow technology marketing strategy, and the explanatory power revealed to be 6.4% higher in broad marketing strategy than narrow marketing strategy. Conclusions - This study confirmed that industry structure and technology characteristics are important factors influencing the performance of technology-based start-ups. Technology-marketing strategy affects the performance of technology-based start-ups between industry structure and technology characteristics. According to additional analysis, moderating variables and technology-marketing strategy are important factors influencing the performance of technology-based start-ups under industry structure and technology characteristics. Broad type of technology-marketing strategy has more attractive industry structure and excellent technology characteristics than narrow types of technology-marketing.
The key conditions for the promotion of innovative technology-based start-ups are expanding the market for innovative technology products and services, increasing equity-based funding opportunities, promoting the commercialization of technological innovation, and establishing a fair-trade system for start-ups to compete fairly in the market. Besides, there is a need for a support system that minimizes the cost of failure in case of business failure to facilitate re-challenge and provides education and training opportunities to enhance entrepreneurial capabilities. To activate technology-based start-ups, the Korean government introduced the TIPS policy in 2013. It is a program that creates technology start-up with private investment led by successful venture entrepreneurs, which has shown remarkable achievement and is regarded as the most successful policy in this field up to now. The most critical factor contributed to the success of this program is to invite private investors to select a technology entrepreneurship team and provide mentoring with the investment. The government provides R&D funding with matching investment, commercialization and marketing support to ensure that technology start-ups survive crossing the death-valley. Subsequent investments from domestic and abroad investors are actively made and it is becoming a representative technology-based start-up program in Korea.
Journal of Information Technology Applications and Management
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v.22
no.4
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pp.1-37
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2015
Micro small business start-ups are receiving financial and marketing support from government or public authority, but business closure rate is very high and it causes a hugh burden to households and national economy. This study aims to verify the causal relationship between the self-determination characteristic of small business start-ups and entrepreneurial intention through learning orientation and innovation ability. The man's intrinsic motivation of self-determination theory is expected to have an impact on the entrepreneurial intention of small business start-ups. The self-determination theory includes perceived autonomy, perceived competence, perceived relationship as independent variables. This study presented a research model for explaining the entrepreneurial intention of small business start-ups, and collected 260 survey responses from the small business start-ups In order to validate the proposed research model, PLS analysis is performed with valid 246 questionnaires. By PLS technique, the measurement reliability and validity of research variables are tested and the path analysis is conducted to do the hypothesis test. Path analysis shows that perceived autonomy does not significantly affect the learning orientation and innovation ability. On the other hand, perceived competence significantly influences learning orientation and innovation ability. Perceived relationships had significant influence on learning orientation. It is found that the parameters of learning orientation and innovation ability significantly influence the dependent variable of entrepreneurial intention. Based on the results, a policy and strategy for supporting small business start-up are presented.
Journal of Korean Institute of Industrial Engineers
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v.40
no.5
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pp.462-476
/
2014
The Korean government has been implementing diverse policies with programs to generate better outcomes and results of university-industry collaboration since 1990s. In this paper, we analyze the effect of universities' competency factors on the performance of technology commercialization and start-ups respectively. We employ multiple regression models using 154 data sets from university information posting system of the Korean Council for University Education. Through conducting statistical analyses with diverse data manipulations, we obtained a high degree of significance on hypotheses, and also could compare mutual differences between the effects of university competence on technology commercialization and start-ups. The technology transfer and commercialization specifically depends on professors' patent applications and technology holding company, while start-ups does professionals in industry-university cooperation. We suggest government to spur on the ongoing customization of university-industry collaboration policy, and university to properly cope with global atmosphere changing from ivory tower to academic capitalism and start-ups promotion.
This paper analyses how technological capabilities and entrepreneurship of technology-based start-ups affect their performance. In this paper, a multiple regression analysis was conducted on 248 technology-based start-ups. The effects of indicators of technological capacity like R&D intensity, R&D organization, technology competitiveness, patents, and certification were analyzed. Factors affecting sales were R&D intensity and technological competitiveness. Technology competitiveness and patents were the significant factors influencing product competitiveness. The factor that positively influenced organizational performance, customer performance, and achievement of start-up goals was technological competitiveness. The results of such an analysis should be designed to discover and foster long-term innovation potential, rather than relying on short-term financial performance.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.13
no.4
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pp.13-22
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2018
In this study, we examined the accuracy of the assessment items for selecting start-ups used in the project to support start-ups and verified their validity in determining whether they are appropriate assessment items based on selection criteria. The results of 973 start-ups that applied for the project fostering startup leading universities were collected and logistic regression was performed using SPSS 18.0. The study results are summarized as follows. First, the differences in characteristics of start-ups were identified in terms of selection. Second, the impact of selection by assessment items was gender in 2015, capability of the founder, business establishment in 2016, performance and potential in the global market, and business startup in 2017. Third, the overall selection accuracy analysis for the last three years confirmed that the accuracy of the selection is lower each year and that the accuracy of the selection is lower than the accuracy of the non-selection. This means that the current assessment items for selecting start-ups are inaccurate for selection, and that changes in the items due to changes in the start-up environment each year have led to lower accuracy of selection. It is meaningful that this study raised the importance of assessment items and the need for improvement of assessment items for the screening functions of good start-ups to enhance efficiency of the policies for startup support.
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