• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.1
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• pp.43-60
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• 2018

The purpose of this study is to inform the university stakeholder and startup policy makers about the current status of startup support programs and to identify criteria that could impact the startup effectively among various support program. The purpose of this study is to categorize the startup support programs into three different types. These types are startup education support, startup activity and commercialization support the startup Intention of university students was analyzed using survey and interview during the these programs. In addition, the impact on startup intention was empirical analyzed utilizing entrepreneurial self-efficacy and opportunity recognition support programs. Research results show that, Firstly, startup activity support program had impacted on both entrepreneurial self-efficacy and opportunity recognition. Commercialization support had impacted entrepreneurial self-efficacy. However, startup education support program had no impact on entrepreneurial self-efficacy and opportunity recognition. secondly, entrepreneurial self-efficacy and opportunity Recognition have influence on startup intention. Thirdly, startup activity support had influenced on startup intention. Finally, startup activity support and startup intention strongly influenced entrepreneurial self-efficacy. Also, commercialization and startup intention strongly influenced opportunity recognition. Other factors only influenced partially. Startup support program shall seek various solutions to improve quality to increase startup intention based on the research results. Also, high quality educational program shall be offered to improve entrepreneurial self-efficacy and opportunity recognition, while promoting startup activity and commercialization support emphasized. Try to realize a strategic development for activation of startup business.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.5
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• pp.45-56
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• 2016

According to attended about startup, there are many policy and program for activating of startup. Government's policy and program was scale up and arrangements for high quality. Nevertheless, policies and programs are concentrated on ante-startup stage. And experts have questioned that effect. So, there are needed a program focusing pre-startup and incubation stage. Accordingly, this study propose a kind of educative program named Pre-Startup Support Program. Through the program, pre-startup teams or entrepreneurs will inspect items, business skills and surroundings of market and competitors. And they have a time for complementation of deficiency. This study selects ETRI spin-off(research based spin-off born ETRI) by means of an object of study. ETRI's programs are started in 2011 with intent to incubate the entrepreneur through market research, mentoring, space of incubation and funds. This study analyze using the ISA(Important-Satisfaction Analyze) and the regression. We classify the pre-startup support program using the ISA. And then, we analyze the influence of satisfaction using the regression. On the basis of results, we identify the effectiveness of pre-startup support program and propose plans for reinforcement. In conclusion, adopting a pre-startup support program is expected to success of startup.

• Journal of Aerospace System Engineering
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• v.10 no.3
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• pp.32-38
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• 2016

This paper explains space-technology startup-business support programs. MSIP (Ministry of Science, ICT and Future Planning) and KARI (Korea Aerospace Research Institute) began running startup-business support programs from 2013 according to a "space-technology industrialization plan." In addition, MSIP and KARI have been running startup academies and STAR-Exploration for future entrepreneurs and startup companies since 2015. From these programs, five startup companies were established and they are generating sales. This paper shows the results of the programs, and the program cases of the startup and venture companies are analyzed for both domestic and international audiences. The future direction of startup-business support programs that are based on space technology is also discussed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.101-114
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• 2022

Recently, various studies on the entrepreneurial ecosystem have been conducted. The entrepreneurial ecosystem is composed of various elements such as entrepreneurs, governments, and infrastructure, and these factors interact to contribute to economic development. The purpose of this study was to analyze differences in importance and performance of the entrepreneurial ecosystem for startups using the importance-performance analysis (IPA) method. Based on this, the importance and current level of the components of the entrepreneurial ecosystem were identified and policy implications were presented. The results of the study are as follows. The importance ranking was in the order of startup support program(4.43), startup funding (4.39), market accessibility(4.30). The ranking of performance was startup support program(3.81), ease of starting a business(3.76), support for startup support institutions(3.66), and startup funding(3.66). All elements of the entrepreneurial ecosystem showed higher importance than performance. This means that the components of the entrepreneurial ecosystem in Korea are recognized as important, but do not play a significant role in terms of performance for startups. In addition, the factors with the highest improvement in the importance-performance matrix were 「safety nets for startup failure」, 「culture of acceptance of failure」, 「ease of market entry」, 「ease of startup survival」, and 「ease of exit」. This study suggested improvement measures such as establishing a social safety net, improving awareness of startup failure culture, matching successful startups, strengthening scale-up support by growth stage, easing regulations in new business fields, and diversifying investment recovery strategies.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.167-179
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• 2024

This study addresses the challenge of objectively evaluating the performance of early-stage startups amidst limited information and uncertainty. Focusing on companies selected by TIPS, a leading private sector-driven startup support policy in Korea, the research develops a new indicator to assess technological efficiency. By analyzing various input and output variables collected from Crunchbase and KIND (Korea Investor's Network for Disclosure System) databases, including technology use metrics, patents, and Crunchbase rankings, the study derives technological efficiency for TIPS-selected startups. A prediction model is then developed utilizing machine learning techniques such as Random Forest and boosting (XGBoost) to classify startups into efficiency percentiles (10th, 30th, and 50th). The results indicate that prediction accuracy improves with higher percentiles based on the technical efficiency index, providing valuable insights for evaluating and predicting startup performance in early markets characterized by information scarcity and uncertainty. Future research directions should focus on assessing growth potential and sustainability using the developed classification and prediction models, aiding investors in making data-driven investment decisions and contributing to the development of the early startup ecosystem.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.6
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• pp.37-46
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• 2014

This study investigates the effects of the degree of preparation engaged in the related industry, and the amount of financial support program on R&D performance of technology based startup companies. This study seeks to discover the core variables that impacts most on business performance. However, it should be noted that the validity of such variables and their impacts on business performance can be contentious. The study sets hypothetical variables as following. Intensity of preparation of the startup company, amount of preparation and amount of work experience in related industry are independent variable. The amount of financial support program was selected as a moderating mediating variable. According to the results, the intensity of preparation had a positive relationship with R&D performance, as opposed to work experience of the founder having a negative relationship on R&D performance. The amount of support program had no significant relationship with R&D performance. Furthermore, there are negative modified effect between the amount of support program and work experience. And, there is no relationship modified effect between support program and work experience. Existing policies tend to lean heavily toward young entrepreneurs through support and guidance. The government has placed great emphasis on policies that aim to promote and create jobs for young individuals. The results suggest that the government should review their policies toward young technological entrepreneurs and that these entrepreneurs should prepare thoroughly before launching any startups.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.127-135
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• 2020

The purpose of this paper is to classify individual startups by growth stage based on data-based quantitative criteria. This is to provide a basis for systematic support for government startups based on accurate statistics on the startup growth process. This startups were the TIPS (Tech Incubator Program for Startup) support company, which used a relatively reliable startup. We found seed money to complete MVP (Minimum Viable Product) within 1.5 years after establishment, verified PMF (Product-Market Fit) within 1 year, attracted Series A investment within 2.5 years after establishment, and successfully commercialized it. It attracted Series B investment for stable growth within 1.5 years (Series B investment within 4 years from start-up). The results of the study, the division of government programs that support stage-based startup commercialization, that is, within three years and within seven years of establishment, is significant to date. Three directions are suggested for future research. First, develop indicators for monitoring startup growth stages. Second, it continuously updates the annual changes and tracks the growth stages of individual startups. Third, we discover the successful growth law of technology-based startups by applying in-depth case analysis of successful startups to the model.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.6
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• pp.15-25
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• 2018

As jobless growth became the new norm and the average life expectancy continues to increase, it is difficult to find quality jobs regardless of gender. In this situation, entrepreneurs who can take charge of creating quality jobs have begun to gain attention from governments. As a result, many startup support programs have been introduced and operated. In Korea, various government-sponsored startup support programs have been in operation since the late 2000s, and the number of startups has increased since. However, there are many cases where they are not able to maintain their business for a long time because such programs often lack expertise and experience. Mentoring programs for startup founders is becoming an attractive solution to these problems. However, when we look at the responses of entrepreneurs, they found the mentoring program beneficial only when it was well planned and operated. Otherwise, they found the program unhelpful. Although there are many startup mentoring programs in various fields, there is little research on whether customized mentoring that matches the characteristics of startups and entrepreneurs are effective. In this study, we study the effects of startup mentoring on mentoring satisfaction. Our model also intends to identify the moderating effects of entrepreneurs' characteristics and provide guidance to future startup mentoring.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.127-140
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• 2022

Recently, accelerators are attracting attention as a new startup incubator. This study empirically analyzed the relative importance and priority of decision-making factors when a startup selects an accelerator using the AHP technique. As a result, startup founders recognized the importance of decision-making factors in the order of funding factors, program factors, and accelerator characteristic factors. there was a difference in the relative importance of detailed factors between startup founders and accelerator workers, depending on the location of the business site and the presence or absence of sales performance. This suggests that accelerators need to strengthen the financial support capabilities and improve customized services to meet the needs of startups. This study can be used as a decision-making criterion when a startup selects an accelerator, and can be used as basic data for additional research on the accelerator program.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.1
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• pp.31-41
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• 2018

The purpose of this study is to look at the difference between the importance and the satisfaction with respect to government startup aid programs perceived by entrepreneurs to improve the effectiveness of government startup aid policy and verify the causal relationship between startup aid project and business performance. In this respect, this study aims to look at the impact of entrepreneurs' perceived satisfaction over government startup aid programs on startup business performance. Major study findings from this study are as follows. First, as a result of testing statistical significance of the difference between importance and satisfaction in startup education, facility/space, consulting, or fund support field, respectively in start-up assistance project, it appeared that there was a significant difference in all fields. In addition, fund support was the field that showed the biggest difference between importance and satisfaction. Second, the results of IPA (importance-performance analysis), which displays relative importance and performance of start-up assistance project on four quadrants so that entrepreneurs can evaluate which start-up assistance projects they think important and which projects they are satisfied with by themselves are as follows. Let us summarize the distribution of start-up assistance project on four quadrants in the first place. Facility/space support project is distributed in the 1st quadrant that requires ongoing maintenance; start-up funding program in the 2nd quadrant that requires concentrated improvement; consulting support project in the 3rd quadrant that requires limited use at low priority; and start-up education support project in the boundary between the 3rd quadrant that requires limited use and the 4th quadrant that requires rejection against unnecessary items. Third, the results from multiple regression analysis to identify the impact of satisfaction with government startup aid programs over business performance are as follows. As a result of analyzing the influence relationship between government startup aid program and financial performance, it appeared that satisfaction with facility/space had a positive (+) impact on financial performance. This suggests that the higher the satisfaction with facility/space, the higher the financial performance. As a result of analyzing the influence relationship between start-up assistance project and non-financial performance, it appeared that satisfaction with startup education had a positive (+) impact on non-financial performance. This suggests that the higher the satisfaction with startup education, the higher the non-financial performance.