• 한국전산유체공학회:학술대회논문집
• /
• 2008.03b
• /
• pp.324-327
• /
• 2008

Two stage startup of high thrust liquid rocket engine can reduce the abrupt impulse to the vehicle and engine by changing oxidizer flow rate to the combustion chamber. Also it ensures stable ignition of combustion chamber against hard start and to prevent pump stall by the sudden supply of large mass flow rate. However high discharge pressure of oxidizer pump or temperature rise in gas generator may be a problem in applying the preliminary stage. To solve this problem, we analyzed the effect of the slope of oxidizer pump's head curve and the oxidizer mass flow rate to combustion chamber during preliminary stage using the rocket engine startup analysis code. A moderate slope(${\circleddash}{\sim}$-3) of head curve and 80% mass flow rate during preliminary stage can reduce the oxidizer pump discharge pressure by 15 to 20% comparing with the condition of ${\circleddash}$=-4.37 head curve and 70% mass flow rate. Also it can maintain the turbine inlet temperature rise within 50K from the nominal value.

• Journal of Information Technology Services
• /
• v.20 no.5
• /
• pp.89-104
• /
• 2021

Food delivery service combined with IT technology and HMR (Home Meal Replacement) are rapidly growing due to the COVID-19. Recently, the demand for salads along with HMR has increased among office workers in their 20s and 30s who are interested in health and beauty. Freshcode is a food startup with 6 years of experience that started selling salad products through O2O service. Freshcode applied for a patent for a service that collects orders from nearby areas and delivers them on the same day to a designated delivery address 'FCOSPOT' to save shipping costs. In March 2021, in recognition of the growth potential of the regular delivery service, Freshcode received an investment of 6 billion won in Series A. This study may have practical implications to early-stage startups and scale-up stage startups through a longitudinal case study on the growth of a single company. As for the research method, the lean startup methodology and lean canvas were used in the early stage of startup. In particular, the process of the build-measure and learn feedback-loop, which is the core of lean startup methodology, was applied to each major decision-making step. In the scale-up stage after 5 years, the business model canvas was used to schematize the growth as a food online O2O platform to verify continuous innovation. This case study has three main findings. First, the idea of 'FCOSPOT' was successfully implemented through the Lean Startup methodology. Second, Freshcode demonstrated the scalability of the differentiated business model of shared base delivery O2O. Third, a key factor of success was the digital integrated communication operation strategy that maximizes the experience for the created customers.

• Korean small business review
• /
• v.43 no.1
• /
• pp.165-186
• /
• 2021

Startups are undergoing a change throughout the growth process of startups that appear in existing studies as they move away from the existing B2B or B2C frame and expand their target customer groups to O2O, C2C. In this regard, a new type of startup known as unicorns, a unicorn which has grown rapidly in a short period of time, is being created by successfully attracting government support and external investment in recognition of the potential value of the startup. This study examined the relationship between investment attraction and growth after founding for five representative unicorns in the U.S. and Korea. As a result, it was found that private investment in Korea is passive and defensive, and is attracted after the Series A stage, compared to the U.S., where the growth potential of the startup ecosystem is positively evaluated. In addition, it found that government's support policy throughout the startup's growth process is an abstract and comprehensive policy focusing on initial funding for startups. Therefore, it was suggested that the scope of government policies should be expanded to forster startups as unicorns, and that it is necessary to establish and implement differentiated support policies for each growth of the scale-up of startups. This study is significant in that it presented the criteria for the growth stage and support of startups as well as policy support for scale-up through practical case analysis of unicorns.

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

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

• Journal of Venture Innovation
• /
• v.6 no.4
• /
• pp.1-21
• /
• 2023

This study is related to the performance of open innovation collaboration between startups and large corporations and financial institutions. In the life cycle of a typical company, the growth of a startup is difficult to predict. Startups that possess innovative technology but have only recently been established seek to verify their technology and capabilities by participating in open innovation with large corporations and financial institutions, and further strive to lay the foundation for corporate growth. However, if you approach it only as a theoretical coexistence plan, it will be viewed as a vague attempt from the startup's perspective. The purpose of this study is to differentiately verify the benefits of open innovation by analyzing the difference in sales growth of startups for the purpose of sales performance based on the open innovation participation of large companies and small and medium-sized companies(startups). In verifying this, the analysis was based on the sales results of the actual open innovation collaboration B2C model, and the difference was confirmed by comparing before and after collaboration. Here, the differentiation of the study was added by reflecting the corporate growth stage theory, a growth theory. When the corporate growth stage theory was excluded, it was confirmed that sales growth due to open innovation of startups was applied from the third month, and sales growth depending on participation was confirmed to be significant. On the other hand, when the corporate growth stage theory was applied, sales growth was not significant, but the difference in growth could be confirmed from the fourth month, and it was also confirmed in sales growth depending on participation. As a result, this study objectively confirms the effects that can be gained when startups participate in Open-innovation, and it is expected that Open-innovation led by large corporations, financial institutions, and government agencies will develop into a high-quality program environment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.12 no.2
• /
• pp.41-54
• /
• 2017

The purpose of this study is to find out how the support system of the government and the local governments for enhancing the success rate of the startup firms affected the performance of the enterprises according to the behavior characteristics of the founders. It is divided entrepreneurial support system into entrepreneurial policy support such as entrepreneurial education, mentoring and consulting, and funding of startup support such as policy fund and R & D fund, distinguished the behavior of founder into behaviors for discovery of entrepreneurial opportunities and behaviors for exploiting entrepreneurial opportunities. In order to analyze whether it affects the corporate management performance, a research model was created based on the previous research and hypotheses were set up, and the hypotheses were verified based on this questionnaire. The results of this study are as follows: First, it is found that the support for entrepreneurial policy has a positive effect on the behavior characteristics of entrepreneur. Second, it is found that the startup support such as policy fund affects the behavioral characteristics for finding the opportunity of the founder, but it does not affect the behavioral characteristics for the opportunity exploit. Third, it was found that the behavior characteristics of entrepreneur founding opportunity and exploition of entrepreneurial opportunity influenced the performance of the company. According to the this study, the following conclusion were obtained, First, it is necessary to apply different policies according to the stage of growth of startup companies. Second, startup companies grow through the stages of development of new technologies and ideas, commercialization, and marketing, at each stage, entrepreneur must overcome the so-called Death Valley, which requires funding.

• International Journal of Costume and Fashion
• /
• v.18 no.2
• /
• pp.65-83
• /
• 2018

The purpose of this study was to explore the dynamics of the newly emerging designer fashion market and examine how startup designers reacted to the tension between creativity and business, and how they grew within such dynamics. In-depth interviews were conducted with 22 DFE entrepreneurs and 7 fashion industry experts. The grounded theory was used to analyze data and yield results. Korean new generation of DFEs, attracted by the growing online market opportunities are directly distributing through online channels, targeting the millennial consumers who are pursuing new values at new distribution channels. They show new growth pattern, start with a few key items in the middle and lower price segments, then upscale their design, quality, and price. This study further investigated designers' enterprise orientation shift, which was explored by Mills. Some creativity-oriented designers encountered difficulties in the orientation shift, while designers who demonstrated business characteristics from the startup stage restored the balance by trying to improve both creativity and business. This study discovered a new way for the designer to enter the growth stage. This growth approach is one of the success strategies applicable to designers launching a brand on online platforms in the global market.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.11 no.2
• /
• pp.113-120
• /
• 2016

Technology based would-be entrepreneurs have constantly increased as coming with increasing demands for technology based startup. However, technology based startup need to go through throne field in the preparation and launching process. This paper help technology based would be entrepreneurs recognizing and pivoting all potential fatal flaws covering entrepreneurs to BM with strategies by providing self check-up lists. This paper have developed all check list based upon the previous literature reviews about technology commercialization with carrying Focused Group Interview with mentor and investor involved in the early stage of venture growth. In particular, this paper have applied these tools over 104 participants(would-be entrepreneur and entrepreneurs in the early startup) attending in Hanbat Startup Item Validation Program and Startup Leading University program. This paper developed the mega categories of list as follows: Entrepreneurship, technology and patent, target customer and market, product, BM and strategy. It also developed 17 different concept of components and 58 specific sub-lists under maga list. The research results of paper will provide solid foundation of communication with participants about checking up their state of preparation for startup as applying to mentoring for would-be entrepreneurs and to entrepreneurship education.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.15 no.6
• /
• pp.27-42
• /
• 2020

Startup accelerators have emerged as new investment entities that help early startups, which are not easy to survive continuously due to lack of funds, commercialization capabilities, and experiences. As their positive performance on early startups and the ecosystem has been proven, the number of early startups which want to receive their investment is also increasing. However, they are vaguely preparing to attract accelerators' investment because they do not have any information on what factors the accelerators consider important. In addition, researches on startup accelerators are also at an early level, so there are no remarkable prior studies on factors that decide on investment. Therefore, this study aims to help startups prepare for investment attraction by looking at what factors are important for accelerators to invest, and to provide meaningful implications to academia. In the preceding study, we derived five upper level categories, 26 lower level accelerators' investment determinants through the qualitative meta-synthesis method, secondary data analysis, observation on US accelerators and in-depth interviews. In this study, we want to derive important implications by deriving priorities of the accelerators' investment determinants. Therefore, we used AHP that are evaluated as the suitable methodology for deriving importance and priority. The analysis results show that accelerators value market-related factors most. This means that startups that are subject to investment by accelerators are early-stage startups, and many companies have not fully developed their products or services. Therefore, market-related factors that can be evaluated objectively seem to be more important than products (or services) that are still ambiguous. Next, it was found that the factors related to the internal workforce of startups are more important. Since accelerators want to develop their businesses together with start-ups and team members through mentoring, ease of collaboration with them is very important, which seems to be important. The overall priority analysis results of the 26 investment determinants show that 'customer needs' and 'founders and team members' understanding of customers and markets' (0.62) are important and high priority factors. The results also show that startup accelerators consider the customer-centered perspective very important. And among the factors related to startups, the most prominent factor was the founder's openness and execution ability. Therefore, it can be confirmed that accelerators consider the ease of collaboration with these startups very important.