In an entrepreneurial ecosystem, the failure rate of startups is extremely high at 90%, and every startup that fails becomes an orphan. This phenomenon leads to higher costs of failure for the entrepreneurs in the ecosystem. Failed startups have many lessons to offer to the ecosystem and offer guidance to the potential entrepreneur, and this area is not fully explored compared to the literature on successful startups. We use a case based method distinguishing a failed startup and a successful startup, studying the entrepreneurial characteristics and firm level factors which cause the failures, in the technology startup ecosystem of Bangalore. We study one of the modes of exit adopted by failed startup entrepreneurs and draw key lessons on causes that culminate in failures. We have identified that factors such as the time to minimum viable product cycle, time for revenue realization, founders' complementary skillsets, age of founders with their domain expertise, personality type of founders, attitude towards financial independence and willingness to avail mentorship at critical stages, will decisively differentiate failed startups from the successful ones. Accordingly, implications have been derived for potential entrepreneurs for reducing the cost of failures in the entrepreneurial ecosystem.
To know the long-term growth patterns and determinants of successful startups, 15-year (2006-2020) panel data of 252 companies that had a growth rate of over 20% every year in the last three years were used. In the first analysis, statistics on the period required to designate a gazelle company or listed on the stock market were examined. In addition, five long-term growth patterns were presented. In the panel analysis, the R&D intensity, operating profit ratio, size, and age of the company were pointed out as determinants of growth. The operating profit margin and R&D intensity have a positive effect on growth. Gibrat's law was not supported, but an inverted U-shape was observed. Jovanovic's law was confirmed. Although many studies tend not to point to profitability as a determinant of long-term growth, this is an important long-term growth factor of a company. The operating profit ratio was used in this study.
International Journal of Internet, Broadcasting and Communication
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v.14
no.3
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pp.222-229
/
2022
Through this technology development, companies that operate online shopping malls and prospective startups will support education, consulting and expert group matching so that they can solve various issues that may arise in the course of the entire business life cycle, from startups to closures. It is expected that differentiated consulting programs will be designed for companies that currently operate shopping malls and start ups, and customized consulting programs will be provided to improve the effectiveness of consulting while improving customer satisfaction. It is planning to develop a "successful start-up and operation helper" that helps successful start-ups. It is a system that primarily diagnoses problems of prospective entrepreneurs and operators through an automation system at the start-up and operation stage, and professional consultants participate to derive and solve problems, and takes care of all stages of shopping mall birth and growth. In this paper Metaverse based shopping mall Creation is also discussed. Through Big Data creation these accumulated data, we intend to help operators start and operate shopping malls through accurate information by managing all knowledge of shopping malls as a system in the long run.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.14
no.6
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pp.119-130
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2019
Although a well-established line of research has addressed the funding decision, the activities of investee startups to receive funding have been overlooked because prior research has been conduced from investor's point of view. In addition, funding does not result from one off decisions but from decision process with many stages. Moreover, the emphasis placed on specific investment criteria varies by different stages during the process. Therefore, understanding the initial funding of startups requires to analyze the strategic behaviors of startups throughout the entire funding decision process from first meeting with investors to funding success. This study investigates the initial funding process of startups, and the analysis is based on a case study of LetinAR one of the successful startups founded by students in South Korea. This study investigates how early start-ups were able to receive funding from startup's point of view, and the analysis is based on a case study of LetinAR, an augmented reality(AR) startup using Pin mirror technology. By adding "legitimacy building" stage that had not been addressed previously, we divided funding process into four stages: 1) legitimacy building, 2) familiarization, 3) screening, and 4) bargaining phase. We did not only analyze major criteria, but also strategic activities of startup at each stage. This study makes a contribution by helping us understand complicated process of funding and the successful strategic behavior of investor backed 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.
Entrepreneurship and entrepreneurship courses, including my recent absence undergraduate entrepreneurship-friendly system is activated, the spread of technology startups to be scanning my college. However, the college is successful technology startups to take place in order to be solved many problems still exist. In this paper, we have a hard job and continuing high unemployment and social environment college students majoring in IT technology to enable the establishment of the control action for the establishment and analysis of influencing factors. In particular, IT college students majoring in technology startups will affect students' technical skills and characteristics of entrepreneurs and Entrepreneur's motive, entrepreneurship environment outside the extraction and evaluation items such as IT skills to analyze the impact of entrepreneurship. In analysis result, IT major career college students interested in entrepreneurship as an alternative to the higher technology, technical skills and characteristics of entrepreneurs and start-motivated alternative to independence and had an impact on employment. In addition, the university was founded in tech startups according to the environment of entrepreneurship education has a lot of outside influence.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.18
no.1
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pp.253-270
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2023
Research on investment determinants of accelerators, which are attracting attention by greatly improving the survival rate of startups by providing professional incubation and investment to startups at the same time, is gradually expanding. However, previous studies do not have a theoretical basis in developing investment determinants in the early stages, and they use factors of angel investors or venture capital, which are similar investors, and are still in the stage of analyzing importance and priority through empirical research. Therefore, this study verified for the first time in Korea the discrimination and effectiveness of investment determinants using accelerator investment determinants developed based on the business model innovation framework in previous studies. To this end, we first set the criteria for success and failure of startup investment based on scale-up theory and conducted a survey of 22 investment experts from 14 accelerators in Korea, and secured valid data on a total of 97 startups, including 52 successful scale-up startups and 45 failed scale-up startups, were obtained and an independent sample t-test was conducted to verify the mean difference between these two groups by accelerator investment determinants. As a result of the analysis, it was confirmed that the investment determinants of accelerators based on business model innovation framework have considerable discrimination in finding successful startups and making investment decisions. In addition, as a result of analyzing manufacturing-related startups and service-related startups considering the characteristics of innovation by industry, manufacturing-related startups differed in business model, strategy, and dynamic capability factors, while service-related startups differed in dynamic capabilities. This study has great academic implications in that it verified the practical effectiveness of accelerator investment determinants derived based on business model innovation framework for the first time in Korea, and it has high practical value in that it can make effective investments by providing theoretical grounds and detailed information for investment decisions.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.18
no.2
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pp.141-156
/
2023
The advancement of Information and Communication Technology (ICT), along with the expansion of government and private investment in startup discovery and funding, has led to the emergence of startups seeking to generate outstanding results based on innovative ideas. As successful startups serve as role models, the number of aspiring entrepreneurs preparing to launch their own startups continues to increase. However, unlike entrepreneurs who challenge themselves with serial entrepreneurship after experiencing success, early-stage startups face various challenges such as team building, technology development, and fundraising. Accelerators play a dual role of mentor and investor by providing education, mentoring, consulting, network connection, and initial investment activities to help startups overcome various challenges they face and facilitate their growth. This study investigated whether there is a correlation between the characteristics of startups and their entrepreneurial performance, and analyzed whether accelerators mediate the relationship between startup characteristics and entrepreneurial performance. A total of 11 hypotheses were proposed, and a survey was conducted on 302 startup founders and employees located across the country, including the metropolitan area, for empirical research. SPSS 23.0 and Amos 23.0 were used for statistical analysis. Through this study, it was found that factors such as innovation, organizational culture, financial characteristics, and learning orientation among the characteristics of startups, rather than having a direct impact on entrepreneurial performance, are linked to entrepreneurial performance through the role of accelerators. By analyzing the impact factors of startup characteristics on entrepreneurial performance, this study presents research on the role of accelerators and provides institutional improvements. It is expected to contribute to the expansion of investment and differentiated acceleration programs, enabling startups to seize the market and grow stably in the market.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.17
no.1
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pp.63-77
/
2022
The importance of start-ups and venture companies in the Korean economy is growing. However, the successful growth of startups and venture companies are still challenging as 70% of startups fail within 5 years. A new perspective on innovation is essential to overcome the liability of newness and the liability of smallness in the existing market and obtain the competitive advantage. Recent phenomenon in the Korean startups ecosystem is the remarkable growth of unicorns and future unicorns. Their business models, types of business, and success cases serve as a good example. Neverthless, the process of unicorn and future unicorn startups making new industries and innovative business has poorly understood. In this paper, we first define 175 unicorns and future unicorn startups participating in the K-unicorn project as a unicorn group and analyze current trends of the group. Then the in-depth analyses of industry sectors are conducted. Specifically, focusing on the unicorn forming the new market, we examine the unicorn making the processes of industry category innovation through the business innovation model. Lastly, broadening the scope of the analysis to the unicorn group, policy implications in startups and venture ecosystem are suggested.
On account of multiple causes, including prolonged global economic crisis, addressing environmental pollution and the advent of hyper-connected society, a new paradigm called 'sharing economy' has rapidly emerged. Many startups have attempted to build promising business model based on the sharing economy concept. Nevertheless, successful cases are still very rare in the global level, except for Uber and Airbnb cases. Therefore, this study analyzes necessary causes and sufficient causes for successful settlements in the market through a comparative case analysis on digital matching firms in the sharing economy businesses. For the case study, we compare five successful cases (Uber, Airbnb, Kickstarter, TaskRabbit and DogVacay), three failure cases (Homejoy, Ridejoy and Tuterspree) and a platform cooperativism case (Juno) in accordance with six value attributes of business model including value proposition, market segment, value chain, cost structure and profit potential, value network and competitive strategy. We apply Boolean method to support controlled comparison and eliminate unnecessary attributes. The Boolean analysis result shows that value proposition, cost structure and profit potential, value network and competitive strategy are the essential attributes. Furthermore, the result indicates that each attribute is a necessary condition, where all four conditions should be met simultaneously in order to be successful. With this result, we discuss essential consideration for those who are planning startup based on the sharing economy business model.
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