• Journal of Information Technology Services
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• v.17 no.1
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• pp.1-16
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• 2018

In this research, we tried to suggest the guidelines to stakeholder of ICT startup for picking up the excellent startups and nurturing them. We designed the research model focused on the good startup team's knowledge based interaction mechanism. A research model and hypotheses were developed from literature review and empirically validated. The research model consisted relationship among the knowledge sharing (knowledge donation and knowledge collection), absorptive capacity (member's ability and member's motivation), team creativity, and innovation capability. Data were collected from ICT Service Startups, and a partial least squares (PLS) analysis was made on 175 data points. The analysis results showed that absorptive capacity has significant effect on team creativity and innovation capability directly. And also it has indirect effect on the dependent variable through team creativity. On the contrary, knowledge sharing does not have statistically significant effect on team creativity and innovation capability; only have an effect on absorptive capacity. Based on the results, we proposed several team management skills for ICT startup leaders and members, and the guidelines to stakeholder such as government and private investors. Also there are some ideas for startup nurturing polices for government officers. Theoretical contributions are discussed at the end with limitations and further studies.

• Journal of Korean Society for Quality Management
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• v.45 no.3
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• pp.463-481
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• 2017

Purpose: This study provide the matching mechanism between startup and business incubator to enhance managerial performance of business incubator. In addition, we propose the differentiation strategy for business incubator based on the needs of startups. Methods: In order to carry out the research, we surveyed 216 startups who already have invested in venture capitals and angel investors and currently residing in business incubator and 30 venture capitals and angel investors. Based on survey results, we develop a business incubator capability table matching startup with business incubator. Results: Satisfaction and importance of the supporting programs varied depending on the startup experience and startup lifecycle. As a result, we recommended a R&D center for machinery/material, bio/medical and electric/electronics startups and individual office for ICT and knowledge service startups. In addition, we suggested a differentiation strategy to BI in university specialized for machinery/material, privately operated BI for electric/electronic, (local)government, R&D center and individual office for knowledge service respectively. Conclusion: In this study, business incubator capability table is applied to match startup with business incubator and it could be applied to evaluate the current status of business incubator. Furthermore, it will help to establish a future strategic direction for business incubator.

• Information Systems Review
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• v.21 no.1
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• pp.135-152
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• 2019

Recently there are many development and support policies for start-up companies because of successful venture companies related to ICT services. However, as these policies have focused on the support for the initial stage of start-up, many start-up companies have difficulties to continuously grow up. The main reason for these difficulties is that they recognize start-up tasks as independent activities. However, many experts or related articles say that start-up tasks are composed of related processes from the initial stage to the stable stage of start-up firms. In this study, we models the start-up processes based on the survey collected by the start-up companies, and analyze the start-up process of ICT service companies with process mining techniques. Through process mining analysis, we can draw a sequential flow of tasks for start-ups and the characteristics of them. The analysis of start-up businessman, idea derivation, creating business model, business diversification processes are resulted as important processes, but marketing activity and managing investment funds are not. This result means that marketing activity and managing investment funds are activities that need ongoing attention. Moreover, we can find temporal and complementary tasks which could not be captured by independent individual-level activity analysis. Our process analysis results are expected to be used in simulation-based web-intelligent system to support start-up business, and more cumulated start-up business cases will be helpful to give more detailed individual-level personalization service. And our proposed process model and analyzing results can be used to solve many difficulties for start-up companies.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.87-94
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• 2019

IoT-based services are being released in accordance with the aging population and the demand for well-being pursuit needs. In addition to medical device companies, companies with ideas ranging from global ICT companies to startup companies are accelerating their market entry. The areas where these services are most commonly applied are health/medical, life/safety, city/energy, automotive and transportation. Furthermore, by expanding IoT technology convergence into the area of life care services, it contributes greatly to the development of service models in the public sector. It also provides an important opportunity for IoT-related companies to open up new markets. By addressing the problems of life care services that are still insufficient. We are providing opportunities to pursue the common interests of both users and workers and improve the quality of life. In order to establish IoT-based digital life care services, it is necessary to develop convergence technologies using cloud computing systems, big data analytics, medical information, and smart healthcare infrastructure.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.13-29
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• 2021

The purpose of this study was to analyze the spatial distribution and location factors of startups by generation (young and middle-aged) in Seoul. To this end, a research model was established that included factors of industry, population, and startup institutions by generation in 424 administrative districts using the Seoul Business Enterprise Survey(2018), which includes data on the age group of entrepreneurs. As an analysis method, descriptive statistics were conducted to confirm the frequency, average and standard deviation of startups by generation and major variables in the administrative districts of Seoul, and spatial distribution and characteristics of startups by generation were analyzed through global and local spatial autocorrelation analysis. In particular, the spatial distribution of startups in Seoul was confirmed in-depth by categorizing and analyzing startups by major industries. Afterwards, an appropriate spatial regression analysis model was selected through the Lagrange test, and based on this, the location factors affecting startups by generation were analyzed. The main results derived from the research results are as follows. First, there was a significant difference in the spatial distribution of young and middle-aged startups. The young people started to startups in the belt-shaped area that connects Seocho·Gangnam-Yongsan-Mapo-Gangseo, while middle-aged people were relatively active in the southeastern region represented by Seocho, Gangnam, Songpa, and Gangdong. Second, startups by generation in Seoul showed various spatial distributions according to the type of business. In the knowledge high-tech industries(ICT, professional services) in common, Seocho, Gangnam, Mapo, Guro, and Geumcheon were the centers, and the manufacturing industry was focused on existing clusters. On the other hand, in the case of the life service industry, young people were active in startups near universities and cultural centers, while middle-aged people were concentrated on new towns. Third, there was a difference in factors that influenced the startup location of each generation in Seoul. For young people, high-tech industries, universities, cultural capital, and densely populated areas were significant factors for startup, and for middle-aged people, professional service areas, low average age, and the level of concentration of start-up support institutions had a significant influence on startup. Also, these location factors had different influences for each industry. The implications suggested through the study are as follows. First, it is necessary to support systematic startups considering the characteristics of each region, industry, and generation in Seoul. As there are significant differences in startup regions and industries by generation, it is necessary to strengthen a customized startup support system that takes into account these regional and industrial characteristics. Second, in terms of research methods, a follow-up study is needed that comprehensively considers culture and finance at the large districts(Gu) level through data accumulation.

• Journal of Platform Technology
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• v.11 no.3
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• pp.83-97
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• 2023

This research aims to identify startup trends by analyzing a large number of news articles through semantic network analysis. Using the BIGKinds article analysis service provided by the Korea Press Foundation, 330,628 news articles from 19 newspapers from January 2013 to December 2022 were comprehensively analyzed. The study focused on exploring the changes in key issues over the past decade, considering the impact of the social environment and global economic trends on entrepreneurship. We compared the number of news articles and changes in issues before and after the COVID-19 pandemic, and visualized entrepreneurship trends through frequency analysis, relationship analysis, and correlation analysis. The results of the study showed that the top keywords for entrepreneurship-related words are startup activation and commercialization, and the correlation between COVID-19 and entrepreneurship keywords is almost negligible in a linear sense, but the number of news articles decreased during the pandemic, which has an impact. In particular, the most frequently mentioned keywords are Ministry of SMEs and Startups, place is the United States, and person is limited. The agency was the SBA, and the entrepreneurship sector is more affected by social issues than any other sector, with the important characteristics of increased frequency of prompt access. This study supplies essential basic data for understanding and exploring issues and events related to entrepreneurship and suggests future research topics in the field.

• Journal of the Korean Society of Systems Engineering
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• v.20 no.spc1
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• pp.45-55
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• 2024

Amidst the challenges of the global economy, this paper examines the investment tendencies of professional angel investors, who provide venture capital and management consulting, and explores strategies to revitalize angel investment. According to the research findings, professional angel investors are generally older and more educated than regular angel investors, and they are concentrated in the metropolitan region. Additionally, their investment performance before and after registration remains similar, with investment amounts concentrated between 50 million and 100 million won. Their investment portfolios focus on ICT services, bio/medical, and distribution/service sectors. Based on these findings, policy and institutional support measures are required to revitalize angel investment, including easing registration requirements for professional angel investors, expanding tax benefits related to angel investment, strengthening the provision of information and education related to angel investment, and enhancing angel investment networking. This study is expected to contribute to the revitalization of the venture startup ecosystem and economic growth through the revitalization of angel investment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.1-20
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• 2023

This study attempted to identify the relationship between the investment determinants of accelerators and investment performance through empirical analysis. Through literature review, four dimensions and 12 measurement items were extracted for investment determinants, which are independent variables, and investment performance was adjusted to the cumulative amount of subsequent investment based on previous studies. Performance data from 594 companies selected by TIPS from 2017 to 2019, which are relatively reliable and easy to secure data, were collected, and the subsequent investment cumulative attraction amount, which is a dependent variable, was hypothesized through multiple regression analysis three years after the investment. As a result of the study, 'industrial experience years' in the characteristics of founders, 'market size', 'market growth', 'competitive strength', and 'number of patents' in the characteristics of products and services had a significant positive (+) effect. The impact of independent variables on dependent variables was most influenced by the competitive strength of market characteristics, followed by the number of years of industrial experience, the number of patents, the size of the market, and market growth. This was different from the results of previous studies conducted mainly on qualitative research methods, and in most previous studies, the characteristics of founders were the most important, but the empirical analysis results were market characteristics. As a sub-factor, the intensity of competition, which was the subordinate to the importance of previous studies, had the greatest influence in empirical analysis. The academic significance of this study is that it presented a specific methodology to collect and build 594 empirical samples in the absence of empirical research on accelerator investment determinants, and created an opportunity to expand the theoretical discussion of investment determinants through causal research. In practice, the information asymmetry and uncertainty of startups that accelerators have can help them make effective investment decisions by establishing a systematic model of experience-dependent investment determinants.