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

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.1-16
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• 2022

Although start-up is a key national strategy to increase national competitiveness and create employment, the survival rate of start-ups has not improved significantly. This is an important reason for the inability to provide timely and appropriate support to startups, which are in the early stages of start-up, due to the unique limitations of existing start-up support institutions and investors. The relatively recent accelerator is attracting attention as a subject of solving the above problems through professional incubation and investment. However, there are only a few empirical studies on investment determinants that affect the survival and success of accelerators, and there is a lack of theoretical evidence. Accordingly, in previous studies, 12 investment determinants were derived from a static, strategic, and dynamic perspective as accelerator investment determinants based on a business model innovation framework. This study subdivided the accelerator investment determinants derived through previous studies into 21 and analyzed the importance and priority of each factor using AHP (Analytic Hierarchy Process) analysis technique for domestic accelerator investment experts. As a result of the analysis, the top factors of importance of accelerator investment determinants were in the order of 'human resources', 'customer and market', 'intellectual resources', and 'entrepreneur's ability to realize opportunities'. It can be seen that the accelerator considers the core competencies of startups to implement solutions as the most important factor when making startup investment decisions. It was also confirmed that accelerators are strategic to create a clear value proposition and differentiated market position based on the core competitiveness of startups, and that the core value delivery method prefers a market-oriented business model and recognizes entrepreneurs's innovation capability is an important factor to realize a business model with limited resources in a rapidly changing market. This study is of academic significance in that it analyzes the importance and priority of accelerator investment determinants through demonstration as a follow-up study on accelerator investment determinants derived based on business model innovation theory that reflects the nature, goals, and major activities of accelerator investment. In addition, it is of practical value as it contributes to revitalizing the domestic startup investment ecosystem by providing accelerators with theoretical grounds for investment decisions and specific information on detailed investment determinants.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.5
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• pp.13-35
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• 2020

Startup accelerators are a new type of investors providing a certain amount of shares for imparting education, mentoring, networking, and providing space and seed money that can directly resolve the difficulties faced by nascent entrepreneurs (Clarysse, 2016). Startup accelerators have expanded worldwide as their influence over the startup ecosystem has increasingly been established (Pauwels et al., 2016; Cohen & Hochberg, 2014). This study was conducted to derive investment determinants of startup accelerators that are emerging as major investment players around the world. To this end, the accelerator-type determinants of investment were derived. As previous research on this topic is nonexistent, this process involved qualitative meta-synthesis, literature reviews, observation, and in-depth interviews. First, more than 30 research papers were examined for the determinants of investment for firms at an early stage of their foundation, and the categories and determinants of investment in the relevant studies were comparatively analyzed using qualitative meta-synthesis. Further, related data were investigated to identify the characteristics of accelerators, and the startup evaluation process of US accelerators was studied. The more than 100 questions raised during this process were coded to examine the determinants of investment that accelerators considered important. In-depth interviews were conducted with four US accelerators to identify the characteristics of accelerators and key determinants of investment. Ultimately, 5 categories of accelerator-type determinants of investment and 26 subordinate determinants of investment were derived. The results were verified and supplemented by consulting with seven accelerators in Korea. The results were confirmed after pilot tests and verification by seven domestic accelerators. After confirming the accelerator-type determinants, the reliability of them was verified by examining the importance and priority of each category through the quantitative survey of Korean accelerators. The research that elicited the accelerator-type investment determinants is the first research and is expected to be a major reference to the progress of subsequent studies. This research that systematically derived the investment determinants of the accelerator is expected to make major contributions to the progress of follow-up studies, the process of selecting startups, and the investment decision-making process of the accelerators.

• Journal of Distribution Science
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• v.12 no.4
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• pp.31-39
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• 2014

Purpose - This study investigates the following two issues. First, we attempt to find the important determinants of housing investment and to identify their significance rank using survey panel data. Recently, the expansion of global uncertainty in the real estate market has directly and indirectly influenced the Korean housing market; households demonstrate a sensitive reaction to changes in that market. Therefore, this study aims to draw conclusions from understanding how the impact of financial strength of the household is related to house investment. Second, we attempt to verify the effectiveness of diverse indices of financial strength such as DTI, LTV, and PIR as measures to monitor the housing market. In the continuous housing market recession after the global crisis, the government places top priority on residence stability. However, the government still imposes forceful restraints on indices of financial strength. We believe this study verifies the utility of these regulations when used in the housing market. Research design, data, and methodology - The data source for this study is the "National Survey of Tax and Benefit" from 2007 (1st) to 2011 (5th) by the Korea Institute of Public Finance. Based on this survey data, we use panel data of 3,838 households that have been surveyed continuously for 5 years. We sort the base variables according to relevance of house investment criteria using the decision tree model (DTM), which is the standard decision-making model for data-mining techniques. The DTM method is known as a powerful methodology to identify contributory variables for predictive power. In addition, we analyze how important explanatory variables and the financial strength index of households affect housing investment with the binary logistic multi-regressive model. Based on the analyses, we conclude that the financial strength index has a significant role in house investment demand. Results - The results of this research are as follows: 1) The determinants of housing investment are age, consumption expenditures, income, total assets, rent deposit, housing price, habits satisfaction, housing scale, number of household members, and debt related to housing. 2) The impact power of these determinants has changed more or less annually due to economic situations and housing market conditions. The level of consumption expenditure and income are the main determinants before 2009; however, the determinants of housing investment changed to indices of the financial strength of households, i.e., DTI, LTV, and PIR, after 2009. 3) Most of all, since 2009, housing loans has been a more important variable than the level of consumption in making housing market decisions. Conclusions - The results of this research show that sound financing of households has a stronger effect on housing investment than reduced consumption expenditures. At the same time, the key indices that must be monitored by the government under economic emergency conditions differ from those requiring monitoring under normal market conditions; therefore, political indices to encourage and promote the housing market must be divided based on market conditions.

• 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.

• Clean Technology
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• v.17 no.2
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• pp.181-188
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• 2011

In this study, the complementary or crowding-out effects of public R&D subsidy on private R&D investment in the cleaner production were analysed between the effects and the major determinants (company size, R&D investment intensity, ratio of government investment, R&D manpower intensity). Among 207 firms' projects, the number of the complementary effect was 95 (45.9%) while that of crowding-out effect was 38 (18.4%). Resulting from logistic regression, the higher the R&D investment of sponsored companies is, the more complementary effect they show, responding to public R&D subsidy, and increase own R&D investment. The other determinants, however, showed no significant effects on firms' R&D investment. To heighten the effect of public cleaner production R&D, it is need to increase the priority of R&D investment intensity among the determinants. And to increase the performance of governmental R&D investment, further studies for the individual public R&D programs are necessary.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.173-183
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• 2020

The paper investigates the determinants of foreign direct investment (FDI) in Vietnam in 2000-2019 period. This study uses difference Generalized Methods of Moments (GMM) and Pooled Mean Group (PMG) to analyse panel data officially provided by General Statistical Office of Vietnam. The results show that market size impacts positively significant on FDI attraction: 1% -1.45% (PMG) and 1% -1.25% (GMM). Besides, some other factors have positive influences as labor force, macroeconomic policy, macroeconomic stability and skilled labor. Meantime, the trade openness negatively affects FDI inflows in the short-term, while not being statistically significant in the long-term. Moreover, economic shocks often have a negative impact on FDI inflows. The findings of this study lead to the following recommendations. First, authorities should pay special attention to encourage economic growth rate in Vietnam to expand market size because this is the first priority of foreign investors. Second, authorities need to continue increasing the rate of skilled labor, especially highly qualified management force, engineers and well-skilled workers. Third, the authorities should adjust trade openness to boost the role of its determinant in attracting FDI inflows. Fourth, macroeconomic stability needs to be governed by international standards in order to secure the belief of foreign investors in the long-term.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.31-47
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• 2022

The TIPS, a representative public-private cooperative project to revitalize the start-up ecosystem, is a government supported policy that promotes successful commercialization through various start-up support for technology-based startups. The purpose of this study is to analyze the investment decision factors of the TIPS program and to derive priorities. In order to achieve the research purpose, first, the investment decision factors were derived through literature analysis, a Delphi surveys were conducted on investors and experts participating in the evaluation of the TIPS program, and an AHP analysis was conducted on 20 VCs to empirically analyze the priority of factors on investment decisions. As a result of the analysis, the importance of critical factors was confirmed in the order of entrepreneurs(team) > market > product/service > finance > network. The importance of detailed factors was found in the order of entrepreneur's reliability and authenticity > market growth and scalability > team members' expertise and capabilities > adequacy of current market size > new market creation. This study presented the capabilities of technology-based startups preparing to participate in the TIPS program by deriving factors that influence investment decisions from an investor's perspective and comparing and analyzing the importance. It is also meaningful that basic data on determinants of private-led investment decision-making were presented to stake-holders such as venture capital, accelerator, and start-up support institutions.

• Health Policy and Management
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• v.16 no.4
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• pp.24-47
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• 2006

Based on the findings of a study focused on medical institutions(Fama & French, 2002), this study determined possible causality between determinants of capital structure and liability level, while estimating targeted debt ratio. Moreover, it also examined hypotheses about the adjustment of targeted debt ratio and the of fundraising patterns, so that it verified the relative priority of trade-off theory and pecking order theory. First, profitability had positive(+) relationships with liability level, while investment opportunities had negative(-) relationships with liability level. This finding supported pecking order theory, and non-liability tax shield effects had negative(-) relationships with liability level as estimated in both trade-off theory and pecking order theory. Next, this study verified trade-off and pecking order theory at once by means of regression analysis about the variation of liability level in associations with disparity from targeted debt ratio and short-term fluctuation of profit and investment. As a result, it was noted that liability level became mean-reversed to targeted liability ratio but slowly, SO it was difficult to assert that such mean reverse may support trade-off theory. However, the finding that most of short-term fluctuations of profit and investment are absorbed into liabilities supported pecking order theory. On the other hand, it was found that the larger scale of medical institutions is more supportive of pecking order theory in the associations between liability level and profitability and the fundraising patterns than trade-off theory.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.1
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• pp.1-13
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• 2017

The purpose of this study is to find out which factors determine the success of start-up in the initial market and what are the most important determinants. For the empirical analysis, the questionnaire related to the analysis of success factors for start-up success was designed according to the quantitative analysis (AHP technique). First, we selected 8 representative success factors for successful start-up in the initial market. In order to determine the degree of priority among these factors, we surveyed 12 entrepreneurs who are interested in entrepreneurship, universities, research institutes, and public officials. As a result of the empirical analysis, 51% of the funds in the tier 1 were ranked as the top priority to determine success factors. Followed by research and development (32.5%), management (8.7%) and marketing (7.8%). In particular, when each of the four items is calculated as 100 according to the result of the tier 1, and the tier 2 is converted, the foreign investment is analyzed as 43.7%. It was followed by 15.14% of R & D facilities, 14.07% of ideas, 8.7% of managerial ability, 7.29% of domestic investment, 5.85% of buyer feedback, 3.3% of development strategy and 1.95% of marketing strategy. Among the eight success factors, overseas investment items showed the closest preference to half, and it was the most important variable that determines the success or failure of market entry. The implication of this study is that many start-ups in Korea expect to receive investment and support from overseas accelerators. This means that overseas investment itself has been recognized as a start-up that makes services and products that can be used in the global market. A high preference for attracting foreign investment is due to the fact that the amount of investment is larger than that of Korea and that it can flexibly cope with the pressure on the performance compared to domestic investors. In this study, it was meaningful that we could confirm this fact through questionnaires of start-up experts. In future research, we need to find a viable alternative through studying how to provide start-up to foreign direct investment at the national level.