• 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 Korea Technology Innovation Society
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• v.8 no.1
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• pp.29-50
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• 2005

Real options provide a new and productive way to view corporate r&d investment decisions. DCF approach is well established and beloved of financial executives, but is known to systematically underestimate investment value under significant uncertainty. Though real options are not inherent in a r&d investment, they can be used to compute the investment value including managerial flexibility like option value. In this paper, we explain how the interval of option value in black-scholes model can be estimated using simulation. We also present a process framework for interval estimation of volatility and efficient of period of investment value. In such a setting, we can obtain the appropriate interval estimation of the expanded investment value.

• Asia-Pacific Journal of Business
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• v.4 no.2
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• pp.11-20
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• 2013

This study extends the extant scope of understanding investment decision, beyond the dominant 'technical' emphasis on the application of discounted cash flow techniques. The research methodology draws the positivist and interpretive research paradigms. It uses a deductive approach, survey strategy and principal component analysis for the analysis. Three key sets of factors emerged as important in the investment decision process in the hydropower sector. They are: group consensus (framing), influences on own judgment (heuristics), and application of knowledge & experience (intuition). The use of purposive and convenient sampling might have some unintended impact on the findings. Consequently, any generalizations of the findings to a wider population of organizations and managers need to be made with care. It is hoped that this paper will encourage other researchers to go beyond the analytic techniques of investment appraisal that have dominated investment decision research and seek to balance the emphasis by focusing on human involvement and behavioral aspects of investment decision.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.112-116
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• 2008

Determining the investment priority of the railway project is essential to keep its object of railway investment. [National railway construction plan] provide 4 major evaluation indicators and their weighting range in determining the investment priority of railway construction. Which are investment efficiency, inter-regional balance of development, network effects, government supporting policy. However this present criteria has inconsistency in determining economical feasibility of the railway transportation when applying the same evaluation indicator, investment efficiency, with the road transportation. The railway transportation is superior to road transportation in terms of transportation capacity and distance, while offering less carbon emissions. In spite of the prominent position of the railway transportation, it can be failed to obtain its proper investment priority when being determined under economical feasibility based. Therefore, this study analyzed the inconsistency under present evaluation criteria and proposed new evaluation method for the investment priority of the railway construction using AHP(analytic hierarchy process), while differentiate from the road construction. This method is optimized for only determining the priority of the railway construction itself under object of railway investment respectively.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.6
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• pp.27-38
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• 2018

The purpose of this study is to find out common investment decision factors for CVC's invested technology-based startups and analyze them. We examined 17 CVCs that invested in technology startups for three years and six months from 2015 to June 2018. As a result, the final 9 CVCs that can be used in this study were confirmed and 188 companies were analyzed. This study was conducted as a case study to propose and demonstrate CVC investment objectives and investment decision factors analysis model. The results of this study are as follows. First, CVC focused on strengthening investment. Second, In 2015, Invested in an average of 19 months of technology-based startups. In recent years, we invested in 36 months of proven technology-based startups. Thirdly, ICT service was the main business type of the invested startups. Fourth, the investors were concentrated on the stage of Series A~B. It is observed that CVC investment determinants have a significant impact on product or service and parent company relations. In addition, it was found that factors such as innovation, business planning competency, enterprising, strategic competency, leadership, and opportunity recognition competency were influential factors for the startups of invested companies and it was found that these factors are important for CVC investment decision. Understanding of CVC investment determinants presented in this study is based on the establishment of the investment process of the investee, entrepreneurship and management education program. The results of this study can be applied to the selection of excellent startups, entrepreneurship education programs, mentoring, development of coaching guidelines, and establishment of investment process of other investment institutions when investing in CVC.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.4
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• pp.93-113
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• 1997

In studying an EOQ-like inventory model for a manufacturing process, a number of findings were made. The system can "go out of control" resulting in a relatively minor problem state or "break-down". When the production system is in the minor problem statei produces a number of defective items. It is assumed that each defective piece requires rework cost and related operations. Once the machine breakdown takes place, the production system produces severely defective items that are completely unusable. Each completely unusuable item is immediately discarded and incurs handling cost, scrapped raw material cost and related operations. Two investment options in improving the production process are introduced : (1) reducing the probability of machine breakdown, breakdowns, and (2) simultaneously reducing the probability of machine breakdowns and setup costs. By assuming specific forms of investment cost function, the optimal investment policies are obtained explicitly. Finally, to better understand the model in this paper, the sensitivity of these solutions to changes in parameter values and numerical examples are provided.amples are provided.

• Journal of the Korean Institute of Gas
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• v.7 no.3 s.20
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• pp.1-6
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• 2003

This study has suggested a decision method which determine optimum investment level for safety management by process risk assessment at gas governor station. Hazard and operability study(HAZOP), fault tree analysis(FTA) and consequence analysis(CA) were carried out and potential accident cost and benefit for safety management were estimated. As a result, we could be found the trend of safety cost and benefit by the nonlinear regression method and could be determined the optimum investment level for safety management from analysis of safety management cost and potential accident cost.

• Knowledge Management Research
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• v.19 no.1
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• pp.97-118
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• 2018

The finance-investment industry is currently focusing on research related to artificial intelligence and big data, moving beyond conventional theories of financial engineering. However, the case of equity optimization portfolio by using an artificial intelligence, big data, and its performance is rarely realized in practice. Thus, the purpose of this study is to propose process improvements in equity selection, information analysis, and portfolio composition, and lastly an improvement in portfolio returns, with the case of an equity optimization model based on quantitative research by an artificial intelligence. This paper is an empirical study of the portfolio based on an artificial intelligence technology of "D" asset management, which is the largest domestic active-quant-fiduciary management in accordance with the purpose of this paper. This study will apply artificial intelligence to finance, analyzing financial and demand-supply information and automating factor-selection and weight of equity through machine learning based on the artificial neural network. Also, the learning the process for the composition of portfolio optimization and its performance by applying genetic algorithms to models will be documented. This study posits a model that the asset management industry can achieve, with continuous and stable excess performance, low costs and high efficiency in the process of investment.

• Journal of Korea Technology Innovation Society
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• v.18 no.3
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• pp.444-467
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• 2015

Government has accounted an R&D investment on drug development for the highest share among biotechnology sector. Since competitive investments between each agencies, issues on efficiency or effectiveness of the duplicate investments have been raised continuously. In this research, we investigated the effectiveness of the investment through analysis of portfolio on drug development R&D, journals, patents, and performance of the each process. As a result, reliable technology for current market demands could not compute productive outcome at the early process of the development. On the other hand, grants which support non-clinical process of the development has produced the high-quality patents for active utilization. Moreover, analysis of the performance of the process, which affects rate of success on the drug development, showed decreased efficiency compared to global average. Therefore, we proposed the strategies of reflecting the market demands and bridging between stages without interruption for maximizing the efficiency and effectiveness on investment of drug development R&D. Furthermore, strategies for concentrated support on each process should be prepared for the success of final drug development.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.333-341
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• 2014

The purpose of this study is to forecast the penetration rate of renewable energy and a reasonable scale for the R&D investment plan in Korea based on the relationship between the diffusion and R&D investments drawn by analogy from empirical cases of advanced countries. Among numerous candidate developed countries, the German market was chosen based on the similarity of the diffusion patterns to those of the Korean plan. We then figured out how the investment triggers the growth of technology from the selected benchmark, and applied the technology S-curve relation formula to derive the desirable investment plan for Korea. The present paper is a pioneering attempt to forecast the diffusion process of renewable energy technology in Korea using the comparative analogy from cases of advanced countries.