• New & Renewable Energy
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• v.8 no.2
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• pp.33-43
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• 2012

Why solar companies preferred vertical integration of whole value chain? Major solar companies have built internally strong vertical integration of entire PV value chain. We raise a question whether such integration increases the corporate value and whether market situation affects the result. To test these questions, we conducted multi-variant analysis where characteristic factors mainly affect the corporate value measured in terms of Tobin'Q, based on the financial and non-financial data of PV companies listed in US stock market between 2005 and 2010. We hypothesize that since integration increases the overall efficiency but decreases the flexibility to adjust to various market situation, the combined effect of the efficiency gain and the flexibility loss ultimately determines the sign of integration effect on the corporate vale. We infer that the combined effect will be influenced heavily by business cycle, as in boom market (Seller's market) the efficiency gain may be larger than the flexibility loss and vice versa in bust market. We test whether the sign of combined effect changes after the year of 2009 and which factors influence most the sign. Year of 2009 is known as the year when market shifted from Seller's to Buyer's market. We show that 1) integration increases corporate value in general but after 2009 integration significantly decreases the value, 2) the ratios such as Production/Total Cost, Cash turnover period chosen for reversal of the flexibility measure are negatively affect Tobin's Q and especially stronger after 2009. This shows the flexibility improves corporate value and stronger in the recess period (Buyer's market). These results imply that solar company should set up integration strategy considering the tradeoff between efficiency and flexibility and the impact of the business cycle on both factors. Strategy only based on the price competitiveness determined in boom time can bring undesirable outcomes to the company. In addition, Strategic alliances in some value chains as a flexible bondage should be taken in account as complementary choice to the rigid integration.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.160-160
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• 2019

Water is a limited source that needs to be properly managed and distributed to the ever-growing population of the world. Rapid urbanization and development have increased the overall water demand of the world drastically. However, there is loss of billions of liters of water every year due to leakages in water distribution systems. Such water loss means significant financial loss for the utilities as well. World bank estimates a loss of $14 billion annually from wasted water. To address these issues and for the development of efficient and reliable leakage management techniques, high efforts have been made by the researchers and engineers. Over the past decade, various techniques and technologies have been developed for leakage management and leak detection. These include ideas such as pressure management in water distribution networks, use of Advanced Metering Infrastructure, use of machine learning algorithms, etc. For leakage detection, techniques such as acoustic technique, and in recent yeats transient test-based techniques have become popular. Smart Water Grid uses two-way real time network monitoring by utilizing sensors and devices in the water distribution system. Hence, valuable real time data of the water distribution network can be collected. Best results and outcomes may be produced by proper utilization of the collected data in unison with advanced detection and management techniques. Long term reduction in Non Revenue Water can be achieved by detecting, localizing and repairing leakages as quickly and as efficiently as possible. However, there are still numerous challenges to be met and future research works to be conducted in this field.

• Asia Marketing Journal
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• v.13 no.3
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• pp.25-53
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• 2011

This study probes the effect of loyalty program on the customer retention based on the real transaction data(n=2,892) acquired from education service industry. We try to figure out the outcomes of reward program through more than 1 year-long data gathered and analyzed according to quasi-experimental design(i.e., before and after design). We adopt this kinds of research scheme in regard that previous studies measured the effect of loyalty program by dividing the customers into two group(i.e., members vs. non-members) after the firms or stores had started the program. We believe that it might not avoid the self-selection bias. The research questions of this study could be explained such as: First, most research said that the loyalty programs could increase the customer loyalty and contribute to the sustainable growth of company. But there are little confirmation that this promotional tool could be justified in terms of financial perspective. Thus, we are interested in both the retention rate and financial outcomes caused by the introduction of loyalty programs. Second, reward programs target mainly current customer. Especially CRM(customer relationship management) said that it is more profitable for company to build positive relationship with current customer instead of pursuing new customer. And it claims that reward program is excellent means to achieve this goal. For this purpose, we check in this study whether there is a interaction effect between loyalty program and customer type in retaining customer. Third, it is said that dis-satisfied customers are more likely to leave the company than satisfied customers. While, Bolton, Kannan and Bramlett(2000) claimed that reward program could contribute to minimize the effect of negative service by building emotional link with customer, it is not empirically confirmed. This point of view explained that the loyalty programs might work as exit barrier to current customer. Thus, this study tries to identify whether there is a interaction effect between loyalty program and service experience in keeping customer. To achieve this purpose, this study adopt both Kaplan-Meier survival analysis and Cox proportional hazard model. The research outcomes show that the average retention period is 179 days before introducing loyalty program but it is increased to 227 days after reward is given to the customers. Since this difference is statistically significant, it could be said that H1 is supported. In addition, the contribution margin coming from increased transaction period is bigger than the cost for administering loyalty programs. To address other research questions, we probe the interaction effect between loyalty program and other factors(i.e., customer type and service experience) affecting it. The analysis of Cox proportional hazard model said that the current customer is more likely to engage in building relationship with company compared to new customer. In addition, retention rate of satisfied customer is significantly increased in relation to dis-satisfied customer. Interestingly, the transaction period of dis-satisfied customer is notably increased after introducing loyalty programs. Thus, it could be said that H2, H3, and H4 are also supported. In summary, we found that the loyalty programs have values as a promotional tool in forming positive relationship with customer and building exit barrier.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.4
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• pp.47-60
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• 2017

As the recent cultural contents area start-ups are creating remarkable outcomes such as investment attraction together with the reinforced institutional supports from the government, this study aimed to reverify the significance of researches related to correlation analysis between service of Business Incubating Center of Small & Medium Business Administration operated with no separation of business type, and corporate performance, in the aspect of Business Incubating Center in cultural contents area, and also to suggest the importance of establishing the business incubating system in the systematic and rational cultural contents area through the differentiated business incubating service by verifying the significant effects of the business validity of items on corporate performance, and then discovering services suitable for business incubating in cultural contents area, targeting Gyeonggi-do cultural contents area Business Incubating Center recently showing the biggest growth. Especially, contrary to the existing researches, in order to verify the characteristics of Gyeonggi-do Cultural Contents Business Incubating Center, the personal support service and marketing support service were included. It also aimed to understand the effects of the business validity of start-up items on corporate performance. Summarizing the results of this study, contrary to the results of the existing researches saying that spatial & additional support service, management support service, technical support service, personal support service, and marketing support service had significant effects on corporate performance, among the support service of Gyeonggi-do cultural contents area Business Incubating Center, the spatial & additional support service, personal support service, and marketing support service had significantly positive(+) effects on corporate performance while the management support service and technical support service had no significant effects on it. Comparing with the results of the researches on the support service of Business Incubating Center(BI) of Small & Medium Business Administration, the effects of the management support service and technical support service of Gyeonggi-do cultural contents area Business Incubating Center on corporate financial/non-financial performance were not huge. Also, in the results of analyzing the business validity of star-up items, the spatial & additional support service, management support service, and technical support service did not have significant effects on the business validity of start-up items while the personal support service and marketing support service had significantly positive(+) effects on it. In case when selecting companies, Gyeonggi-do Business Incubating Center emphasized the business validity of start-up items. However, the support service provided after the selection did not have huge effects on the business validity of start-up items. Lastly, in the results of analyzing the effects of the business validity of start-up items in Gyeonggi-do cultural contents area on corporate performance, among the success factors of business start-up, the business validity of start-up items was an important element having effects on corporate performance(financial/non-financial) in the cultural contents area.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.110-118
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• 2017

This study investigated empirically one of the controversial subjects in modern finance, in that there is an optimal level of capital structure for KOSPI-listed firms in the Korean capital market. Given the major theories on the capital structure, such as Myers' pecking order, trade-off, and agency cost ones, this study applied an analysis of covariance models in parametric and non-parametric statistical methods. In particular, two covariates to control for the possible effects of trade-off and agency cost, were employed separately in each corresponding model, while the other proxy for pecking order rationale was adopted in previous research [1] to conduct inter- and intra-industry analyses. Based on the outcomes obtained from the study, it was demonstrated empirically that there are optimal capital structures for firms in the sample industries at the inter-industry level, whereas statistical differences indicating non-existence of an optimal point, were revealed within the industry. Accordingly, these findings suggest a new vision to potential investors that firms in the domestic market may have financial opportunities to increase their value by gradually adjusting the leverage ratios in terms of the intra-industry perspective.

• Journal of Preventive Medicine and Public Health
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• v.49 no.4
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• pp.220-229
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• 2016

Objectives: The association between educational status and 10-year risk for acute coronary syndrome (ACS) and all-cause mortality was evaluated. Methods: From October 2003 to September 2004, 2172 consecutive ACS patients from six Greek hospitals were enrolled. In 2013 to 2014, a 10-year follow-up (2004-2014) assessment was performed for 1918 participants (participation rate, 88%). Each patient's educational status was classified as low (<9 years of school), intermediate (9 to 14 years), or high (>14 years). Results: Overall all-cause mortality was almost twofold higher in the low-education group than in the intermediate-education and high-education groups (40% vs. 22% and 19%, respectively, p<0.001). Additionally, 10-year recurrent ACS events (fatal and non-fatal) were more common in the low-education group than in the intermediate-education and high-education groups (42% vs. 30% and 35%, p<0.001), and no interactions between sex and education on the investigated outcomes were observed. Moreover, patients in the high-education group were more physically active, had a better financial status, and were less likely to have hypertension, diabetes, or ACS than the participants with the least education (p<0.001); however, when those characteristics and lifestyle habits were accounted for, no moderating effects regarding the relationship of educational status with all-cause mortality and ACS events were observed. Conclusions: A U-shaped association may be proposed for the relationship between ACS prognosis and educational status, with participants in the low-education and high-education groups being negatively affected by other factors (e.g., job stress, depression, or loneliness). Public health policies should be aimed at specific social groups to reduce the overall burden of cardiovascular disease morbidity.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.