• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.159-173
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• 2017

In order to provide technical financial support to small and medium-sized venture companies based on technology, the government implemented the TCB evaluation, which is a kind of technology rating evaluation, from the Kibo and a qualified private TCB. In this paper, we briefly review the current state of TCB evaluation and available indicators related to technology evaluation accumulated in the Korea Credit Information Services (TDB), and then use indicators that have a significant effect on the technology rating score. Multiple regression techniques will be explored. And the relative importance and classification accuracy of the indicators were calculated by applying the key indicators as independent features applied to the generalized boosting model, which is a representative machine learning classifier, as the class influence and the fitness of each model. As a result of the analysis, it was analyzed that the relative importance between the two models was not significantly different. However, GBM model had more weight on the InnoBiz certification, R&D department, patent registration and venture confirmation indicators than regression model.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.555-564
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• 2020

The purpose of this study is to analyze the efficiency of research institutes of futures companies, and to promote the development of futures market and real economy. This study employs DEA-solver software to conduct super-efficiency data envelopment analysis (SE-DEA), and also selects 40 representative futures research institutes in China as decision-making units (DMUs). For data of input and output indicators, we collect from the China Futures Association, Futures Daily, Hexun.com and Webstock.com respectively, and the time duration is the 103 trading days between from October 2019 to February 2020. Then the indicator for the strategy accuracy rate is calculated separately by analyzing the strategies published by each DMUs in public media. In conclusions, most institutes have excessive investment in human resources, and also have insufficient strategy accuracy rate and insufficient published research reports. The findings of this study suggest that Chinese futures companies need to improve the efficiency of research institutes, and better meet the demand of the financial market. In fact, the analysis of the efficiency of the futures company research institute has not been found in the literature worldwide, Application of DEA model in efficiency analysis of securities and futures research institutions and establishment of indicators are the innovations of this paper.

• Journal of the Korean Society of Marine Environment & Safety
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• v.16 no.3
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• pp.287-293
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• 2010

As an exploratory research to understand the nature of relationships between harbors and their neighboring communities, this study analyzes how harbors influence their residents' quality of life(QOL). The QOL was measured by 18 indicators reconstructed by reviewing relevant literatures. As a result, both Busan and Incheon were found to have statistically significant influence on many of QOL indicators including general expenditure per capita, number of manufacturing factories per capita, rate of housing supply, number of financial agencies per capita, number of cultural assets per capita, number of schools per capita, number of sick-beds per capita, and the size of welfare expenditure per capita.

• Journal of Korea Technology Innovation Society
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• v.15 no.3
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• pp.700-721
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• 2012

This paper deals with methods for determining the reasonable royalty rates in the valuation of patents. To calculate the reliable reasonable royalty rate of a patent, we review pros and cons of the 25% rule royalty calculating method and the recent trend of this method. We also review the game theory of Nash Bargaining equation and review the Investment of Rate of Return Method according to the financial analysis. Next, we refer to the reasonable royalty damage cases among the recent patent infringement cases in USA and analyze the corresponding patents. We extract the patent indicators from the patent bibliographic information. Finally, we obtain a regression model for calculating a reasonable royalty rate using the patent indicators and the reasonable royalty rates in the recent patent infringement cases.

• The Journal of Information Systems
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• v.29 no.3
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• pp.119-144
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• 2020

Purpose Real estate usually takes charge of the highest proportion of physical properties which individual, organizations, and government hold and instability of real estate market affects the economic condition seriously for each economic subject. Consequently, practices for predicting the real estate market have attention for various reasons, such as financial investment, administrative convenience, and wealth management. Additionally, development of machine learning algorithms and computing hardware enhances the expectation for more precise and useful prediction models in real estate market. Design/methodology/approach In response to the demand, this paper aims to provide a framework for forecasting the real estate market with machine learning algorithms. The framework consists of demonstrating the prediction efficiency of each machine learning algorithm, interpreting the interior feature effects of prediction model with a state-of-art algorithm, LIME(Local Interpretable Model-agnostic Explanation), and comparing the results in different cities. Findings This research could not only enhance the academic base for information system and real estate fields, but also resolve information asymmetry on real estate market among economic subjects. This research revealed that macroeconomic indicators, real estate-related indicators, and Google Trends search indexes can predict real-estate prices quite well.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.201-217
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• 2015

In this paper, we report computational testing result to examine the validity of firm's bankruptcy risk estimation through quantification of supply chain risk. Supply chain risk in this study refers to upstream supply risk and downstream demand risk, To assess the firm's risk affected by supply chain risk, we adopt unit of analysis as industry level. since supply and demand relationships of the firm could be generalized by the industry input-output table and the availability of various valid economic indicators which are chronologically calculated. The research model to estimate firm's risk level is the linear regression model to assess the industry bankruptcy risk estimation of the focal firm's industry with the independent variables which could quantitatively reflect demand and supply risk of the industry. The publicly announced macro economic indicators are selected as the candidate independent variables and validated through empirical testing. To validate our approach, in this paper, we confined our research scope to steel industry sector and its related industry sectors, and implemented the research model. The empirical testing results provide useful insights to further refine the research model as the valid forecasting mechanism to capture firm's future risk estimation more accurately by adopting supply chain industry risk aspect, in conjunction with firm's financial and other managerial factors.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.251-261
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• 2020

The paper examines the role of some determinants of economics, politics and institutions on the budget deficit volatility in some countries of the Association of South East Asian Nations (ASEAN) such as Indonesia, Thailand and Vietnam. The paper uses the fixed effects model (FEM) and the random effects model (REM) to investigate panel data of these countries in the period of 1990-2018. Moreover, the study also explores ordinary least square (OLS) to analyze time-series data for each country in the same period to make comparison among them. The economic data is collected from international financial statistics and world development indicators. The data on political variables are collected from International Country Risk Data Guide (ICRG). The empirical results both confirm that corruption and political stability are important indicators of budget deficit. Besides, the paper suggests authorities should pay more attention on improving the institutional setup of the economy in order to avoid high and unstable deficit. The findings offer new insight on the budget deficit in essence and suggest that the most important thing need to be done ahead is to strongly implement anti-corruption actions. By doing so, the status of budget deficit would be remarkably improved immediately.

• Journal of Construction Engineering and Project Management
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• v.2 no.3
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• pp.30-39
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• 2012

Design-build (D&B) has been broadly perceived as an effective project delivery method and become popular in the world. However, the implementation process of this innovative procurement method in Vietnam encounters difficulties due mainly to unfamiliarity and inexperience with the approach. Critical success factors (CSFs) which could be used to enhance the project execution are useful to practitioners in Vietnam if identified. A questionnaire survey was employed to identify CSFs of D&B projects in Vietnam. Parties' competence, especially financial capability, and contract documentation are the most important factors significantly affecting project success. It was also shown that the perspectives of two principal parties in D&B projects on the CSFs are statistically correlated. The identified CSFs were then validated with some various D&B projects. The execution results of CSFs' were compared with the projects' performance measured try key performance indicators (KPIs). The most important success factors of this study were also compared with other countries'. The validation and comparison results provide project participants with some useful information to perform D&B projects better. Practitioners should well perform the identified CSFs to enhance the chance of the success of D&B projects in Vietnam. The findings of this study are useful not only to Vietnamese practitioners but also to others who are concerned about D&B method and plan to employ it in Vietnam in future.

• Korea Journal of Hospital Management
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• v.22 no.3
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• pp.46-60
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• 2017

The purpose of this study is to analyze the difference of productivity according to environmental factors among 25 Regional base public hospitals. Also this study is to propose a method to improve the productivity of Regional base public hospitals in the future by improving the public performance and stable management performance by studying the productivity variables affecting profitability. The survey period was based on the last three years, and 25 Regional base public hospitals were selected for the survey. The dependent variable is the total capital medical marginal profitability and the medical profit marginal profitability which are the indicators of profitability. The independent variable, productivity, is classified into three indicators: capital productivity, labor productivity, and value added productivity. The ANOVA analysis method was used to analyze the productivity difference according to the frequency factor and the environmental factors of the Regional base public hospitals. Finally, we conducted a hierarchical regression analysis to examine the productivity variables affecting profitability. The results of this study showed that there were differences in productivity due to environmental factors such as hospital size, competition in the local medical market, and differences in management performance. The difference in productivity and profitability depending on the environmental factors suggests that it is difficult for Regional base public hospitals in each regional base to perform a balanced public service. In order to overcome this, it is necessary to provide balanced medical services such as government financial support expansion, regional medical demand forecasting and facility infrastructure construction.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.77-88
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• 2021

The stock markets in the BRICS (Brazil, Russia, India, China and South Africa) countries are the leading emerging markets globally. Therefore, it is pertinent to ascertain the critical drivers of stock market development in these economies. The currrent study empirically investigates to identify the linkages between stock market development, key macro-economic factors and institutional factors in the BRICS economies. The study covers the time period from 2000 to 2017. The dependent variable is the country's stock market development and the independent variables consist of six macroeconomic variables and five institutional variables. The study employs a panel cointegration test, Fully Modified OLS (FMOLS), a Pooled Mean Group (PMG) approach and a heterogeneous panel non-causality test.The findings of the study indicate co-integration among the selected variables across the BRICS stock markets. Long-run estimations reveal that five macroeconomic variables and four variables related to institutional quality are positive and statistically significant. Further, short-run causalities between stock market capitalization and selected variables are detected through the test of non-causality in a heterogeneous panel setting. The findings suggest that policymakers in the BRICS countries should enhance robust macroeconomic conditions to support their financial markets and should strengthen the institutional quality drivers to stimulate the pace of stock market development in their countries.