• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.785-793
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• 2021

The purpose of the research is to assess the factors affecting the liquidity of the commercial banks that are conducting mergers and acquisitions activities in Vietnam during the 2008-2018 period. This study employs samples based on 2-component data sets with cross-section and time-series data collected from the annual report of the State Bank and the audited acquisitions financial statements of nine commercial banks engaged in mergers and acquisitions activities. To carry out the research objectives, the authors conducted quantitative analysis through the Pooled OLS, REM, FEM and GMM models. The results shown that: (i) bank liquidity is positively affected by liquidity lagged, the return on equity (ROE) and economic growth; negatively affected by bank size, non-performing loan, short-run loan to deposit ratio; (ii) there is not enough evidence to conclude about the relationship between net profit margin, equity-to-assets ratio and inflation rate to bank liquidity; (iii) notably, we found evidence that, after the mergers and acquisitions, the liquidity of Vietnamese commercial banks decreased. The findings of this study suggest that bank managers take a more comprehensive view of the results of mergers and acquisitions and implications for banks to improve liquidity in the post-merger and acquisitions conditions.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.105-112
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• 2022

The current study is at the forefront of examining the theory of principal-agent framework and financing constraints to explain the level of corporate innovation. To boost the firm's level of innovation, this study uses corporate governance and corporate performance as driving factors. The study's secondary goal is to give information on the parallel relationship between corporate governance and the level of corporate innovation. This study used a two-step least square (TSLS) regression analysis to examine such a simultaneous association using secondary data from Indonesian listed businesses from 2000 to 2021, which totaled around 1,910 observations. This study uses the Principal Component Analysis (PCA) tool to test cumulative variances of potential corporate governance indicators such as the total commissioner of the firm (TCOM), total independent commissioner of the firm (INDPCOM), the proportion of institutional ownership (INSOWN), total female commissioner (FEMCOM), CEO duality (CEODUAL), and type of the firm (SOE). As a result, PCA reveals that four of these variables, omitting CEODUAL and SOE, were a corporate governance construct. Furthermore, the study discovered that the amount of firm innovation and corporate governance are related.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.459-466
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• 2013

Risk exists in all construction projects and resides among the collection of subcontractors and their array of individual activities. Wherever risk resides, the interrelation of participants to one another becomes paramount for the way in which risk is measured. Inherent risk becomes recognizable and quantifiable within network schedules in the form of consuming float - the flexibility to absorb delays. Allocating, owning, valuing, and expending such float in network schedules has been debated since the inception of the critical path method itself. This research investigates the foundational element of a three-part approach that examines how float can be traded as a commodity, a concept whose promise remains unfulfilled for lack of a holistic approach. The Capital Asset Pricing Model (CAPM) of financial portfolio theory, which describes the relationship between risk and expected return of individual stocks, is explored as an analogy to quantify the inherent risk of the participants in construction projects. The inherent relationship between them and their impact on overall schedule performance, defined as schedule risk -the likelihood of failing to meet schedule plans and the effect of such failure, is matched with the use of CAPM's beta component - the risk correlation measure of an individual stock to that of the entire market - to determine parallels with respect to the inner workings and risks represented by each entity or activity within a schedule. This correlation is the initial theoretical extension that is required to identify where risk resides within construction projects, allocate and commoditize it, and achieve actual tradability.

• Asia pacific journal of information systems
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• v.32 no.2
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• pp.275-306
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• 2022

Crowdfunding has emerged as an important financing source for diverse cultural projects and commercial ventures in the early stages. Unlike traditional investment evaluation, where structured financial data is critical, such information is typically unavailable for crowdfunding campaigns. Instead, campaign creators prepare pitches containing essential information about themselves and the campaigns, which are crucial in attracting and persuading contributors. Prior literature has examined the effects of different aspects in campaign pitches, but a comprehensive understanding of the theme is lacking. This study aims to fill this gap by identifying the lexicon of frequently used vocabulary in campaign pitches and examining how they are associated with crowdfunding success. Moreover, we examine how the association differs between culture and commercial crowdfunding campaigns. We randomly collected 50,000 campaigns from the cultural and commercial categories on Kickstarter and extracted the 100 most used verbs in the campaign pitches. Based on a machine learning approach combined with principal component analysis, we constructed sets of verbal factors statistically significant in predicting crowdfunding success. The findings also show that cultural and commercial campaigns consist of different verbal components with different effects on crowdfunding success.

• Communications for Statistical Applications and Methods
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• v.31 no.2
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• pp.213-234
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• 2024

In recent decades, increasing research attention has been directed toward predicting the price of stocks in financial markets using deep learning methods. For instance, recurrent neural network (RNN) is known to be competitive for datasets with time-series data. Long short term memory (LSTM) further improves RNN by providing an alternative approach to the gradient loss problem. LSTM has its own advantage in predictive accuracy by retaining memory for a longer time. In this paper, we combine both supervised and unsupervised dimension reduction methods with LSTM to enhance the forecasting performance and refer to this as a dimension reduction based LSTM (DR-LSTM) approach. For a supervised dimension reduction method, we use methods such as sliced inverse regression (SIR), sparse SIR, and kernel SIR. Furthermore, principal component analysis (PCA), sparse PCA, and kernel PCA are used as unsupervised dimension reduction methods. Using datasets of real stock market index (S&P 500, STOXX Europe 600, and KOSPI), we present a comparative study on predictive accuracy between six DR-LSTM methods and time series modeling.

• Journal of Korea Water Resources Association
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• v.52 no.6
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• pp.441-449
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• 2019

Drought is a longer lasting and more extensive disaster than other natural disasters, resulting in significant socioeconomic damage. Even though drought events have same severity, their damage vary from region to region because of spatial, technical, economic, and social circumstances. In this study, drought vulnerability was assessed considering socioeconomic factors. Preliminary factors were identified from the case study for Chungcheong province, and evaluative factors were selected by applying the principal component analysis. The entropy method was applied to determine the weights of evaluative factors. As a result, in Chungcheong province, farm population, number of recipient of basic living, water fare gap indicator, area of industrial complex, amount of underground water usage, amount of water available per capita, water supply ratio, financial soundness for water resources, amount of domestic water usage, amount of agricultural water usage and agricultural land area were chosen as the evaluative factors. Among them, the factors associated with agriculture had larger weights. The overall assessment of vulnerability indicated that Cheongju, Dangjin and Seosan were the most vulnerable to drought.

• Journal of Navigation and Port Research
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• v.39 no.3
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• pp.261-266
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• 2015

Many of previous studies suggested that working capital management is an important component of firm's financial decision and efficient working capital management affects firms' profitability and it's value. Recently, Korean shipping firms have been suffering from financial distress by recession of shipping economy. In this point of view, this study tries to investigate the relationship between working capital management and shipping firm's profitability, using panel data on 46 Korean shipping firms for the period of 2004-2013. As result of panel regression, it proved that average payment period, inventory turnover, cash conversion cycle and operating cycle are significantly associated with firms profitabilities such as profit margin ratio and operating profit ratio, and the manager of shipping firm can increase firms profitability by more efficient working capital management. There are strong positive relationships between average payment period and operating cycle and firm's profitability. These results suggest that managers can create firm's value by increasing average payment period and operating cycle. Otherwise inventory turnover and cash conversion cycle have negative relationships with firm's profitability. It means that managers can increase firm's profitability by reducing these variables.

• Journal of Digital Convergence
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• v.18 no.9
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• pp.103-112
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• 2020

The purpose of this study is to examine the current status and components of Korean National Debt and to analyze the effects of each component on National Debt. In the Korean Statistical Information Service (KOSIS), we searched for data such as General Accounting Deficit Conservation, For Foreign Exchange Market Stabilization, For Common Housing Stability, Local Government Net Debt Public Funds, etc that constitute National Debt. The analysis period used a total of 23 annual data from 1997 to 2019. The data collected in this study use the rate of change compared to the previous year for each component. Using this, this study attempted index analysis, numerical analysis, and model analysis. Correlation analysis result, the National Debt has a high relationship with the For Common Housing Stability. For Foreign Exchange Market Stabilization, Public Funds, etc., but has a low relationship with the Local Government Net Debt. Since 1997, National Debt has been increasing similarly to the For Foreign Exchange Market Stabilization, For Common Housing Stability and Public Funds etc. Since 2020, Korea is expected to increase significantly in terms of For Common Housing Stability and Public Funds, etc due to Corona19. At a time when the global economic situation is difficult, Korea's National Debt is expected to increase significantly due to the use of national disaster subsidies. However, if possible, the government expects to operate efficiently for economic growth and financial market stability.

• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.94-102
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• 2012

Recently, the global financial crisis and the increasing number of unsold houses in Korea are construction companies to assess their efficiency. The most important factor in analyzing the efficiency of a company is the input-output variable. However, systematic stud the core input-output variables, which have a great influence on the efficiency analysis. Thus, to the core input-output variables for efficiency analysis of construction companies, this study propose a model that includes all combinations of input-output variables and to find the core input-output variables using the Data Envelopment Analysis(DEA) model and Principal Component Analysis(PCA). Existing research and theories were studied variables and 21 models were established to measure efficiency. were obtained that the core input and output variable in 2006 the number of employees and sales. For 2008, the core input variable was capital stock and the core output variable was quarterly net profit. For 2010, the core input variable was fixed asset and the core output variable was sales. Through obtaining the variables that greatly affect the efficiency of construction companies, it is considered that individual construction companies will be able to prepare a priority strategy to enhance efficiency.

• 한국노년학
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• v.31 no.4
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• pp.1047-1065
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• 2011

The main purpose of this study is to provide the sustainability and continuous development of Long-term care Insurance in projecting changes of the Long-term care Insurance beneficiary population and Cost. We conducted a transformed cohort-component projection method that are employed for the beneficiary population projection and applied the previous experiences in Japan and German. A transformed cohort-component method means that we also projected the increasing beneficiary of long-term care insurance for using the data of geriatric disease in NHIC and estimated the cost of insurance's financial resources. First of all, beneficiary increase and strategy of extending to level 4 are categorized 2 and the expense account projection are categorized 2. If it is thought experience of Japan and German, The Level 4 extend of insuree is projected 2012 or 2013. With the results of this study, we proposed that extended level 4 insuree include the 40%~90% of geriatric disease in elderly people. The number of beneficiaries in 2011 is expected to reach to about 342,896 and in 2015 is 415,905 on scenario 1. Scenario 2(40%of geriatric disease in elderly people), the number of beneficiaries in 2011 is 342,896 and in 2015 is 483,453. Scenario 3(90%of geriatric disease in elderly people), the number of beneficiaries in 2012 is 545,068 and in 2015 is 565,565. The cost of beneficiaries insurance benefit of scenario 1 are projected from 3,000billion in 2012 to 3,500billion won in 2015. Scenario 2 are projected from 3,100billion in 2012 to 4,000billion won 2015. Finally, The cost of Level 4 extending are need minimum 300billion to maximum 1,400billion won.