• Management Science and Financial Engineering
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• v.14 no.1
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• pp.23-34
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• 2008

In this study, we consider stationary waiting times in a Poisson driven single-server m-node queues in series. We assume that service times at nodes are independent, and are either deterministic or non-overlapped. Each node excluding the first node has a finite waiting line and every node is operated under a FIFO service discipline and a communication blocking policy (blocking before service). By applying (max, +)-algebra to a corresponding stochastic event graph, a special case of timed Petri nets, we derive the explicit expressions for stationary waiting times at all areas, which are functions of finite buffer capacities. These expressions allow us to compute the performance measures of interest such as mean, higher moments, or tail probability of waiting time. Moreover, as applications of these results, we introduce optimization problems which determine either the biggest arrival rate or the smallest buffer capacities satisfying probabilistic constraints on waiting times. These results can be also applied to bounds of waiting times in more general systems. Numerical examples are also provided.

• 한국전산유체공학회:학술대회논문집
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• 2007.04a
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• pp.153-158
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• 2007

Since the introduction of Nanoimprint in the mid-1990s, Nanoimprint lithography, a low-cost, non-convential method, has been the dominant lithography technology that guarantees high-throughput patterning of nanostructures. Based on the mechanical embossing mechanism, Nanoimprint lithography creates the nanopatterns on the polymer material cast on the substrate. In essence, the process needs nanofabrication equipment for printing with the adequate control of temperature, pressure and control of parallels of the stamp and substrate. This article introduce the possibility and reality of the thermal control on the hot plate using a CFD code. Numerical computation has been conducted for assessing the feasibility of a hot plate($120{\times}120\;mm2$). PID control is adopted to ensure high temperature uniformity in several zones. Parallel experiments have also been performed for verifying thermal performance. Not only show the results the optimum number of thermocouples related to controllers but also suggest that the thermal simulation using a CFD code would be an alternative method to design and develop the thermal control equipment in the financial aspect.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.527-538
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• 2021

The purpose of the study is to determine the efficiency, position, and partner selection of securities companies via the negative super-SBM model used in data envelopment analysis (DEA). This model utilizes a variety of inputs, including current assets, non-current assets, fixed assets, liabilities, owner's equity and charter capital, and outputs including net revenue, gross profit, operating profit, and net profit after tax collected from the financial reports (Vietstock, 2020) of 32 securities companies, operating during the period from 2016 to 2019, negative data are collected as well. Empirical results determined both efficient and inefficient terms, and then further determined the position of each securities firm under consideration of every term. The overall score arrived at discovered a large performance change realizing a maximum score able to reach 20.791. In the next stage, alliancing inefficient companies was carried out based on the 2019 scores to seek out optimal partners for the inefficient companies. The tested result indicated that AAS was the best partner selection when its partners received a good result after alliancing, as with FTS (11.04469). The partner selection is deemed as a solution helpful to inefficient securities companies in order to improve their future efficiency scores.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.741-750
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• 2021

The research aims to analyze the level of efficiency by grouping banks during the period 2017 - 2018 into category 1 and category 2 banks and then dividing them as Regional Development Banks (BPD) and Non-BPD Conventional Commercial Banks (BUK) within each category. The research objects are banks within the categories BPD and BUK comprised 18 BPDs and 35 BUKs. The research methodology uses 3 stages, first, using Data Envelopment Analysis (DEA) we measure the level of bank efficiency; second, using the Tobit regression model we evaluate the effect of financial performance on DEA efficiency, and third, using the Mann-Whitney test we determine whether there is a difference in the efficiency of category 1 and 2 banks. The results showed that there was a decrease in the efficiency of category 1 and 2 banks but on average, the efficiency of category 1 banks is higher than category 2 banks. The estimation results of the Tobit regression model show that only the ROA variable affects the efficiency level of category 1 banks, while category 2 banks are influenced by NPL and ROA variables. In the Mann-Whitney test, it was proven that there were differences in efficiency between BUK and BPD in category 1 and 2 banks.

• The Journal of Economics, Marketing and Management
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• v.10 no.3
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• pp.21-36
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• 2022

Purpose: The purpose of this study is to compare and analyze the enterprise's score index calculated from atypical data and corrected data. Research design, data, and methodology: In this study, news articles which are non-financial information but qualitative data were collected from 2,432 SMEs that has been extracted "square proportional stratification" out of 18,910 enterprises with fixed data and compared/analyzed each enterprise's score index through text mining analysis methodology. Result: The analysis showed that qualitative data can be quantitatively evaluated by region, industry and period by collecting news from SMEs, and that there are concerns that it could be an element of alternative credit evaluation. Conclusion: News data cannot be collected even if one of the small businesses is self-employed or small businesses has little or no news coverage. Data normalization or standardization should be considered to overcome the difference in scores due to the amount of reference. Furthermore, since keyword sentiment analysis may have different results depending on the researcher's point of view, it is also necessary to consider deep learning sentiment analysis, which is conducted by sentence.

• Journal of Korea Trade
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• v.23 no.6
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• pp.93-112
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• 2019

Purpose - First, this study contextually examines the governance codes of South Africa and South Korea. Second, it analyzes board features of South African (JSE) Mainboard and South Korean (KRX) KOSPI-listed companies. Design/methodology - This review is qualitative and uses data from the annual reports of the selected markets' companies, respective exchanges' official web sites and corporate governance-related web sites in order to examine the corporate governance practices in the two markets. In addition, Nvivo is employed in analyzing the content of the corporate governance codes of the selected countries. Findings - Our analysis indicates that the corporate governance codes of the two countries are evolving to keep up with the international trend of principles-based approach. The composition of the board of directors (BODs) of non-financial companies of both South Africa and South Korea shows no significant variation between the companies with regards to the executive (inside) and nonexecutive (outside) directors. On the contrary, there is a significant variation between South African and South Korean listed companies with respect to diversity. Originality/value - While previous studies are centered on the impact of governance codes on performance, this study intends to contextually evaluate the codes and features of South Africa and South Korea listed companies. This is essential and timely for regulators and policy makers given the importance of corporate governance features such as board independence and diversity in recent times.

• Geomechanics and Engineering
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• v.39 no.1
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• pp.27-41
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• 2024

Accurately estimating the performance of tunnel boring machines (TBMs) is crucial for mitigating the substantial financial risks and complexities associated with tunnel construction. Machine learning (ML) techniques have emerged as powerful tools for predicting non-linear time series data. In this research, six advanced meta-heuristic optimization algorithms based on long short-term memory (LSTM) networks were developed to predict TBM penetration rate (TBM-PR). The study utilized 1125 datasets, partitioned into 20% for testing, 70% for training, and 10% for validation, incorporating six key input parameters influencing TBM-PR. The performances of these LSTM-based models were rigorously compared using a suite of statistical evaluation metrics. The results underscored the profound impact of optimization algorithms on prediction accuracy. Among the models tested, the LSTM optimized by the particle swarm optimization (PSO) algorithm emerged as the most robust predictor of TBM-PR. Sensitivity analysis further revealed that the orientation of discontinuities, specifically the alpha angle (α), exerted the greatest influence on the model's predictions. This research is significant in that it addresses critical concerns of TBM manufacturers and operators, offering a reliable predictive tool adaptable to varying geological conditions.

• Journal of Distribution Science
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• v.18 no.3
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• pp.77-85
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• 2020

Purpose: This study examined marketing value as online word-of-mouth media in the foodservice industry, and it did research on online word-of-mouth (e-WOM) communication marketing schemes using mass communication in the industry. The study is also intended to investigate the impact of electronic word-of-mouth (e-WOM) information and communication on product awareness risks, benefits, and word-of-mouth (WOM) impacts on restaurant consumers. Research design, data, and methodology: The analysis was conducted on a valid questionnaire of 425 menu product consumers. The survey was conducted for two months in March 2019. The collected data was analyzed using SPSS and hierarchical regression analysis was applied. Results: It did empirical research on the reciprocal casual relations to online and the existing word-of-mouth communication that have to be preceded to understand characteristics of online word-of-mouth communication for the purpose of this study. The result is summarized as follows. First, the online word-of-mouth (e-WOM) effect on product recognition risk shows the statistically significant effect of information sender characteristics, information recipient characteristics, and online word-of-mouth (e-WOM) communication on product recognition risk. Second, the influence of online word-of-mouth (e-WOM) on product risk benefits shows that the information sender characteristics, the information receiver characteristics, and online communications have a statistically significant effect on product risk benefits. Third, online word of mouth risk recognition had a statistically significant effect on word of mouth acceptance. Fourth, online risk benefit had a statistically significant positive effect on word of mouth (WOM) effect. Conclusions: The communication between online word of mouth (e-WOM) sender and recipient had a positive influence on the product evaluation and attitude change in the foodservice industry, and the word-of-mouth (WOM) effect affected financial and non-financial performance. The results mentioned above indicated that the communication between the sender of the information and the receiver of the information had a positive effect on the product evaluation and attitude change of the menu consumer, and the word-of-mouth (WOM) result affected the financial. Therefore, the online word-of-mouth (e-WOM) effect has a positive effect on the word-of-mouth (WOM) effect of menu products when performed simultaneously and positively between the information sender and the information receiver.

• Korean Journal of Construction Engineering and Management
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• v.17 no.5
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• pp.13-21
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• 2016

Insolvency of construction companies that play the role of main contractors can lead to clients' losses due to non-fulfillment of construction contracts, and it can have negative effects on the financial soundness of construction companies and suppliers. The construction industry has the cash flow financial characteristic of receiving a project and getting payment based on the progress of the construction. As such, insolvency during project progress can lead to financial losses, which is why the prediction of construction companies is so important. The prediction of insolvency of Korean construction companies are often made through the KMV model from the KMV (Kealhofer McQuown and Vasicek) Company developed in the U.S. during the early 90s, but this model is insufficient in predicting construction companies because it was developed based on credit risk assessment of general companies and banks. In addition, the predictive performance of KMV value's insolvency probability is continuously being questioned due to lack of number of analyzed companies and data. Therefore, in order to resolve such issues, the Bayesian Probabilistic Approach is to be combined with the existing insolvency predictive probability model. This is because if the Prior Probability of Bayesian statistics can be appropriately predicted, reliable Posterior Probability can be predicted through ensured conditionality on the evidence despite the lack of data. Thus, this study is to measure the Expected Default Frequency (EDF) by utilizing the Bayesian Probabilistic Approach with the existing insolvency predictive probability model and predict the accuracy by comparing the result with the EDF of the existing model.

• Management & Information Systems Review
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• v.34 no.5
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• pp.213-231
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• 2015

In this paper, I examine whether the listed companies in Korea tend to manage operating cash flows upward via classification shifting after the adoption of K-IFRS. As proxies for cash flow management, I derive a measure of abnormal operating cash flows borrowing from Lee(2012). Alternative proxies include a series of categorical variables designed to identify the types of classification shifting of interest and dividend payments among others, in the statement of cash flows. Higher level of estimated abnormal operating cash flows, and the classification of interest/dividend payments in non-operating activity sections are considered to indicate the managerial intention to maximize reported operating cash flows. I consider several potential incentives to manage operating cash flows, which include financial distress, the credit rating proximity to investment/non-investment cutoff threshold, avoidance of negative or decreasing operating cash flows relative to previous period and so forth. In a series of empirical analyses, I do not find evidence in support of the opportunistic classification shifting explanation, inconsistent with several previous literature in Korea. In contrast, I observe negative associations between the CFO management proxies and selected incentives, which suggest that the classification is likely to represent above average cash flow performance rather than opportunistic motives exercised to maximize reported operating cash flows. I reckon that this observation is, in part, driven by the K-IFRS requirement to maintain temporal consistency in classifying interest and dividend receipts/payments in cash flow statement.