• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.25-28
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• 2018

유동인구는 상권 분석에서 중요하게 사용되는 지표 중 하나로 유동인구 수와 속성에 따라 점포의 개점 가능성이 달라진다. 그중 유동인구 수는 상권의 이익과 직결되는 항목으로 그 수가 많을수록 기대되는 수익이 높다. 하지만 유동인구 조사는 사람이 직접 길목에 서서 세는 방식을 사용하고 있어 조사에 소모되는 비용이 크다. 본 논문에서는 통계 대이터와 일반 근사 이론에 기반한 심층신경망을 통해서 유동인구를 예측하는 방법을 제시하고자 한다.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2000.05a
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• pp.425-463
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• 2000

본 연구에서는 3단계에 걸쳐 투자하고 있는 초고속 국가망사업에 대해서 과연 사회적으로 경제성을 갖고 있는지 여부를 분석해 보았다. 이를 위하여 첫째, 산업연관모형을 이용하여 초고속 국가망 사업에 투입한 투자액이 유발시킨 부가가치 창출효과와 고용창출효과를 계산하였다. 다음으로 초고속 국가망 사업으로부터 파생되는 초고속 국가망의 기본서비스 수요를 예측하는 방법론을 제시하였다. 셋째, 초고속 국가망으로부터 파생되는 기본서비스 수요 창출로 인하여 향후 2010년까지 얼마만큼의 새로운 부가가치가 창출되고, 새로운 고용이 얼마만큼 창출되는지 여부를 산업연관모형을 통하여 분석하였다. 마지막으로 초고속 국가망 사업에 투자한 총금액에 대비하여 이를 통하여 얻어지는 부가가치창출효과, 고용창출효과 및 수요창출효과 등을 감안하여 과연 초고속 국가망 사업이 얼마만큼 사회적으로 경제성을 지니고 있는지를 계산해 보고자 하였다. 초고속 국가망 사업을 통한 직접적인 유발효과와 부가적인 효과를 모두를 고려하였을 때 예상되는 순수익의 투자수익율은 5439.2%로서 투자액의 54배의 사회적 수익성을 창출한다고 본다. 다음으로 부가가치유발액, 매출이익에 새로운 고용유발로 인한 소득증가분을 감안하여 사회적 수익을 계산하고, 이에 근거하여 경제성 분석을 하면 21,493.3.%와 같이 215배의 사회적 수익성이 창출된다고 계산되어진다. 따라서 간단하게 이익률법에 근거한 초고속국가망 사업에 대한 사회적 편익과 비용에 근거한 경제성 분석을 하면 초고속 국가망 사업은 투자액의 무려 215배의 사회적 편익을 제공하는 것으로 나타났다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.6
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• pp.1353-1360
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• 2009

This study examines the effects of internal control system and Analysis of characteristics and Earning management in Vulnerable Cooperation. During research period 2005${\sim}$2007, Purpose of this study is to examines whether financial characteristics has exist or not. Second, Earning management also. As a result of analysis are as follows, First T-test and logistic regression has found explanatory with stastical significance about CURRENT, RNPS, and DEPT. Second, DA of Vulnerable Cooperation is significantly higher than Normal cooperation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.26
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• pp.217-235
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• 1992

종래에서 부터 원가관리의 대상은 제품시방이 결정되고 제조준비가 대체로 완료된 후의 활동, 즉 제조활동이었다. 그러나 우리나라에서는 제조활동이 자동화, FMS화, CIM화가 진전되어, 제조과정에 들어와서부터 원가를 콘트롤하는 여지가 매우 좁아져 왔다. 따라서 관리효과를 얻기 위해서 제조준비활동이나 제품설계 활동으로 관리대상을 이동시킬 필요가 생기게 되었다. 이와 같은 배경하에서 제품설계단계와 제조준비단계에서 결정되는 신제품의 원가를 관리하고자 하는 것이 여기서 말하는 제품설계단계의 원가관리(일본에서는 원가기획이라고 부르는 경우가 있다. )인것이다. 제품설계단계의 원가관리의 개념은 수년전 부터 확대화의 경향에 있다. 즉, 그것은 단순히 제품설계와 제조준비의 단계에서 결정되는 제품원가의 관리만으로서가 아니라 신제품에서 기대되는 이익의 예측과 관리까지도 포함하기에 이르고 있다. 그리고 제품설계단계의 원가관리의 대상영역에 제품 컨셉트 작성활동이라든가 판매가격설정에 이르는 문제까지 포함하고 있는 것이며, 마케팅 전략이라든가 장기이익계획으로 보아서 전개하는 것으로 보이는 것이다. 이와 같이 아주 다양한 내용을 지닌 제품설계단계의 원가관리로 되고 있는 것이다. 이와 같은 원가기획의 유용성과 발전성을 표시하는 것이며 금후의 연구과제에 대한 명시적인 것이기도 한 것이다. 그러나 여기에서는 이러한 현상을 찾아보면서 제품설계단계의 원가관리에 대한 일반적인 Job plan(제품설계단계의 원가관리를 효과적으로 실시하기 위한 표준적 수준)의 주요과제에 대하여 논술키로 한다.

• KDI Journal of Economic Policy
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• v.31 no.1
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• pp.239-276
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• 2009

The paper investigates the possible relationship between earnings prediction by security analysts and special ownership ties that link security companies those analysts belong to and firms under analysis. "Security analysts" are known best for their role as information producers in stock markets where imperfect information is prevalent and transaction costs are high. In such a market, changes in the fundamental value of a company are not spontaneously reflected in the stock price, and the security analysts actively produce and distribute the relevant information crucial for the price mechanism to operate efficiently. Therefore, securing the fairness and accuracy of information they provide is very important for efficiencyof resource allocation as well as protection of investors who are excluded from the special relationship. Evidence of systematic distortion of information by the special tie naturally calls for regulatory intervention, if found. However, one cannot presuppose the existence of distorted information based on the common ownership between the appraiser and the appraisee. Reputation effect is especially cherished by security firms and among analysts as indispensable intangible asset in the industry, and the incentive to maintain good reputation by providing accurate earnings prediction may overweigh the incentive to offer favorable rating or stock recommendation for the firms that are affiliated by common ownership. This study shares the theme of existing literature concerning the effect of conflict of interests on the accuracy of analyst's predictions. This study, however, focuses on the potential conflict of interest situation that may originate from the Korea-specific ownership structure of large conglomerates. Utilizing an extensive database of analysts' reports provided by WiseFn(R) in Korea, we perform empirical analysis of potential relationship between earnings prediction and common ownership. We first analyzed the prediction bias index which tells how optimistic or friendly the analyst's prediction is compared to the realized earnings. It is shown that there exists no statistically significant relationship between the prediction bias and common ownership. This is a rather surprising result since it is observed that the frequency of positive prediction bias is higher with such ownership tie. Next, we analyzed the prediction accuracy index which shows how accurate the analyst's prediction is compared to the realized earnings regardless of its sign. It is also concluded that there is no significant association between the accuracy ofearnings prediction and special relationship. We interpret the results implying that market discipline based on reputation effect is working in Korean stock market in the sense that security companies do not seem to be influenced by an incentive to offer distorted information on affiliated firms. While many of the existing studies confirm the relationship between the ability of the analystand the accuracy of the analyst's prediction, these factors cannot be controlled in the above analysis due to the lack of relevant data. As an indirect way to examine the possibility that such relationship might have distorted the result, we perform an additional but identical analysis based on a sub-sample consisting only of reports by best analysts. The result also confirms the earlier conclusion that the common ownership structure does not affect the accuracy and bias of earnings prediction by the analyst.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.375-384
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• 2022

The shipping industry is cyclically impacted by complex variables such as various economic indicators, social events, and supply and demand. The purpose of this study was to analyze the operating profit of 13 Korean liner companies over 30 years, including the financial crisis of the late 1990s, the global financial crisis of the late 2000s, and the COVID-19 global pandemic. This study was conducted to also identify factors that impacted the profit ratio of Korea's liner shipping companies according to economic conditions. It was divided into ocean-going and short-sea shipping, reflecting the characteristics of liner shipping companies, and was analyzed by hierarchical multiple regression analysis. The time series data are based on the Korean International Financial Reporting Standards (K-IFRS) and comprise seaborne trade volume, fleet evolution, and macroeconomic indicators. The outliers representing the economic downturn due to social events were separately analyzed. As a result of the analysis, the China Container Freight Index (CCFI) positively impacted ocean-going as well as short-sea liner shipping companies. However, the Korean container shipping volume only impacted ocean-going liners positively. Additionally, world and Korea's GDP, world seaborne trade volume, and fuel price are factored in the operating profit of short sea liner shipping. Also, the GDP growth rate of China, exchange rate, and interest rate did not significantly impact both groups. Notably, the operating profitability of Korea's liner shipping shows an exceptionally high rate during the recessions of 1998 and 2020. It is paradoxical, and not correlated with the classical economic indicators. Unlike other studies, this paper focused on the operating profit before financial expenses, considering the complexity as well as difficulty in forecasting the shipping cycle, and rendered conclusions using relatively long-term empirical analysis, including three economic shocks.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.428-428
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• 2011

댐은 우리사회에 다양한 이익을 제공하는 반면 과거의 댐 붕괴 사례에 비추어 볼 때 붕괴로 인한 피해 규모는 막대하다. 세계 각국에서는 기존 댐들에 대한 잠재적 붕괴에 대비하기 위해 비상대처계획(Emergency Action Plan, EAP)과 같은 대책을 수립하여 붕괴로 인한 피해를 최소화하기 위한 노력을 기울이고 있다. 댐붕괴 모델링은 크게 댐 결괴부에 대한 예측과정과 댐 붕괴로 인한 하류부 홍수추적 과정으로 분류할 수 있다. 결괴부 예측과정은 댐붕괴로 인한 저수지 유출량에 가장 큰 영향을 미치는 부분이며 하류부 영향지역의 평가에도 매우 중요한 요소이다. 댐붕괴 예측모형은 결괴부에 대한 예측에 따라 매개변수 기반 모형과 물리기반 모형으로 분류된다. 매개변수 기반모형은 결괴형성과정을 단순 시간에 의한 함수로 고려하고 있으며 결괴부를 통한 흐름은 위어흐름으로 가정하고 있다. 이 모형은 현재 댐 붕괴 실무에서 가장 널리 이용되고 있으며 대표적인 모형은 FLDWAV/ DAMBRK 모형, HEC-RAS 모형 등이 있다. 물리기반 모형은 댐 붕괴진행 과정의 상세한 이해를 위해 시작되었으며 결괴부 흐름상황, 제체 침식, 제체가 불안정해지는 과정을 수리실험과 수리학, 토질역학, 구조역학 등의 이론을 통합하여 예측하는 기법으로 댐붕괴 과정을 좀 더 현실적으로 예측할 수 있으며 기존 붕괴된 댐들에 대한 붕괴 원인 및 진행과정을 규명할 수 있는 장점을 가진다. 최근 개발된 물리기반 댐 붕괴 모형은 HR-BREACH 모형, WINDAM 모형, FIREBIRD 모형 등이 있으며 지속적으로 연구되고 있다. 본 연구에서는 현재 진행 중에 있는 물리기반 댐 붕괴 모형들을 검토하고 현재 USDA, ARS에서 개발 중에 있는 WINDAM 모형을 이용하여 물리기반 모형의 수행에 요구되는 입력변수, 수행과정, 결과물에 대한 검토를 통해 댐 붕괴 관련 연구의 발전 방향을 모색하고 국내에서 물리기반 댐 붕괴 모형을 적용하기 위해 요구되는 사항과 한계점을 파악하여 댐 붕괴 실무로의 적용 방안을 마련하는 데 그 목적이 있다.

• Management & Information Systems Review
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• v.28 no.3
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• pp.69-98
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• 2009

This study investigates in-sample and out-of-sample predictive abilities of accruals and accruals components with respect to future cash flows using models developed by Barth et al.(2001). In tests, data collected fromda62 Korean KOSPI and KOSDAQ listed firms for ccr4-2007 are used. Results of in-sample prediction tests are similar with those of Barth et al.(2001). Their accrual components model is better than other three models(NI only model, CF only model and NI-total accruals model) in future cash flows predictive ability. That is, in the case of in-sample prediction, accrual components excluding amortization have additional information contents for future cash flows. But in out-of-sample tests, the results are different. The model including operational cash flows(CF only model) shows best out-of-sample predictive ability with respect to future cash flows among above four prediction models. The accrual components model of Barth et al.(2001) has worst out-of-sample predictive ability. The results are robust to sensitivity analyses. In conclusion, we can't find the evidence that accruals and accrual components have predictive ability with respect to future cash flows in out-of-sample prediction tests. This results are consistent with results of Lev et al.(2005), and inconsistent with the belief of accounting standards formulating organizations such as FASB and KASB.

• International Journal of Highway Engineering
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• v.9 no.1 s.31
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• pp.17-27
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• 2007

Since early 1990s, several developed countries have applied the Electronic Toll Collection System (ETCS) to toll roads in order to solve traffic congestion and delay problems at toll plazas. For the successful operation of the ETCS, it is important to correctly forecast the ETCS using rate. In this study, it was conceived to develop a sophisticated demand forecasting model of the ETCS for toll roads in Changwon City The Binary Logit and neural network models were tested for the model considering 11 explaining variables. The best results in prediction accuracy and goodness-of-fit were obtained on the neural network model. However, because of the difficulty in predicting the 11 variables and its fitness in wide range, the Binary Logit model which considers three policy variables only is recommended as the model to forecast the ETCS using rate.

• The Journal of Society for e-Business Studies
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• v.24 no.4
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• pp.119-133
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• 2019

Recently, the importance prediction of photovoltaic power (PV) is considered as an essential function for scheduling adjustments, deciding on storage size, and overall planning for stable operation of PV facility systems. In particular, since most of PV power is generated in peak time, PV power prediction in a peak time is required for the PV system operators that enable to maximize revenue and sustainable electricity quantity. Moreover, Prediction of the PV power output in peak time without meteorological information such as solar radiation, cloudiness, the temperature is considered a challenging problem because it has limitations that the PV power was predicted by using predicted uncertain meteorological information in a wide range of areas in previous studies. Therefore, this paper proposes the LSTM (Long-Short Term Memory) based the PV power prediction model only using the meteorological, seasonal, and the before the obtained PV power before peak time. In this paper, the experiment results based on the proposed model using the real-world data shows the superior performance, which showed a positive impact on improving the PV power in a peak time forecast performance targeted in this study.