• Asian Journal of Business Environment
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• 제12권3호
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• pp.1-12
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• 2022

Purpose: This study aims to investigate whether AIS data can be used as a supporting indicator or as an initial signal to describe Indonesia's export-import conditions in real-time. Research design, data, and methodology: This study performs several stages of data selection to obtain indicators from AIS that truly reflect export-import activities in Indonesia. Also, investigate the potential of AIS indicators in producing forecasts of the value and volume of Indonesian export-import using conventional statistical methods and machine learning techniques. Results: The six preprocessing stages defined in this study filtered AIS data from 661.8 million messages to 73.5 million messages. Seven predictors were formed from the selected AIS data. The AIS indicator can be used to provide an initial signal about Indonesia's import-export activities. Each export or import activity has its own predictor. Conventional statistical methods and machine learning techniques have the same ability both in forecasting Indonesia's exports and imports. Conclusions: Big data AIS can be used as a supporting indicator as a signal of the condition of export-import values in Indonesia. The right method of building indicators can make the data valuable for the performance of the forecasting model.

• Journal of the Korean Data and Information Science Society
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• 제27권3호
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• pp.725-732
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• 2016

본 연구에서는 제주를 방문하는 관광객 수를 여행목적 별로 분석하였다. 여행목적은 "휴양 및 관람", "레저 및 스포츠", 그리고 "회의 및 업무"를 위한 여행으로 구분되어 있으며, 2005년 1월부터 2016년 3월까지 자료를 이용하였다. 2015년 5월에 발생한 메르스 (MERS, 중동호흡기증후군) 사태의 영향을 반영하기 위하여 계절형 ARIMA-Intervention 모형을 이용한 개입분석을 수행하였다. 분석결과 메르스사태는 "레저 및 스포츠"와 "회의 및 업무"를 목적으로하는 관광객 수에 6월 한 달간 영향을 끼친 것으로 나타났으며, 이로 인하여 이 기간 동안 30%에서 40% 정도의 관광객이 감소한 것으로 추정되었다. 반면, "휴양 및 관람"에서는 메르스사태의 영향이 유의하지 않은 것으로 나타났다. 본 결과를 토대로 향후 1년의 월별 관광수요를 예측하여 보았다.

• 한국항해항만학회지
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• 제46권5호
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• pp.449-457
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• 2022

The Port of Busan is currently ranked as the seventh largest container port worldwide in terms of cargo throughput. However, port competition in the Far-East region is fierce. The growth rate of container throughput handled by the port of Busan has recently slowed down. In this study, we analyzed how economic conditions and multiple external shocks could influence cargo throughput and identified potential implications for port business. The aim of this study was to build a model to accurately forecast port throughput using the ARIMA model, which could incorporate external socio-economic shocks, and the VEC model considering causal variables having long-term effects on transshipment cargo. Findings of this study suggest that there are three main areas affecting container throughput in the port of Busan, namely the Russia-Ukraine war, the increased competition for transshipment cargo of Chinese ports, and the weaker growth rate of the Korean economy. Based on the forecast, in order for the Port of the Port of Busan to continue to grow as a logistics hub in Northeast-Asia, policy intervention is necessary to diversify the demand for transshipment cargo and maximize benefits of planned infrastructural investments.

• 한국건설관리학회논문집
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• 제14권2호
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• pp.131-140
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• 2013

과거부터 축적된 시계열 데이터 기반의 정량적 예측 모형은 수치적인 정확성을 추구함으로써 다양한 분야의 투자 효과 예측에 활용되고 있다. 특히, R&D 사업의 경우 그 투자효과에 대해 역설할 필요가 있고, 이에 따라 건설 산업을 포함한 각 산업 정부 R&D 투자효과 예측을 위해 이러한 모형이 활용되고 있다. 그러나 5개의 세부 사업으로 분리 발주되는 건설 분야 정부 R&D 사업의 경우, 세부 사업 관련 축적된 데이터가 부족하고, 각 세부 사업별로 투자의 파급과정이 상이하다. 이에 따라 데이터 기반의 계량적 예측모형 개발에 제약이 있고, 개발된다 하더라도 투자 파급과정에 대한 설명력이 부족하여 투자 당위성을 설명해야 하는 각 세부 사업 담당자의 요구를 만족시키기에 한계가 있다. 이러한 문제를 해결하기 위해 적용되는 시스템다이내믹스 (System Dynamics) 시뮬레이션 방법론은 변수 간 인과관계를 기반으로 시스템 내 순환적 동태적 상호작용을 설명함으로써 건설 R&D 세부 사업들의 다양한 투자 파급과정을 이해하는 데 장점이 있다. 따라서 본 연구는, 각 사업별 특성에 대한 분석 및 관련된 정성적 자료를 기반으로 건설 R&D 투자의 파급과정을 설명하는 시스템다이내믹스 예측 모형을 개발하였다. 또한, 시스템다이내믹스 모형의 수치적 예측 정확성을 보완하기 위해 기 개발된 데이터 기반의 계량적 예측 모형과의 상호 연동체계를 제안하고, 이를 활용하였다. 본 모델링 방법은 정성적 자료와 정량적 데이터를 복합적으로 활용함으로써, R&D 투자의 파급과정 등 시스템 구조에 대한 이해를 가능하게 할 뿐 아니라 예측의 수치적 정확성을 보완할 수 있다. 제안한 모델링 방법을 가용데이터가 부족한 정부의 건설 R&D 세부 사업들의 경제적 투자효과 분석에 적용함으로써, 상이한 각 사업별 투자 파급과정에 대한 이해를 바탕으로 투자효과 극대화를 위한 전략 도출 및 수치적 예측력이 보완된 투자효과 분석에의 활용 가능성을 확인하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2003년도 추계종합학술대회
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• pp.31-34
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• 2003

In recent, the rapid convergence of telecommunication and broadcasting has been considered as one of the hot issues in the IT industry. This convergence will provide telecom operators with both opportunities and threatens. This is because that telecom operators can enter the broadcasting industry, whereas broadcasters will also have a chance to provide telecom services. This work aims to discuss the business strategy for telecom operators to provide a TV VOD service, one of the convergence services between telecommunication and broadcasting, through the high-speed internet which is so much served in Korea. It seems that this service will achieve two business goals, namely "to minimise an additional investment" and "to find out a new benefit source", by fully utilising a current high-speed internet infrastructure. Finally, this paper mainly contains the market overview of in telecom and broadcasting service, the definition of TV VOD service and the necessity for this service, a market forecasting and the provision strategy of major telecom operators, and key success factors and a benefit model.

• ETRI Journal
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• 제45권6호
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• pp.982-995
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• 2023

Technological innovation generates products, services, and processes that can disrupt existing industries and lead to the emergence of new fields. Distributed ledger technology, or blockchain, offers novel transparency, security, and anonymity characteristics in transaction data that may disrupt existing industries. However, research attention has largely examined its application to finance. Less is known of any broader applications, particularly in Industry 4.0. This study investigates academic research publications on blockchain and predicts emerging industries using academia-industry dynamics. This study adopts latent Dirichlet allocation and dynamic topic models to analyze large text data with a high capacity for dimensionality reduction. Prior studies confirm that research contributes to technological innovation through spillover, including products, processes, and services. This study predicts emerging industries that will likely incorporate blockchain technology using insights from the knowledge structure of publications.

• Environmental Engineering Research
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• 제22권3호
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• pp.302-311
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• 2017

Nowadays, with the burgeoning development of economy, $CO_2$ emissions increase rapidly in China. It has become a common concern to seek effective methods to forecast $CO_2$ emissions and put forward the targeted reduction measures. This paper proposes a novel hybrid model combined principal component analysis (PCA) with regularized extreme learning machine (RELM) to make $CO_2$ emissions prediction based on the data from 1978 to 2014 in China. First eleven variables are selected on the basis of Pearson coefficient test. Partial autocorrelation function (PACF) is utilized to determine the lag phases of historical $CO_2$ emissions so as to improve the rationality of input selection. Then PCA is employed to reduce the dimensionality of the influential factors. Finally RELM is applied to forecast $CO_2$ emissions. According to the modeling results, the proposed model outperforms a single RELM model, extreme learning machine (ELM), back propagation neural network (BPNN), GM(1,1) and Logistic model in terms of errors. Moreover, it can be clearly seen that ELM-based approaches save more computing time than BPNN. Therefore the developed model is a promising technique in terms of forecasting accuracy and computing efficiency for $CO_2$ emission prediction.

• The Journal of Asian Finance, Economics and Business
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• 제7권4호
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• pp.59-70
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• 2020

The purpose of this study is to construct the ACD model for the block trading volume duration. The ACD model based on the block trading volume duration is referred to as Volume ACD (VACD) in this study. By integrating with GARCH-type models, the VACD based GARCH type models, which include VACD-GARCH, VACD-IGARCH and VACD-FIGARCH models, are set up. This study selects Chunghwa Telecom (CHT) Inc., offering the America Depository Receipt (ADR) in NYSE, to investigate the block trading volume duration in Taiwanese equity market. The empirical results indicate that the long memory in volume duration series increases dependence at level of volatility clustering by VACD (2,1)-FIGARCH (3,d,1) model. Moreover, the VACD (2,1)-IGARCH (1,1) exhibits relatively better performance of prediction on capturing block trading volume duration. This volatility model is more appropriate in this study to portray the change of the CHT Inc. prices and provides more information about the volatility process for investment strategy, which can be a reference indicator of financial asset pricing, hedging strategy and risk management.

• 품질경영학회지
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• 제50권3호
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• pp.349-371
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• 2022

Purpose: Compared to the rapid growth rate of the domestic automotive LED industry so far, the predictive analysis method for demand forecasting or market outlook was insufficient. Accordingly, product characteristics are analyzed through the life trend of LEDs for automotive exterior lamps and the relative strengths of p and q using the Bass model. Also, future demands are predicted. Methods: We used sales data of a leading company in domestic market of automotive LEDs. Considering the autocorrelation error term of this data, parameters m, p, and q were estimated through the modified estimation method of OLS and the NLS(Nonlinear Least Squares) method, and the optimal method was selected by comparing prediction error performance such as RMSE. Future annual demands and cumulative demands were predicted through the growth curve obtained from Bass-NLS model. In addition, various nonlinear growth curve models were applied to the data to compare the Bass-NLS model with potential market demand, and an optimal model was derived. Results: From the analysis, the parameter estimation results by Bass-NLS obtained m=1338.13, p=0.0026, q=0.3003. If the current trend continues, domestic automotive LED market is predicted to reach its maximum peak in 2021 and the maximum demand is $102.23M. Potential market demand was $1338.13M. In the nonlinear growth curve model analysis, the Gompertz model was selected as the optimal model, and the potential market size was $2864.018M. Conclusion: It is expected that the Bass-NLS method will be applied to LED sales data for automotive to find out the characteristics of the relative strength of q/p of products and to be used to predict current demand and future cumulative demand.

• 경영과학
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• 제25권1호
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• pp.29-41
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• 2008

In the mobile communication service market, this study represents an attempt to forecast the subscribers of the IMT-2000 service market using the questionnaire of experts which is the qualitative technique is used. In this study, by using the substitution model of next generations among products in order to analyze the IMT-2000 demand of service, a demand was predicted. And by estimating the market demand prospect in which it becomes the important factor of the IMT-2000 service diffusion according to each bandwidth frequency the politically necessary approaching direction about the frequency was presented. It will be able to become the important part to not only the business carrier but also the policy maker to examine a prospect toward the subscriber of the IMT-2000 service. As a result, the market demand was exposed to be most big when the SKT 800MHz, and the KTF 800(900)MHz were used as the additional frequency. And it was likely to reach to the IMT-2000 number of subscribers to about 35.750 thousand peoples in the future at 2015.