• Journal of Korea Trade
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• v.25 no.7
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• pp.41-55
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• 2021

Purpose - This paper empirically investigates the relationship between the Economic Complexity Index (ECI) and the level of development. Moreover, this research attempts to discover the determinants of ECI in the globalization wave. Design/methodology - Our empirical model considers the relationship between ECI and the level of development in middle- and high-income economies from 1995 to 2010 by using systemic qualitative analysis, including OLS, fixed-effects, and system GMM. Next, this research used OLS regression to find the determinants of ECI. In particular, we compared the effects of different factors on ECI in the different development stages. Findings - Our main findings can be summarized as follows: 1. If the ECI increases by 1, it could lead to an increase of about 30% in the level of development in middle- and high-income economies. 2. Human capital plays an important role in the development of and increase in ECI. 3. GVC participation and outflow FDI enhance an increase in ECI, in particular in middle-income economies. 4. The development of manufacturing industries is helpful to increase ECI; however, middle-income economies should pay more attention to their comparative advantage industries. 5. R&D has positive effects on the ECI. Originality/value - To the best of our knowledge, this is the first paper that uses systemic qualitative analysis to investigate the relationship between ECI and the level of development. The paper provides suggestions for policy makers to increase ECI under the current wave of globalization, in particular in middle-income economies.

• Journal of Korea Trade
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• v.24 no.1
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• pp.131-145
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• 2020

Purpose - The recent growth of South Korean products in the international market is the benchmark for both developed as well as developing countries. According to the development index, the role of international trade is indeed crucial for the development of the national economy. However, the visualization of the international trade profile of the country is the prerequisite of governmental policy decision-makers and guidance for forecasting of foreign trade. Design/methodology - We have utilized data visualization techniques in order to visualize the import & export product space and trade partners of South Korea. Economic Complexity Index (ECI) and Revealed Comparative Advantage (RCA) were used to identify the Korean international trade diversification, whereas the time series approach is used to forecast the economy and foreign trade variables. Findings - Our results show that Chine, U.S, Vietnam, Hong Kong, and Japan are the leading trade partners of Korea. Overall, the ECI of South Korea is growing significantly as compared to China, Hong Kong, and other developed countries of the world. The expected values of total import and export volume of South Korea are approximately US$535.21 and US$ 781.23B, with the balance of trade US$ 254.02B in 2025. It was also observed from our analysis that imports & exports are equally substantial to the GDP of Korea and have a significant correlation with GDP, GDP per capita, and ECI. Originality/value - To maintain the growth rate of international trade and efficient competitor for the trade partners, we have visualized the South Korea trade profile, which provides the information of significant export and import products as well as main trade partners and forecasting.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.195-200
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• 2021

In recent years, Vietnam's economic growth rate has been attributed to the growth of many well-managed industries within Southeast Asia. Among them is the civil construction industry. Construction projects typically take a long time to complete and require a huge budget. Many socio-economic variables and factors affect total construction project costs due to market fluctuations. In recent years, crucial socioeconomic development indicators of construction reached a fairly high growth rate. Also, most infrastructure and construction projects have a high degree of complexity and uncertainty. This makes it challenging to predict the accurate project price. These challenges raise the need to recognize significant factors that influence the construction price index of civil buildings in Vietnam, both micro and macro. Therefore, this paper presents critical factors that affect the construction price index using the fuzzy extent analysis process in an uncertain environment. This proposed quantitative model is expected to reflect the uncertainty in the process of evaluating and ranking the influencing factors of the construction price index in Vietnam. The research results would also allow project stakeholders to be more informed of the factors affecting the construction price index in the context of Vietnam's civil construction industry. They also enable construction contractors to estimate project costs and bid rates better, enhancing their project and risk management performance.

• Asia pacific journal of information systems
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• v.11 no.4
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• pp.99-111
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• 2001

The prediction of stock price index is a very difficult problem because of the complexity of stock market data. It has been studied by a number of researchers since they strongly affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network(BPN). Finally, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.427-436
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• 2000

The prediction of stock price index is a very difficult problem because of the complexity of the stock market data it data. It has been studied by a number of researchers since they strong1y affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain Intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network (BPN). Fina1ly, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

• Communications for Statistical Applications and Methods
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• v.27 no.6
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• pp.589-602
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• 2020

The development of smart grids has enabled the easy collection of a large amount of power data. There are some common patterns that make it useful to cluster power consumption patterns when analyzing s power big data. In this paper, clustering analysis is based on distance functions for time series and clustering algorithms to discover patterns for power consumption data. In clustering, we use 10 distance measures to find the clusters that consider the characteristics of time series data. A simulation study is done to compare the distance measures for clustering. Cluster validity measures are also calculated and compared such as error rate, similarity index, Dunn index and silhouette values. Real power consumption data are used for clustering, with five distance measures whose performances are better than others in the simulation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.151-156
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• 2023

This paper deals with the optimization problem that decides the number of advertising for any media among various medium to maximize the perception quality index of new product meets the given budget and over the minimum reached people constraints. For this problem, there is only in used the mathematical approach as linear programming (LP) software package and has been unknown the polynomial time algorithm. In this paper we suggest the heuristic algorithm with O(nlog n)time complexity to solve the optimal solution for this problem. This paper suggests the evaluation index to select the media most economically-efficient way and decides the media and the number of advertisement. While we utilize Excel, the proposed algorithm can be get the same optimal solution as LP for experimental data.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.39-53
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• 2013

Although the efficient formation of urban space structure is a key factor in energy saving and environmentally-friendly aspect, the maintenance of the center and sub-center of the city that are key factors has been becoming increasingly difficult due to the variability and complexity of urban activities. In the case of Busan, amid the expansion of urban scale due to rapid economic development and overpopulation, systematic approaches to professional diagnosis and maintenance have been significantly insufficient - other than the city basic plan which has been conducted at an interval of 20 years. For the effective management of urban central area, systematic monitoring of the CBD through demand forecast and blight forecast at a city level must first be implemented. In order to fulfill this goal, this study is to figure out the current state of the CBD through the diagnosis on blight of the urban central area in the viewpoint of rehabilitation of the CBD and to propose the measures for practical utilization of the information about space for the further management of the central area of the city. For analysis, the study looks into the present state in terms of physical index, economic index, and social index. And then as a micro-approach by utilizing economic index, the study has thoroughly examined the economic blight of the Seomyun urban central area of Busan. The outcome of the analysis shows that in terms of population distribution and land utilization the area is in the stage of inefficient dispersion after having gone through the stage of suburbanization. It is expected that this study, as the material that proves the necessity of enhancing the function of the CBD, can propose the direction for the management of the urban center of Busan through blight prediction and management of the urban center and can provide the basic data for the long-term urban development that aims at the efficient strengthening of functions of the CBD.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.991-1001
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• 2013

Instead of building new substations or transmission lines, proper installation of flexible AC transmission systems (FACTS) devices can make the transmission networks accommodate more power transfers with less expansion cost. In this paper, the problem to maximize power system loadability by optimally installing two types of FACTS devices, namely static var compensator (SVC) and thyristor controlled series compensator (TCSC), is formulated as a mixed discrete-continuous nonlinear optimization problem (MDCP). To reduce the complexity of the problem, the locations suitable for SVC and TCSC installations are first investigated with tangent vector technique and real power flow performance index (PI) sensitivity factor and, with the specified locations for SVC and TCSC installations, a set of schemes is formed. For each scheme with the specific locations for SVC and TCSC installations, the MDCP is reduced to a continuous nonlinear optimization problem and the computing efficiency can be largely improved. Finally, to cope with the technical and economic concerns simultaneously, the scheme with the biggest utilization index value is recommended. The IEEE-14 bus system and a practical power system are used to validate the proposed method.

• ETRI Journal
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• v.34 no.4
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• pp.602-612
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• 2012

It is becoming increasingly difficult to identify promising technologies due to the influx of new technologies and the high level of complexity involved in many of these technologies. Identifying promising information and communications technology (ICT)-based converging technologies holds the key to finding new sources of economic growth and forward momentum. The goal of this study is to identify cutting-edge ICT-based converging technologies by examining the latest trends in the US patent market. Analyzing the US patent market, the most competitive of such markets in the world, can yield certain clues about which of the ICT-based converging technologies may be the next revolutionary technologies. For a classification of these technologies, this study follows the International Patent Classification system. As for ICT, there are 58 related fields at the subclass level and 831 fields at the main-group level. For emerging and converging technologies, there are 75 at the main-group level. From these technologies, a final selection for cutting-edge ICT-based converging technologies is made using a composite index reflecting the converging coefficient, emerging coefficient, and technology impact index.