• International Commerce and Information Review
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• v.13 no.1
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• pp.97-120
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• 2011

Purpose of this study is to define competitiveness and attribution factors of Busan port on attracting high value added business such as transshipment cargo. Research finds condition to become optimal transshipment port comprises both internal and external circumstances. As for the internal circumstance, scale and location of the distripark as well as port facilities and the rates, for the external circumstance, international network and information technology on logistics managements are providing positive effects. Optimal plans to attract transshipment cargo should include, first, development of total logistics management system from port entry to unloading, transportation, processing, loading to departure. Second, assign port as free trade zone under customs law to attract foreign investment and goods traffic through tax exemption. Third, unless it is illegal, government needs to grant substantial freedom to shift capital for the foreign investors which will lead increase in cargo traffic and foreign investment.

• Korean Journal of Construction Engineering and Management
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• v.16 no.6
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• pp.53-62
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• 2015

Time-Cost Trade-Off (TCTO) model is an important model in the construction project planning and control area. Two types of Existing TCTO model, continuous and discrete TCTO model, have been developed by researchers. However, Using only one type of model has a limitation to represent a realistic crash scenario of activities in the project. Thus, this paper presents a comprehensive TCTO model that combines a continuous and discrete model. Additional advanced features for non-linear relationship, incentive, and liquidated damage are included in the TCTO model. These features make the proposed model more applicable to the construction project. One CPM network with 6 activities is used to explain the proposed model. The model found an optimal schedule for the example to satisfy all the constraints. The results show that new model can represent more flexible crash scenario in TCTO model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.628-629
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• 2011

E-commerce is a kind of trade type between buyers and sellers rely on computer networks. Carried out according to certain standards of various business activities. e-commerce is based on modern information technology and network technology, financial electronic collection, management, information technology, business and trade information networks into one, aimed at logistics, capital flow and information flow of harmony and unity of the new trade, trade activities of the entire process, electronic, networking and digital. E-commerce has brought to the traditional ways of trading a huge impact, led to changes in economic structures, is a business revolution in the way and is recognized internationally as the 21st century is an important driver of economic development compared to current traditional companies. In this material, we first consider the current problem, analyze particular characteristics of clothing shopping mall to increase the purchasing power of customer. For these reasons, we describe the process for building the clothing site.

• Journal of Korea Trade
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• v.25 no.3
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• pp.48-64
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• 2021

Purpose - This study examined the effect of tariff cuts on productivity in Korea's manufacturing industries and the effect of initial productivity level before tariff cuts on productivity improvement after tariff cuts. We also attempted to identify whether import-driven or export-driven factors are more important for productivity improvement, especially in low productivity industries. Design/methodology - Since tariff reduction is a policy decision that can affect cross-industry, its impact is spread across all industries beyond the scope of a single firm through the input and output network of industry structure. Accordingly, we proposed a new method to measure the change in productivity to reflect the impact of tariff cuts across industries. Through an Armington CGE analysis, changes in endogenous variables can be directly measured after the exogenous shock of tariff reduction, and the amount of movements in productivity triggered by tariff cuts can also be calculated. We can thus assess the effectiveness of exogenous policy, such as tariff cuts, through the difference between the benchmark and counterfactual values of endogenous variables. Findings - This study confirmed that tariff reduction positively affected productivity improvement in Korea's manufacturing industries. It also confirmed that productivity gains occur in Korea's leading export industries. Finally, greater productivity gains were recorded in the group with additional high-export-share or high-import-share conditions for low productivity industries. These results are, in a limited sense, consistent with the existing studies that emphasize the importance of exports and imports on productivity improvement, especially for low productivity industries. Originality/value - The results of our experiments are different from those of non-CGE studies, which measure the industry-level change in productivity with dummy coefficients, in terms of directly calculating the amount of change in productivity. In addition, we propose that the Armington CGE model is more appropriate than the Melitz CGE model to directly measure the productivity after tariff cuts. This is because the Melitz CGE model assumes the given specific productivity density, which does not change after an overall drop of tariffs. To the best of our knowledge, this approach to directly calculating productivity by reflecting the impact of tariff reduction across industries through CGE analysis, is unprecedented in this literature.

• Korea Trade Review
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• v.46 no.5
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• pp.65-81
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• 2021

The technological development in the era of the 4th industrial revolution is changing the paradigm of various industries. Various technologies such as big data, cloud, artificial intelligence, virtual reality, and the Internet of Things are used, creating synergy effects with existing industries, creating radical development and value creation. Among them, the logistics sector has been greatly influenced by quantitative data from the past and has been continuously accumulating and managing data, so it is highly likely to be linked with big data analysis and has a high utilization effect. The modern advanced technology has developed together with the data mining technology to discover hidden patterns and new correlations in such big data, and through this, meaningful results are being derived. Therefore, data mining occupies an important part in big data analysis, and this study tried to analyze data mining techniques that can contribute to the logistics field and common logistics using these data mining technologies. Therefore, by using the AHP technique, it was attempted to derive priorities for each type of efficient data mining for logisticalization, and R program and R Studio were used as tools to analyze this. Criteria of AHP method set association analysis, cluster analysis, decision tree method, artificial neural network method, web mining, and opinion mining. For the alternatives, common transport and delivery, common logistics center, common logistics information system, and common logistics partnership were set as factors.

• Journal of information and communication convergence engineering
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• v.12 no.3
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• pp.135-139
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• 2014

Opportunistic routing was originally introduced in various multihop network environments to reduce the number of hops in such a way that, among the relays that decode the transmitted packet for the current hop, the one that is closest to the destination becomes the transmitter for the next hop. Unlike the conventional opportunistic routing case where there is a single active S-D pair, for an ad hoc network in the presence of fading, we investigate the performance of parallel opportunistic multihop routing that is simultaneously performed by many source-destination (S-D) pairs to maximize the opportunistic gain, thereby enabling us to obtain a logarithmic gain. We first analyze a cut-set upper bound on the throughput scaling law of the network. Second, computer simulations are performed to verify the performance of the existing opportunistic routing for finite network conditions and to show trends consistent with the analytical predictions in the scaling law. More specifically, we evaluate both power and delay with respect to the number of active S-D pairs and then, numerically show a net improvement in terms of the power-delay trade-off over the conventional multihop routing that does not consider the randomness of fading.

• ETRI Journal
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• v.43 no.5
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• pp.799-811
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• 2021

This paper considers a challenging problem: to simultaneously optimize the cost and the quality of service in opaque wavelength division multiplexing (WDM) networks. An optimization problem is proposed that takes the information including network topology, traffic between end nodes, and the target level of congestion at each link/ node in WDM networks. The outputs of this problem include routing, link channel capacities, and the optimum number of switch ports locally added/dropped at all switch nodes. The total network cost is reduced to maintain a minimum congestion level on all links, which provides an efficient trade-off solution for the network design problem. The optimal information is utilized for dynamic traffic in WDM networks, which is shown to achieve the desired performance with the guaranteed quality of service in different networks. It was found that for an average link blocking probability equal to 0.015, the proposed model achieves a net channel gain in terms of wavelength channels (𝛾_w) equal to 35.72 %, 39.09 %, and 36.93 % compared to shortest path first routing and 𝛾_w equal to 29.41 %, 37.35 %, and 27.47 % compared to alternate routing in three different networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2736-2750
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• 2022

As demands for the maritime communications increase, a variety of functions and information are required to exchange via elements of maritime systems, which leads communication traffic increases in maritime frequency bands, especially in VHF (Very High Frequency) band. Thus, effective resource management is crucial to the future maritime communication systems not only to the typical terrestrial communication systems. VHF data exchange system (VDES) enables to utilize more flexible configuration according to the communication condition. This paper focuses on the VDES communication system among VDES terminals such as shore stations, ship stations and aids to navigation (AtoN) to address efficient resource allocation. We propose a resource management method considering a MIMO (Multiple Input Multiple Output) technique in VDES, which has been widely used for modern terrestrial wireless networks but not for marine environments by scheduling the essential communication resources. We introduce the general channel model in marine environment and give two metrics, spectral and the energy efficiencies to examine our resource scheduling algorithm. Based on the simulation results and analysis, the proposed method provides a possibility to enhance spectral and energy efficiencies. Additionally, we present a trade-off relationship between spectral and energy efficiencies. Furthermore, we examine the resource efficiencies related to the imperfect channel estimation.

• Journal of Korea Port Economic Association
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• v.34 no.2
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• pp.97-114
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• 2018

The East Asian region, an important part of Korea's imports and exports, is expected to grow further driven by the geographical, political, economic, social, and cultural complementarity. With the recent increase in imports and exports, the port trade volume between Korea and East Asian countries is also growing. However, due to various factors, such as economic size, growth rate, port infrastructure level, and geographical location of these countries, the volume of traffic with these ports is fluctuating. Despite much research on the volatility of port trade volume and changes in port network, this study tries to supplement the gap in a more detailed study of ports in Korea and East Asia since these kinds of studies are limited. The purpose of this study is to analyze the trend of distribution routes of export container cargo among ports in Korea and to present policy and practical implications of Korean trading companies, shipping companies, logistics companies, and port authorities. This study analyzes the variability of the trade volume between Korea's major ports and Daedong. Results show that Shanghai, Ningbo, Ho Chi Minh, and Haiphong were the most important factors in terms of size and volume increase. In terms of ports, the Busan port is the port responsible for trades with Yantai, Weihai, Hakata, Kobe, Ho Chi Minh, and Haiphong; Incheon port deals with Lianyungang, Tianjin, Osaka, Kobe, Ho Chi Minh, Haiphong; Gwangyang port trades with Tianjinxingang, Weihai, Yokohama, Mihn and Tanjong, and Ulsan port is strategically important for the Yantai, Lianyungang, Nagoya, Kobe, Ho Chi Minh and Portkelang ports. Therefore, the Korean government, port authorities, and shipping and logistics companies need to strengthen logistic network cooperation with these ports and actively promote investments in them.

• Journal of Korea Trade
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• v.24 no.7
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• pp.1-28
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• 2020

Purpose - This paper empirically investigates the predictors and main determinants of consumers' ratings of mobile applications in the Google Play Store. Using a linear and nonlinear model comparison to identify the function of users' review, in determining application rating across countries, this study estimates the direct effects of users' reviews on the application rating. In addition, extending our modelling into a sentimental analysis, this paper also aims to explore the effects of review polarity and subjectivity on the application rating, followed by an examination of the moderating effect of user reviews on the polarity-rating and subjectivity-rating relationships. Design/methodology - Our empirical model considers nonlinear association as well as linear causality between features and targets. This study employs competing theoretical frameworks - multiple regression, decision-tree and neural network models - to identify the predictors and main determinants of app ratings, using data from the Google Play Store. Using a cross-validation method, our analysis investigates the direct and moderating effects of predictors and main determinants of application ratings in a global app market. Findings - The main findings of this study can be summarized as follows: the number of user's review is positively associated with the ratings of a given app and it positively moderates the polarity-rating relationship. Applying the review polarity measured by a sentimental analysis to the modelling, it was found that the polarity is not significantly associated with the rating. This result best applies to the function of both positive and negative reviews in playing a word-of-mouth role, as well as serving as a channel for communication, leading to product innovation. Originality/value - Applying a proxy measured by binomial figures, previous studies have predominantly focused on positive and negative sentiment in examining the determinants of app ratings, assuming that they are significantly associated. Given the constraints to measurement of sentiment in current research, this paper employs sentimental analysis to measure the real integer for users' polarity and subjectivity. This paper also seeks to compare the suitability of three distinct models - linear regression, decision-tree and neural network models. Although a comparison between methodologies has long been considered important to the empirical approach, it has hitherto been underexplored in studies on the app market.