• The Journal of Engineering Geology
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• v.30 no.3
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• pp.315-325
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• 2020

This study was performed to develop a model to predict landslides and determine the variable importance of landslides susceptibility factors based on the probabilistic prediction of landslides occurring on slopes along the road. Field survey data of 30,615 slopes from 2007 to 2020 in Korea were analyzed to develop a landslide prediction model. Of the total 131 variable factors, 17 topographic factors and 114 geological factors (including 89 bedrocks) were used to predict landslides. Automated machine learning (AutoML) was used to classify landslides and non-landslides. The verification results revealed that the best model, an extremely randomized tree (XRT) with excellent predictive performance, yielded 83.977% of prediction rates on test data. As a result of the analysis to determine the variable importance of the landslide susceptibility factors, it was composed of 10 topographic factors and 9 geological factors, which was presented as a percentage for each factor. This model was evaluated probabilistically and quantitatively for the likelihood of landslide occurrence by deriving the ranking of variable importance using only on-site survey data. It is considered that this model can provide a reliable basis for slope safety assessment through field surveys to decision-makers in the future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.5
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• pp.466-473
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• 2020

A marine air drone is a new device that can be used to respond to and prevent marine casualties. Determining the districts where marine air drones can be deployed helps the government decision makers identify efficient policy. The aim of this study is to develop a model using the fuzzy-analytic hierarchy process (F-AHP) and additive ratio assessment (ARAS) method to evaluate appropriate districts for deploying marine air drones. To verify the applicability of the proposed model, a case study was performed with respect to the Korea coast guard (KCG) districts. Since the deployed marine air drones are characterized by a high degree of overlap between the evaluation attributes. the F-AHP is used to determine the weights of identified criteria. The results of this study, show that missing people from the shore was the most important criterion for deployment of the drone. For ranking the local districts of the KCG, the ARAS is applied in the case study with the single goal of 50% reduction in marine casualties. Consequently, the highest priority district was identified as Mokpo, followed by Incheon, Seogwipo, Taean, Wando, Yeosu, Pohang, Tongyeong, Gunsan, Bolyeong, Jeju, Buan, Donghae, Sokcho, Ulsan, Uljin, Busan, Changwon, and Pyeongtaeg.

• Journal of East Asia Management
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• v.1 no.1
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• pp.1-27
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• 2020

Military experience has a great impact on a soldier ability to handle risks. Therefore, when those soldiers become managers, they may behave differently in making risky corporate decisions, especially in activities like the R&D investment. However, studies on how military experience affect R&D have been largely missing in the largest emerging economy, i.e. China, despite that the country hires a higher percentage of military managers than the US. In addition, it remains a question whether military managers affect the state-owned enterprises (SOEs) in China, as many of the corporate decisions are made by the government. This paper tries to address these questions. The imprinting theory and the upper echelon theory suggest that managers' personal experience can affect their behaviour, which in turn influences their corporate decisions. In this paper, we examine whether managers with military experience lead to higher R&D investment and whether such an effect exists in state-owned enterprises. Based on a sample of listed firms in China's A-share market over 2008-2017, we make two findings. First, companies with military managers have high R&D investment. By dividing managers' military positions into high and low rank, we find that companies tend to have higher (lower) R&D investment if their managers hold a high-rank (low-rank) position. Second, the effect of high-rank military managers on R&D investment is more pronounced if the manager is also the founder and the company is a non-state-owned enterprise. For low-ranking military managers, a stronger effect on R&D investment is also observed if they are also the founder, but whether their companies are state-owned or not has no impact on R&D investment. This study identifies managers' military experience as a contributing factors to corporate R&D investment in the largest emerging economy. This paper tests an implication of the imprinting theory and the upper echelon theory, i.e., managers' personal experience can affect their behaviour, which in turn influences their corporate decisions. Specifically, we focus on one aspect of personal experience - military experience - and look at whether it is beneficial to firms' technological innovation, therefore enriches the literature of managerial heterogeneity. Our findings on the influence of managers' military experience on firms' technological innovation can help us better understand the role of managers play in corporate decision making, and how managers' individual traits interact with the firm's characteristics.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.628-637
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• 2014

The purpose of this study is to investigate the actual conditions of the mobility convenience facilities for pedestrians and their perception of the facilities, and thereby provide fundamental material necessary to establish a strategy of improving mobility convenience facilities. This study tried to analyze the characteristics of the mobility convenience facilities for pedestrians. Based on previous studies and "Report of Mobility Facilities of the Mobility Handicapped", this study first chose the evaluation items related to mobility convenience facilities, and then conducted a questionnaire survey and Importance-Performance Analysis (IPA). According to the study results, first, the item that needs intensive improvement was sidewalks, and the detailed indicators for sidewalks were walking safety, convenient facilities for the disabled, and pavement in order. Secondly, the items that need to be maintained were bus and crossroad. Thirdly, the low-ranking items were under-passageway and pedestrian overpass. And lastly, the items that need to be controlled were facilities for passenger terminals and bus terminals. Based on the comprehensive IPA result, this researcher judged the actual use conditions of the mobility convenience facilities in Buyeo-gun, Chungcheongnamdo. Therefore, it was found that it would be urgent to improve the direct walking environment on sidewalks. In this aspect, for future policy decision and facility maintenance, it is desirable to put the item in priority in terms of investment and come up with an improvement strategy.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.109-122
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• 2019

The expansion of double-income households is increasing the social interest in child care. In particular, children's entrance into elementary school is considered to be the main cause of women's career break as well as childbirth. This study proposes an optimal location selection method for caring facilities for elementary school students. As a candidate for care facilities, we selected existing child care facilities. We proposed a dual structure evaluation method that considers locational characteristics as well as mathematical optimization when selecting the optimal location. The experiment was conducted in Songpa-gu, Seoul. A total of 36 optimal locations were selected from a total of 258 candidate facilities. First, the evaluation criteria were established using public data, and the primary candidate facilities were selected by ranking the location scores. At this time mesh resampling method was used to integrate various public data into one. Next, the final care facilities were selected using the p-median method. The results chosen are not only the optimal location considering total distance but also satisfy various location criteria considering the characteristics of the care facility. We expect that the proposed method will contribute to public data convergence or utilization and it will be helpful for policy decision when selecting the optimal location for public facilities.

• Journal of Service Research and Studies
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• v.7 no.4
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• pp.51-68
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• 2017

Financial technology (FinTech) is an emerging financial service sector include innovations in financial literacy and investment, retail banking, education, and crypto-currencies like bitcoin. One of the crucial branch of financial technology-third-party payment (TPP) is undergoing rapid growth, with online/mobile systems replacing offline financial systems. System quality and user attitudes are key perceptions driving third-party payment usage, the importance of these perceptions, however, may be different with countries as users' thinking varies from country to country. Thus, the purpose of this study is to elaborate how factors differ from China to Korea by drawing on the unified theory of acceptance and use of technology (UTAUT2). Additionally, this study also aims to propose a multi-attribute evaluation of the third-party online payment system based on analytic hierarchy process (AHP), fuzzy sets and technique for order performance by similarity to ideal solution (TOPSIS), to examine the relative importance of the perceptions influencing new technology adoption intention. The results showed that the price value has the most significant influence on Chinese perceptions, while the perceived credibility has the most significant effect on Korean perceptions. Sub-criteria also performs different results to Chinese and Korean third-party online payment system.

• Journal of Korea Water Resources Association
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• v.39 no.2 s.163
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• pp.161-178
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• 2006

Heathcote (1998) identified a systematic, seven-step approach to general watershed planning and management. It consists of 1) understanding watershed components and processes, 2) identifying and ranking problems to be solved, 3) setting clear and specific goals, 4) developing a list of management options, 5) eliminating infeasible options 6) testing the effectiveness of remaining feasible options, and 7) developing the final options. In this study the first five steps of that process were applied to the Anyangcheon watershed in Korea, which experiences streamflow depletion, frequent flood damages, and poor water quality typical of highly urbanized watersheds. This study employed four indices: Potential Flood Damage(PFD), Potential Streamflow Depletion(PSD), Potential Water Quality Deterioration(PWQD) and Watershed Evaluation Index(WEI) to identify and quantify problems within the watershed. WEI is the integration index of the others. Composite programming which is a method of multi-criteria decision making is applied for the calculation of PSD, PWQD and WEI (Step 2). The primary goal of the study is to secure instreamflow in the Anyangcheon during dry seasons. The second management goals of flood damage mitigation and water quality enhancement are also set (Step 3). Management options include not only structural measures that can alter the existing conditions, but also nonstructural measures that rely on changes in human behavior or management practices (Step 4). Certain management options which are not technically, economically, and environmentally feasible, are eliminated (Step S). Therefore, this study addresses a Pre-feasibility study, which established a master plan using Steps 1 through 5.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• The Korean Journal of Financial Management
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• v.21 no.2
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• pp.99-123
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• 2004

We focus in this study on incremental financing decisions and estimate a logit model for the probability a firm will choose a private placement over a public bond issue. We hypothesize that information asymmetry, financial risk, agent cost, and proprietary information may affect a firm's choice between public debt and private placements. We find that as the size of firm increases, the probability of choosing a private placement declines significantly. The age of the firm, however, is not a significant factor affecting the firm's choice between public and privately-placed bond. The coefficients on the firm's leverage and non-investment grade dummy are significantly positive, meaning firms with high financial risk and credit risk select private placements. The findings regarding agency-related variables, PER and Tobin's Q, are somewhat complex. We find significant evidence that firms with high PER prefer private placements to public bonds, suggesting that borrowers with options to engage in asset substitution or underinvestment are more likely to choose private placements. The coefficient of Tobin's Q is negative, but not significant, which weakly support the hold-up hypothesis. When we construct an interaction term on the Tobin's Q with a non-investment rating dummy, however, the Tobin's Q interaction term becomes positive and significant. Thus, high Tobin's Q firms with a speculative rating are significantly more likely to choose a private placement, regardless of the potential hold-up problems. The ratio of R&D to sales, proxy for proprietary information, is positively significant. This result can be interpreted as evidence in favor of a role for proprietary information in the debt sourcing decision process for these firms.

• Horticultural Science & Technology
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• v.31 no.3
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• pp.259-268
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• 2013

This study was carried out to evaluate the visual turfgrass's color quality, winter color, and spring green-up under three different soil systems and to make a practical use for sports turf design and construction. Several turfgrasses were evaluated in multi-layer, USGA and mono-layer systems. Turfgrass entries in the study comprised of 3 cultivars from Korean lawngrass (Zoysia japonica Steud.) of typical warm-season grass (WSG) and 3 blends and 3 mixtures from Kentucky bluegrass (KB, Poa pratensis L.), perennial ryegrass (PR, Lolium perenne L.), and tall fescue (TF, Festuca arundinacea Schreb.) of cool-season grass (CSG). Significant differences were observed in the turfgrass's color quality, winter color, and spring green-up in the study. Seasonal variation of visual turf color greatly occurred according to soil systems and turfgrasses. Multi-layer and USGA systems were highly associated with better visual color ratings, as compared with mono-layer system. Regardless of soil system, visual turf color in all entries was better from spring to fall than in winter. Great color differences were observed during a period of early December to early spring. CSG produced a better color quality over WSG in any soil system. Overall color ratings for CSG were KB > PR > Mixtures > TF. As for a winter color, its ranking was USGA > multi-layer > mono-layer system. No difference was found in winter among cultivars of Korean lawngrass, being completely brown, but great differences among CSG. Rated best for winter color was PR, followed by CSG mixtures, KB and finally TF in order. It was generally conceded that fast green-up in spring was greatly related with multi-layer over mono-layer system and also CSG over WSG. Among CSG, TF had a fastest green-up. PR was also fast in green-up, but poor in color uniformity. KB, however, was the slowest due to shallow rooting system, when compared with other CSGs. These results demonstrate color differences were greatly variable according to soil systems and also among turfgrass species. A precise decision should be made in selecting turfgrass species and soil system. Multi-layer and USGA systems were considered as the suitable one for turfgrass color quality, winter color and spring green-up. It is a great necessity to combine proper soil system, right turfgrass species, and appropriate mixing rates by a concept-oriented approach, when establishing garden, parks, soccer field, and golf courses and so on.