This study estimated the long-run and the short-run price and income elasticity of crude oil demand by using the ARDL model in Korea. First, the long-run cointegration relationship existed between crude oil demand and price or income in the ARDL-bounds tests. Second, the long-run own price, the cross price elasticity and the income elasticity were both statistically significant elastic and sensitive in the ARDL. Third, there was autocorrelation of the residuals, but no misspecification errors and heteroscedasticity, and then the residuals showed a normal distribution. And the CUSUM & CUSUMSQ tests showed that the coefficients were stable. Fourth, the short-run own price, the cross price elasticity and the income elasticity were both statistically significant elastic and sensitive in the ARDL-RECM. The ECM with the short-run dynamics showed rapid adjustments in the long-run equilibrium of oil demand after the economic crisis. In the short-run, the sensitivity of crude oil demand to price and income changes has moved in the same direction as the long-run case. Korea, depending too much on foreign crude oil, is vulnerable to the shocks of oil prices, so rising oil prices can certainly have a negative impact on Korea's trade balance. And the elasticity of long-run oil prices may help to control and manage Korea's oil demand. The government needs to strengthen monitoring of the country's policies and market trends related to crude oil, establish strategies to customize national policies and market conditions, and strengthen active market dominance efforts through pioneering new market and diversification.
The GloSea5 (Global Seasonal forecasting system version 5) is provided and operated by the KMA (Korea Meteorological Administration). GloSea5 provides Forecast (FCST) and Hindcast (HCST) data and its horizontal resolution is about 60km ($0.83^{\circ}{\times}0.56^{\circ}$) in the mid-latitudes. In order to use this data in watershed-scale water management, GloSea5 needs spatial-temporal downscaling. As such, statistical downscaling was used to correct for systematic biases of variables and to improve data reliability. HCST data is provided in ensemble format, and the highest statistical correlation ($R^2=0.60$, RMSE = 88.92, NSE = 0.57) of ensemble precipitation was reported for the Yongdam Dam watershed on the #6 grid. Additionally, the original GloSea5 (600.1 mm) showed the greatest difference (-26.5%) compared to observations (816.1 mm) during the summer flood season. However, downscaled GloSea5 was shown to have only a -3.1% error rate. Most of the underestimated results corresponded to precipitation levels during the flood season and the downscaled GloSea5 showed important results of restoration in precipitation levels. Per the analysis results of spatial autocorrelation using seasonal Moran's I, the spatial distribution was shown to be statistically significant. These results can improve the uncertainty of original GloSea5 and substantiate its spatial-temporal accuracy and validity. The spatial-temporal reproducibility assessment will play a very important role as basic data for watershed-scale water management.
Journal of the Korea Academia-Industrial cooperation Society
/
v.18
no.8
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pp.181-189
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2017
This study examines whether the variables used in the Unified Theory of Acceptance and Use of Technology(performance expectancy, effort expectancy, social influence, and facilitating conditions) is applicable to continuous usage of uTradeHub at a time of expansion in the use of uTradeHub. In addition, the role of user satisfaction(mediating effect) and CEO support(interaction effect) in the relationship is identified attempting to provide basic data to help uTradeHub management strategy establishment. A total of 101 valid responses collected through questionnaires were used for empirical analysis(using SPSS 24.0), and the results are as follows. First, for the effect of the integration technology acceptance factor on user satisfaction(H1), only performance expectancy, effort expectancy, and social influence were significant, but facilitating conditions was not significant. Second, for the effect of user satisfaction on the continued use of uTradeHub(H2), there was a significant result. Third, the mediation effect on verification of user satisfaction(H3) was full where performance expectancy, effort expectancy, and social influence prompted continuous usage through user satisfaction. Fourth, for interactive effect verification of CEO support(H4), an interaction effect was shown only in the influence relationship of performance expectancy and social influence on user satisfaction.
Journal of the Korean Society of Environmental Restoration Technology
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v.21
no.6
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pp.95-113
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2018
We studied the change of wetland vegetation structure to understand ecological restoration process of wetlands through the field survey of ecological restoration projects in Incheon, Iksan and Busan. We compared the vegetation plan at the time of planted with the results of the vegetation monitoring in 2018, and analyzed the changes in wetland vegetation structure. Based on results, we attempted to understand the restoration process of those wetlands and discuss the management measures for sustainable wetland restoration. As a result, in the Incheon Yeonhee restoration wetland, the number of plant species was increased, from 18 species in 2016 to 29 in 2018. The dominant species, Myriophyllum verticillatum, covered the wetland most and its occupied area was increased. On the other hand, the distribution area of the planted emergent hydrophytes was reduced. The area of open water decreased from 71.7% in 2016 to 48.8% in 2018. In Busan Igidae restoration wetland, the number of plant species was increased, from 6 species in 2014 to 31 in 2018. The dominant species was Myriophyllum verticillatum and its occupied area was increased. The area of floating plant communities that planned has decreased. The open water area decreased from 83.9% in 2014 to 31.8% in 2018. In Iksan Sorasan restoration wetland, the number of plant species was increased, from 13 species in 2016 to 36 in 2018. The dominant species was Phragmites communis Trin. and its occupied area was increased. The other planted species showed a tendency to be decreased by Phragmites communis Trin. and its terrestrialization. The open water area decreased from 86.6% in 2016 to 6.7% in 2018. These results suggest that wetlands should be managed by considering the change of vegetation structure and open water areas based on the following succession process, because it affects the habitat suitability of wetland organisms and biodiversity as well. Thus, the continuous monitoring for the ecological structure of restored wetland is important, and it could be possible step to develop sustainable wetland ecological restoration model.
Purpose: With the rapid changes in the technical development and the trend of consumption trend, the convenience store industry is facing an unprecedented competitive situation in the consumption environment where the boundary between online and offline is broken due to the stagnation of offline distribution channels and the spread of online shopping. The biggest innovation strategy of the major convenience store brands in recent years are introducing the O2O (Online to Offline) platform and presenting new products and services beyond the boundaries of online and offline to transform themselves into Omni Channel stores. The study is designed to analyze the effect of innovativeness of convenience store as a stimulus in O2O platform which customers perceive on store loyalty, the final response to external stimuli, through customer engagement with convenience store brands. Specifically, the innovativeness of convenience stores was divided into types of core activities in corporate marketing and focused on innovations in services, products(proposals), promotions and experiences. Research design, data, and methodology: Various hypotheses have been developed to achieve this research purpose. The data were collected from 1,128 questionnaires the age between 15 and 60 who had experience using retail store apps and delivery apps and were analyzed using SPSS 22.0 and SmartPLS 3.3.7 program. Measurement model analysis was carried out to assess convergent and discriminant validity. Also, common method bias was tested using the values of VIF (variance inflation factor). The hypotheses were tested using structural equation modeling with SmartPLS 3.3.7 program. Results: First, service innovation has a positive effect on cognitive engagement. Second, product, promotion and experience innovation have a positive effect on cognitive and affective engagement. Third, cognitive influences affective engagement. Finally, both cognitive and affective engagement affect store loyalty, but affective engagement has a stronger effect on store loyalty than cognitive engagement. Conclusions: All four types of innovation and cognitive engagement have a positive effect on emotional engagement, which has a stronger effect on store loyalty than cognitive engagement. Thus, while innovation can build loyalty through emotional engagement, innovation strategies must be designed and pursued with caution in terms of impact through cognitive engagement may not achieve the planned goals.
The disconnection and fragmentation of ecological spaces that occur during the development process pose a significant threat to biodiversity. Urban center areas with high development pressure are particularly susceptible to low connectivity due to a scarcity of ecological space. This issue tends to be more pronounced in larger cities.To address this challenge, continuous efforts are needed to assess and improve the current state of ecological space connectivity at the level of individual projects and urban management. However, there is a lack of discussion regarding the analysis and improvement of ecological connectivity in metropolitan cities In line with this objective, this study evaluated the connectivity of ecological spaces in the city centers of Seoul, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan. The evaluation revealed that city centers exhibited lower connectivity of ecological spaces compared to their peripheries or the overall city. In addition, in the ecological network analysis that reflected regional characteristics, such as the species distribution model conducted on Daejeon, 510 optimal paths connecting forests of more than 1ha were derived. This study is significant as an example of deriving an ecological network based on regional characteristics, including quantitative figures necessary for establishing goals to improve urban ecological connectivity and biodiversity. It is anticipated that the results can be utilized to propose directions for enhancing ecological connectivity in environmental impact assessments or urban management and to establish an evaluation framework.
Conceptualization of store image have been suggested in the past by many marketing scholars. The dominant perspective about store image is treated as the results of a multi-attribute model. Store image is expressed as a function of the salient attributes of a particular store that are evaluated. Though, there is a little confusions about what elements compose the store image, most scholars agree that merchandise, service, atmosphere, physical facilities, comfort, and location are generally accepted elements as store image. A considerable researches support that shopping can provide both hedonic and utilitarian value. Hedonic shopping value reflects the value received from fantasy and emotive aspects of shopping experience, while utilitarian shopping value reflects the acquisition of products. These two types of shopping value can affect shopping satisfaction. This study examines the relationships among stores images(store atmosphere, salespeople services, facilities, product assortment, and store location), shopping values(utilitarian shopping value and hedonic shopping value), and shopping satisfaction based on discount stores (E-Mart, Home plus, and Lotte Mart). The author hypothesized that five store image components affect shopping values, and these shopping values affect shopping satisfaction. The author focused on the roles of perceived retail crowding between these relationships. Specifically, the author hypothesized that perceived retailing crowding moderated the relationship between shopping values and shopping satisfaction. The author also hypothesized the direct effect of perceived retail crowding on shopping satisfaction. Finally, the author hypothesized that five store image components affect directly shopping satisfaction. Research model is presented in
. To test model and hypotheses, data were collected from 114 consumers located mid-size city in local area. The author employs PLS methodology (SmartPLS 2.0) to test hypotheses. Data analysis results indicate that among five store images salespeople services, and store location affect utilitarian shopping value. Store atmosphere, salespeople services, and store location affect hedonic shopping value. Two shopping values affect shopping satisfaction. Hedonic shopping value affect more shopping satisfaction than utilitarian shopping value. Data analysis results is presented in
. The author examines the moderating effects of perceived retail crowding between shopping values and shopping satisfaction. Results indicate that there are no moderating effects between shopping values and shopping satisfaction. Moderating effects of perceived retail crowding between utilitarian shopping value and shopping satisfaction are presented in
. Moderating effects of perceived retail crowding between hedonic shopping value and shopping satisfaction is presented in . The author examines the direct effect of perceived retail crowding on shopping satisfaction. Results are presented in
. The author analyzed the relationship between perceived retail crowding and shopping satisfaction using WarpPLS 3.0 which can analyze the non-linear relationship. Result indicates that perceived retail crowding affects directly shopping satisfaction and there is a non-linear relationship between them. Among five store image components, store atmosphere and salespeople services affect directly shopping satisfaction. The author describes about the managerial implications, limitations, and future research issues.
This study was conducted to provide basic data for habitat management and preservation of Jeongmaek. A total of 18 priority research areas were selected with consideration to terrain and habitat environment, and 54 fixed plots were selected for three types of habits: development, valley, and forest road and ridge. The survey was conducted in each season (May, August, and October), excluding the winter season, from 2016 to 2018. The distribution analysis of birds observed in each habitat type using a self-organizing map (SOM) classified them into a total of four groups (MRPP, A=0.12, and p <0.005). The comparative analysis of the number of species, the number of individuals, and the species diversity index for each SOM group showed that they were all the highest in group III (Kruskal-Wallis, the number species: x2 = 13.436, P <0.005; the number of individuals: x2 = 8.229, P <0.05; the species diversity index: x2 = 17.115, P <0.005). Moreover, the analysis by applying the land cover map to the random forest model to examine the index species of each group and identify the characteristics of the habitat environment showed a difference in the ratio of the habitat environment and the indicator species among the four groups. The index species analysis identified a total of 18 bird species as the indicator species in three groups except for group II. When applying the random forest model and indicator species analysis to the results of classification into four groups using the SOM, the composition of the indicator species by the group showed a correlation with the habitat characteristics of each group. Moreover, the distribution patterns and densities of observed species were clearly distinguished according to the dominant habitat for each group. The results of the analysis that applied the SOM, indicator species, and random forest model together can derive useful results for the characterization of bird habitats according to the habitat environment.
Recently, numerous documents have been made available electronically. Internet search engines and digital libraries commonly return query results containing hundreds or even thousands of documents. In this situation, it is virtually impossible for users to examine complete documents to determine whether they might be useful for them. For this reason, some on-line documents are accompanied by a list of keywords specified by the authors in an effort to guide the users by facilitating the filtering process. In this way, a set of keywords is often considered a condensed version of the whole document and therefore plays an important role for document retrieval, Web page retrieval, document clustering, summarization, text mining, and so on. Since many academic journals ask the authors to provide a list of five or six keywords on the first page of an article, keywords are most familiar in the context of journal articles. However, many other types of documents could not benefit from the use of keywords, including Web pages, email messages, news reports, magazine articles, and business papers. Although the potential benefit is large, the implementation itself is the obstacle; manually assigning keywords to all documents is a daunting task, or even impractical in that it is extremely tedious and time-consuming requiring a certain level of domain knowledge. Therefore, it is highly desirable to automate the keyword generation process. There are mainly two approaches to achieving this aim: keyword assignment approach and keyword extraction approach. Both approaches use machine learning methods and require, for training purposes, a set of documents with keywords already attached. In the former approach, there is a given set of vocabulary, and the aim is to match them to the texts. In other words, the keywords assignment approach seeks to select the words from a controlled vocabulary that best describes a document. Although this approach is domain dependent and is not easy to transfer and expand, it can generate implicit keywords that do not appear in a document. On the other hand, in the latter approach, the aim is to extract keywords with respect to their relevance in the text without prior vocabulary. In this approach, automatic keyword generation is treated as a classification task, and keywords are commonly extracted based on supervised learning techniques. Thus, keyword extraction algorithms classify candidate keywords in a document into positive or negative examples. Several systems such as Extractor and Kea were developed using keyword extraction approach. Most indicative words in a document are selected as keywords for that document and as a result, keywords extraction is limited to terms that appear in the document. Therefore, keywords extraction cannot generate implicit keywords that are not included in a document. According to the experiment results of Turney, about 64% to 90% of keywords assigned by the authors can be found in the full text of an article. Inversely, it also means that 10% to 36% of the keywords assigned by the authors do not appear in the article, which cannot be generated through keyword extraction algorithms. Our preliminary experiment result also shows that 37% of keywords assigned by the authors are not included in the full text. This is the reason why we have decided to adopt the keyword assignment approach. In this paper, we propose a new approach for automatic keyword assignment namely IVSM(Inverse Vector Space Model). The model is based on a vector space model. which is a conventional information retrieval model that represents documents and queries by vectors in a multidimensional space. IVSM generates an appropriate keyword set for a specific document by measuring the distance between the document and the keyword sets. The keyword assignment process of IVSM is as follows: (1) calculating the vector length of each keyword set based on each keyword weight; (2) preprocessing and parsing a target document that does not have keywords; (3) calculating the vector length of the target document based on the term frequency; (4) measuring the cosine similarity between each keyword set and the target document; and (5) generating keywords that have high similarity scores. Two keyword generation systems were implemented applying IVSM: IVSM system for Web-based community service and stand-alone IVSM system. Firstly, the IVSM system is implemented in a community service for sharing knowledge and opinions on current trends such as fashion, movies, social problems, and health information. The stand-alone IVSM system is dedicated to generating keywords for academic papers, and, indeed, it has been tested through a number of academic papers including those published by the Korean Association of Shipping and Logistics, the Korea Research Academy of Distribution Information, the Korea Logistics Society, the Korea Logistics Research Association, and the Korea Port Economic Association. We measured the performance of IVSM by the number of matches between the IVSM-generated keywords and the author-assigned keywords. According to our experiment, the precisions of IVSM applied to Web-based community service and academic journals were 0.75 and 0.71, respectively. The performance of both systems is much better than that of baseline systems that generate keywords based on simple probability. Also, IVSM shows comparable performance to Extractor that is a representative system of keyword extraction approach developed by Turney. As electronic documents increase, we expect that IVSM proposed in this paper can be applied to many electronic documents in Web-based community and digital library.
To assess environmental contamination with carcinogens, carbonaceous compounds, water-soluble ionic species and trace gaseous species were identified and quantified every three hours for three days st three different atmospheric layer at the heart of chiang-Mai, bangkok and hat-Yai from December 2006 to February 2007. A DRI model 2001 Themal/Optical Carbon Analyzer with the IMPROVE thermal/optical reflectance (TOR) protocol was used to quantify the organic carbon(OC) and elemental carbon content in $PM_{10}$. Diurnal and vertical variability was also carefully investigated. In general, OC and EC contenttration shoeed the highest values at the monitoring period o 21.00-00.00 as consequences of human activities at night bazaar coupled with reduction of mixing layer, decreased wind speed and termination of photolysis nighttime. Morning peaks of carboaceous compounds were observed during the sampling period of 06:00 -09:00, emphasizing the main contribution of traffic emission in the three cities. The estimation of incremental lifetime partculate matter exposure (ILPE) raises concern of high risk of carbonaceous accumulation over workers and residents living close to the observatory sites. The average values of incremental lifrtime particulate matter exposure (ILPE) of total carbon at Baiyoke Suit Hotel and Baiyoke Sky Hotel are approsimately ten time shigher then those air sample collected at prince of songkla University Hat-Yai campus corpse incinerator and fish-can maufacturing factory but only slightly higher than those of rice straw burnig in Songkla province. This indicates a high risk of developing lung cancer and other respiratory diseases across workers and residents living in high buildings located in Pratunam area. Using knowledge of carbonaceous fractions in $PM_{10}$, one can estimate the gas-particle partitioning of polycyclic aromatic hydrocarbons (PAHs). Dachs-Eisenreich model highlights the crucial role of adsorption in gas-particle partitioning of low molecular weight PAHs, whereas both absorption and adsorption tend to account for gas-particle partitioning of high molecular weight PAHs in urban residential zones of Thailand. Interestingly, the absorption mode alone plays a minor role in gas-partcle partitiining of PAHs in Chiang-Mai, Bangkok and hat-Yai.
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