• Journal of Distribution Research
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• v.17 no.2
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• pp.93-115
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• 2012

This study empirically examines the impact of changes in market shares among retailing types on the price index. The retailing type is classified into 6 groups: department store, big mart, super market, convenient store, specialty merchant, and on-line store. The market shares of retailing types are calculated by the ratio of each retailing type monthly sales to total monthly retailing sales in which total retailing sales is the sum of each retailing type sales. We employed several price indices: consumer price index (CPI), CPI for living necessaries, and fresh food price index. In addition, this study used fundamental price indices based on 25 product families as well as 42 representative products. The empirical model also included several variables in order to control for the macroeconomic effects and those variables are the exchange rate, M1, an oil price, and the industrial production index. The data is monthly time-series data spanning over the period from January 2000 to December 2010. In order to test for the stability of data series, we conducted ADF test and PP test in which the model and length of lag were determined by the relevant previous literature and based on the AIC. The empirical results indicate that changes in market shares among retailing types have impacts on the price index. Table A shows that impacts differ as to which price index to use and which product families and products to use. For department store, it lowers the price of food and non-alcoholic beverages, home appliances, fresh food, fresh and vegetables, but it keeps the price high for fresh fruit. The big mart retailing type has a positive impact on the price of food, nut has a negative effect on clothing and foot wear, non-food, and fresh fruit. For super market, it has a positive impact on food and non-alcoholic beverages, fresh food, fresh shellfishes, but increases the price of CPI for living necessaries and non-food. The specialty merchant retailing type increases the price level of CPI for living necessaries and fresh fruit. For on-line store type, it keeps the price high for CPI for living necessaries and non-food as well as fresh fruit. For the analysis based on 25 product families shows that changes in market shares among retailing types also have different effects on the price index. Table B summarizes the different results. The 42 representative product level analysis is summerized in Table C and it indicates that changes in market shares among retailing types have different effects on the price index. The study offers the theoretical and practical implication to these findings and also suggests the direction for the further analysis.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.27 no.4
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• pp.404-412
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• 1994

Radium isotopes were measured together with oceanographical parameters in the southern coastal region of the Korean East Sea during the period of September $2{\sim}8$, 1991. In September, there were various water masses vertically distributed in this region due to formation of strongly seasonal thermoclines. These water masses were characterized by activity of radium isotopes as well as water temperature and dissolved oxygen. Among the water masses, Japan Sea Proper Water(JSPW) below $1^{\circ}C$ had the highest Ra-226 activities but the lowest Ra-228 concentrations. However, Tsushima Surface Water (TSW) above $20^{\circ}C$ in water temperature had the highest Ra-228 which decreased sharply with depth. In TSW, Ra-228 activities were in the range of $194{\sim}270$ dpm/kl, which were approximately 10 times higher than JSPW. Activity ratios(A.R's) of Ra-228/Ra-226 were $1.9{\sim}2.6$ for TSW, $0.7{\sim}1.1$ for Tsushima Middle Water(TMW) of $12{\sim}17^{\circ}C\;to\;0.4{\sim}0.7$ for North Korea Cold Water(NKCW) with $1{\sim}7^{\circ}C$ and below 0.2 for JSPW. The Ra-228/Ra-226 ranged from 0.6 to 0.9 in the cold waters of $2{\sim}6^{\circ}C$, which were observed at depth of $65{\sim}120\;m$ in this study area. Radium isotopes provided a useful means of identifying origins of the cold water which occurred annually at intermediate or bottom layers in the southern coastal zone of the Korean East Sea. By plotting radium isotopes against water temperature, it could be observed clearly that the cold waters between $2{\sim}6^{\circ}C$ did not originate from the mixed water of JSPW and TMW but from NKCW.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.35 no.1
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• pp.35-45
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• 2002

Seasonal quantitative van Veen grab sampling was conducted to characterize the composition and structure of the benthic polychaete community inhabiting the shellfish farming ground of a coastal bay system of Jiniu Bay (Korea). A total of 132 polychaete species were identified and the polychaetes accounted for about $80\%$ of overall abundance of benthic animals. There was little significant seasonal difference in densities (abundances) of polychaetes, Maximum biomass was obseued in summer (August) and minimum value was recorded in winter (February) and spring (May). Conversely, diversity and richness were lowest in summer, indicating a seasonal variability in the polychaetous community structure, The cluster analysis indicated that such a seasonal variability resulted mainly from the appearance of a few small, r-selected opportunists in spring and the tubiculous species of the family Maldanidae in summer. On the other hand, several indicator species for the organically enriched environments such as Capitelia capitata, Notoniashs Jatericeus and hmbrineris sp. showed high densities during all the study period. Density and biomass of univariate measures of community structure were significantly lower in the arkshell-farming ground of the southern area than in the non-farming sites of the bay, A similar general tendency was also found in the spatial distributions of species diversity and richness. Principal component analysis revealed the existence of different groups of benthic assemblages between the arkshell-farming ground and non-farming sites, The lack of colonization of r-selected opportunists and/or tubiculous species in the former ground seemed to contribute to the spatial differences in the composition and structure of the polychaetous communities. Although finer granulometric composition and high sulfide concentration in sediments of the arkshell-farming ground and low salinity in the northern area were likely to account for parts of the differences, other environmental variables observed were unlikely. The spatial distribution of polychaetes in Jiniu Bay may be rather closely related to the sedimentary disturbance by selection of shells for harvesting in spring.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.131-142
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• 2011

In recent years, Social Network Service, which is defined as a web-based service that allows an individual to construct a public or a semi-public profile within a bounded system, articulates a list of other users with whom they share connections, and traverses their list of connections. For example, Facebook and Twitter are the representative sites of Social Network Service, and these sites are the big issue in the world. A lot of people use Social Network Services to connect and maintain social relationship. Recently the users of Social Network Services have increased dramatically. Accordingly, many organizations become interested in Social Network Services as means of marketing, media, communication with their customers, and so on, because social network services can offer a variety of benefits to organizations such as companies and associations. In other words, organizations can use Social Network Services to respond rapidly to various user's behaviors because Social Network Services can make it possible to communicate between the users more easily and faster. And marketing cost of the Social Network Service is lower than that of existing tools such as broadcasts, news papers, and direct mails. In addition, Social network Services are growing in market place. So, the organizations such as companies and associations can acquire potential customers for the future. However, organizations uniformly communicate with users through Social Network Service without consideration of the characteristics of the networks although networks have different effects on information deliveries. For example, members' cohesion in an offline communication is higher than that in an online communication because the members of the offline communication are very close. that is, the network of the offline communication has a strong tie. Accordingly, information delivery is fast in the network of the offline communication. In this study, we compose two networks which have different characteristic of communication in Twitter. First network is constructed with data based on an offline communication such as friend, family, senior and junior in school. Second network is constructed with randomly selected data from users who want to associate with friends in online. Each network size is 250 people who divide with three groups. The first group is an ego which means a person in the center of the network. The second group is the ego's followers. The last group is composed of the ego's follower's followers. We compare the networks through social network analysis and follower's reaction analysis. We investigate density and centrality to analyze the characteristic of each network. And we analyze the follower's reactions such as replies and retweets to find differences of information delivery in each network. Our experiment results indicate that density and centrality of the offline communicationbased network are higher than those of the online-based network. Also the number of replies are larger than that of retweets in the offline communication-based network. On the other hand, the number of retweets are larger than that of replies in the online based network. We identified that the effect of information delivery in the offline communication-based network was different from those in the online communication-based network through experiments. So, you configure the appropriate network types considering the characteristics of the network if you want to use social network as an effective marketing tool.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.203-219
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• 2011

Previously common users just want to watch the video contents without any specific requirements or purposes. However, in today's life while watching video user attempts to know and discover more about things that appear on the video. Therefore, the requirements for finding multimedia or browsing information of objects that users want, are spreading with the increasing use of multimedia such as videos which are not only available on the internet-capable devices such as computers but also on smart TV and smart phone. In order to meet the users. requirements, labor-intensive annotation of objects in video contents is inevitable. For this reason, many researchers have actively studied about methods of annotating the object that appear on the video. In keyword-based annotation related information of the object that appeared on the video content is immediately added and annotation data including all related information about the object must be individually managed. Users will have to directly input all related information to the object. Consequently, when a user browses for information that related to the object, user can only find and get limited resources that solely exists in annotated data. Also, in order to place annotation for objects user's huge workload is required. To cope with reducing user's workload and to minimize the work involved in annotation, in existing object-based annotation automatic annotation is being attempted using computer vision techniques like object detection, recognition and tracking. By using such computer vision techniques a wide variety of objects that appears on the video content must be all detected and recognized. But until now it is still a problem facing some difficulties which have to deal with automated annotation. To overcome these difficulties, we propose a system which consists of two modules. The first module is the annotation module that enables many annotators to collaboratively annotate the objects in the video content in order to access the semantic data using Linked Data. Annotation data managed by annotation server is represented using ontology so that the information can easily be shared and extended. Since annotation data does not include all the relevant information of the object, existing objects in Linked Data and objects that appear in the video content simply connect with each other to get all the related information of the object. In other words, annotation data which contains only URI and metadata like position, time and size are stored on the annotation sever. So when user needs other related information about the object, all of that information is retrieved from Linked Data through its relevant URI. The second module enables viewers to browse interesting information about the object using annotation data which is collaboratively generated by many users while watching video. With this system, through simple user interaction the query is automatically generated and all the related information is retrieved from Linked Data and finally all the additional information of the object is offered to the user. With this study, in the future of Semantic Web environment our proposed system is expected to establish a better video content service environment by offering users relevant information about the objects that appear on the screen of any internet-capable devices such as PC, smart TV or smart phone.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.53-74
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• 2018

Since South Korea has an economic structure that has a characteristic which market-dependent on overseas, the tourism industry is considered as a very important industry for the national economy, such as improving the country's balance of payments or providing income and employment increases. Accordingly, the necessity of more accurate forecasting on the demand in the tourism industry has been raised to promote its industry. In the related research, economic variables such as exchange rate and income have been used as variables influencing tourism demand. As information technology has been widely used, some researchers have also analyzed the effect of media on tourism demand. It has shown that the media has a considerable influence on traveler's decision making, such as choosing an outbound destination. Furthermore, with the recent availability of online information searches to obtain the latest information and two-way communication in social media, it is possible to obtain up-to-date information on travel more quickly than before. The information in online media such as blogs can naturally create the Word-of-Mouth effect by sharing useful information, which is called eWOM. Like all other service industries, the tourism industry is characterized by difficulty in evaluating its values before it is experienced directly. And furthermore, most of the travelers tend to search for more information in advance from various sources to reduce the perceived risk to the destination, so they can also be influenced by online media such as online news. In this study, we suggested that the number of online media posting, which causes the effects of Word-of-Mouth, may have an effect on the number of outbound travelers. We divided online media into public media and private media according to their characteristics and selected online news as public media and blog as private media, one of the most popular social media in tourist information. Based on the previous studies about the eWOM effects on online news and blog, we analyzed a relationship between the volume of eWOM and the outbound tourism demand through the panel model. To this end, we collected data on the number of national outbound travelers from 2007 to 2015 provided by the Korea Tourism Organization. According to statistics, the highest number of outbound tourism demand in Korea are China, Japan, Thailand, Hong Kong and the Philippines, which are selected as a dependent variable in this study. In order to measure the volume of eWOM, we collected online news and blog postings for the same period as the number of outbound travelers in Naver, which is the largest portal site in South Korea. In this study, a panel model was established to analyze the effect of online media on the demand of Korean outbound travelers and to identify that there was a significant difference in the influence of online media by each time and countries. The results of this study can be summarized as follows. First, the impact of the online news and blog eWOM on the number of outbound travelers was significant. We found that the number of online news and blog posting have an influence on the number of outbound travelers, especially the experimental result suggests that both the month that includes the departure date and the three months before the departure were found to have an effect. It is shown that online news and blog are online media that have a significant influence on outbound tourism demand. Next, we found that the increased volume of eWOM in online news has a negative effect on departure, while the increase in a blog has a positive effect. The result with the country-specific models would be the same. This paper shows that online media can be used as a new variable in tourism demand by examining the influence of the eWOM effect of the online media. Also, we found that both social media and news media have an important role in predicting and managing the Korean tourism demand and that the influence of those two media appears different depending on the country.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.4
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• pp.377-392
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• 2017

A set of BFM (Brute Force Method) simulations with the CMAQ (Community Multiscale Air Quality) model were conducted in order to estimate self-contributions and conversion rates of PPM (Primary $PM_{2.5}$), $NO_x$, $SO_2$, $NH_3$, and VOC emissions to $PM_{2.5}$ concentrations over the SMA (Seoul Metropolitan Area). CAPSS (Clean Air Policy Support System) 2013 EI (emissions inventory) from the NIER (National Institute of Environmental Research) was used for the base and sensitivity simulations. SCCs (Source Classification Codes) in the EI were utilized to group the emissions into area, mobile, and point source categories. PPM and $PM_{2.5}$ precursor emissions from each source category were reduced by 50%. In turn, air quality was simulated with CMAQ during January, April, July, and October in 2014 for the BFM runs. In this study, seasonal variations of SMA $PM_{2.5}$ self-sensitivities to PPM, $SO_2$, and $NH_3$ emissions can be observed even when the seasonal emission rates are almost identical. For example, when the mobile PPM emissions from the SMA were 634 TPM (Tons Per Month) and 603 TPM in January and July, self-contributions of the emissions to monthly mean $PM_{2.5}$ were $2.7{\mu}g/m^3$ and $1.3{\mu}g/m^3$ for the months, respectively. Similarly, while $NH_3$ emissions from area sources were 4,169 TPM and 3,951 TPM in January and July, the self-contributions to monthly mean $PM_{2.5}$ for the months were $2.0{\mu}g/m^3$ and $4.4{\mu}g/m^3$, respectively. Meanwhile, emission-to-$PM_{2.5}$ conversion rates of precursors vary among source categories. For instance, the annual mean conversion rates of the SMA mobile, area, and point sources were 19.3, 10.8, and $6.6{\mu}g/m^3/10^6TPY$ for $SO_2$ emissions while those rates for PPM emissions were 268.6, 207.7, and 181.5 (${\mu}g/m^3/10^6TPY$), respectively, over the region. The results demonstrate that SMA $PM_{2.5}$ responses to the same amount of reduction in precursor emissions differ for source categories and in time (e.g. seasons), which is important when the cost-benefit analysis is conducted during air quality improvement planning. On the other hand, annual mean $PM_{2.5}$ sensitivities to the SMA $NO_x$ emissions remains still negative even after a 50% reduction in emission category which implies that more aggressive $NO_x$ reductions are required for the SMA to overcome '$NO_x$ disbenefit' under the base condition.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.10
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• pp.1058-1064
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• 2005

This research was designed to investigate the removal of anionic species, such as $F^-$, $Cl^-$ and ${NO_3}^-$, by adsorption on the clay minerals. Bentonite, $Ca^{2+}$ or $Na^+$ ion exchanged bentonite and montmorillonite, such as KSF and K10 from Sigma Aldrich, were used as the adsorbent. The component of five inorganic adsorbent was analyzed by XRF and XRD and the concentration of anion was measured by ion chromatography. From the experimental results, it was shown that the adsorption equilibrium was attained after 8-24 hours. For the amount of 6 g of each adsorbent, the adsorption capacities of $F^-$ and ${NO_3}^-$ on KSF was the largest as $825\;{\mu}g/g$ and $707\;{\mu}g/g$ respectively and that of $F^-$ on $Ca^{2+}$ ion exchanged bentonite was $255\;{\mu}g/g$ and that of ${NO_3}^-$ on K10 was $103\;{\mu}g/g$. In general, the efficiency of removal for the anionic species was increased with increasing of the amount of the adsorbent. Especially, for the amount of 6 g of KSF, the efficiency of removal for $F^-$ and ${NO_3}^-$ was 99% and 95% respectively. But, for all adsorbents, the efficiency of removal for $Cl^-$ was less than 9%. Also, a Freundlich equation was used to fit the acquired experimental data. As the result, for the $F^-$ and ${NO_3}^-$ on KSF, Freundlich constants, K, was respectively 1.09 and $0.45\;[mg/g][L/mg]^{1/n}$ and the adsorption intensity(1/n) was determined to be 0.08 and 0.27 respectively.

• Journal of Nutrition and Health
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• v.42 no.8
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• pp.682-690
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• 2009

The purpose of this study is to analyse the relation between dietary habit and nutrition knowledge, and ADHD (Attention Deficit Hyperactivity Disorder) in the middle school students in Seoul, Korea. Total study subjects were 631 students, 51.8% was male and 48.2% was female. In the assessment of predisposition of ADHD, 93% was normal group and 7% was ADHD group. As for the gender in ADHD group, 56.8% was male and 43.2% was female. Normal group showed the higher breakfast consumption rate than ADHD group (p < 0.05). Dietary habits were better in normal group than ADHD group. Nutrition knowledge scores of normal group was 7.38 out of 15 and scores of ADHD group was 5.77 out of 15 (p < 0.01). The nutrition knowledge score and the dietary habits score showed a positive correlation (p < 0.01). The nutrition knowledge score and snack meal purchasing frequency showed a negative correlation (p < 0.05). There are significant negative correlation between attention deficit hyperactivity score and nutrition knowledge score (p < 0.01). In conclusion, ADHD group showed lower level of nutrition knowledge and worse dietary habits than the normal group.