• Asia pacific journal of information systems
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• v.24 no.4
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• pp.577-610
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• 2014

Although service innovation is not a new concept, innovation research in general tends to focus on technological innovation by manufacturing firms. With this view, innovation studies focus on product(e.g., goods) and process(e.g., product systems) innovation, ignoring service innovation and its inherent opportunities. Since major economy has been transformed to service economy, service innovation is considered a new effective way to sustain and gain a competitive advantage. Service innovation is no longer regarded merely as a side activity to product innovation; it has become a main research topic in its own right, accompanied by an increasing focus on services. While the number of service innovation studies has increased dramatically in the past 30 years in international research, few studies have been performed in domestic studies because domestic service innovation research began from the middle of 2000. In addition, there are no comprehensive literature reviews describing the evolution of service innovation research in both international and domestic studies because of the heterogeneities of service industry and multidiscipline characteristics of service innovation studies. To bridge this research gap, the purpose of this paper is to perform an extensive literature review and synthesis to enable a critical review of extant research on service innovation and trace its evolution, which will establish a foundation for further studies. By reviewing 169 articles (136 international papers; 33 domestic papers) published between 2000 and 2014 (in past 15 years), primarily in leading service, innovation and management information systems journals, this study analyzes the progression of service innovation research according to the four aspects such as number of studies, topics, methodologies and target industries. Overall, the view of service innovation has evolved, from a complement of traditional product innovation to a multidimensional, all-encompassing concept that entails several functions, both within and outside the firms. The results showed that domestic research still stays at the formation phase of service innovation studies although international research is in the maturity or multidimensional phase. We found increasing recent activities pertaining to service innovation, resulting from the increasing interest in services innovation across various industries and the links of new topics to the service innovation concept in both international and domestic studies. However, the main focus of service innovation research showed a different propensity between international and domestic studies: the former mainly focuses on a much more diversified pattern, emphasizing the linkages between service innovation and business strategy while the latter mainly focuses on the service innovation process(system) and service design. In addition, there are many case studies in domestic studies while many empirical studies in international studies. Domestic studies should increases the understanding of the interplay between service innovation and product innovation within manufacturing firms. Furthermore, rather than focusing on intrinsic distinctions between service innovation and product innovation, researchers should strive to develop and conceptualize service innovation in domestics studies. The present research also provides useful implications for practitioners. First, this study contributes to expand the current understanding of service innovation research by performing an extensive literature review. Second, tracing and comparing the progression and trends of service innovation research between international and domestic studies, this study showed the similarities and differences between them, which provide practical guidance on future research directions and research agenda. Third, this study performed literature review establishing the analysis system in the initial stage and using them to analyze articles, which is leading to explain the research review of service innovation more systematically and objectively. Finally, this study suggests the domestic researchers their future interests and topics of service innovation research.

• Journal of Wetlands Research
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• v.6 no.3
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• pp.71-81
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• 2004

In recent, the heavy rainfall is frequently occurred and the damage tends to be increased. So, more careful hydrologic analysis is required for the designs of the hydraulic or disaster prevention structures. The time distribution of a rainfall is one of the important factors for the estimation of peak flow in hydrologic and hydraulic designs. This study is to suggest a methodology for the estimation of a rainfall time distribution which can reflect the meteorologic and topographical characteristics of Daejeon area. We collect the 34 years' rainfall data recorded in the range of 1969 to 2002 for Daejeon area and we performed the rainfall analysis with the data in between May and October of each year. According to the Huff method, the collected data corresponds to the first quartile which the rainfall is concentrated in the primary stage but the suggested method shows the different rainfall distribution with the Huff method in time. The reason is that the Huff method determines the quartile in each storm event while the suggested one determines it by estimating the dimensionless distribution of rainfall in duration after the accumulation of rainfall in time. The rainfall distributions estimated by two methodologies were applied to the Gabcheon basin in Daejeon area for the estimation of flood flow. Here we use the SCS method for the effective rainfall and unit hydrograph for the flood discharge. As the results, the peak flow for 24-hour of 100-year frequency was estimated as a $3421.20m^3/sec$ by the Huff method and $3493.38m^3/sec$ by the suggested one. We can see the difference of $72.18m^3/sec$ in between two methods and thus we may carefully determine the rainfall time distribution and compute the effective rainfall for the estimation of the peak flow.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.93-102
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• 2005

An Origin-Destination (O/D) is considered as one of the important information in route choices and trip assignments. A household interview survey is deemed to be the traditional and the most widely used method in making sample O/D and its conversion to the total O/D. Some researchers have studied to estimate dynamic O/D from the relationship between link volumes and trip assignment model. Nowadays, owing to the recent rapid spread of cellular phones. Location information of the cellular phone through the Base Station(BS) is considered as an alternative to O/D estimation. In this study, the methodology of generating BS-based O/D and the methodology of converting this O/D into an administrative district-based O/D are proposed. The information of GPS positions and cellular BS positions have acquired by establishing GPS equipment and cellular phone on taxies in Cheongju. Three weeks data are collected and used in estimating O/D by matching them on a digital map. Scatter diagram and sample correlation coefficients are used to investigate the similarity of the GPS-based O/D pattern among weeks, among days, and among times in day. The results show that there are few significant differences among weeks. But there is a difference in O/C pattern between weekday and weekend. Furthermore, there is a difference between morning peak and afternoon peak. Two methodologies are proposed to convert BS-based O/D into an administrative district-based O/D. The first one is to use the distribution pattern of GPS coordinates, the other is to use the coverage area of the BSs. To validate such converted O/D, GPS O/D is used as a true value. The statical analyses through scatter diagram, MAE and RMSE shows that there is few significant defference of pattern between the estimated BS-based O/D and GPS O/D. In the case of using only cellular information, the methodology using coverage area of the BSs is recommended for estimating O/D.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.171-183
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• 2012

In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

• Journal of Global Scholars of Marketing Science
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• v.17 no.2
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• pp.111-131
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• 2007

As a brand becomes a core asset in creating a corporation's value, brand marketing has become one of core strategies that corporations pursue. Recently, for customer relationship management, possession and consumption of goods were centered on brand for the management. Thus, management related to this matter was developed. The main reason of the increased interest on the relationship between the brand and the consumer is due to acquisition of individual consumers and development of relationship with those consumers. Along with the development of relationship, a corporation is able to establish long-term relationships. This has become a competitive advantage for the corporation. All of these processes became the strategic assets of corporations. The importance and the increase of interest of a brand have also become a big issue academically. Brand equity, brand extension, brand identity, brand relationship, and brand community are the results derived from the interest of a brand. More specifically, in marketing, the study of brands has been led to the study of factors related to building of powerful brands and the process of building the brand. Recently, studies concentrated primarily on the consumer-brand relationship. The reason is that brand loyalty can not explain the dynamic quality aspects of loyalty, the consumer-brand relationship building process, and especially interactions between the brands and the consumers. In the studies of consumer-brand relationship, a brand is not just limited to possession or consumption objectives, but rather conceptualized as partners. Most of the studies from the past concentrated on the results of qualitative analysis of consumer-brand relationship to show the depth and width of the performance of consumer-brand relationship. Studies in Korea have been the same. Recently, studies of consumer-brand relationship started to concentrate on quantitative analysis rather than qualitative analysis or even go further with quantitative analysis to show effecting factors of consumer-brand relationship. Studies of new quantitative approaches show the possibilities of using the results as a new concept of viewing consumer-brand relationship and possibilities of applying these new concepts on marketing. Studies of consumer-brand relationship with quantitative approach already exist, but none of them include sub-dimensions of consumer-brand relationship, which presents theoretical proofs for measurement. In other words, most studies add up or average out the sub-dimensions of consumer-brand relationship. However, to do these kind of studies, precondition of sub-dimensions being in identical constructs is necessary. Therefore, most of the studies from the past do not meet conditions of sub-dimensions being as one dimension construct. From this, we question the validity of past studies and their limits. The main purpose of this paper is to overcome the limits shown from the past studies by practical use of previous studies on sub-dimensions in a one-dimensional construct (Naver & Slater, 1990; Cronin & Taylor, 1992; Chang & Chen, 1998). In this study, two arbitrary groups were classified to evaluate reliability of the measurements and reliability analyses were pursued on each group. For convergent validity, correlations, Cronbach's, one-factor solution exploratory analysis were used. For discriminant validity correlation of consumer-brand relationship was compared with that of an involvement, which is a similar concept with consumer-based relationship. It also indicated dependent correlations by Cohen and Cohen (1975, p.35) and results showed that it was different constructs from 6 sub-dimensions of consumer-brand relationship. Through the results of studies mentioned above, we were able to finalize that sub-dimensions of consumer-brand relationship can viewed from one-dimensional constructs. This means that the one-dimensional construct of consumer-brand relationship can be viewed with reliability and validity. The result of this research is theoretically meaningful in that it assumes consumer-brand relationship in a one-dimensional construct and provides the basis of methodologies which are previously preformed. It is thought that this research also provides the possibility of new research on consumer-brand relationship in that it gives root to the fact that it is possible to manipulate one-dimensional constructs consisting of consumer-brand relationship. In the case of previous research on consumer-brand relationship, consumer-brand relationship is classified into several types on the basis of components consisting of consumer-brand relationship and a number of studies have been performed with priority given to the types. However, as we can possibly manipulate a one-dimensional construct through this research, it is expected that various studies which make the level or strength of consumer-brand relationship practical application of construct will be performed, and not research focused on separate types of consumer-brand relationship. Additionally, we have the theoretical basis of probability in which to manipulate the consumer-brand relationship with one-dimensional constructs. It is anticipated that studies using this construct, which is consumer-brand relationship, practical use of dependent variables, parameters, mediators, and so on, will be performed.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Journal of Distribution Science
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• v.8 no.4
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• pp.5-15
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• 2010

This study investigated research trends of JDS that KODISA published and gave implications to elevate quality of scholarly journals. In other words, the study classified scientific system of distribution area to investigate research trends and to compare it with other scholarly journals of distribution and to give implications for higher level of JDS. KODISA published JDS Vol.1 No.1 for the first time in 1999 followed by Vol.8 No.3 in September 2010 to show 109 theses in total. KODISA investigated subjects, research institutions, number of participants, methodology, frequency of theses in both the Korean language and English, frequency of participation of not only the Koreans but also foreigners and use of references, etc. And, the study investigated JDR of KODIA, JKDM(The Journal of Korean Distribution & Management) and JDA that researched distribution, so that it found out development ways. To investigate research trends of JDS that KODISA publishes, main category was made based on the national science and technology standard classification system of MEST (Ministry Of Education, Science And Technology), table of classification of research areas of NRF(National Research Foundation of Korea), research classification system of both KOREADIMA and KLRA(Korea Logistics Research Association) and distribution science and others that KODISA is looking for, and distribution economy area was divided into general distribution, distribution economy, distribution, distribution information and others, and distribution management was divided into distribution management, marketing, MD and purchasing, consumer behavior and others. The findings were as follow: Firstly, main category occupied 47 theses (43.1%) of distribution economy and 62 theses (56.9%) of distribution management among 109 theses in total. Active research area of distribution economy consisted of 14 theses (12.8%) of distribution information and 9 theses (8.3%) of distribution economy to research distribution as well as distribution information positively every year. The distribution management consisted of 25 theses (22.9%) of distribution management and 20 theses (18.3%) of marketing, These days, research on distribution management, marketing, distribution, distribution information and others is increasing. Secondly, researchers published theses as follow: 55 theses (50.5%) by professor by himself or herself, 12 theses (11.0%) of joint research by professors and businesses, Professors/students published 9 theses (8.3%) followed by 5 theses (4.6%) of researchers, 5 theses (4.6%) of businesses, 4 theses (3.7%) of professors, researchers and businesses and 2 theses (1.8%) of students. Professors published theses less, while businesses, research institutions and graduate school students did more continuously. The number of researchers occupied single researcher (43 theses, 39.5%), two researchers (42 theses, 38.5%) and three researchers or more (24 theses, 22.0%). Thirdly, professors published theses the most at most of areas. Researchers of main category of distribution economy consisted of professors (25 theses, 53.2%), professors and businesses (7 theses, 14.9%), professors and businesses (7 theses, 14.9%), professors and researchers (6 theses, 12.8%) and professors and students (3 theses, 6.3%). And, researchers of main category of distribution management consisted of professors (30 theses, 48.4%), professors and businesses (10 theses, 16.1%), and professors and researchers as well as professors and students (6 theses, 9.7%). Researchers of distribution management consisted of professors, professors and businesses, professors and researchers, researchers and businesses, etc to have various types. Professors mainly researched marketing, MD and purchasing, and consumer behavior, etc to demand active participation of businesses and researchers. Fourthly, research methodology was: Literature research occupied 45 theses (41.3%) the most followed by empirical research based on questionnaire survey (44 theses, 40.4%). General distribution, distribution economy, distribution and distribution management, etc mostly adopted literature research, while marketing did empirical research based on questionnaire survey the most. Fifthly, theses in the Korean language occupied 92.7% (101 theses), while those in English did 7.3% (8 theses). No more than one thesis in English was published until 2006, and 7 theses (11.9%) were published after 2007 to increase. The theses in English were published more to be affirmative. Foreigner researcher published one thesis (0.9%) and both Korean researchers and foreigner researchers jointly published two theses (1.8%) to have very much low participation of foreigner researchers. Sixthly, one thesis of JDS had 27.5 references in average that consisted of 11.1 local references and 16.4 foreign references. And, cited times was 0.4 thesis in average to be low. The distribution economy cited 24.2 references in average (9.4 local references and 14.8 foreign references and JDS had 0.6 cited reference. The distribution management had 30.0 references in average (12.1 local references and 17.9 foreign references) and had 0.3 reference of JDS itself. Seventhly, similar type of scholarly journal had theses in the Korean language and English: JDR( Journal of Distribution Research) of KODIA(Korea Distribution Association) published 92 theses in the Korean language (96.8%) and 3 theses in English (3.2%), that is to say, 95 theses in total. JKDM of KOREADIMA published 132 theses in total that consisted of 93 theses in the Korean language (70.5%) and 39 theses in English (29.5%). Since 2008, JKDM has published scholarly journal in English one time every year. JDS published 52 theses in the Korean language (88.1%) and 7 theses in English (11.9%), that is to say, 59 theses in total. Sixthly, similar type of scholarly journals and research methodology were: JDR's research methodology had 65 empirical researches based on questionnaire survey (68.4%), followed by 17 literature researches (17.9%) and 11 quantitative analyses (11.6%). JKDM made use of various kinds of research methodologies to have 60 questionnaire surveys (45.5%), followed by 40 literature researches (30.3%), 21 quantitative analyses (15.9%), 6 system analyses (4.5%) and 5 case studies (3.8%). And, JDS made use of 30 questionnaire surveys (50.8%), followed by 15 literature researches (25.4%), 7 case studies (11.9%) and 6 quantitative analyses (10.2%). Ninthly, similar types of scholarly journals and Korean researchers and foreigner researchers were: JDR published 93 theses (97.8%) by Korean researchers except for 1 thesis by foreigner researcher and 1 thesis by joint research of the Korean researchers and foreigner researchers. And, JKDM had no foreigner research and 13 theses (9.8%) by joint research of the Korean researchers and foreigner researchers to have more foreigner researchers as well as researchers in foreign countries than similar types of scholarly journals had. And, JDS published 56 theses (94.9%) of the Korean researchers, one thesis (1.7%) of foreigner researcher only, and 2 theses (3.4%) of joint research of both the Koreans and foreigners. Tenthly, similar type of scholarly journals and reference had citation: JDR had 42.5 literatures in average that consisted of 10.9 local literatures (25.7%) and 31.6 foreign literatures (74.3%), and cited times accounted for 1.1 thesis to decrease. JKDM cited 10.5 Korean literatures (36.3%) and 18.4 foreign literatures (63.7%), and number of self-cited literature was no more than 1.1. Number of cited times accounted for 2.9 literatures in 2008 and then decreased continuously since then. JDS cited 26,8 references in average that consisted of 10.9 local references (40.7%) and 15.9 foreign references (59.3%), and number of self-cited accounted for 0.2 reference until 2009, and it increased to be 2.1 references in 2010. The author gives implications based on JDS research trends and investigation on similar type of scholarly journals as follow: Firstly, JDS shall actively invite foreign contributors to prepare for SSCI. Secondly, ratio of theses in English shall increase greatly. Thirdly, various kinds of research methodology shall be accepted to elevate quality of scholarly journals. Fourthly, to increase cited times, Google and other web retrievals shall be reinforced to supply scholarly journals to foreign countries more. Local scholarly journals can be worldwide scholarly journal enough to be acknowledged even in foreign countries by improving the implications above.