• Journal of the Korean Geographical Society
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• v.30 no.1
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• pp.35-56
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• 1995

During the last two decades, Korea has achieved remarkable economic growth. In this process the nation has become urbanized and industrialized. But we have also encountered widening regional disparity, housing shortage of larger cities, transportation congestion, environmental pollution and many other problems. Rapid increasing urbanization and continuous migration toward Seoul since the late 1960s have been one of the major concerns of government. Government has sought ways to moderate the population increase in Seoul. The regulation which include new town development near Seoul and dispersion strategies of higher education and other administration and living facilities outside of Seoul havemade a great expansion of the spatial influence of Seoul city. Seoul metropolitan reaion has evolved as the most powerful center of political and economical spaces. Generally within a metropolitan region, there exists a growing mutual interdependence economically, as well as socially between a central city and its surrounding area. Seoul metropolitan region manifests itself not only as a coherent system of urbanized regions, but also as an integral part of the daily urban system. The surrounding Gyunggi province and Seoul city become closely linked both economically and functionally, constituting true functlonai urban system. This study is primarily undertaken with the purpose of delineation of the sphere of influence of Seoul city in 1990. At the time of 1985, Seoul metropolitan region was delineated according to the result of the study which was performed by Korea Research Institute for Human Settlements. Afterward, the rapid speed of metropolitanization process with dramatic increase in mobility through the provision of wider transportation system across the Capital region have evolved, resulting in the great expansion of the spatial influence of Seoul city. So this study examines the expanded area of Seoul metropolitan regin during the period of 1985-90. In order to delineate Seoul metropolitan region, the indices of urbanization and functional linkage are selected. Variables included in the measurement of the urbanization level are agricultural structure, population characteristics, manufacturing and service industries, and cultural aspects such as newspaper circulation, the ratio of car ownership and piped water supply. Variables included in the measurement of functional linkage are commuting, shopping pattern, centralized service such as medical facilities and trade of agricultural products. The standardization method and factor analysis are employed in making the delineation of Seoul metropolitan region. According to the result of this study, 2 cities, 8 Eups and 46 Myuns are included Seoul metropolitan region in 1990. If we compare this delineated area in 1990 to that of 1985, we can find the distinctive pattern of expanded axes according to the main transportation routes such as Seoul-Suweon, Seoul-Gwangju, Seoul-Incheon. In 199O, all the Gyunggi province, except a few Myuns located at the north and northwest part of Gyunggi province, are included in Seoul metropolitan region. Furthermore, this study attempts to the analysis of regional structure of Seoul metropolitan region according to the functional characteristics of each city and Gun. Variables included in this analysis are the new residential function, manufacturing function, service function, education and infermation function, public facility function and agricultural function. Factor analysis and cluster analysis are employed in making regionalization. Seoul metropolitan reaion is subdivided into four subregions which reflect different functional specialization. The first group is the specialized region of newly formed residential function. The second group is the specialized reaion of manufacturing function. The third group is the specialized region of service function. And the fourth group has little specialized in terms of manufacturing, service, and residential function. But this region has some potentiality of development when Seoul metropolitan region grow continuously. Seoul metropolitan region accounted for 43% of national population, despite 11.8% of national land size in 1990. Although Seoul metropolitan region enjoys important agglomeration economies, it also has huge social cost in the form of transportation congestion, housing shortage, rapid increase of land value, environment pollution, and etc. Efficient metropolitan plan making is a vital element in promoting Seoul's economic development and providing high quality living environment at low cost. In the light of the result of this study, the outer ring of Seoul metropolitan region, especially northeastern part, are underdeveloped compared to overdeveloped southwestern area. It is needed to develop the guidelines for the implement of the growth control and management plan, inducing more balanced development for whole Seoul metropolitan reaion.

• Management & Information Systems Review
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• v.34 no.5
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• pp.191-212
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• 2015

Unlike the existing researches related to salespersons, this study intends to place the focus on salespersons' psychological characteristic as an element affecting their selling behavior. This is because employees' psychological characteristic is very likely to affect their devotion and commitment to relationship with customers and long-term production by a company. In particular, salespersons are likely to get a feeling of fatigue or loss, or make a cynical or cold response to customers because of frequent interaction with them, and to show emotional indifference in an attempt to keep their distance from customers. But the likelihood can vary depending on salespersons' own psychological characteristic; in particular, the occurrence of these phenomena is very likely to vary significantly depending on relationship belief in interpersonal relations. In the field of psychology, under way are researches related to personal psychological characteristics to improve the quality of interpersonal relations and to maximize personal performance and enhance situational adaptability during this process; it is a personal relationship belief that is recently mentioned as such a psychological characteristic. For salespersons having frequent interaction with customers, particularly, relationship belief can be a very important element in forming relations with customers. So this study aims at determining how salespersons' relationship belief affects negative emotion regulation strategies and prosocial behavior to customer. As a result, salespersons' relationship belief was found to have effects on their negative emotion regulation strategies and prosocial behavior to customer. Negative emotion regulation strategies was found to have effects on prosocial behavior. Salespersons with intimate relationship belief try to use active regulation, support-seeking regulation and salespersons with controlling relationship belief try to use avoidant/distractive regulation. Intimate relationship belief was found to have more prosocial behavior, controlling relationship belief was found to have less prosocial behavior to customer. salespersons' negative emotion regulation strategies was found to have effects on their prosocial behavior to customer. Active, support-seeking influence prosocial behavior to customer positively, avoidant/distractive regulation influence prosocial behavior to customer negatively.

• Journal of The Korean Society of Grassland and Forage Science
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• v.34 no.4
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• pp.296-306
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• 2014

This study was conducted to survey and analyze the quantity of various organic wastes and to vitalize the utilization of agri-food by-products as raw materials for Total mixed ration (TMR), to improve feed cost savings and the quality of animal products. On-the-spot obstacles for animal farmers, along with legal and institutional alternatives are presented. The results are as follows. First, organic wastes in Korea are managed by the Allbaro system created in the Wastes Control Act, which processes 10,488 tons of cooking oil waste, 832,493 tons of animal and plant residues, 5,740 tons of animal carcasses, 1,171,892 tons of animal residues, and 2,172,415 tons of plant residues including 12,905 tons of rice hull and bran, for a total of 4,205,931 tons. Raw materials for TMR, namely rice hulls and bran as well as plant residues, accounted for 51.7% of the total national organic waste. The top 10 municipalities process 76~100% of all organic wastes and a supply management system is needed for the waste. Second, the 10 major agri-food by-products used as raw materials for TMR are bean curd by-product, rice bran, oil-cake, brewers dried grain, Distiller's Dried Grains with Solubles (DDGS), barley bran, soy sauce by-product, citrus fruit by-product, mushroom by-product and other food by-product (bread, noodles, snacks, etc.). Third, the biggest difficulties in using agri-food by-products are legal obstacles. Because agri-food by-products are regulated as industrial wastes by the Waste Control Act, animal farmers that wish to use them have legal reporting obligations including the installation of recycling facilities. To enable the use of agri-food by-products as raw materials for TMR, waste management system improvements such as 'the end of waste status' and the establishment of more than 10 public distribution centers nationwide are deemed essential.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.4
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• pp.69-85
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• 2024

Social enterprises, hybrid organizations that blend the logic of the public and market economies, have emerged as an alternative to market failure. However, due to the government-led compressed growth of social enterprises, many social enterprises rely on government financial support, and when the support ends, the survival rate drops significantly and the scale remains at the microenterprise level, raising concerns about the quality growth and sustainability of social enterprises. Therefore, the purpose of this study is to identify the social entrepreneurial orientation that affects the sustainable management performance and to empirically analyze the moderating effect of network utilization capabilities in this process. To achieve the purpose of this study, a questionnaire was distributed to a random sample of member organizations in the metropolitan area, including the Incheon City Small Business Association, the Gyeonggi-do Small Business Association etc. The survey was conducted for about two months and a total of 1,300 questionnaires were distributed and 180 were returned, of which 173 were used for empirical analysis, excluding seven that were not returned. The collected survey data were subjected to structural equation modeling test using Smart PLS ver. 4.1 statistical package. The results showed that entrepreneurial value orientation and social value orientation positively influenced both economic and social performance. Convergent value orientation was only found to have an effect on economic performance, but not on social performance. Finally, the moderating effect of network capabilities was also found, suggesting that social entrepreneurial orientation positively affects organizational performance when social network capabilities are higher.

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.141-173
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• 2007

The study examines how the environmental factors of store influence service brand personality and repurchase intention in the service environment. The service industry has been experiencing the intensified competition with the industry's continuous growth and the influence from rapid technological advancement. Under the circumstances, it has become ever more important for the brand competitiveness to be distinctively recognized against competition. A brand needs to be distinguished and differentiated from competing companies because they are all engaged in the similar environment of the service industry. The differentiation of brand achievement has become increasingly important to highlight certain brand functions to include emotional, self-expressive, and symbolic functions since the importance of such functions has been further emphasized in promoting consumption activities. That is the recent role of brand personality that has been emphasized in the service industry. In other words, customers now freely and actively express their personalities or egos in consumption activities, taking an important role in construction of a brand asset. Hence, the study suggests that it is necessary to disperse the recognition and acknowledgement that the maintenance of the existing customers contributes more to boost repurchase intention when it is compared to the efforts to create new customers, particularly in the service industry. Meanwhile, the store itself can offer a unique environment that may influence the consumer's purchase decision. Consumers interact with store environments in the process of,virtually, all household purchase they make (Sarel 1981). Thus, store environments may encourage customers to purchase. The roles that store environments play are to provide informational cues to customers about the store and goods and communicate messages to stimulate consumers' emotions. The store environments differentiate the store from competing stores and build a unique service brand personality. However, the existing studies related to brand in the service industry mostly concentrated on the relationship between the quality of service and customer satisfaction, and they are mostly generalized while the connective studies focused on brand personality. Such approaches show limitations and are insufficient to investigate on the relationship between store environment and brand personality in the service industry. Accordingly, the study intends to identify the level of contribution to the establishment of brand personality made by the store's physical environments that influence on the specific brand characteristics depending on the type of service. The study also intends to identify what kind of relationships with brand personality exists with brand personality while being influenced by store environments. In addition, the study intends to make meaningful suggestions to better direct marketing efforts by identifying whether a brand personality makes a positive influence to induce an intention for repurchase. For this study, the service industry is classified into four categories based on to the characteristics of service: experimental-emotional service, emotional -credible service, credible-functional service, and functional-experimental service. The type of business with the most frequent customer contact is determined for each service type and the enterprise with the highest brand value in each service sector based on the report made by the Korea Management Association. They are designated as the representative of each category. The selected representatives are a fast-food store (experimental-emotional service), a cinema house (emotional-credible service), a bank (credible-functional service), and discount store (functional-experimental service). The survey was conducted for the four selected brands to represent each service category among consumers who are experienced users of the designated stores in Seoul Metropolitan City and Gyeonggi province via written questionnaires in order to verify the suggested assumptions in the study. In particular, the survey adopted 15 scales, which represent each characteristic factor, among the 42 unique characteristics developed by Jennifer Aaker(1997) to assess the brand personality of each service brand. SPSS for Windows Release 12.0 and LISREL were used in the analysis of data verification. The methodology of the structural equation model was used for the study and the pivotal findings are as follows. 1) The environmental factors ware classified as design factors, ambient factors, and social factors. Therefore, the validity of measurement scale of Baker et al. (1994) was proved. 2) The service brand personalities were subdivided as sincerity, excitement, competence, sophistication, and ruggedness, which makes the use of the brand personality scales by Jennifer Aaker(1997) appropriate in the service industry as well. 3) One-way ANOVA analysis on the scales of store environment and service brand personality showed that there exist statistically significant differences in each service category. For example, the social factors were highest in discount stores, while the ambient factors and design factors were highest in fast-food stores. The discount stores were highest in the sincerity and excitement, while the highest point for banks was in the competence and ruggedness, and the highest point for fast-food stores was in the sophistication, The consumers will make a different respond to the physical environment of stores and service brand personality that are inherent to the corresponding service interface. Hence, the customers will make a different decision-making when dealing with different service categories. In this aspect, the relationships of variables in the proposed hypothesis appear to work in a different way depending on the exposed service category. 4) The store environment factors influenced on service brand personalities differently by category of service. The factors of store's physical environment are transferred to a brand and were verified to strengthen service brand personalities. In particular, the level of influence on the service brand personality by physical environment differs depending on service category or dimension, which indicates that there is a need to apply a different style of management to a different service category or dimension. It signifies that there needs to be a brand strategy established in order to positively influence the relationship with consumers by utilizing an appropriate brand personality factor depending on different characteristics by service category or dimension. 5) The service brand personalities influenced on the repurchase intention. Especially, the largest influence was made in the sophistication dimension of service brand personality scale; the unique and characteristically appropriate arrangement of physical environment will make customers stay in the service environment for a long time and will lead to give a positive influence on the repurchase intention. 6) The store environment factors influenced on the repurchase intention. Particularly, the largest influence was made on the social factors of store environment. The most intriguing finding is that the service factor among all other environment factors gives the biggest influence to the repurchase intention in most of all service types except fast-food stores. Such result indicates that the customers pay attention to how much the employees try to provide a quality service when they make an evaluation on the service brand. At the same time, it also indicates that the personal factor is directly transmitted to the construction of brand personality. The employees' attitude and behavior are the determinants to establish a service brand personality in the process of enhancing service interface. Hence, there should be a reinforced search for a method to efficiently manage the service staff who has a direct contact with customers in order to make an affirmative improvement of the customers' brand evaluation at the service interface. The findings suggest several managerial implications. 1) Results from the empirical study indicated that store environment factors have a strong positive impact on a service brand personality. To increase customers' repurchase intention of a service brand, the management is required to effectively manage store environment factors and create a friendly brand personality based on the corresponding service environment. 2) Mangers and researchers must understand and recognize that the store environment elements are important marketing tools, and that brand personality influences on consumers' repurchase intention. Based on such result of the study, a service brand could be utilized as an efficient measure to achieve a differentiation by enforcing the elements that are most influential among all other store environments for each service category. Therefore, brand personality established involving various store environments will further reinforce the relationship with customers through the elevated brand identification of which utilization to induce repurchase decision can be used as an entry barrier. 3) The study identified the store environment as a component of service brand personality for the store's effective communication with consumers. For this, all communication channels should be maintained with consistency and an integrated marketing communication should be executed to efficiently approach to a larger number of customers. Mangers and researchers must find strategies for aligning decisions about store environment elements with the retailers' marketing and store personality objectives. All ambient, design, and social factors need to be orchestrated so that consumers can take an appropriate store personality. In this study, the induced results from the previous studies were extended to the service industry so as to identify the customers' decision making process that leads to repurchase intention and a result similar to those of the previous studies. The findings suggested several theoretical and managerial implications. However, the situation that only one service brand served as the subject of analysis for each service category, and the situation that correlations among store environment elements were not identified, as well as the problem of representation in selection of samples should be considered and supplemented in the future when further studies are conducted. In addition, various antecedents and consequences of brand personality must be looked at in the aspect of the service environment for further research.

• Journal of Genetic Medicine
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• v.8 no.2
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• pp.89-99
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• 2011

Over the years Korean health care system has improved in delivery of quality care to the general population for many areas of the health problems. The system is now being recognized in the world as the most cost effective one. It is covered by the uniform national health insurance policy for which most people in Korea are mandatory policy holders. Genetic counseling service, however, which is well recognized as an integral part of clinical genetics service deals with diagnosis and management of genetic condition as well as genetic information presentation and family support, is yet to be delivered in comprehensive way for the patients and families in need. Two major obstacles in providing genetic counseling service in korean health care system are identified; One is the lack of recognition for the need for genetic counseling service as necessary service by the national health insurance. Genetic counseling consumes a significant time in delivery and the current very low-fee schedule for physician service makes it very difficult to provide meaningful service. Second is the critical shortage of qualified professionals in the field of medical genetics and genetic counseling who can provide the service of genetic counseling in clinical setting. However, recognition and understanding of the fact that the scope and role of genetic counseling is expanding in post genomic era of personalized medicine for delivery of quality health care, will lead to the efforts to overcome obstacles in providing genetic counseling service in korean health care system. Only concerted efforts from health care policy makers of government on clinical genetics service and genetic counseling for establishing adequate reimbursement coverage and professional communities for developing educational program and certification process for professional genetic counselors, are necessary for the delivery of much needed clinical genetic counseling service in Korea.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• 대한공업교육학회지
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• v.38 no.1
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• pp.1-27
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• 2013

The purpose of this study was to find out the areas and their constitute elements of new apprenticeship through the expert of vocational education to improve the growth potential in the field of industry. Through the three times Delphi research process final composing areas and elements(total 6 areas and 41 sub-elements) of new apprenticeship were extracted. Followings are specific study results of 41 sub-elements for the 6 areas. In area A(Technology Skill aspect) total nine sub-elements were deducted as follows. Technology skill's field appling ability, new technology skill's acquisition, quality assurance ability, research development ability, material management using ability, problem solving ability, core technology skill understanding ability, idea's imagery expressing ability, creative design ability. In area B(Institutional aspect) total five sub-elements were deducted as follows. Flexible human material support, precise division of works, objective result assessment, institutionalization of responsibilities and liabilities between teacher and student, institutionalization of duty invention reward. In area C(Affective aspect) total eight sub-elements were deducted as follows. Manners and cooperation between teacher & student and peer, values for job, basic attitude for technology, job ethic sense, respect of other organization, active action to organization change, attitude of technology successor, service mind. In area D(Self-improvement aspect) total nine sub-elements were deducted as follows. Self evaluation and reflection, cultivate of organization understanding, career planning and developing ability, sound philosophy of life, communication ability, decision making ability, prepare of individual competence enhance system, self-control ability improvement, reaction of unexpected situation. In area E(Knowledge aspect) total four sub-elements were deducted as follows. Basic knowledge of relevant area, knowledge of new technology & preceding technology, fusion and relocation of knowledge, practical knowledge. In area F(Environmental aspect) total six sub-elements were deducted as follows. Awareness of business environment, understanding of education and practice environment, understanding of apprenticeship's business demand, connectivity of region community, adapt ability of labor market's change, awareness of society environment change.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.305-316
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• 2011

Recommender system is the system which, by using automated information filtering technology, recommends products or services to the customers who are likely to be interested in. Those systems are widely used in many different Web retailers such as Amazon.com, Netfix.com, and CDNow.com. Various recommender systems have been developed. Among them, Collaborative Filtering (CF) has been known as the most successful and commonly used approach. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. However, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting in advance whether the performance of CF recommender system is acceptable or not is practically important and needed. In this study, we propose a decision making guideline which helps decide whether CF is adoptable for a given application with certain transaction data characteristics. Several previous studies reported that sparsity, gray sheep, cold-start, coverage, and serendipity could affect the performance of CF, but the theoretical and empirical justification of such factors is lacking. Recently there are many studies paying attention to Social Network Analysis (SNA) as a method to analyze social relationships among people. SNA is a method to measure and visualize the linkage structure and status focusing on interaction among objects within communication group. CF analyzes the similarity among previous ratings or purchases of each customer, finds the relationships among the customers who have similarities, and then uses the relationships for recommendations. Thus CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. Under the assumption that SNA could facilitate an exploration of the topological properties of the network structure that are implicit in transaction data for CF recommendations, we focus on density, clustering coefficient, and centralization which are ones of the most commonly used measures to capture topological properties of the social network structure. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. We explore how these SNA measures affect the performance of CF performance and how they interact to each other. Our experiments used sales transaction data from H department store, one of the well?known department stores in Korea. Total 396 data set were sampled to construct various types of social networks. The dependant variable measuring process consists of three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used UCINET 6.0 for SNA. The experiments conducted the 3-way ANOVA which employs three SNA measures as dependant variables, and the recommendation accuracy measured by F1-measure as an independent variable. The experiments report that 1) each of three SNA measures affects the recommendation accuracy, 2) the density's effect to the performance overrides those of clustering coefficient and centralization (i.e., CF adoption is not a good decision if the density is low), and 3) however though the density is low, the performance of CF is comparatively good when the clustering coefficient is low. We expect that these experiment results help firms decide whether CF recommender system is adoptable for their business domain with certain transaction data characteristics.