• Journal of the East Asian Society of Dietary Life
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• v.22 no.6
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• pp.744-757
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• 2012

This study was designed to obtain basic data for the globalization of Korean food and the expansion of food exports through contract foodservices. A survey of dietary habits and attitudes toward school foodservices was given to students in three American international schools served by a domestic contract foodservice management company located in Seoul and Gyeonggi area. The results showed an average of three meals taken daily 3.39 times for male students and 2.95 times for female students and the time required for a meal was about 24~26 minutes. The average breakfast frequency was 5.10 times(4.59 times for male students and 5.35 times for female students) and many students reported skipping breakfast due to a lack of time. The average weekly frequency of dining out was 1.78 times(2.15 times for male students and 1.60 times for female students). In all schools, irrespective of gender and grade, students responded that a desire for snacking was 'why they want to have cookies', and snacking hours were frequently listed as 'between noon and evening'. Many also responded that an unbalanced diet is the reason some snacks are 'not to their taste'. Overall, students were highly satisfied with the foodservice menu, although there was a significant difference in what was considered proper food temperature, proper food seasoning, suitable amounts of food, and freshness of food. Male and female students were specifically highly satisfied with the 'freshness of food materials' and 'variety of menu' respectively. Overall, all students were highly satisfied with the foodservice, including the 'cleanliness of tables and trays'.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.