• Journal of Applied Tourism Food and Beverage Management and Research
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• v.14 no.2
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• pp.17-22
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• 2003

Although researchers have, during the past decade, become increasingly interested in customer satisfaction customer reaction, and service quality issues, very little of research has devoted to the family restaurant. Family restaurant industry is among the fastest growing sectors of the tourism market. This paper discusses the importance of the family restaurant product and service quality, and presents the relationship among service quality, customer satisfaction, and customer reaction. The literature supports the value of family restaurant's service quality and relation between service quality and customer reaction. Exploratory study examined customer's satisfaction with service quality components and customer's reaction with satisfaction. The survey was conducted in four phases; service quality, customer reaction(satisfaction, repurchase intention, and word of mouth), restaurant information, general profile of customer. The results of the study show that service quality(product's quality, physical character) provided family restaurant customer with the overall satisfaction, and service quality affected on customer reaction(repurchase intention, positive word of mouth). Also overall satisfaction affected on repurchase intention and positive word of mouth.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.775-782
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• 2002

As electronic commerce systems have been widely used, the necessity of adaptive e-commerce agent systems has been increased. These kinds of agents can monitor customer's purchasing behaviors, clutter them in similar categories, and induce customer's preference from each category. In order to implement our adaptive e-commerce agent system, we focus on following 3 components-the monitor agent which can monitor customer's browsing/purchasing data and abstract them, the conceptual cluster agent which cluster customer's abstract data, and the customer profile agent which generate profile from cluster, In order to infer more accurate customer's preference, we propose a 2 layered structure consisting of conceptual cluster and inductive profile generator. Many systems have been suffered from errors in deriving user profiles by using a single structure. However, our proposed 2 layered structure enables us to improve the qualify of user profile by clustering user purchasing behavior in advance. This approach enables us to build more user adaptive e-commerce system according to user purchasing behavior.

• Korean Journal of Organic Agriculture
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• v.27 no.3
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• pp.247-269
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• 2019

Although food related lifestyle has been widely discussed over the last ten years, the majority of research on food related lifestyle has been only conducted in terms of a variable-centered approach. But, recently there is a growing body of research on food related lifestyle profiles over the last three years from the view of a person-centered approach. This study conducted both a cluster analysis and a latent profile analysis (LPA) to identify the patterns of potential food related lifestyle customer profiles based on the five components on the sample of customer, who bought organic products (n=509). The results of each statistical analysis showed both quantitatively and qualitatively different types of food related lifestyle customer profiles even though there were similar types of profiles identified in common between these two analyses. These various profiles were then compared with customer's level of buying behaviors (e.g., buying attitude and buying intentions). Results showed that food related lifestyle profiles with respect to the high level of interesting in dietary life in terms of health and safety are associated with the higher level of buying behaviors. Based on the results, implications for food related lifestyle literature, practices and future research are discussed.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1205-1212
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• 2004

As electronic commerce systems have been widely used, the necessity of adaptive e-commerce agent systems has been increased. These kinds of adaptive e-commerce agents can monitor customer's behaviors and cluster thou in similar categories, and include user's preference from each category. In order to implement our adaptive e-commerce agent system, in this paper, we propose an adaptive e-commerce agent systems consider customer's information of interest and goodwill ratio about preference goods. Proposed system build user's profile more accurately to get adaptability for user's behavior of buying and provide useful product information without inefficient searching based on such user's profile. The proposed system composed with three parts , Monitor Agent which grasps user's intension using monitoring, similarity reference Agent which refers to similar group of behavior pattern after teamed behavior pattern of user, Interest Analyzing Agent which personalized behavior DB as a change of user's behavior.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.281-287
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• 2012

The customer load profile clustering method is used to make the TDLP (Typical Daily Load Profile) to estimate the quarter hourly load profile of non-AMR (Automatic Meter Reading) customers. This study examines how the repeated clustering method improves the ability to discriminate among the TDLPs of each cluster. The k-means algorithm is a well-known clustering technology in data mining. Repeated clustering groups the cluster into sub-clusters with the k-means algorithm and chooses the sub-cluster that has the maximum average error and repeats clustering until the final cluster count is satisfied.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.379-385
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• 2013

On the internet, the rating scores assigned by customers are considered as the preference information of themselves and thus, these can be used efficiently in the customer profile generation process of recommender system. However, since anyone is free to assign a score that has a biased rating, using this without any filtering can exhibit a reliability problem. In this study, we suggest the methodology that measures the reliability of rating scores and then applies them to the customer profile creation process. Unlikely to some related studies which measure the reliability on the user level, we measure the reliability on the individual rating score level. Experimental results show that prediction accuracy of recommender system can be enhanced when ratings with higher reliability are selectively used for the customer profile configuration.

• IE interfaces
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• v.19 no.1
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• pp.86-96
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• 2006

Some customer data of manufacturing industries have a large number of incomplete data set due to the customer's infrequent purchasing behavior and the limitation of customer profile data gathered from sales representatives. So that, most sophisticated data analysis methods may not be applied directly. This paper proposes a heuristic data analysis method to classify customers in household appliances industries. The proposed PD (percent of difference) method can be used for the discriminant analysis of incomplete customer data with simple mathematical calculations. The method is composed of variable distribution estimation step, PD measure and cluster score evaluation steps, variable impact construction step, and segment assignment step. A real example is also presented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1625-1631
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• 2008

This paper is going to research about RFID real time position finder technology and the offline shopping mall's client shop list managed by the RF fused Tag USB memory to analyze out the output of the data for providing real time interactive customer intelligence commodity system.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.187-196
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• 2000

A lot of Internet shopping malls strive for obtaining a competitive advantage over others in an increasingly tighter electronic marketplace. To this end, understanding customer preference toward products (or services) and administering appropriate marketing strategy is essential for their continuous survival. However, only a few marketing researchers and practicioners focused on this issue, compared with academic and industry efforts devoted to traditional market segmentation. In this paper, we suggest a methodology of conjoint segmentation for electronic shopping malls. Traditional market segmentation methodologies based on customer's profile sometimes fail to utilize abundant information given while navigating around cyber shopping malls. In this methodology, we do not impose information overload to the customer for preference elicitation, but this methodology, we do not impose information overload to the customer for preference elicitation, but capture automatically generated surfing or buying data and analyze them to get useful market segmentation information. The methodology consists of 4-stages: 1) analyzing legacy homepages, 2) data preparation, 3) estimating and interpreting the result, and 4) developing marketing mix. Our methodology was to give useful guidelines for market segmentation to companies working in the electronic marketplace.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1068-1071
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• 1996

Good shape on flat rolled product is necessary to meet today's customer quality requirement. To meet the increasing demand in quality of strip shape from downstream customers, POSCO has replaced the Automatic Shape Control(ASC) system with the existing one that had used noncontact type measuring system at No.2 Cold Rolling Mill, Pohang works in October, 1995. The strip shape is influenced by the profile, roll crown, bending control, skew control system, as well as work roll cooling system. We have used ASC to adjust those factors in Cold Rolling Mill that could get a satisfactory result, almost less than .+-.5 1-unit deviation from the target shape. However, the downstream customer(i.e. Continuos Annealing Line) wants a good shape not only at the moment of exit of roll bite, but after rolling without tension. In this investigation, the difference will be discussed and how deal with this problem.