• Journal of Agricultural Extension & Community Development
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• v.23 no.3
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• pp.321-334
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• 2016

Food is one of the essential elements of the tourist experiences. The study aims to segment food tourists for benefit sought. This study attempted to segment tourists who had experienced local food at tourist destinations by their benefit sought to meet local food. A self-administered survey was obtained from 498 visitors in the study areas. Results from the factor analysis show that the most explained variances of benefit sought were food taste (17.2%) and refresh (12.9%). Five distinct segments were identified based on the benefits; family seeker (17.6%), passive seeker (15.1%), want-it-all seeker (23.1%), raw material seeker (31.8%), gastronomic seeker (12.4%). In addition, a significant difference in the characteristics of tourists who had tasted local food at tourist destinations was observed in terms of occupation, income, education, expenditure for food, and tour distance. Implications are discussed relative to marketing strategies.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.1
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• pp.100-110
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• 2003

The purpose of this study were 1) to find out the structural elements in classifying clothes images, and 2) to segment the consumer market for women's street clothes based on clothes image preferences and to identify the group differences in psychological variables, purchasing behavior variables and demographic variables. The sample was taken from 1106 middle class women who were in thier 30's∼40's living in Gwangju city. Consumers were classified into six groups: active image group (35.4%), feminine image group (25.9%). daring image group (16.5%), elegant image group (10.8%), dressy image group (8.9%) and brisk image group (3.5%). Women in their 30's∼40's preferred elegant image, daring image, active image and feminine image. Elegant image oriented group: This group is the lowest education level group and has the highest rating of housewife. This group has the lowest scores use of person information search, Daring image oriented group: Woman in their 30's prefers daring image. This group thinks practical benefit sought is less important than self-expression benefit sought. This group has the highest scores use of non-person information search, Active image oriented group: This group is practical benefit seeking group. and purchases the lowest amount of clothes. The amount of average household income is the lowest. Feminine image oriented group: The amount of average household income is the highest. This group perceives more youth$.$fashion benefit sought and self-expression benefit sought than elegant image oriented group. ANOVA, $\chi$$^2$-test revealed differences among groups according to benefit sought use of information sources, purchasing behavior variables and demographic variables.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.333-335
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• 2015

A computer vision-based scene recognition algorithm is proposed for monitoring construction sites. The system analyzes images acquired from a surveillance camera to separate regions and classify them as building, ground, and hole. Mean shift image segmentation algorithm is tested for separating meaningful regions of construction site images. The system would benefit current monitoring practices in that information extracted from images could embrace an environmental context.

• Asia pacific journal of information systems
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• v.32 no.3
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• pp.496-513
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• 2022

Artificial intelligence or big data technologies can benefit finance companies such as those in the insurance sector. With artificial intelligence, companies can develop better customer segmentation methods and eventually improve the quality of customer relationship management. However, the application of AI-based customer segmentation in the insurance industry seems to have been unsuccessful. Findings from our interviews with sales agents and customer service managers indicate that current customer segmentation in the Korean insurance company relies upon individual agents' heuristic decisions rather than a generalizable data-based method. We propose guidelines for AI-based customer segmentation for the insurance industry, based on the CRISP-DM standard data mining project framework. Our proposed guideline provides new insights for studies on AI-based technology implementation and has practical implications for companies that deploy algorithm-based customer relationship management systems.

• Culinary science and hospitality research
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• v.16 no.4
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• pp.139-150
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• 2010

The purpose of this study is to examine the market segments of Korea specialty coffee shops based on the benefit variables by customers when they visit a coffee shop. For this study, SPSS WIN 17.0 was used for the frequency analysis, factor analysis, reliability test, cluster analysis, one-way ANOVA and cross tabulation. Benefit factors were divided into atmosphere factor, value factor, marketing factor, cleanliness & comfort factor, and service factor. Three distinct segments of customers were identified: passive benefit seekers, marketing benefit seekers and emotion benefit seekers. In order to explore differences between clusters and demographic and behavior variables, cross tabulation were used. These findings could be helpful for the marketers who need to establish a marketing strategy for grasping the characteristics of market segments and generating profits.

• 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.

• International Journal of Costume and Fashion
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• v.15 no.2
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• pp.19-36
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• 2015

The purpose of this study is to research the purchasing behavior according to the pursuit benefit for outdoor wear and to present a direction to outdoor wear. Questionnaire survey was administered to 533 male and female adults in their 30s to 40s living in Seoul and Gyeonggido from May 1 to 15, 2014. Concerning the statistic treatment for data analysis, SPSS for Window 18.0 was used to carry out frequency analysis, factor analysis, reliability test, cluster analysis, ANOVA and Duncan test as post-test. Benefit was drawn out as 4 elements including 'showing off & brand benefit sought', 'fashion benefits sought', 'functionality benefits sought' and 'economic benefits sought'. Group analysis according to benefit showed that it was materialized to 'multiple benefit sought group', 'unconcern group', 'showing off & brand benefit sought group' and 'utility benefit sought group'. There is an academic significance in that this research found out the level of benefit in purchasing outdoor wear and the difference of purchasing behavior by consumer groups according to benefit. This result might be used efficiently by marketers in outdoor clothing industry in classifying consumers and establishing the marketing strategy to deal with it.

• Journal of Applied Tourism Food and Beverage Management and Research
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• v.10
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• pp.139-158
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• 1999

This study is concerned with analysis of user satisfaction for travel behavior. It is aimed at investigating the socioeconomic characteristics, motivation, and use pattern of the visitors at tour. For tourists' perception and preference analysis, multi-dimensional scaling was used. It is left that this type of marketing analysis of tourism and travel offers great potentional for those concerned with the developement and management of tourist vacation areas. First, the study demanstrated clearly that different tourist and portential visitors to a tourist area seek different benefit bundles from their vacation in a particular tourist areas. Second, it demonstrated that a benefit segmentation approach to tourism and travel would be the most effective that the demographic segmentation approach usually pursued in the tourism and travel industry. Form a methodological viewpoint, it has demonstrated an application of multidimensional scaling techniques to marketing in an important industry.

• The Research Journal of the Costume Culture
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• v.6 no.3
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• pp.100-110
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• 1998

The purpose of this study is to find out the benefits sought factors of clothing and to segment the female apparel market to analyze clothing preferences and demographic characteristics of benefit segments. The subjects were 303 female in their 30's and 40's living in Seoul and the Kyunggi province. For data analysis, mean, Factor Analysis, Cluster Analysis, ANOVA, Duncan test, x²-test were conducted. The results are as follows: 1. Benefits sought by female were found to include five different factors-brand, individuality, fashionability, activity and economy. As a result of subdividing the female, five distinctive groups were formed on the basis of benefit factors-brand oriented group, indifference group, indifference group, fashion oriented group, economy oriented group, individuality oriented group. 2. Among the classified benefit groups, there were significant differences in clothing preferences according to fabric, style and color. 3. Among the classified benefit groups, there were significant differences in demographic variables according to the academic background, occupation of the subjects.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.111-123
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• 1996

In this paper, a new edge-based segmentation algorithm for range image using pseudo reflectance images (PRIs) is proposed. A model of pseudo reflectance which is useful in analyzing three dimensional scene and objects is introduced and then three PRIs are generated by the model. For generating three PRIs, bels and jain's differential window operator is selected and three different light source directions are determined. Three edge images are extracted from each PRI and a fused (logical ORing) edge image is constructed for the benefit of enhanced edge formation. The final segmentation results of the proposed algoritm are obtained after the processing of thinning, labeling and correcting erroeneous regions with the fused edge image. The good performance of edge detection and segmentation is confirmed via computer simulation with synthetic and real range images.