• Fashion & Textile Research Journal
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• v.15 no.3
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• pp.393-405
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• 2013

This study considers the effect of smartphone involvement for purchase intentions in fashion shopping malls based on mobile web apps and on PC web apps; in addition, it investigates the correlation between purchase intention in fashion shopping malls (based on activated PC web apps) and those of fashion shopping malls (based on newly created mobile web apps). The results of this study are: First, the analysis of smartphones factors showed that smartphones consist of 6 kinds of dimensions of 'appearance involvement', 'time and information search involvement', 'application involvement', 'entertainment involvement', 'communication involvement', and 'transaction involvement'. Second, the higher the entertainment and transaction involvement among descriptive variables for smartphone involvement were due to the positive responses displayed towards fashion shopping mall purchases based on mobile web apps. Third, a higher application and entertainment involvement in the descriptive variables for smartphones resulted in a positive response displayed for purchases in fashion shopping malls based on PC web apps shown in a regression analysis that verified the smartphone and purchase intention relationship in fashion shopping malls based on PC web apps. Fourth, consumers with high purchase intention in the existing PC web app based fashion shopping malls were shown to have a high purchase intention in mobile web app based fashion shopping malls due to the results of a correlation analysis that analyzed the relationship between purchase intention in PC web app based fashion shopping malls and mobile web app based fashion shopping malls.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.261-269
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• 2009

In this paper we consider Internet Protocol Tele-Vision (IPTV) Service that started recently in Korea. IPTV makes it possible to watch high quality TV programs and a lot of multimedia contents with TV by way of Internet. The service providers are interested in the factors that influence the diffusion of new service such as IPTV. We therefore search the functional-attribute that would influence the acceptance of IPTV service, and propose a model for analyzing the relationship between the attributes and the intention of buying. The model is based on the extended Technology Acceptance Model (TAM). Survey results show that the significant functional attributes influencing the intention of buying are contents variety and convenience.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.6
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• pp.734-745
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• 2004

This paper investigated the consumer's purchase behaviors on the home-shopping private brand apparel. Female consumers of age in the range of 20∼50 were asked to complete a questionnaire, who had experienced to search apparel on home shopping media or had purchased it from home shopping business. Through this empirical study, the importance of home-shopping private brand apparel is confirmed. And the model of home-shopping private brand purchase determination, consists of private brand purchase intention, brand evaluation and company patronage, is suggested focusing on two brand types and three different home shopping media. The data were analyzed by mean, multiple regression analysis, ANOVA, Duncan-test of SPSS Win(ver.10.0). The result generated from this study are as follows: First. there are significant differences in preferred private brand types according to the types of media they preferred to purchase. Consumers's sex and age are also important demographic variables in relation to purchase determination variables of home-shopping private brand apparel. Second, the home-shopping company patronage is directly influenced in consumer's purchase intention of home-shopping private brand apparel as well as the consumer's brand evaluation. Consequently, the company patronage is more related to purchase intention of home shopping private brand apparel.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.772-774
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• 2017

Currently, there are many simple searches for local culture and tourism, but systematic information retrieval using ontology technology is weak. The keyword-based search, which is an existing search method, derives a search result that is different from a user's wanted intention. On the other hand, semantic search using ontology constructs shows the information related to the search term by creating a relation between words and words. Therefore, when tourists search for cultural and tourist attractions in the area, they provide information that includes meaning relevance in the search results. If the ontology provides information on the culture, sightseeing area, transportation, Can be more easily grasped. In this paper, we propose an ontology-based retrieval system based on culture and tourist sites utilizing public institutions database by using mobile application by extending search system which relied only on existing internal database to provide accurate and reliable information to users. This efficient structure of the ontology makes it possible to provide information suitable for the user quickly and accurately.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.173-181
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• 2008

This study aims to prove the connection between satisfaction and re-visit intention of customers by examining shopping value and store image depending on product types purchased at Internet shopping malls. The finding of this study revealed that shopping value could be classified into hedonic and utilitarian value, while store image could be extracted into six dimensions such as reputation, product and information service, customer service after purchase, atmosphere, convenience, and safety. Both search goods and experience goods among store image factors were found to have stronger effect on utilitarian shopping value than hedonic shopping one. In addition, it was found that store image and shopping value had an effect on customer satisfaction and re-visit intention depending on product types, with a significant difference. These findings are expected to provide marketing complications for the understanding of differentiated market segments in the Internet shopping mall market, which is facing ever-growing market.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.137-142
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• 2012

Snippet is a summaries information of representing web pages which search engine provides user. Snippet and page rank in search engine abundantly influence user for visiting web pages. User sometime visits the wrong page with respect to user intention when uses snippet. The snippet extraction method is difficult to accurate comprehending user intention. In order to solve above problem, this paper proposes a new snippet extraction method using fuzzy association and pseudo relevance feedback. The proposed method uses pseudo relevance feedback to expand the use's query. It uses the fuzzy association between the expanded query and the web pages to extract snippet to be well reflected semantic user's intention. The experimental results demonstrate that the proposed method can achieve better snippet extraction performance than the other methods.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.179-186
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• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.318-326
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• 2010

In this paper we investigate the factors influencing the purchase intention of Smart-Phone which was introduced recently. Smart-Phone is a new information technology that converges PDA into a mobile phone. It has a various functions such as phone, information processing, Internet search etc. New information technology like Smart-Phone gives us a very important and interesting research issue, which is to find and prove the factors influencing the purchase intention. We try to find and prove the factors influencing the purchase intention of Smart-Phone by expanding Technology Acceptance Model. We include the perceived playfulness to the research model in order to analyze the factors. This empirical paper proves that the perceived usefulness, the perceived ease-of-use, and the perceived playfulness give positive effects to the purchase intention. In addition, this paper indicates some managerial implications that various and useful applications and the easy user interface can help to increase the degree of user acceptance.

• Journal of Korean Society for Quality Management
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• v.47 no.2
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• pp.237-254
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• 2019

Purpose: The purpose of this study is to analyze correlation of perceived cosmetics brand apps attributes and use intentions, mediating role of customer satisfaction, and relationship between customer satisfaction and continuous usage intention. Then provide basic data for development management strategy of beauty industry and enhancement of competitiveness corresponding to smart era. Methods: The questionnaires were surveyed by an online company(EMBRAIN). After data collection, frequency analysis was performed on the general attributes of questionnaire survey using SPSS 22.0, and data conclusions were derived by verifying reliability and validity of data and hypotheses. Results: First, perceived cosmetic brand app attributes have a positive effect on customer satisfaction, Second, perceived cosmetic brand app attributes have a positive effect on continuous usage intention. Third, customer satisfaction was found to have a mediating role in the effect of perceived cosmetic brand app attributes on continuous usage intention. Fourth, involvement proved to control the relationship between perceived cosmetic brand app attributes perceived interactivity and customer satisfaction. Finally, Involvement has proven to control the relationship between cosmetic brand app attributes perceived interactivity and continuous usage intention. Conclusion: Consumers buying products from cosmetics brand apps will be more likely to use cosmetics brand apps if they feel comfortable with calculation process, search, booking confirmation and payment methods.

• The Research Journal of the Costume Culture
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• v.31 no.5
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• pp.651-668
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• 2023

This study aims to help companies with efficient investment and marketing strategies by empirically verifying the impact on satisfaction and purchase intention for artificial intelligence-based digital technology supported shopping assistants introduced in e-commerce. Frequency, factor, SEM, and multiple group analysises were conducted using SPSS 26.0 and Amos 26.0. As a result, first, motivated consumer innovativeness elements of AI shopping assistant were derived into a total of four categories: functional, hedonic, rational, and reliable. Second, in the order of hedonic and rational, satisfaction with the AI shopping assistant was significantly affected, and in the order of rational and functional, purchase intention was significantly affected. The satisfaction with the AI shopping assistant did not affect the purchase intention. Third, in the case of hedonic, the AI-preferred group had a more significant effect on satisfaction than the human-preferred group, and in the case of rational, there was no difference by group in purchase intention. Thus, it was found that consumers prefer AI shopping helpers for e-commerce because they can shop reasonably and are functionally convenient. Therefore, when introducing AI shopping assistants, it is essential to include content that can compare and analyze fundamental information, such as product prices, as well as search functions and payment system compatibility that facilitate shopping.