• 제목/요약/키워드: Social Search

검색결과 953건 처리시간 0.03초

패션명품 소비자의 상표충성에 영향을 미치는 요인에 관한 연구 (Explanatory Variables of Customer's Brand Loyalty to Fashion Luxury Goods)

  • 박민주;이유리
    • 한국의류학회지
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    • 제29권11호
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    • pp.1485-1497
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    • 2005
  • The purpose of this study was to define the mutual relationship between the explanatory variables of brand loyalty and consumer's fashion luxury brand loyalty, and ultimately to show a path model of fashion luxury brand loyalty. Especially this was focused on the relationship among social risk perception, symbolism involvement, marketer leading information search, and continuing brand loyalty. In the empirical study, a questionnaire was developed through the literature search and a survey was conducted both in on-line and off-line questionnaire simultaneously. Finally 291 data from males and females who had a buying experience of luxury brand goods were analyzed. The result showed the 4 significant paths of fashion luxury brand loyalty existed, such as social risk perception$\rightarrow$symbolism involvement, social risk perception$\rightarrow$marketer leading information search, symbolism involvement$\rightarrow$continuing brand loyalty, marketer leading information search$\rightarrow$continuing brand loyalty. And the explanatory factor which has the strongest influencing power to continuing brand loyalty was symbolism involvement. The powers of social risk perception and marketer leading information search to continuing brand loyalty were weaker than symbolism involvement. The findings of this study are expected to contribute to develop a theory on the consumer's loyalty to fashion luxury goods and marketing strategies for enhancing the brand loyalty.

한국한의학연구원 시맨틱 소셜 네트워크 시스템 구축 (A Semantic Social Network System in Korea Institute of Oriental Medicine)

  • 김상균;장현철;김철;예상준;김진현;송미영
    • 한국한의학연구원논문집
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    • 제16권2호
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    • pp.91-99
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    • 2010
  • In this paper, we designed and implemented a semantic social network system in Korea Institute of Oriental Medicine (abbreviated as KIOM). Our social network system provides the capabilities such as tracking search, ontology reasoning, ontology graph view, and personal information input, update and management. Tracking search provides the search results by the research information of relevant researchers using ontology, in addition to those by keywords. Ontology reasoning provides the reasoning for experts, mentors, and personal contacts. Users can easily browse the personal connections among researchers by traversing the ontology by graph viewer. These allows KIOM researchers to search other researchers who could aid the researches and to easily share their research information.

인터넷 패션 소비자의 특성과 쇼핑동기 및 가격민감도가 부정적 구매행동에 미치는 영향 (The Effects of Internet Fashion Consumer Characteristics, Shopping Motivation, and Price Sensitivity on Negative Purchasing Behavior)

  • 이은진;김종욱
    • 한국의류산업학회지
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    • 제15권3호
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    • pp.381-392
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    • 2013
  • This study analyzed the effects of internet fashion consumer characteristics and shopping motivation on price sensitivity as well as the effect of price sensitivity on negative purchasing behavior. A survey was conducted from August 10 to September 20 in 2012 and 364 responses were used in the data analysis. The statistical analysis methods were frequency analysis, factor analysis, reliability analysis, and multiple regression analysis. The characteristics of internet fashion consumers were composed of innovation tendency, impulse buying tendency, information orientation, and variety seeking tendency. Shopping motivation was composed of convenient motivation, social motivation, hedonic motivation, product motivation, and economic motivation. The information orientation and variety seeking tendency of internet fashion consumers influenced the price search. The innovation tendency, impulse buying tendency, and variety seeking tendency of internet fashion consumers influenced the price importance. Convenient motivation, hedonic motivation, and product motivation positively affected the price search; however, social motivation negatively affected the price search. The social motivation, hedonic motivation, and economic motivation of internet fashion consumers positively affected price importance. Price search and price importance influenced the purchasing delay; in addition, price search influenced the switching intention. The results of this study provide useful information for customer management and internet shopping mall marketing strategies.

The effect of image search, social influence characteristics and anthropomorphism on purchase intention in mobile shopping

  • KIM, Won-Gu;PARK, Hyeonsuk
    • 산경연구논집
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    • 제11권6호
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    • pp.41-53
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    • 2020
  • Purpose: The purpose of this study is to review the previous studies on the characteristics of the image search service provided by using artificial intelligence, the social impact characteristics, and the moderating effect of perceived anthropomorphism, and conduct empirical analysis to identify the constituent factors affecting purchase intention. To clarify. Through this, I tried to present theoretical and practical implications. Research design, data, and methodology: Research design was that characteristics of image search service (ubiquity and information quality) and social impact characteristics (subjective norms, electronic word of mouth marketing) are affected by mediation of satisfaction and flow, therefore, control of perceived anthropomorphism have an effect on purchase intention to increase. For analysis, research conducted literature review, and developed questionnaires, so that EM firm which is a specialized research institute has collected data. This was conducted on 410 people between the 20s and 50s who have mobile shopping experiences. SPSS Statistics 23 and AMOS 23 had been used to perform necessary analysis such as exploratory factor analysis, reliability analysis, feasibility analysis, and structural equation modeling based on this data. Results: first, ubiquity, information quality and subjective norms were found to have a positive effect on purchase intention through satisfaction and flow parameters. Second, satisfaction and flow were found to have a mediating effect between ubiquity, information quality, and subjective norms and purchase intentions. However, there was no mediating effect between eWOM information and purchase intention. Third, perceived anthropomorphism was found to have a moderating effect between information quality and satisfaction, and it was found that there was no moderating effect on the relationship between information quality and flow. Conclusions: The information quality of image search services using artificial intelligence has a positive effect on satisfaction, and it has been found that there is a positive moderate effect of perceived anthropomorphism in this relationship, which may be an academic contribution to the distribution science utilizing artificial intelligence. Therefore, it is possible to propose a distribution strategy that improves purchase intention by utilizing image search service and anthropomorphism in practical business and providing a more enjoyable immersive experience to customers.

인공지능의 사회적 수용도에 따른 키워드 검색량 기반 주가예측모형 비교연구 (Comparison of Models for Stock Price Prediction Based on Keyword Search Volume According to the Social Acceptance of Artificial Intelligence)

  • 조유정;손권상;권오병
    • 지능정보연구
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    • 제27권1호
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    • pp.103-128
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    • 2021
  • 최근 주식의 수익률과 거래량을 설명하는 주요 요인으로서 투자자의 관심도와 주식 관련 정보 전파의 영향력이 부각되고 있다. 또한 인공지능과 같은 혁신 신기술을 개발보급하거나 활용하려는 기업의 경우 거시환경 및 시장 불확실성 때문에 기업의 미래 주식 수익률과 주식 변동성을 예측하기 어렵다는 문제를 가지고 있다. 이는 인공지능 활성화의 장애요인으로 인식되고 있다. 따라서 본 연구의 목적은 인공지능 관련 기술 키워드의 인터넷 검색량을 투자자의 관심 척도로 사용하여, 기업의 주가 변동성을 예측하는 기계학습 모형을 제안하는 것이다. 이를 위해 심층신경망 LSTM(Long Short-Term Memory)과 벡터자기회귀(Vector Autoregression)를 통해 주식시장을 예측하고, 기술의 사회적 수용 단계에 따라 키워드 검색량을 활용한 주가예측 성능 비교를 통해 기업의 투자수익 예측이나 투자자들의 투자전략 의사결정을 지원하는 주가 예측 모형을 구축하였다. 또한 인공지능 기술의 세부 하위 기술에 대한 분석도 실시하여 기술 수용 단계에 따른 세부 기술 키워드 검색량의 변화를 살펴보고 세부기술에 대한 관심도가 주식시장 예측에 미치는 영향을 살펴보았다. 이를 위해 본 연구에서는 인공지능, 딥러닝, 머신러닝 키워드를 선정하여, 2015년 1월 1일부터 2019년 12월 31일까지 5년간의 인터넷 주별 검색량 데이터와 코스닥 상장 기업의 주가 및 거래량 데이터를 수집하여 분석에 활용하였다. 분석 결과 인공지능 기술에 대한 키워드 검색량은 사회적 수용 단계가 진행될수록 증가하는 것으로 나타났고, 기술 키워드를 기반으로 주가예측을 하였을 경우 인식(Awareness)단계에서 가장 높은 정확도를 보였으며, 키워드별로 가장 좋은 예측 성능을 보이는 수용 단계가 다르게 나타남을 확인하였다. 따라서 기술 키워드를 활용한 주가 예측 모델 구축을 위해서는 해당 기술의 하위 기술 분류를 고려할 필요가 있다. 본 연구의 결과는 혁신기술을 기반으로 기업의 투자수익률을 예측하기 위해서는 기술에 대한 대중의 관심이 급증하는 인식 단계를 포착하는 것이 중요하다는 점을 시사한다. 또한 최근 금융권에서 선보이고 있는 빅데이터 기반 로보어드바이저(Robo-advisor) 등 투자 의사 결정 지원 시스템 개발 시 기술의 사회적 수용도를 세분화하여 키워드 검색량 변화를 통해 예측 모델의 정확도를 개선할 수 있다는 점을 시사하고 있다.

인터넷 검색추세를 활용한 빅데이터 기반의 주식투자전략에 대한 연구 (A Study on Big Data Based Investment Strategy Using Internet Search Trends)

  • 김민수;구평회
    • 한국경영과학회지
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    • 제38권4호
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    • pp.53-63
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    • 2013
  • Together with soaring interest on Big Data, now there are vigorous reports that unearth various social values lying underneath those data from a number of application areas. Among those reports many are using such data as Internet search histories from Google site, social relationships from Facebook, and transactional or locational traces collected from various ubiquitous devices. Many of those researches, however, are conducted based on the data sets that are accumulated over the North American and European areas, which means that direct interpretation and application of social values exhibited by those researches to the other areas like Korea can be a disturbing task. This research has started from a validation study against Korean environment of the former paper which says an investment strategy that exploits up and down of Google search volume on a carefully selected set of terms shows high market performance. A huge difference between North American and Korean environment can be eye witnessed via the distinction in profit rates that are exhibited by the corresponding set of search terms. Two sets of search terms actually presented low correlation in their profit rates over two financial markets. Even in an experiment which compares the profit rates with two different investment periods with the same set of search terms showed no such meaningful result that outperforms the market average. With all these results, we cautiously conclude that establishing an investment strategy that exploits Internet search volume over a specified word set needs more conscious approach.

여대생의 퍼스널 이미지 만족도와 구직효능감과의 관계에서 외모관리행동의 매개효과 (Mediation Effect of Appearance Management Behavior on the Relationship between Satisfaction of Personal Image and Job Search Efficacy among Female College Students)

  • 김미경
    • 패션비즈니스
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    • 제22권4호
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    • pp.160-177
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    • 2018
  • The objective of this study was to investigate mediation effect of appearance management behavior on the relationship between satisfaction of personal image and job search efficacy. Based on previous studies on components of personal image, appearance management behaviors, and job search efficacy, questionnaire items were developed. For this study, we conducted a questionnaire survey among 422 students from women's university in Seoul. Statistical analyses were performed using SPSS 23. Results are as follows. First, there were positive and moderate bivariate correlations among satisfaction of personal image, appearance management behavior, and job search efficacy. Second, satisfaction of personal image was found to have a partially significant effect on job search efficacy while satisfaction of internal image, visual image, and social image had a positive effect on job search skill. Satisfaction of internal image had a positive effect on job search strength. However, satisfaction of visual image or social image did not have a significant effect on job search strength. Third, fashion management behavior among components appearance management behavior could partially mediate the relationship between satisfaction of personal image and job search efficacy, indicating that satisfaction of internal image and visual image among components personal image not only has a direct effect on job search skill among job search efficacy, but also has an indirect effect on job search skill by affecting fashion management behavior. These results suggest that it is important to build personal image effectively and increase satisfaction with oneself through active appearance management behavior to improve job search efficacy.

성인여성의 가치인식과 의복쇼핑성향 및 의복만족에 관한 연구 (A Study on Consumer Values Clothing Shopping Orientation and Clothing Satisfaction)

  • 구자명;이명희
    • 한국의류학회지
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    • 제23권3호
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    • pp.459-470
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    • 1999
  • The objectives of this study were to investigate the difference the clothing shopping orientation and clothing satisfaction according to satisfaction·dissatisfaction group to examine how the clothing satisfaction was influenced by consumer values demographic variable clothing shopping orientation. The subject were 457 women in Seoul Korea The results of the study were as follows. 1. five factors of clothing shopping orientation (SO) derived by factor analysis : F.1. conspicious SO : F,2 search SO: F,3 recreational SO : F,4 addictive SO :F,5 independent SO . Two factors of terminal value derived by factor analysis : F,1 responsible : F.2 ambitious. 2. Satisfaction group had high levels of search SO, dissatisfaction group had high levels of addictive SO. Satisfaction group was satisfied with color style appropriateness for wearer in order dissatisfaction group was dissatisfied with care price size in order. 3. Conspicious SO were influenced bysocial stratification social recognition and happiness. Search SO were influenced by dwelling area and age. Recreational SO were influenced by social stratification social recognition and responsible value. Addictive SO influenced by responsible value social recognition and happiness. independent SO were influenced by marital status and ambitious value. 4. Clothing satisfaction was influenced by addictive conspicious SO happiness and recreational SO(R2=24.6)

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여행자 관심 기반 스마트 여행 수요 예측 모형 개발: 웹검색 트래픽 정보를 중심으로 (The Development of Travel Demand Nowcasting Model Based on Travelers' Attention: Focusing on Web Search Traffic Information)

  • 박도형
    • 한국정보시스템학회지:정보시스템연구
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    • 제26권3호
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    • pp.171-185
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    • 2017
  • Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

SNS에서의 개선된 소셜 네트워크 분석 방법 (Improved Social Network Analysis Method in SNS)

  • 손종수;조수환;권경락;정인정
    • 지능정보연구
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    • 제18권4호
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    • pp.117-127
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    • 2012
  • 최근 온라인 소셜 네트워크 서비스(SNS)의 사용자가 크게 늘어나고 있으며 다양한 분야에서 SNS의 사용자 관계 구조 및 메시지를 분석하기 위한 연구를 진행하고 있다. 그러나 대부분의 소셜 네트워크 분석 방법들은 노드 사이의 최단 거리를 기초로 하고 있으므로 계산 시간이 오래 걸린다. 이는 점차 대형화 되어가는 SNS의 데이터를 여러 분야에서 활용하는데 걸림돌이 되고 있다. 이에 따라 본 논문에서는 SNS의 사용자 그래프에서 사용자간 최단거리를 빠르게 찾기 위한 휴리스틱 기반의 최단 경로 탐색 방법을 제안한다. 제안하는 방법은 1) 트리로 표현된 소셜 네트워크에서 시작 노드와 목표 노드를 설정한다. 그리고 2) 만약 목표 노드가 경사 트리의 단말에 있다면 경사 트리가 시작하는 노드를 임시 골 노드로 설정한다. 마지막으로 3) 연결의 차수를 평가값으로 하는 휴리스틱 기반 최단거리 탐색을 수행한다. 이렇게 최단거리를 탐색한 후 매개 중심성 분석(Betweenness Centrality) 및 근접 중심성(Closeness Centrality)를 계산한다. 제안하는 방법을 사용하면 소셜 네트워크 분석에서 가장 많은 시간이 필요한 최단거리 탐색을 빠르게 수행할 수 있으므로 소셜 네트워크 분석의 효율성을 기대할 수 있다. 본 논문에서 제안하는 방법을 검증하기 위하여 약 16만 명으로 구성된 SNS에서의 실제 데이터를 이용하여 매개 중심성 분석과 근접 중심성 분석을 수행하였다. 실험 결과, 제안하는 방법은 전통적 방식에 비하여 매개 중심성, 근접 중심성의 계산 시간이 각각 6.8배, 1.8배 더 빠른 결과를 보였다. 본 논문에서 제안한 방법은 소셜 네트워크 분석의 시간을 향상시켜 여러 분야에서 사회 현상 및 동향을 분석하는데 유용하게 활용될 수 있다.