• Title/Summary/Keyword: Attribution Information

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The effect on purchasing intention of Hotel Brand-image and Choice-attribution (호텔 브랜드이미지와 선택속성이 구매의도에 미치는 영향에 관한 연구)

  • Lee, Ji-Yeong;Kim, Tae-Jin
    • Journal of Applied Tourism Food and Beverage Management and Research
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    • v.16 no.1
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    • pp.43-69
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    • 2005
  • Generally, brand is the title for discriminating their own goods and service from other competitive company, brand-image means customer's good and bad affection or loyalty the brand of specific company. Customers often choose the goods according to the value of goods brand. In terms of this viewpoint, the value of company's brand is very important factor to the company's success. Brand-image also effects customers on selling company's goods. Specially, to the hotel business that should ensure lots of customer for a long period with the interest and credit of customers, its brand-image is more significant. What the image is looked upon as a important factor in marketing is due to the difficulty of discrimination against goods standardized in price and quality. Therefore, the company's image acts as a more important marketing factor in the high industrial society. Also it means a lot to the customer's purchasing behavior. When the company's brand-image is recognized or discriminated, customer's memory is longer and customer's reliability is raised than other company's advertisement and public information. Nowadays, most of hotels are perceiving the importance on their own brand-image but in the lack of deep study and systematic strategy in reality. The purpose of this study is to research the effect on customer's purchasing intention of hotel brand-image and choice-attribution. The empirical research has been done from 23April, 2004 to 20May, 2004. Data were collected from general customers who are using hotel located in Taegu. In conclusion, hotel brand-image depends highly on, the service quality of hotel staff and reputation of hotel. Besides, this acts on customer's hotel choice decisively.

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Performance Improvement of Collaborative Filtering System Using Associative User′s Clustering Analysis for the Recalculation of Preference and Representative Attribute-Neighborhood (선호도 재계산을 위한 연관 사용자 군집 분석과 Representative Attribute -Neighborhood를 이용한 협력적 필터링 시스템의 성능향상)

  • Jung, Kyung-Yong;Kim, Jin-Su;Kim, Tae-Yong;Lee, Jung-Hyun
    • The KIPS Transactions:PartB
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    • v.10B no.3
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    • pp.287-296
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    • 2003
  • There has been much research focused on collaborative filtering technique in Recommender System. However, these studies have shown the First-Rater Problem and the Sparsity Problem. The main purpose of this Paper is to solve these Problems. In this Paper, we suggest the user's predicting preference method using Bayesian estimated value and the associative user clustering for the recalculation of preference. In addition to this method, to complement a shortcoming, which doesn't regard the attribution of item, we use Representative Attribute-Neighborhood method that is used for the prediction when we find the similar neighborhood through extracting the representative attribution, which most affect the preference. We improved the efficiency by using the associative user's clustering analysis in order to calculate the preference of specific item within the cluster item vector to the collaborative filtering algorithm. Besides, for the problem of the Sparsity and First-Rater, through using Association Rule Hypergraph Partitioning algorithm associative users are clustered according to the genre. New users are classified into one of these genres by Naive Bayes classifier. In addition, in order to get the similarity value between users belonged to the classified genre and new users, and this paper allows the different estimated value to item which user evaluated through Naive Bayes learning. As applying the preference granted the estimated value to Pearson correlation coefficient, it can make the higher accuracy because the errors that cause the missing value come less. We evaluate our method on a large collaborative filtering database of user rating and it significantly outperforms previous proposed method.

Digital Watermarking for Three-Dimensional Polygonal Mesh Models in the DCT Framework (DCT영역에서 3차원 다각형 메쉬 모델의 디지헐 워터마킹 방법)

  • Jeon, Jeong-Hee;Ho, Yo-Sung
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.40 no.3
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    • pp.156-163
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    • 2003
  • Most watermarking techniques insert watermarks into transform coefficients in the frequency domain because we can consider robust or imperceptible frequency bands against malicious attacks to remove them. However, parameterization of 3-D data is not easy because of irregular attribution of connectivity information, while 1-I) or 2-D data is regular. In this paper we propose a new watermarking scheme for 3-D polygonal mesh models in the DCT domain. After we generate triangle strips by traversing the 3-D model and transform its vertex coordinates into the DCT domain, watermark signals are inserted into mid-frequency bands of AC coefficients for robustness and imperceptibility. We demonstrate that our scheme is robust against additive random noise, the affine transformation, and geometry compression by the MPEG-4 SNHC standard.

The Impact of Interactivity in Smart Signage and Flow on the Engagement and Memory Accessibility (스마트 사이니지의 상호작용성과 플로우(Flow)가 인게이지먼트와 기억 접근성에 미치는 영향)

  • Han, Kwang-Seok
    • Journal of the Korea Convergence Society
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    • v.9 no.2
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    • pp.171-176
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    • 2018
  • The purpose of this study is to establish smart signage in a certain space and to analyze not only media ingestion and advertising inducement as well as any information (high vs. low vs. low) and flow level And the memory effect related to whether or not to remember. The results of this study show that the higher the interaction level and the higher the engagement level, the higher the advertising engagement is. In addition, media involvement was high when interaction level was low and flow level was high. Finally, if the level of interactivity is low and the level of flow is high, then non - valued attribution information is more likely to be recalled than the comprehensive evaluation information. If the interaction of smart signage is high and the flow of users is low, Recalled more recall information. In the future, detailed strategies for enhancing user flow will be needed rather than a strategy for unconditional enhancement of interaction in smart signage strategy.

The Concept Analysis of Won-Buddhism's Maumgongbu in Group Counseling based on Walker and Avant's Strategy (Walker와 Avant 기법을 활용한 원불교 마음공부집단상담 프로그램에서의 마음공부의 개념 분석)

  • Yang, Kyung Hee
    • Journal of Oriental Neuropsychiatry
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    • v.24 no.3
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    • pp.229-244
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    • 2013
  • Objectives : The purpose of this study was to provide information about Maumgongbu to meet the needs of people by analysing the concept of Maumgongbu in group counseling. Methods : This study was conducted using Walker and Avant's Concept Analysis Strategy. Dictionaries, Wonbuddhism's Kyunjions and literatures, and participants' journals were reviewed after enrolling in Onsarm maumgongbu group counseling. Results : The attributes of the Maumgongbu include emotion, object, self-reflection, attribution, and creativity. The antecedents of "Maumgongbu" are the conditions arising from negative emotions. The Maumgongbu helps people find the emotional causality of their inner self by self-reflecting, getting out of false belief, restoring positive emotions, maintaining healthy and warm relationships with oneself, family, friends and society. Above all, the Maumgongbu makes people experience tranquility and true happiness and activate their positive energy or power. Conclusions : If there is a clear indication of linkage to principles, attributions, precedents and consequences, and empirical referents to any of Maumgongbu programs, there is no doubt that our understanding of the human mind and lives will be greatly enriched. Furthermore, self-discipline and steadfast complements give us calmness, peacefulness and better quality of life.

A Study on the Determinants of Third Party Logistics Service Suppliers in Dongdaemun Market

  • Zhang, Yu-Liang;Yoo, Chang-Gwon;Kim, Gi-Pyoung
    • Journal of Distribution Science
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    • v.15 no.2
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    • pp.27-36
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    • 2017
  • Purpose - This study was intended to find the selection attribution factors and service satisfaction determinants of third party logistics suppliers in Dongdaemun wholesale market. Research design, data, and methodology - A questionnaire survey was performed, and the retailers and wholesalers in Dongdaemun wholesale market were asked to fill in it. Company employees using third party logistics service were selected by a random sampling method. Results - It is easy for both retailers and wholesalers to use third party logistics service. The logistics companies in Dongdaemun wholesale market have paid more heed to the security of freight and the operability. That is, the freight safety and operating service are the most important factors in selecting third party logistics suppliers, and they both have a close relationship with user satisfaction. There is no relation between service level and recognition in selection factors of third party logistics suppliers. All the responsiveness, operability and informativeness of third-party logistics providers has a significant relationship with user satisfaction. Conclusions - Third party logistics service is entirely different from the existing delivery or transport service. The most market vendors' wish for third party logistics suppliers is the stability of freight and robust operating service. They also demand the responsiveness for special or emergency situation with having information strength.

Evaluation and Functionality Stems Extraction for App Categorization on Apple iTunes Store by Using Mixed Methods : Data Mining for Categorization Improvement

  • Zhang, Chao;Wan, Lili
    • Journal of Information Technology Services
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    • v.17 no.2
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    • pp.111-128
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    • 2018
  • About 3.9 million apps and 24 primary categories can be approved on Apple iTunes Store. Making accurate categorization can potentially receive many benefits for developers, app stores, and users, such as improving discoverability and receiving long-term revenue. However, current categorization problems may cause usage inefficiency and confusion, especially for cross-attribution, etc. This study focused on evaluating the reliability of app categorization on Apple iTunes Store by using several rounds of inter-rater reliability statistics, locating categorization problems based on Machine Learning, and making more accurate suggestions about representative functionality stems for each primary category. A mixed methods research was performed and total 4905 popular apps were observed. The original categorization was proved to be substantial reliable but need further improvement. The representative functionality stems for each category were identified. This paper may provide some fusion research experience and methodological suggestions in categorization research field and improve app store's categorization in discoverability.

An Exploratory Study on the Selection Attributes of Food Courts through the Conjoint Analysis (컨조인트 분석을 통한 푸드코트 선택 속성에 관한 탐색적 연구)

  • Jung, Young-Woo;Lee, Eun-Yong
    • Culinary science and hospitality research
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    • v.14 no.4
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    • pp.106-118
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    • 2008
  • Even though the number of food courts increased in recent years, there were few studies about them. Considering the effects of a food court on the sales of a mall or other shopping spots, it was necessary to analyze what kind of attribute attracts customers. For this research, conjoint analysis was used to test which attribute was the most decisive factor, and the results of this study were as follows. First, price was the first factor that customers attached great importance to. Next were time required from order to eat and menu diversity. Second, cluster analysis used by the individual value of utilities derived through the conjoint analysis showed two clusters. Third, the most preferred food court form gained 35.4% potential market share from the simulation. The information gained from this analysis provided an important starting point for marketing and determined what kind of attribution was considered in being part of the malls or buildings. Also, it could be made full use of creating and executing the most effective marketing strategies.

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Pattern classification on the basis of unnecessary attributes reduction in fuzzy rule-based systems (퍼지규칙 기반 시스템에서 불필요한 속성 감축에 의한 패턴분류)

  • Son, Chang-Sik;Kim, Doo-Ywan
    • Journal of Internet Computing and Services
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    • v.8 no.3
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    • pp.109-118
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    • 2007
  • This paper proposed a method that can be simply analyzed instead of the basic general Fuzzy rule that its insufficient characters are cut out. Based on the proposed method. Rough sets are used to eliminate the incomplete attributes included in the rule and also for a classification more precise; the agreement of the membership function's output extracted the maximum attributes. Besides, the proposed method in the simulation shows that in order to verify the validity, compare the max-product result of fuzzy before and after reducing rule hosed on the rice taste data; then, we can see that both the max-product result of fuzzy before and after reducing rule are exactly the same; for a verification more objective, we compared the defuzzificated real number section.

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Self-Directed Learning Strategies of High Academic Achievers Majoring in Engineering (공학전공 우수학습자의 자기주도학습전략 탐색)

  • Jin, Sung-Hee
    • Journal of Engineering Education Research
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    • v.16 no.5
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    • pp.24-35
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    • 2013
  • This study aims to explore self-directed learning strategies of high academic achievers majoring in engineering. The research participants were 21 fourth-year students who had attained the first or second highest cumulative grade point average in each department during the past three-year and were asked to write an essay on "my successful learning methods or techniques." The essays were analyzed by theme analysis method which is one of the qualitative methods to extract the self-directed learning strategies used by high performing students. According to the results of this study, the self-directed learning strategies of excellent students could be categorized into fundamental strategies to induce self-directed learning, preparatory strategies, implementation strategies and management strategies for marinating self-directed learning. Detail information on each category is as follow: 1) fundamental strategies refer to positive and pleasant mind, academic confidence and effort attribution, 2) preparatory strategies refer to concrete and challenging goal setting, establishment of learning strategies adjusted courses characteristics and practical learning planning, 3) implementation strategies refer to intensive learning in class, knowledge exploration, knowledge acquisition, social networking and exhaustive preparation for exams and 4) management strategies refer to time management and learning environment management.