• Title/Summary/Keyword: Brand identification

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A Comparative Analysis on Image Structures of Jeju 'Oreum' between Koreans and Foreigners (제주 '오름'에 대한 내국인과 외국인의 경관이미지 비교 분석)

  • Suh, Joo-Hwan;Kim, Sang-Beom;Rho, Jae-Hyun;Huh, Joon
    • Journal of the Korean Institute of Landscape Architecture
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    • v.37 no.1
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    • pp.65-77
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    • 2009
  • This study conducted a comparative analysis between Koreans and foreigners on how they feel of the 'Oreum' so that the data could be used to conserve and utilize 'Oreum' as a brand of Jeju, which is one of the natural and original sceneries of the island along with Halla Mountain. Four aerial photo slides were selected to be assessed among 18 overlooked views of 'Oreums' through quasi-preliminary and preliminary surveys. The assessment group was divided into native and foreigner groups. Image and preference were measured based on 7 step categorization on 26 adjectives, and factor analysis was implemented. The selected factors from factor analysis reflected that calmness was recognized as common image identification variable to natives and foreigners. However, foreigners choose 'dynamics', 'peculiarity' and 'grandeur' in order to explain the image while Koreans selected words in the order of 'attractiveness', 'grandeur', 'dynamics' and 'peculiarity'. This means Koreans identify the image of 'Oreum' as absolute beauty while foreigners see the dynamics and relative peculiarity as its attractive point. As a result of factor score, preference and multiple regression analysis, Koreans selected 'calmness', 'attractiveness' and 'dynamics' as important variables to explain preference. On the other hand, foreigners choose 'dynamics' and 'calmness' as well as 'evenness', 'peculiarity' and 'simplicity'. This represents that foreigners are highly influenced by the structural peculiarity and simplicity on the image preference.

Identification of Microorganisms from Eggs in Hypermarket in the Northern Gyeonggi Area (경기 북부 일부 지역 대형 마트 유통계란에 오염된 미생물의 분리)

  • Chun, Myoung-Sook;Hong, Seung-Hee
    • The Korean Journal of Food And Nutrition
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    • v.22 no.3
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    • pp.396-401
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    • 2009
  • Microorganisms or their toxins can be transferred to eggs and cause food poisoning in humans. Therefore, this study was conducted to detect microbial contamination of eggs and to identify microorganisms in any contaminated eggs. Four different brands of eggs were collected from hypermarkets in the northern Gyeonggi area. The total bacterial counts on the shells of the eggs varied greatly between brands. In addition, various bacterial species including Klebsiella pneumoniae, Pseudomonas mendocina, Alcaligenes xylosoxidans, Alcaligenes faecalis, and Enterobacter cloacae were identified on eggshells. Furthermore, mean of total bacterial counts of four brands was $3.4{\times}10^4 cfu/m{\ell}$ and E. coli was detected on the eggshell of one brand egg. However, Salmonella was not identified on all brands of collected eggs. We also demonstrated that the E. coli isolated from the eggshell was not pathogenic based on the absence of pathogen-specific gene expression patterns. Taken together, the result of this study indicate that strict quality control and improved distribution controls are required to decrease microbial contamination and improve human health.

Financial Fraud Detection using Text Mining Analysis against Municipal Cybercriminality (지자체 사이버 공간 안전을 위한 금융사기 탐지 텍스트 마이닝 방법)

  • Choi, Sukjae;Lee, Jungwon;Kwon, Ohbyung
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.119-138
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    • 2017
  • Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.

Typology of Korean Eco-sumers: Based on Clothing Disposal Behaviors (관우한국생태학적일개예설(关于韩国生态学的一个预设): 기우복장탑배적행위(基于服装搭配的行为))

  • Sung, Hee-Won;Kincade, Doris H.
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.1
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    • pp.59-69
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    • 2010
  • Green or an environmental consciousness has been a major issue for businesses and government offices, as well as consumers, worldwide. In response to this movement, the Korean government announced, in the early 2000s, the era of "Green Growth" as a way to encourage green-related business activities. The Korean fashion industry, in various levels of involvement, presents diverse eco-friendly products as a part of the green movement. These apparel products include organic products and recycled clothing. For these companies to be successful, they need information about who are the consumers who consider green issues (e.g., environmental sustainability) as part of their personal values when making a decision for product purchase, use, and disposal. These consumers can be considered as eco-sumers. Previous studies have examined consumers' purchase intention for or with eco-friendly products. In addition, studies have examined influential factors used to identify the eco-sumers or green consumers. However, limited attention was paid to eco-sumers' disposal or recycling behavior of clothes in comparison with their green product purchases. Clothing disposal behaviors are ways that consumer can get rid of unused clothing and in clue temporarily lending the item or permanently eliminating the item by "handing down" (e.g., giving it to a younger sibling), donating, exchanging, selling, or simply throwing it away. Accordingly, examining purchasing behaviors of eco-friendly fashion items in conjunction with clothing disposal behaviors should improve understanding of a consumer's clothing consumption behavior from the environmental perspective. The purpose of this exploratory study is to provide descriptive information about Korean eco-sumers who have ecologically-favorable lifestyles and behaviors when buying and disposing of clothes. The objectives of this study are to (a) categorize Koreans on the basis of clothing disposal behaviors; (b) investigate the differences in demographics, lifestyles, and clothing consumption values among segments; and (c) compare the purchase intention of eco-friendly fashion items and influential factors among segments. A self-administered questionnaire was developed based on previous studies. The questionnaire included 10 items of clothing disposal behavior, 22 items of LOHAS (Lifestyles of Health and Sustainability) characteristics, and 19 items of consumption values, measured by five-point Likert-type scales. In addition, the purchase intention of two eco-friendly fashion items and 11 attributes of each item were measured by seven-point Likert type scales. Two polyester fleece pullovers, made from fabric created from recycled bottles with the PET identification code, were selected from one Korean brand and one US imported brand among outdoor sportswear brands. A brief description of each product with a color picture was provided in the survey. Demographic variables (i.e., gender, age, marital status, education level, income, occupation) were also included. The data were collected through a professional web survey agency during May 2009. A total of 600 final usable questionnaires were analyzed. The age of respondents ranged from 20 to 49 years old with a mean age of 34 years. Fifty percent of the respondents were males and about 58% were married, and 62% reported having earned university degrees. Principal components factor analysis with varimax rotation was used to identify the underlying dimensions of the clothing disposal behavior scale, and three factors were generated (i.e., reselling behavior, donating behavior, non-recycling behavior). To categorize the respondents on the basis of clothing disposal behaviors, k-mean cluster analysis was used, and three segments were obtained. These consumer segments were labeled as 'Resale Group', 'Donation Group', and 'Non-Recycling Group.' The classification results indicated approximately 98 percent of the original cases were correctly classified. With respect to demographic characteristics among the three segments, significant differences were found in gender, marital status, occupation, and age. LOHAS characteristics were reduced into the following five factors: self-satisfaction, family orientation, health concern, environmental concern, and voluntary service. Significant differences were found in the LOHAS factors among the three clusters. Resale Group and Donation Group showed a similar predisposition to LOHAS issues while the Non-Recycling Group presented the lowest mean scores on the LOHAS factors compared to the other segments. The Resale and Donation Groups described themselves as enjoying or being satisfied with their lives and spending spare-time with family. In addition, these two groups cared about health and organic foods, and tried to conserve energy and resources. Principal components factor analysis generated clothing consumption values into the following three factors: personal values, social value, and practical value. The ANOVA test with the factors showed differences primarily between the Resale Group and the other two groups. The Resale Group was more concerned about personal value and social value than the other segments. In contrast, the Non-Recycling Group presented the higher level of social value than did Donation Group. In a comparison of the intention to purchase eco-friendly products, the Resale Group showed the highest mean score on intent to purchase Product A. On the other hand, the Donation Group presented the highest intention to purchase for Product B among segments. In addition, the mean scores indicated that the Korean product (Product B) was more preferable for purchase than the U.S. product (Product A). Stepwise regression analysis was used to identify the influence of product attributes on the purchase intention of eco product. With respect to Product A, design, price and contribution to environmental preservation were significant to predict purchase intention for the Resale Group, while price and compatibility with my image factors were significant for the Donation Group. For the Non-Recycling Group, design, price compatibility with the factors of my image, participation to eco campaign, and contribution to environmental preservation were significant. Price appropriateness was significant for each of the three clusters. With respect to Product B, design, price and compatibility with my image factors were important, but different attributes were associated significantly with purchase intention for each of the three groups. The influence of LOHAS characteristics and clothing consumption values on intention to purchase Products A and B were also examined. The LOHAS factor of health concern and the personal value factor were significant in the relationships with the purchase intention; however, the explanatory powers were low in the three segments. Findings showed that each group as classified by clothing disposal behaviors showed differences in the attributes of a product, personal values, and the LOHAS characteristics that influenced their purchase intention of eco-friendly products. Findings would enable organizations to understand eco-friendly behavior and to design appropriate strategic decisions to appeal eco-sumers.