• Journal of Fashion Business
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• v.19 no.2
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• pp.36-52
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• 2015

Nowadays, firms face the challenge of how to balance between the environmental request and business profit under the circumstances of being eco-friendly and sustainable. The purpose of this study was to investigate the effects of business environmental factors on the 4p mix of an eco-friendly textile in the textile fashion firms. This research was conducted by a questionnaire method, in which the questionnaires were distributed to the textile fashion firms. Of the returned questionnaires, one hundred of them were selected to be included in the analysis by developing descriptive statistics, factor analysis, cronbach's alpha, and regression analysis using SPSS18.0. The results of this study were as follows: There were significant effects of the firms' environmental management, organizational structure, and CEOs' environmental sensitivity in descending order of the business internal factors on the textile fashion firms' eco-friendly textile product. The factors of the firms' environmental management, organizational structure(internal factors), and legal regulation(external factor), in descending order, significantly affected the promotion of the eco-friendly textile. The factor of firms' environmental management (internal factor) significantly affected the distribution of the eco-friendly textile. The factors of CEOs' environmental sensitivity(internal factor), legal regulation(external factor), and firms' environmental management(internal factor), in descending order, significantly affected the price of the eco-friendly textile.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.158-163
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• 2008

Ozone monitor based on UV techniques has been widely used due to their signal stability. The high concentration ozone monitor for real time ozone monitoring from ozone generator was composed of a low pressure mercury lamp as UV source and a photo multiplier tube as UV detector. The structure could be very useful for low price high concentration ozone monitor and showed good linearity to ozone in the concentration range between 0.05 and 2wt%. For accurate ambient ozone monitoring, the system composed of a high power pulsed xenon lamp as UV source, an optical spectrometer with a high sensitivity linear CCD array as UV detector. The optical signal form the CCD array was converted to digital signal, and the digital signal was displayed on screen using PC interface. The developed system showed good linearity and sensitivity in relatively low measuring range between 10ppm and 10,000ppm, and showed some feasibility of hish resolution ozone monitor using CCD array as a photodetecor.

• Journal of Korean Home Economics Education Association
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• v.28 no.3
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• pp.79-88
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• 2016

The purpose of this study was to distinguish which food is fast foods and to define the characteristics of fast foods. The 14 kind of foods(hamburger, pizza, fried chicken, raymyeon, hotdog, doughnut, fried fish cake, jajangmyeon udong, ice cream, dukbokki, spaghetti, sandwich, gimbab, and salad) and 5 characteristics of fast foods(takeout, franchise, fast serving, unhealthy, and cheap price foods) were selected based on the dictionary and previous research papers about fast foods for this study. A total of 306 male and female high school student in Daejeon area were participated. The data were gathered by questionnaire and analyzed by SPSS/WIN 18.0 program. The participants evaluated the fast foods as delicious and convenient foods but non-nutritious, i.e. high fat but vitamin deficient foods. Among the 14 foods examined, hamburger, pizza, and fried chicken were the foods which more than 90% of the participants acknowledged to fast foods. Dukbokki, spaghetti, sandwich, gimbab, and salad were the foods which less than 50% of the participant acknowledged to fast foods. Among the 5 characteristics of fast food examined, unhealthy foods showed the highest sensitivity, specificity, predictive value, and odds ratio(0.803, 0.712, 0.597, and 2.79, respectively), and cheap price showed the lowest values of those(0.565, 0.335, 0.242, and 0.85, respectively) for acknowledging foods to fast foods. As conclusion, hamburger, pizza, and fried chicken were the representative foods of fast foods. Fast foods are generally considered as fast served cheap price foods, but the participants did not think the fast foods as fast and cheap foods. The most distinguished characteristics of fast foods in the students' minds was unhealthy foods.

• Journal of Distribution Science
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• v.10 no.8
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• pp.25-34
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• 2012

Understanding customer' lifestyles important for banks because it will guide in determining marketing policies, such as services, pricing, service delivery and promotion decisions. From the customer' lifestyle, banks will know what kind of customers' attitudes, interests and opinions, so they also will understand what the costumer' needs and what services needed by them. For Islamic banks, customers understanding are important because, nowadays, the competition of the banks is not only with other Islamic banks but also with the well-established conventional banks offering Islamic products or services The aims of this research paper are to describe what factors underline the customer's lifestyle of both Islamic and conventional bank, to segment the bank customers based on their lifestyles and investigate the profile of each segments, to compare the characteristics of the segments, and to identify marketing policies based on the characteristics. The population of the study is banking customers in Indonesia, in which the researchers have used judgment sampling as sample selection. There were 186 customers of Islamic banks and 244 customers of conventional bank as respondents in this study. Statistical methods employed were exploratory factor analysis and cluster analysis. The finding of the study shows that there are twelve factor underlining the customers' lifestyle, namely: factor of fashion conscious, internet usage, sports spectator, financial and technology optimism, price sensitivity, independent, compulsive housekeeper, new brand tryer community activities, opinion leader, credit usage, and homebody. In addition, for Islamic banking, there are two market segments, namely fashionable-independent and innovative-social segment. Based on the lifestyle characteristics, the first segment has higher level in factor of fashion conscious, homebody, independent, optimism and price conscious, which is therefore called fashionable-independent segment. On the other hand, the second cluster has higher level in factor of new brand tryer, community minded, sport spectator, credit user, internet usage, opinion leader, and compulsive housekeeper, which is therefore called the innovative-social segment. Furthermore, for conventional banking, there are also two segments, namely persuasive-optimistic and sensitive-independent segment. The first segment has higher level on some factors, namely: opinion leader, optimism, internet usage rate, credit usage level, sport spectator, and new brand tryer. On the other hand, the second cluster is characterized by higher level in factor of price conscious, confidence, community minded, homebody, fashion conscious, and compulsive housekeeper. Managerial implications for the management of Islamic banks could be identified in this study as follows. Firstly, the twelve lifestyle factors of this study could be an alternative view in observe Islamic banking customers. The domination of both the fashionable conscious and the internet usage factor show that the aspects are quite instrumental in perceiving the customer' lifestyles, in which reflects the importance of these two aspects to customers. Secondly, in serving their customers, Islamic banks need to understand the customer lifestyle, in which the lifestyle segments found in this study provide a guide of how their needs were reflected. Finally, by understanding the segments and the characteristics each segment of the conventional banks, Islamic banks could adjust their marketing strategies differently from the conventional banks.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.27-38
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• 2002

VTIS(Value-added Traffic Information System), among the sub-systems of ATIS, is an Advanced Traffic System which innovates efficiency and safety. And this system, having marketability and publicness, is very important. Moreover, This system offers definite traffic information according to the demand of specified users. And it is expected to produce additional spread effects because of high participation rate of private sector. However, the VTIS service media are varied and there are varied optimal Prices and payment methods according to each medium. Because of that, there needs the study on these problems or optimal criteria. But because existing studies were devoted to estimate the optimal route, the study toward the optimal price which was considered part of user and service use demand do not exist. Accordingly, we surveyed under imaginary alternative pricing scenarios and forecasted the use demand of VTIS by using Binary Logit model. Also, for the users who answered that they would use VTIS service in survey, we classified their use's behaviors as four categories and estimated the use ratio to each category by using Ordered Probit model. Last, using sensitivity analysis for results form above, we derived the optimal price that is 2800won in monthly. 145won in payment per call. Then, VTIS service use rate is respectively 65%, 75%.

• Journal of the Korean association of regional geographers
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• v.3 no.2
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• pp.151-162
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• 1997

Although modern versions of the traditional Von $Th{\ddot{u}}nen$ theory have contributed to a description of spatial organization in agriculture, they did not incorporate the market mechanism as an integral part of location theory. This deficiency has been indicated and new mathematical structure has been proposed elsewhere by the author. The closed model, which simultaneously considered a basic principle of supply and demand, exposed a computational complexity. Based on the problem, this study attempts to extend market mechanism in order to consider the influence of city (market) size in agricultural location theory. To theoretically explore the economic relationship in a location theory, this study simplifies agricultural activity as just two activities in one-dimensional spatial economy. The problem has been solved by equating total supply and demand of agricultural products, and then by determining each agricultural price from the relationship. All of the mathematical problems have been arranged in matrix form. First, the traditional model and closed model have been compared by quantitative comparative statics which provides the sensitivity test for each model. The results have shown that the traditional model shows a relatively excessive change in land use, besides the deficiency of a constant agricultural price. Second, the effects of the size of market town and its population increase were examined, using the closed model. In this case, the price of agricultural product is increased, and the land use is extended outward. This proves that locational rent is related to the expansion of land use. Third, environmental uncertainty was associated with the closed model, in order to further consider the difference of farmers attitude in strategic perspective. In this study, two extreme attitudes, which reflects the maximum average expected returns and the maximum guaranteed returns, were examined in their land use and their effects on the prices of agricultural products. It was shown that the two farmers attitudes can be interconnected with location theory. Due to the exogenous data, the differences in the area of land use and total quantities of agricultural products were not clearly shown in this study. However, it was shown that the land use pattern is very different. That is, maximum guaranteed return model reveals a mixed land use pattern around the market town. Basically, this study shows some spatial and economic implications related to Von $Th{\ddot{u}}nen$ model.

• The Journal of Fisheries Business Administration
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• v.48 no.3
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• pp.1-14
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• 2017

The aim of this study is to examine profiles of consumers in Thai seaweed market segments. A total of 321 consumers were surveyed in bangkok, thailand. The multiple regression analysis performed indicates that consumer preference toward seaweed snack is significantly influenced by seaweed consumption frequency. The cluster analysis performed indicates that there are three segments based on consumer purchasing attributes toward seaweed snack : leading type, pursuing type, beginner type. The results show that there are consumer segment with different purchasing attributes level and seaweed preference. in this study Thai seaweed market's biggest consumer is leading type consumer(n=40.8%) that have high level of purchasing attributes toward seaweed snack when compared to other segments. pursuing type segment(n=27.4%) consists of consumers who have low level of purchasing attributes but have high consumption frequency. beginner type segment(n=31.8%) consists of consumers who rarely eat seaweed snack and have high price sensitivity. This study can inform Thai seaweed consumer's behavior and effective segment market strategies and target consumer based on purchasing behavior toward seaweed snack.

• Culinary science and hospitality research
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• v.16 no.2
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• pp.322-329
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• 2010

The objective of this study is to investigate the attributes of purchasing soybean paste and calculate the priorities among the attributes focusing on traditional soybean paste in the Jeju region. To achieve this goal, the priorities was analyzed through a survey for restaurants and housewives with AHP methodology. The result showed that soybean paste made in B company was most preferred among domestic products, followed by one made in A company and traditional Jeju soybean paste. As a result of the sensitivity analysis, traditional Jeju soybean paste is considered to have a high market share if its price can be lower.

• Proceedings of the Korean Environmental Health Society Conference
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• 2004.06a
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• pp.139-141
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• 2004

Emission of volatile organic compounds (VOCs) are one of the popular issues of air pollution in Korea, especially in Ulsan city, where much chemical plants are located. It is necessary to detect the VOCs precisely in order to control the air pollution during the plant operation. In general, to examine the concentration of VOCs, gas chromatography (GC) is used. However, most plant operators are using the easy operating handy VOCs detector, which is imported, because GC is difficult to treat and the installation price is high although it is very useful equipment. Therefore, the development of the VOCs detector becomes one of the urgent issues. In this study, sensing characteristics of selected VOCs for the development of VOCs detector was investigated. Semiconductor sensor and several VOCs such as aliphatic, aromatic, and non-homogeneous hydrocarbons were used for the experiment. Through the various experiments, sensor used in the experiment has shown high linearity and sensitivity for most VOCs in the range of 1 -500 ppm concentration.

• Journal of Construction Engineering and Project Management
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• v.6 no.3
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• pp.1-7
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• 2016

The purpose of this paper is to develop a model for selecting the best contractor in the Gaza Strip using the Artificial Neural Network (ANN). The contractor's selection methods and criteria were identified using a field survey. Fifty four engineers were asked to fill a questionnaire that covers factors related to the selection criteria of contractors practiced in Gaza Strip. The results shows that the dominant part of respondents (91%) confirmed that the current awarding method "the lowest bid price" is considered one of the major problems of the construction sector, "award the bid to the highest weight after combination of the technical and financial scores" represented 50% of the respondents. The criteria weights were determined based on Relative Importance Index (RII. Ninety-one tenders(13 projects) were used to train and test the ANN model after re-evaluating the contractors depend on the weights of factors to select the best contractor who achieves the highest score. Neurosolution software was used to train the models. The results of the trained models indicated that neural network reasonably succeeded in selection the best contractor with 95.96% accuracy. The performed sensitivity analysis showed that the profitability and capital of company are the most influential parameters in selection contractors. This model gives chance to the owner to be more accurate in selecting the most appropriate contractor.