• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.61-79
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• 2016

Recently, digital broadcasting service is growing as a TV-based commerce market spread. However, in previous studies, many researchers studied TV home shopping and T-Commerce separately each other, and there is little research on the attribute to increase the satisfaction of consumers. In this study, we analyzed the attribute to increase satisfaction of consumer using TV-based commerce, and we propose to the direction to move forward. We selected characteristics of TV home shopping and T-Commerce through previous studies, and analyzed satisfaction of customers with quality attributes of TV-based commerce using KANO model and ASC(Average Satisfaction Coefficient).

• Journal of the Korean Institute of Landscape Architecture
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• v.28 no.1
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• pp.19-28
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• 2000

The purposes of this study are two folds: a) to introduce conjoint choice model to research the choice behavior of theme park users, and b) to suggest the strategies to strengthen the competitiveness of theme parks. The major four theme parks in Seoul metropolitan areas were selected as study areas. A leading polling agency was employed to select 432 respondents by probability sampling and to conduct face-to-face interview. Both alternative generating and choice set generating fractional factorial design were conducted simultaneously to meet the necessary and sufficient conditions for calibration of the conjoint choice model. Dummy coding was used to represent the attribute levels, and the alternative-specific model was calibrated. The goodness-of-fit of the model was quite satisfactory($\rho$$^2$=0.47950), and most parameters values had to expected sign and magnitude. Car was preferred transport mode to shuttle bus for visiting theme parks ; however the most ideal attribute levels only were estimated significantly. Most attribute levels of shuttle bus were estimated significantly except the Dream Land, which is the least attractive park among study areas. Simulation results showed that the shuttle bus was a mode worth providing to switch the current car dominant visiting pattern of theme parks, which will be one the effective strategies to attract more patrons, especially for potential users adjacent to parks. Several ideals were suggested for future researches, in terms of utilization of more general utility function and new base alternative, and inclusion of more salient attributes such as constraints in the model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3128-3149
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• 2018

A number of effective methods for multiple-attribute group decision making (MAGDM) with interval-valued intuitionistic fuzzy numbers (IVIFNs) have been proposed in recent years. However, the different methods frequently yield different, even sometimes contradictory, results for the same problem. In this paper a novel criterion to determine the advantages and disadvantages of different methods is proposed. First, the decision-making process is divided into three parts: translation of experts' preferences, aggregation of experts' opinions, and comparison of the alternatives. Experts' preferences aggregation is considered the core step, and the quality of the collective matrix is considered the most important evaluation index for the aggregation methods. Then, methods to calculate the similarity measure, correlation, correlation coefficient, and energy of the intuitionistic fuzzy matrices are proposed, which are employed to evaluate the collective matrix. Thus, the optimal method can be selected by comparing the collective matrices when all the methods yield different results. Finally, a novel approach for aggregating experts' preferences with IVIFN is presented. In this approach, experts' preferences are mapped as points into two-dimensional planes, with the plant growth simulation algorithm (PGSA) being employed to calculate the optimal rally points, which are inversely mapped to IVIFNs to establish the collective matrix. In the study, four different methods are used to address one example problem to illustrate the feasibility and effectiveness of the proposed approach.

• Journal of the Korean Home Economics Association
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• v.39 no.10
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• pp.55-67
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• 2001

The purpose of this study were 1) to find out the benefits sought factors and segment the customers of internet shopping mall, 2) to find out the store image factors of internet shopping mall, and 3) to analyze the internet shopping mall market using perceptual map of segmented groups. The questionnaires dealing with attribute dimension of internet shopping mall image, benefits sought, and demographic variables were selected from the previous studies or were developed for this study. The data from 319 respondents which were collected through the internet survey site was analyzed by factor analysis, cluster analysis, one-way ANOVA, and $X^2$-test. The results of this study were as follows: 1. Benefit sought by consumer in internet shopping malls was found to include six different factors: assortments of products, search efficiency, brand/fashionability, delivery convenience, promotion service and informativeness. 2. As a result of subdividing the consumers, four distinctive groups were formed on the basis of benefit factors: multi-benefit oriented group, convenience oriented group, brand oriented group and low-benefit oriented group. Demographic traits such as education and income level were proven to significantly differentiate the benefit segments. 3. In the structural components of internet shopping-malls image, product/information, service/convenience and economy were drawn from attribute dimensions. 4. 12 perceptual maps of internet shopping mall image were constructed and each ideal vector were drawn.

• Ocean and Polar Research
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• v.29 no.1
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• pp.69-80
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• 2007

This paper attempts to measure the environmental value of the Nakdong-river estuary, which is ecologically important but confronted with the threat of development. Especially, in order to elicit the environmental values of its four attributes, contingent valuation method(CVM) based on multi-attribute utility theory is applied and the CVM survey was rigorously designed to comply with the guidelines for best-practiced CVM studies. We surveyed a randomly selected sample of 400 and 350 households in Busan and six large cities(Seoul, Incheon, Daegu, Daejeon, Gwangju, and Ulsan), respectively and asked respondents questions in person-to-person interviews about how they would willing to pay for the estuary conservation and management program. Respondents overall accepted the contingent market and were willing to contribute a significant amount(2,457 won in Busan and 3,560 won in six large cities), on average, per household per year, which implies that there exists a large difference between the two. The aggregate values of the Nakdong-river estuary in Busan and six large cities amount to 2.92 and 22.32 billion won, respectively, per year. In addition, expanding the values to Korea produces 51.34 billion won per year. The quantitative values can be utilized in planning and decision-making about development versus conservation of the estuary.

• Current Research on Agriculture and Life Sciences
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• v.26
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• pp.45-54
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• 2008

The purpose of this research is to develope street trees management program for more an effective street trees management. The principal point of this program is to relate spatial data and attribute data that is the main concept in GIS(Geographic Information System). To do this function, MapObjects which is ESRI's mapping and GIS components was used to process spatial data and Access which had been developed by MS was used to manipulate attribute data in this program. Visual Basic also was used to design and develop user interfaces and procedures, relate two sort of data, and lastly complete Application. Relational data model was adopted to design tables and their relation, Antenucci's GIS development model was selected to design and complete this program. The configuration of this application is composed of management data and reference data. The management data includes the location of street tree, a growth condition, a surrounding environment, the characters of tree, an equipments, a management records and etc. The reference data include general information about tree, blight and insects.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.84-91
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• 2021

The purpose of this study is to investigate the structural relationship between resort selection attributes, emotional responses, and empirical values of scuba diving participants. The general population who enjoys scuba diving in Korea was selected as the population. Using the convenience sampling method, 553 of the 600 questionnaire samples were extracted as the final valid sample. For data processing, frequency analysis, exploratory factor analysis, and Cronbach's α test were performed using SPSS 23, and confirmatory factor analysis and structural equation model analysis were performed with AMOS 18. The results are as follows: First, among the sub-factors of selection attributes, equipment, facility environment, and diving point showed a positive effect on emotional response, but staff service did not have any significant effect. Second, the emotional response positively affected by the selection attribute showed a positive effect on all factors of service excellence, consumer utility, fun value, and aesthetic value of empirical value. Therefore, scuba diving resort managers must recognize the importance of equipment, facility environment, and diving point among these selection attributes of customers. And to satisfy the customer needs the resort must accurately identify the needs for diving equipment, facility environment and diving point. Various methods for this should be explored through the needs of the identified customers, and efforts should be made to provide safe equipment, comfortable facilities, and various diving points.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.27-36
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• 2019

In this study, experiments on the improvement of the emotion classification, analysis and accuracy of EEG data were proceeded, which applied DEAP (a Database for Emotion Analysis using Physiological signals) dataset. In the experiment, total 32 of EEG channel data measured from 32 of subjects were applied. In pre-processing step, 256Hz sampling tasks of the EEG data were conducted, each wave range of the frequency (Hz); Theta, Slow-alpha, Alpha, Beta and Gamma were then extracted by using Finite Impulse Response Filter. After the extracted data were classified through Time-frequency transform, the data were purified through Independent Component Analysis to delete artifacts. The purified data were converted into CSV file format in order to conduct experiments of Machine learning algorithm and Arousal-Valence plane was used in the criteria of the emotion classification. The emotions were categorized into three-sections; 'Positive', 'Negative' and 'Neutral' meaning the tranquil (neutral) emotional condition. Data of 'Neutral' condition were classified by using Cz(Central zero) channel configured as Reference channel. To enhance the accuracy ratio, the experiment was performed by applying the attributes selected by ASC(Attribute Selected Classifier). In "Arousal" sector, the accuracy of this study's experiments was higher at "32.48%" than Koelstra's results. And the result of ASC showed higher accuracy at "8.13%" compare to the Liu's results in "Valence". In the experiment of Random Forest Classifier adapting ASC to improve accuracy, the higher accuracy rate at "2.68%" was confirmed than Total mean as the criterion compare to the existing researches.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.29-40
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• 2024

Recently, the technology of autonomous driving, one of the core of the fourth industrial revolution, is developing, but sensor-based autonomous driving is showing limitations, such as accidents in unexpected situations, To compensate for this, HD-map is being used as a core infrastructure for autonomous driving, and interest in the public and private sectors is increasing, and various studies and technology developments are being conducted to secure the latest and accuracy of HD-map. Currently, NGII will be newly built in urban areas and major roads across the country, including the metropolitan area, where self-driving cars are expected to run, and is working to minimize data error rates through quality verification. Therefore, this study analyzes the spatial relationship of reference objects in the attribute structuring process for rapid and accurate renewal and production of HD-map under construction by NGII, By applying the attribute input automation methodology of the reference object in which spatial relations are established using the library of open source-based PyQGIS, target sites were selected for each road type, such as high-speed national highways, general national highways, and C-ITS demonstration sections. Using the attribute automation tool developed in this study, it took about 2 to 5 minutes for each target location to automatically input the attributes of the spatial relationship reference object, As a result of automation of attribute input for reference objects, attribute input accuracy of 86.4% for high-speed national highways, 79.7% for general national highways, 82.4% for C-ITS, and 82.8% on average were secured.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.213-222
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• 1998

The objective of this study is to develop a knowledge-based scheduler applying simulation and knowledge base. This study utilizes a machine induction to build knowledge base which enables knowledge acquisition without domain expert. In this study, the best job dispatching rule for each order is selected according to the specifications of the order information. And these results are built to the fact base and knowledge base using the attribute-oriented induction method and simulation. When a new order enters in the developed system, the scheduler retrieves the knowledge base in order to find a matching record. If there is a matching record, the scheduling will be carried out by using the job dispatching rule saved in the knowledge base. Otherwise the best rule will be added to the knowledge base as a new record after scheduling to all the rules. When all these above steps finished the system will furnish a learning function.