• The Research Journal of the Costume Culture
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• v.4 no.2
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• pp.157-171
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• 1996

The purpose of this study was to find out the effect of fashion information source in the stage of purchase decision-making and difference by stage of purchase decision-making and difference by stage of the effect extend, and to analyze the difference by fashion information source. For this study, the data were collected through the questionnaire distributed to 337 female students from five universities. The results are as follows: 1) There was significant difference among the effect to fashion information source according to the purchase decision-making stage. At the adoption stage, fashion information source have the most effect on clothing purchase. 2) The effect of Impersonal Source in the purchase decision-making stage was gradually decreased fro the initial (awareness, interest) sage to the late stage. 3) The effect of Personal Source in the purchase decision-making stage was gradually increased from the initial (awareness, interest) stage to the late stage. 4) Addition stage was highly influenced by friend and family that was Personal Independent Source than other fashion information source. However the final selection on clothing purchase was not influenced by friend and family. 5. There was significant difference among the effect of fashion information source according to the grade. Low garde students were highly influenced by Personal Source on clothing purchase, but high grade students were highly influenced by Impersonal Sources on clothing purchase. 6) There was significant difference among the effect of fashion information source according to the major. The students a majored clothing & textile-design were highly influenced by Impersional Source. These results suggest that fashion information source was significantly different according to purchase decision-making stage and was influenced by grade and major of subjects.

• The Research Journal of the Costume Culture
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• v.12 no.3
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• pp.468-484
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• 2004

The purposes of this study were (1) to segment female college students' apparel shoppers into unique apparel buying decision-making style groups; and (2) to profile for each segment in terms of personal characteristics (material values, change seeking tendency and prestige sensitivity) and fashion information sources. Data were collected through questionnaires from convenient sample of 290 female college students. As a result of cluster analysis and univariate analysis of variance, distinctive consumer decision-making style groups of consumers were identified; Value-maximizing Recreational Shoppers, Brand-Maximizing Emotional Shoppers, and Apathetic Shoppers. These three groups were compared as to the effect of personal characteristics variables and fashion information sources through univariate analysis of variance and chi-square statistics. The result showed that personal characteristics (material values, change seeking tendency and prestige sensitivity) and fashion-information sources do influence the consumer decision-making styles and that these three groups were unique in their decision-making characteristics showing that consumer decision-making styles can be a good segmentation base for apparel market.

• Journal of Information Technology Applications and Management
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• v.14 no.4
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• pp.97-120
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• 2007

Development of information technology and Internet brought big changes in information society. Quantity of information increased rapidly and various types of information were presented through diverse channels. This change brought an impact in electronic commerce environment. A large number of products are transacted in online market. And various search functions and product information are presented for supporting customer's decision making. This study examined the effect of external information on purchase decision-making in electronic commerce environment. An experiment was conducted to see the customer product review, unit sales, etc. on purchase decision-making process in online shopping mall based electronic commerce. As a result of study, external information referring to number of purchasing, positive product review, and reliability of information has a positive effect on purchase-decision. The significance of the study can be found in that it defined 1) external information has an effect on decision-making, 2) positiveness and reliability of product information showed that they have an influence on customer, and 3) when self opinion and other person's opinion are different, one is not satisfied with decision making process. The results of the study can be of practical use in the design and implementation of online shopping mall in electronic commerce.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.377-389
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• 2021

This study aims at investigating the effects of big accounting data on the sustainable business growth of listed firms in Thailand. In addition, it examines the mediating effects of accounting information quality and decision-making effectiveness and the moderating effects of digital innovation on the research relationships. The study's useful samples are the 289 listed Thai companies. To examine the research relationships, the structural equation model and multiple regression analysis are used in this study. According to the results of this study, big accounting data has a significant effect on accounting information quality, decision-making effectiveness, and sustainable business growth. Next, accounting information quality significantly affects decision-making effectiveness and sustainable business growth. Similarly, decision-making effectiveness significantly affects sustainable business growth. Both accounting information quality and decision-making effectiveness mediate the big accounting data-sustainable business growth relationships. Lastly, digital innovation moderates the effects of accounting information quality and decision-making effectiveness on sustainable business growth. Accordingly, In conclusion, big accounting data has emerged as a key source of sustainable competitive advantage. As a result, to succeed in competitive environments, businesses must have a thorough understanding of big accounting data.

• Journal of Distribution Science
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• v.20 no.11
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• pp.89-98
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• 2022

Purpose: Increasing competition in the higher education sector has prompted universities to enhance their marketing efforts and understand their potential customers. The study aims to explore how information sources are used and changed among prospective Vietnamese students during the decision-making process. Research Design, Data, and Methodology: This study undertakes a longitudinal study involving multiple rounds of data collection to better understand the decision-making process of prospective students. Data was collected from 12th -grade students in Vietnam through two rounds of quantitative surveys with 251 students and one round of qualitative interviews, spanning the duration of their senior year. The three stages of the decision-making process correspond to the three stages of pre-purchase period. Results: Most students decide that attending open days, taking career assessments, and looking up information online are the most important information sources to consider. The WOM sources are more important in the early stages, while university-generated sources and events are important in the later stages. Conclusion: Implications from this study may contribute to the design of more effective marketing communications campaigns as university marketers gain a better understanding of the distribution of information sources utilized for each specific stage of the decision-making process.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.287-294
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• 2012

The spread of infectious diseases in the event of livestock is getting faster and the route of spread gets more varied. It is important for the responsible agency to detect early and establish a prevention and surveillance system. If the spread cannot be contained effectively, great damage and loss will be inevitable in terms of social, environment and economic aspects as well as the welfare of the farmers. At present in Korea, a web-based Infectious Livestock Diseases Statistics System (AIMS: Animal Infectious Disease Data Management System) has been already implemented for this purpose and the service is available to the general public. But this system does not provide geospatial information and does not provide support for decision making and does not provide multi-dimensional information. In this study, an open source-based SOLAP (Spatial On-Line Analytical Processing) technology is applied to enable many diverse forms of data analysis from many aspects to support decision making. The SOLAP system was designed to integrate geospatial information and the analysis of information has been largely divided into map-based analysis and table-based analysis.

• Journal of Information Technology Services
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• v.5 no.3
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• pp.99-108
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• 2006

Public institutions are considering adoption of open-source software in the process of information projects. However, there doesn't exist reliable information about an adoption process for open-source software. Performance and stability problems of this software also persist, as a result, current open-source software is not widely used. As a software market and industry grows, Benchmark test has been performed more often than before in order to help customers understand and select the most appropriate product among myriad similar ones. It is certain that more objective and trustful data evidence should be obtained by way of utilizing the procedures and methods of Benchmark Test in decision making process for selecting an open-source software. For this research, Benchmark test was applied as a way of demonstrating performance verification of an open-source software in the public institutions. It is certain that more objective and trustful data evidence should be obtained by way of utilizing the procedures and methods of Benchmark Test in decision making process for selecting an open-source software. It also introduces a case study of a information system, which selected and implemented open-source software, in order to confirm the validity of this research. This research will serve as a guideline to adopt open-source software in governments as well as public institutions.

• Journal of Information Technology Services
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• v.4 no.2
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• pp.61-69
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• 2005

RFID is used for tracking systems in various business fields these days and these systems brought considerable efficiencies and cost savings to companies. Real-time based information acquired through RFID devices could be a valuable source of information for making decisions if it is combined with decision support tools like OLAP of a data warehouse that has originally been designed for analyzing static and historical data. As an effort of extending the data source of a data warehouse, RFID is combined with a data warehouse in this research. And OLAP is designed to analyze the dynamic real-time based information gathered through RFID devices. The implemented prototype shows that ubiquitous computing technology such as RFID could be a valuable data source for a data warehouse and is very useful for making decisions when it is combined with online analysis. The system architecture of such system is suggested.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.1
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• pp.293-315
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• 2017

This study investigated how college students seek and use information sources at the time of their decision making (especially during elections on this study). More than 360 students in 12 colleges located in Seoul were randomly selected and participated in this study. The survey asked them what kind of information sources they use at the time of their decision making as well as when they use information as usual. Several criteria for information evaluation were adopted to analyze information attributes and information seeking behavior of the population. Compare to the previous studies, Internet resources are more used than ever, information credibility and authority affected more to the population's political decision making. Additional examinations were executed to see deeper story of their information seeking at the end.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2534-2546
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• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.