• Journal of the HCI Society of Korea
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• v.11 no.1
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• pp.47-55
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• 2016

Three Dimensional Printing (herein, 3D printing) not only gives novelty and interests to modern people but is also a spotlighted technology that could herald a new industrial revolution. The introduction of various 3D printing service platforms has enabled individuals to easily possess products designed through 3D printing. However, there are still many issues to consider until the era of new manufacturing, when 3D printing becomes available to the general public so that anyone can make and design products with 3D printing. For instance, there needs to be sufficient consideration and research on whether the current 3D printing services can prove their higher capability to produce products conventionally done by machines and hands through 3D printing, and on the meaning of selling a wide range of product families like those of most 3D printing service platforms to the consumers. This study, which was initiated in this context, aimed to gain insight on the directions that 3D printing services need to advance going forward by letting consumers have first-hand experience on 3D printing online service platforms with a wide range of product families and those with relatively limited services, and then asking them to answer multiple-choice and short-answer survey questions on the websites they wish to purchase from, diversity of designs, design satisfaction, perceived technical skills, perceived purchase satisfaction, perceived after-sales service(A/S). As a result, we were able to witness that consumers generally had a strong preference for services with a wide range of product families (e.g. Shapeways) compared to services with a narrow range (e.g. Digital Forming). We also verified that design diversity and the possibility of realizing the designs were the crucial aspects that need to be considered with 3D printing services. Moreover, we also carried out discussions on carrying out design consulting by securing a pool of designers from diverse fields, on providing web-based designing software that can be utilized even by beginners, and on operating shops both online and offline in order to provide more competitive 3D printing services.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.106-116
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• 2022

As part of the Fire Evacuation Service scenario using mobile applications, this study aims to find the appropriate colors to be used in the interface of the application and to define and apply colors that can positively and reliably affect human unstable psychology in the course of evacuating the room in case of fire. In the situation of fire, proper design and placement of the colored escape guidance interface is important, taking into account the psychology of the occupants. However, literature and previous research have shown that colors used to induce evacuation are not suitable for effective evacuation in case of fire. In this study, the purpose of the study was to provide a color that would provide psychological stability in the event of a evacuation in consideration of the psychological issues of those who are still in need of shelter, and to use it to help induce an efficient evacuation in the event of a disaster. Using the image evaluation method, the form and color of images have been derived through frequency analysis to a number of unspecified people, and the main and secondary colors of images were analyzed through KSCA color analysis. Finally, the final application color was constructed through mutual verification between the results by comparing and analyzing the colors obtained through the image evaluation analysis results and the KSCA color analysis results. The results of the study showed that the green line can help stabilize the human mind through comparative analysis with prior research. Therefore, the main color for guiding calm and calm applications in case of fire escape is proposed in the green line. In this study, the experiment with image evaluation cannot accurately measure the effect of factors on color among complex factors. A subsequent study of this will help quantify images if it allows the subject matter of color and image to be defined to some extent through factor analysis.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.