• Asia Marketing Journal
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• v.14 no.2
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• pp.65-96
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• 2012

Brand has received much attention from considerable marketing research. When consumers consume product or services, they are exposed to a lot of brand related stimuli. These contain brand personality, brand experience, brand identity, brand communications and so on. A special kind of new crisis occasionally confronting companies' brand management today is the brand related rumor. An important influence on consumers' purchase decision making is the word-of-mouth spread by other consumers and most decisions are influenced by other's recommendations. In light of this influence, firms have reasonable reason to study and understand consumer-to-consumer communication such as brand rumor. The importance of brand rumor to marketers is increasing as the number of internet user and SNS(social network service) site grows. Due to the development of internet technology, people can spread rumors without the limitation of time, space and place. However relatively few studies have been published in marketing journals and little is known about brand rumors in the marketplace. The study of rumor has a long history in all major social science. But very few studies have dealt with the antecedents and consequences of any kind of brand rumor. Rumor has been generally described as a story or statement in general circulation without proper confirmation or certainty as to fact. And it also can be defined as an unconfirmed proposition, passed along from people to people. Rosnow(1991) claimed that rumors were transmitted because people needed to explain ambiguous and uncertain events and talking about them reduced associated anxiety. Especially negative rumors are believed to have the potential to devastate a company's reputation and relations with customers. From the perspective of marketer, negative rumors are considered harmful and extremely difficult to control in general. It is becoming a threat to a company's sustainability and sometimes leads to negative brand image and loss of customers. Thus there is a growing concern that these negative rumors can damage brands' reputations and lead them to financial disaster too. In this study we aimed to distinguish antecedents of brand rumor transmission and investigate the effects of brand rumor characteristics on rumor spread intention. We also found key components in personal acceptance of brand rumor. In contextualist perspective, we tried to unify the traditional psychological and sociological views. In this unified research approach we defined brand rumor's characteristics based on five major variables that had been found to influence the process of rumor spread intention. The five factors of usefulness, source credibility, message credibility, worry, and vividness, encompass multi level elements of brand rumor. We also selected product involvement as a control variable. To perform the empirical research, imaginary Korean 'Kimch' brand and related contamination rumor was created and proposed. Questionnaires were collected from 178 Korean samples. Data were collected from college students who have been experienced the focal product. College students were regarded as good subjects because they have a tendency to express their opinions in detail. PLS(partial least square) method was adopted to analyze the relations between variables in the equation model. The most widely adopted causal modeling method is LISREL. However it is poorly suited to deal with relatively small data samples and can yield not proper solutions in some cases. PLS has been developed to avoid some of these limitations and provide more reliable results. To test the reliability using SPSS 16 s/w, Cronbach alpha was examined and all the values were appropriate showing alpha values between .802 and .953. Subsequently, confirmatory factor analysis was conducted successfully. And structural equation modeling has been used to analyze the research model using smartPLS(ver. 2.0) s/w. Overall, R² of adoption of rumor is .476 and R² of intention of rumor transmission is .218. The overall model showed a satisfactory fit. The empirical results can be summarized as follows. According to the results, the variables of brand rumor characteristic such as source credibility, message credibility, worry, and vividness affect argument strength of rumor. And argument strength of rumor also affects rumor intention. On the other hand, the relationship between perceived usefulness and argument strength of rumor is not significant. The moderating effect of product involvement on the relations between argument strength of rumor and rumor W.O.M intention is not supported neither. Consequently this study suggests some managerial and academic implications. We consider some implications for corporate crisis management planning, PR and brand management. This results show marketers that rumor is a critical factor for managing strong brand assets. Also for researchers, brand rumor should become an important thesis of their interests to understand the relationship between consumer and brand. Recently many brand managers and marketers have focused on the short-term view. They just focused on strengthen the positive brand image. According to this study we suggested that effective brand management requires managing negative brand rumors with a long-term view of marketing decisions.

• The Korean Journal of Archival Studies
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• no.51
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• pp.133-173
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• 2017

The records and archives center provide a variety of archival information services in an effort to get closer to the public. However, there are still some problems with regard to the lack of awareness of records and archives. In order to activate the use of archives, it is necessary to understand the users of archives. Given the problems, this study aims to investigate the awareness of records and archives in university students who are potential users of archives as well as to suggest methods to activate the use of records and archives reflecting the characteristics of university students' awareness. As such, this study surveyed 182 university students at J university. The questionnaire items referred to Market & Opinion Research International (MORI) (2003) as a part of the projects conducted by the Museums Libraries Archives Council (MLA) and Cho's study (2008). The questionnaire items consisted of four major areas: awareness of records and archives, experience with records and archives or reasons of not using them, requirements for the use of archives by potential users, and efficient method of promoting archives. As a result of the survey, most of the university students are indifferent to records. However, they recognized that it is highly important to manage records that are related to historical values and archives that are relevant to information values. In addition, they showed a positive intention to use the archives in the future; thus, it is highly likely for them to be converted into active users through appropriate services. Based on the results, this study proposed important considerations for activating the use of the archives to university students, and suggested methods to activate the archives in terms of user education, program development, and user segmentation.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.4
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• pp.277-301
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• 2020

This study surveyed 503 adults to examine the effect of gaming disorder classification, recently announced by World Health Organization(WHO), when it is applied to Korean game market. Considering the difference in respondents' background knowledge on gaming disorder, half of the respondents were randomly assigned to read an informative news article describing WHO's decision and its expected effect on domestic game industry. Based on previous literature of gaming disorder, we categorized respondents into a normal-use group and a potentially problematic-use group. As a result of analyses, it was found that the gaming disorder classification would yield overall reduction of game-related consumption in terms of gaming time(24%), game cost(28%), the number of games(22%), etc. The potentially problematic group showed higher willingness to pay for gaming than the normal group did, even if the game cost presumably increases due to the gaming disorder classification. A similar outcome was observed in those with high stress levels. This implies that the policy to solve game addiction problems may ironically lead to unexpected cost increases to the target group of the policy. Hence, problematic groups, especially, highly stressful people and the people with the lack of self-control, need to be considered when the gaming disorder classification policy is established. Furthermore, the informative news article had the preventive effect on the attitude and the intention of the people with moderate or high self-control capacity, but not to the people with gaming-additive tendencies, Again, this finding confirms the necessity of the tweezers policy to refine target groups by their characteristics and prepare for differentiated policies. When the gaming disorder classification is simply adopted with no consideration of domestic circumstances, irreversible loss could affect Korean game users, game industries, and related companies. This calls for urgent cooperation between academia, government, and industry to set up appropriate measures to deal with the gaming disorder classification.

• Management & Information Systems Review
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• v.37 no.1
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• pp.139-154
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• 2018

R programming is free and open source system associated with a rich and ever-growing set of libraries of functions developed and submitted by independent end-users. It is recognized as a popular tool for handling big data sets and analyzing them. Reflecting these characteristics, R has been gaining popularity from data analysts. However, the antecedents of R technology acceptance has not been studied yet. In this study we identify and investigates cognitive factors contributing to build user acceptance toward R in education environment. We extend the existing technology acceptance model by incorporating social norms and software capability. It was found that the factors of subjective norm, perceived usefulness, ease of use affect positively on the intention of acceptance R programming. In addition, perceived usefulness is related to subjective norms, perceived ease of use, and software capability. The main difference of this research from the previous ones is that the target system is not a stand-alone. In addition, the system is not static in the sense that the system is not a final version. Instead, R system is evolving and open source system. We applied the Technology Acceptance Model (TAM) to the target system which is a platform where diverse applications such as statistical, big data analyses, and visual rendering can be performed. The model presented in this work can be useful for both colleges that plan to invest in new statistical software and for companies that need to pursue future installations of new technologies. In addition, we identified a modified version of the TAM model which is extended by the constructs such as subjective norm and software capability to the original TAM model. However one of the weak aspects that might inhibit the reliability and validity of the model is that small number of sample size.

• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.645-652
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• 2008

First question: what makes inclusive design truly inclusive? Most inclusive design products are far from being appealing to their intended customers. This is mainly because designers are typically concerned with enhancing the usability, and not the emotional value that creates the connection between the product and the users. Typical solutions are larger displays and larger buttons, and these solutions often make the product less tasteful, graceful, and favorable. As a result, such products become less inclusive, veering from the original intention of the designers. Emotional design is not about making fun products, but about enjoyable products. Positive emotional design increases the affection value in products that enable users to create emotional connection with products. With the emotional connection, the user can engage in learning about the product as well as enjoy using the product. This can also resolve most usability issues by increasing the attention level and decreasing boredom. When more people feel that a product is enjoyable, it becomes more inclusive. Second question: Can't inclusive design have innovative value? Most inclusive design products are far from being innovative, and thus, they cannot create market opportunities. While emotional design approach increases value for users, innovative design approach creates value for the businesses. This will eventually promote development of inclusive products. This paper discusses the benefits of emotional design approach in inclusive design. It also argues how emotional design can help make inclusive design more innovative. Accompanied exemplar design process illustrates how emotional design contributes to inclusive design and how it leads to innovative products.

• Journal of Digital Convergence
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• v.10 no.3
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• pp.241-250
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• 2012

Low birth rate is a persisting national challenge that causes a decrease in productive population and an increase in encumbrances by ever rising insurance premiums, eventually threatening the existence of the country. This study investigated the effectiveness of the current government's undergoing economic support of the child-birth promotion policy, "go-un-mam card", and suggested improvement plans about the problems derived on the basis of the perceptions of the card users. Multi-response analysis was used to find out the preference of the policy, and chi-square test was conducted to discover the user satisfaction rate and intent of re-parturition. Also, descriptive analysis was performed to identify the degree of the policy recognition. The results illustrated that a significant association exists between the satisfaction rate and the intention of re-parturition. In addition, pregnant women gained information about the policy from governmental agencies and medical institution as well as by word of mouth; then, applied to the policy. Also, the card users only took an advantage of discounts in the hospitals within the supported monetary amounts. Moreover, the card users expressed their dissatisfaction at the monetary amounts. For instance, the users were dissatisfied with the limit on the amount to be used in a day and requested upgrade on the monetary amounts. Based on the result, the government will improve and develop the go-un-mam card for the ultimate purpose of policy, increasing birth-rate.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.4
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• pp.303-315
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• 2020

The development of ICT is spreading various contents to enhance health care and management efficiency through convergence between mobile and healthcare, but it indicates consumer acceptance and imbalance of mobile healthcare, and there is a lack of empirical research on functions and acceptability required according to consumer behavior and characteristics. This study sought to understand whether users were aware of and how to address the risks associated with smartphone use, and to conduct research on the acceptability and function and price of healthcare applications. For the purpose of the study, the data prepared in depth 1:1 survey for those who participated in and attended the 'BIO 2018 in Boston' exhibition was used for the actual analysis. The collected sample data included frequency analysis, technical statistical analysis, speech only correlation, chi square test, one-way analysis, and accuracy test. As a result, the more you realize the wrong attitude, the higher the awareness of risk and willingness to take action to solve problems. Second, it is necessary to increase satisfaction with the functions of healthcare apps, as well as to utilize health care and healthcare apps. Third, focus should be placed on systems or functional implementations centered on user behavior changes. Fourth, it is necessary to develop services that can enhance visual motivation. This study is meaningful in that it identifies a variety of consumer characteristics and provides directions for development of functions, and can be used as a basis for providing efficient healthcare applications in the future.

• Archives of design research
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• v.18 no.2 s.60
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• pp.219-232
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• 2005

Moderns are living within flood of web contents, animation, reflex data etc. as well as sight, product, environment design. There fore, modern consumer has much options. Designer must provide various result for consumer for this reason. And must invent new sensitivity and propose to consumer. As purpose of this MCC sensitivity palette research takes advantage of the most sensitive color, do. Because applying correct sensitivity more than when design with matter already settled, rid private prejudice, and is thing to convey design intention exactly to user. Excellent culture contents must be able to equip international color design sensitivity. MCC sensitivity palette research studies and carries on the head emotion and sensitivity language that is nationality first, and collect End arranged sensitivity adjective through data analysis and picture data analysis that is the next time research leader Munheonjeok. And distributed collected adjective equally, and arrange distributed adjective by field of each sensitivity and collect system. Do 3 colors, 4 colors color scheme in selected sensitivity adjective and completed Simheom version. Result of beta version research to color specialist and designer last digital palette through question and inquiry compose. Through this process, completed more real and correct digital color sensitivity palette. Completed color scheme is operated in www.mcdri.net on web, and also programs to windows base and developed to software. MCC color scheme palette that research result is made includes sensitivity data database. This database can use directly in industry and continuous development is available. Software can search color scheme in language and idea development through classification search that use 3 attributes of color is available there is cough data of each output device different color error.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.197-206
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• 2014

Motor imagery based Brain-computer Interface(BCI), which has recently attracted attention, is the technique for decoding the user's voluntary motor intention using Electroencephalography(EEG). For classifying the motor imagery, event-related desynchronization(ERD), which is the phenomenon of EEG voltage drop at sensorimotor area in ${\mu}$-band(8-13Hz), has been generally used but this method are not free from the performance degradation of the BCI system because EEG has low spatial resolution and shows different ERD-appearing band according to users. Common spatial pattern(CSP) was proposed to solve the low spatial resolution problem but it has a disadvantage of being very sensitive to frequency-band selection. Discriminative filter bank common spatial pattern(DFBCSP) tried to solve the frequency-band selection problem by using the Fisher ratio of the averaged EEG signal power and establishing discriminative filter bank(DFB) which only includes the feature frequency-band. However, we found that DFB might not include the proper filters showing the spatial pattern of ERD. To solve this problem, we apply a band-selection process using CSP feature vectors and linear discriminant analysis to DFBCSP instead of the averaged EEG signal power. The filter selection results and the classification accuracies of the existing and the proposed methods show that the CSP feature is more effective than signal power feature.