• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.15-19
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• 2011

The T-DMB(Terrestrial Digital Multimedia Broadcasting) which was developed by the convergence of digital broadcasting technology and communication technology provides us with very good quality of music like CD, and provides TV services in a super express train like the KTX whose velocity is over 300 Km per hour. The T-DMB is diffusing toward the world as a technology which is be able to provide the various convergent services of broadcasting and communication through mobile phone, PDA, dedicated terminal, and so on. A business model needed for the diffusion of the T-DMB toward the world was established and utilized to expand the T-DMB into Vietnam in the paper. In addition, this paper describes not only some predicting methods for the technological valuation of the T-DMB Total Solution, but also a case study on the marketing related to establishing the T-DMB system in order to provide the paid services in Vietnam. Finally, A couple of business models needed to globally expand the T-DMB have been provided.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.730-737
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• 2018

With the increasing number of health consumers aiming for a happy quality of life, the O2O medical marketing market is activated by choosing reliable health care facilities and receiving high quality medical services based on the medical information distributed on web's blog. Because unstructured text data used on the Internet, mobile, and social networks directly or indirectly reflects authors' interests, preferences, and expectations in addition to their expertise, it is difficult to guarantee credibility of medical information. In this study, we propose a blog reading system that provides users with a higher quality medical information service by classifying medical information blogs (medical blog, ad blog) using bigdata and MLP processing. We collect and analyze many domestic medical information blogs on the Internet based on the proposed big data and machine learning technology, and develop a personalized health information recommendation system for each disease. It is expected that the user will be able to maintain his / her health condition by continuously checking his / her health problems and taking the most appropriate measures.

• International Area Studies Review
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• v.12 no.3
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• pp.367-390
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• 2008

The Chinese cellular phone markets growth has the character which is two-sided gives the chance and threat in Korean mobile communication industry. This also demands the localization of the international marketing strategies which establishes in grasp of consumer consuming propensity and purchase intention. It is the goal that provides a strategic current point to the Korean enterprise which enter to China. To observe a test of hypothesis results concretely from empirical analysis with after words is same. The hypothesis 1, 'corporate image really will plus affect(+) in purchase intention' the hypothesis was adopted. The hypothesis 2, 'brand image really will plus affect(+) in purchase intention' also the hypothesis was adopted. The hypothesis 3, 'product attributes really will plus affect(+) in purchase intention' also the hypothesis was adopted. The other research hypothesis which sex and age were rejected, school was adopted partially, others was adopted. When about the consumer who is used from empirical analysis measurement items in the center application presents the strategies which is possible in fact.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.231-238
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• 2021

In this paper, we suggest a method of analysis for daily food delivery & consumption trends through big data of the post-Covid-19 era. Through analysis of big data and the database system, four analyzed factors, excluding weather, was proved to have significant correlation with delivery sales for 'Baedarui Minjok' of a catering delivery application. The research found that KBS, MBC and SBS Media showed remarkable results in food delivery & consumption sales soaring up to about 60 percent increase on the day after the Covid-19 related new article was issued. In addition, it proved that mobile media and web surfing were the main factors in increasing sales of food delivery & consumption applications, suggesting that viral marketing and emotional analysis by crawling data from SNS used by Millennials might be an important factor in sales growth. It can contribute the companies in the economic recession era to survive by providing the method for analyzing the big data and increasing their sales.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.58-73
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• 2022

The purpose of this study is to construct a predictable estimation model that reflects the relationship between the variables of mobile app performance and to verify how app reviews affect app performance. In study 1 and 2, the relationship between app performance indicators was derived using correlation analysis and random forest regression estimation of machine learning, and app performance estimation modeling was performed. In study 3, sentiment scores for app reviews were by using sentiment analysis of text mining, and it was found that app review sentiment scores have an effect one lag ahead of the number of daily installations of apps when using multivariate time series analysis. By analyzing the dissatisfaction and needs raised by app performance indicators and reviews of apps, companies can improve their apps in a timely manner and derive the timing and direction of marketing promotions.

• Smart Media Journal
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• v.12 no.8
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• pp.37-44
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• 2023

This study investigated the influence of travel-related content on the popular short-form platform TikTok in China on users' intentions to visit travel destinations and purchase travel products. Conducted in July 2023, amidst the rising consumption of short-form content through mobile devices due to the COVID-19 pandemic, the research surveyed 337 participants using an online survey platform in China. The findings revealed that the entertainment factor within TikTok's content did not significantly impact the perception of travel destinations, whereas informativeness and trustworthiness had positive effects. Moreover, expertise and interactivity also had positive effects. The study demonstrated that the image of travel destinations formed through short-form content on TikTok positively and significantly influenced visitors' intentions. These results provide valuable insights for crafting effective strategies in the tourism industry and marketing efforts.

• Knowledge Management Research
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• v.21 no.3
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• pp.249-269
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• 2020

Recently, as the online market has matured, it is facing many problems to prevent the growth. The most common problem is the homogenization of online products, which fails to increase the number of customers any more. Moreover, although the portion of the online market has increased significantly, it now becomes essential to expand offline for further development. In response, many online firms have recently sought to expand their businesses and marketing channels by securing offline spaces that can complement the limitations of online platforms, on top of their existing advantages of online channels. Based on their competitive advantage in terms of analyzing large volumes of customer data utilizing information technologies (e.g., big data and artificial intelligence), they are reinforcing their offline influence as well through this online for offline (O4O) business model. On the other hand, most of the existing research has primarily focused on online to offline (O2O) business model, and there is still a lack of research on O4O business models, which have been actively attempted in various industrial fields in recent years. Since a few of O4O-related studies have been conducted only in an experience marketing setting following a case study method, it is critical to conduct an empirical study on O4O selection attributes and their impact on customer satisfaction and loyalty. Therefore, focusing on China's representative O4O business model, 'Fresh Hema,' this study attempts to identify some key selection attributes specialized for O4O services from the customers' viewpoint and examine the impact of these attributes on customer satisfaction and loyalty. The results of the structural equation modeling (SEM) with 300 O4O (Fresh Hema) experienced customers, reveal that, out of seven O4O selection attributes, four (mobile app quality, mobile payment, product quality, and store facilities) have an impact on customer satisfaction, which also leads to customer loyalty (reuse intention, recommendation intention, and brand attachment). This study would help managers in an O4O area well adapt to rapidly changing customer needs and provide them with some guidelines for enhancing both customer satisfaction and loyalty by allocating more resources to more significant selection attributes, rather than less significant ones.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.73-91
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• 2013

Advertising market has been facing new challenges due to dramatic change in advertising channels and the advent of innovative media such as mobile devices. Recent research related to mobile devices is mainly focused on the fact that mobile devices could identify users'physical location in real-time, and this sheds light on how location-based technology is utilized to achieve competitive advantage in advertising market. With the introduction of smartphone, the functionality of smartphone has become much more diverse and context awareness is one of the areas that require further study. This work analyses the influence of context awareness value resulted from the transformation of advertising channel in mobile communication market, and our research result reflects recent trend in advertising market environment which is not considered in previous studies. Many constructs has intensively been studied in the context of advertising channel in traditional marketing environment, and entertainment, irritation and information are considered to be the most widely accepted variables that has positive relationship with advertising value. Also, in smartphone advertisement, four main dimensions of context awareness value are recognized: identification, activity, timing and location. In this study, we assume that these four constructs has positive relationship with context awareness value. Finally, we propose that advertising value and context awareness value positively influence smartphone advertising attitude. Partial Least Squares (PLS) structural model is used in our theoretical research model to test proposed hypotheses. A well designed survey is conducted for college students in Korea, and reliability, convergent validity and discriminant validity of constructs and measurement indicators are carefully evaluated and the results show that reliability and validity are confirmed according to predefined statistical criteria. Goodness-of-fit of our research model is also supported. In summary, the results collectively suggest good measurement properties for the proposed research model. The research outcomes are as follows. First, information has positive impact on advertising value while entertainment and irritation have no significant impact. Information, entertainment and irritation together account for 38.8% of advertising value. Second, along with the change in advertising market due to the advent of smartphone, activity, timing and location have positive impact on context awareness value while identification has no significant impact. In addition, identification, activity, location and time together account for 46.3% of context awareness value. Third, advertising value and context awareness value both positively influence smartphone advertising attitude, and these two constructs explain 31.7% of the variability of smartphone advertising attitude. The theoretical implication of our research is as follows. First, the influence of entertainment and irritation is reduced which are known to be crucial factors according to previous studies related to advertising value, while the influence of information is increased. It indicates that smartphone users are not likely interested in entertaining effect of smartphone advertisement, and are insensitive to the inconvenience due to smartphone advertisement. Second, in today' ubiquitous computing environment, it is effective to provide differentiated advertising service by utilizing smartphone users'context awareness values such as identification, activity, timing and location in order to achieve competitive business advantage in advertising market. For practical implications, enterprises should provide valuable and useful information that might attract smartphone users by adopting differentiation strategy as smartphone users are sensitive to the information provided via smartphone. Also enterprises not only provide useful information but also recognize and utilize smarphone users' unique characteristics and behaviors by increasing context awareness values. In summary, our result implies that smartphone advertisement should be optimized by considering the needed information of smartphone users in order to maximize advertisement effect.

• Management & Information Systems Review
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• v.38 no.4
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• pp.1-24
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• 2019

This study confirms the responses of consumers when the composition of emoticon bundles can be selected by individuals in MIM service. This aims to verify that customized bundling is a valid marketing strategy in the MIM emoticon market. Currently, the emoticon bundling used in Korean MIM services is in the form of pure bundling. As a result, Consumers must purchase an entire bundle even though he/she doesn't need to use all the emoticons contained in it. Some researches(e.g. Hitt & Chen, 2005; Wu & Anandalingam, 2002) show that when consumers value only part of the products or services included in pure bundling, customized bundling is much more profitable. In their works, customized bundling is appropriate when marginal costs are near zero. Information goods, such as emoticons, meet the condition. On the other hand, customized bundling increase the choosable options, so it can pose a problem of complexity (Blecker et al., 2004). And consumers may experience information overload(Huffman & Kahn, 1998). Thus, judgement on the necessity to introduce customized bundling needs to be made through empirical analyses in the light of characteristics of the product and the reaction of consumers. Results show that when customized bundling was introduced, consumers' purchase intention and willingness to pay significantly increased. Purchase intention for customized bundles has increased by 0.44 based on the five point Likert scale than the purchase intention for existing pure bundles. The increase in purchase intention for customized bundles was statistically independent of the existing purchasing experience. In addition, the willingness to pay was increased by about 2.8% compared to the price of the existing emoticon bundles in the whole group. The group with experience in purchasing pure bundles were willing to pay 5.9% more than pure bundles. The other group without experience in purchasing pure bundles were willing to buy if they were about 5% cheaper than the existing price. Overall, introducing customized bundling into emoticon bundles can lead to positive consumers responses and be a viable marketing strategy.