• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.83-88
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• 2022

The purpose of this study is to present an analysis and implications for the metaverse-based virtual real estate transaction service. Through blockchain-based technology and metaverse, the world we live in is expanding naturally. Therefore, changes in the environment and perceptions of market participants are also very important factors. The concept and thinking about the existing asset value change and investment are also changing. This means that you can generate profits through value and investment in intangible assets. The service user aspect is a case of investing in the future value of virtual real estate that if more users participate rather than the present value, the principle of supply and demand will be applied to increase the number of consumers and the price will naturally rise according to the principle of scarcity. The service provider provides a technical platform for the service to directly transact the portion of the virtual area considered of interest directly through the virtual real estate purchase business. As the number of participants increases as well as funds and transaction fees, various revenue models such as advertisements can be discovered and provided. It plays the role of providing jobs and information through new services. As a stakeholder, governments can exploit the emergence of new technologies and products to create people and services and secure economic benefits. Of course, various institutional supports should be provided so that new services can settle in the market while mitigating risk factors. This study is meaningful in that it contributes to the establishment of a domestic metaverse-based environment and related research and is utilized in the study of virtual space real estate services.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.85-96
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• 2023

With advance of cloud computing technology, Blockchain as a Service of Cloud Service Provider has been utilized in various areas such as e-Commerce and financial companies to manage customer history and distribution history. However, if users' search history, purchase history, etc. are to be utilized in a BaaS in areas such as recommendation algorithms and search engine development, the users' search queries will be exposed to the company operating the BaaS, and privacy issues will be occured. Z. Guan et al. ensure the unlinkability between users' search query and search result using searchable encryption, and based on the inner product similarity, they select Top-k results that are highly relevant to the users' search query. However, there is a problem that the Top-k results selection may be not possible due to ties of inner product similarity, and BaaS over cloud is not considered. Therefore, this paper solve the problem of Z. Guan et al. using cosine similarity, so we improve accuracy of search result. And based on this, we design a BaaS with secure Top-k search that improved accuracy. Furthermore, we design a smart contracts that preserve privacy of users' search and obtain Top-k search results that are highly relevant to the users' search.

• Information Systems Review
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• v.23 no.3
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• pp.177-200
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• 2021

Recently, the use of prepaid electronic payments such as electronic wallets, digital currency and prepaid points is gradually increasing. Prepaid electronic payments has the characteristic of being used after charging first. This study empirically investigated the factors affecting the intention to use online charging in order to help improve the service that require prepaid recharge by applying transformed TAM. Since there are not many previous studies for the intention to use online charging, we extract factors through preceding researches for electronic cash and mobile easy payment. Also we analyze the intention to use online charging for transportation card users, focusing on the moderating effects. As a result of the study, it was found that 'convenience', 'ubiquity', and 'self-efficacy' among the independent variables had a positive (+) effect on mediation variable 'perceived usefulness'. 'Perceived usefulness' was analyzed to have a significant influence on the dependent variable 'usage intention'. According to users' gender, internet usage time, internet shopping frequency, online charging frequency and transportation card usage type, the moderating effect was significant on 'perceived usefulness' and 'usage intention'. As an implication, it was suggested that service improvement and differentiated marketing are needed in direction of increasing the usefulness of services. Additional research directions were proposed for services such as e-wallets, prepaid points and digital currencies by adding other factors and moderate variables.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.167-175
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• 2024

Due to the Fourth Industrial Revolution, ICT(Information and Communication Technology) industry is becoming more important and sophisticated than ever. In B2B based ICT industry demand forecasting by analyzing the previous customer data is so important. RFM, one of customer relationship management models is a marketing technique that evaluates Recency, Frequency and Monetary value to predict customers behavior. RFM model has been studied focusing on the B2C based industry. On the other hand there is a lack of research on B2B based technology industry. Therefore this study applied it to B2B based high technology industry and considered T(technology collaboration) value, which are identified as important factors in the technology industry. To present an improved model for market performance in B2B technology industry, an empirical study was conducted on comparing the accuracy of the traditional RFM model and the improved RFM-T model. The objective of this study is to contribute to market performance by presenting an improved model in B2B based high technology industry.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.105-119
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• 2017

Smartphone users hit over eighty-five percentage of Korean populations and personal private items and various information are stored in each user's smartphone. There are so many cases to propagate malicious codes or spywares for the purpose of catching illegally these kinds of information and earning pecuniary gains. Thus, need of information security is outstanding for using smartphone but also user's security perception is important. In this paper, we investigate about how information security affects smartphone operating system choices by users. For statistical analysis, the online survey with questionnaires for users of smartphones is conducted and effective 218 subjects are collected. We test hypotheses via communalities analysis using factor analysis, reliability analysis, independent sample t-test, and linear regression analysis by IBM SPSS statistical package. As a result, it is found that hardware environment influences on perceived ease of use. Brand power affects both perceived usefulness and perceived ease of use and degree of personal risk-accepting influences on perception of smartphone spy-ware risk. In addition, it is found that perceived usefulness, perceived ease of use, degree of personal risk-accepting, and spy-ware risk of smartphone influence significantly on intention to purchase smartphone. However, results of independent sample t-test for each operating system users of Android or iOS do not present statistically significant differences among two OS user groups. In addition, each result of OS user group testing for hypotheses is different from the results of total sample testing. These results can give important suggestions to organizations and managers related to smartphone ecology and contribute to the sphere of information systems (IS) study through a new perspective.

• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.61-81
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• 2007

Recently, use of foreign models and foreign language in advertising is a general trend in Korea even though the effect has not been well-known..Most of the previous research shows rather an opposite effect claiming marketing communication is more effective when higher congruity between marketing communication and consumer's cultural values are achieved. However, the introduction of global culture due to the expansion of new media such as Internet or cable television makes the congruity not the best choice of marketing strategy. In addition, use of highly attractive models in advertising to increase the effect of advertising is general. However, recent studies show that targeted women audience tend to compare themselves to the highly attractive models and do experience negative sentiment. Bower (2001) proved the difference between 'comparer' and 'noncomparer' when women face highly attractive models. The results show that a comparer who has an intention to compare highly attractive model (HAM) with herself has a significantly negative effect on model expertise, product argument, product evaluation and buying intention. Therefore, HAM is not always a good choice and model attractiveness plays a role in the processing other cues or changing the advertising effect from result of processing other cues. The purpose of this study is to investigate the effect of the use of foreign language on the advertising response of the audience with regard of the model attractiveness. For the empirical study, the virtual advertising using foreign models (HAM, NAM), brand names and slogans(Korean, English) were used as stimuli. The respondents of each stimulus were 75('HAM-Korean'), 75('NAM-Korean'), 66('HAM-English') and 66 ('NAM-English') respectively. To establish the effect of marketing communication, the attitude for media(AM), the attitude for product(AP), targetedness(TD), overall quality(OQ), and purchase intention(PI) with 7 point likert scale were measured. The manipulation was verified to check the difference between HAM attractiveness assessment (m=3.27) and NAM attractiveness assessment (m=5.12). The mean difference was statiscally significant (p<.05). As a result, all consequences were significantly changed with model attractiveness, and overall quality evaluation(OQ) were significantly changed with language. The interaction effect from model attractiveness and language was significant on attitude toward the product(AP) and purchase intention(PI). To analyze the difference, the mean values and standard deviation of consequences were compared. The result was more positive when model attractiveness was high for all consequences. For language effect, the assessment was more positive when English was used for OQ. Considering model attractiveness and language simultaneously, HAM-Korean was more positive for AP and PI, and NAM-English was more positive for AP and PI. In other words, the interaction effect was confirmed by model attractiveness and language. As mentioned above, use of foreign models and foreign language in advertising was explained by cultural match up hypothesis (Leclerc et al. 1994) which claimed that culture of origin effect. In other words, in advertising, use of same cultural language with the foreign model could make positive assessment for OQ. But this effect was moderated by model attractiveness. When the model attractiveness was low, the use of English makes PI high because of the effect of foreign language which supported the cultural match up hypothesis. When the model attractiveness was low, the use of Korean made AP and PI high because the effect of foreign language was diluted. It was a general notion that the visual cues got processed before (Holbrook and Moore, 1981; Sholl et al, 1995) compared to linguistic cues. Therefore, when consumers were faced HAM, so much perception was already consumed at processing visual cues making their native language of Korean to strongly and positively connected with the advertising concept. On the contrary, when consumers were faced with NAM, less perception was consumed compared to HAM, making English to accompany cultural halo effect which affected more positively. Therefore, when foreign models were employed in advertising, the language must be carefully selected according to the level of model attractiveness.

• The Korean Journal of Vision Science
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• v.20 no.4
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• pp.553-560
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• 2018

Purpose : To investigate a disposal method of disposing contact lenses and the recognition of environmental pollution by micro plastics which may be caused by the wrong disposal method of domestic contact lens wearers. Methods : Two hundred sixty one adults(124 males, 137 females, mean age $21.48{\pm}3.14years$) were participated in this study. They were given the questionnaire survey on contact lenses purchasing place, type of contact lenses, duration of wearing contact lenses, the disposal method of disposing contact lenses and the recognition of the occurrence of environmental pollution. Results : It appeared that eyeglass shop(50.0%) and contact lens shop(48.3%) were the main purchasing places, and the most common type of contact lenses were disposable lenses(38.5%) and daily wearing lenses(52.5%). On the duration of wearing contact lenses they answered more than 5 years(29.3%), less than 1 year (26.0%), less than 1 year to less than 3 years (26.0%), and on wearing a contact lens during a week they did 1-2 days (32.0%), 1 week (28.0%), 5-6 days (22.4%) and 3-4 days (17.6%). It was shown "no(78.3%)" and "yes(21.7%)" to the questionnaire of whether they received information or education about a disposal method at the place where the contact lens was purchased, and "no(87.5%)" and "yes(12.5%)" to the questionnaire of whether they received information or education from schools, public institutions or public media such as the internet. As for the disposal methods, landfill waste(45.6%), recycled garbage(29.6%), and drainage(16.8%) from the sink or toilet responded in order. Although men were more educated and informed about disposal than women (t=3.63189, p<0.00001), women were more aware of environmental pollution(t=2.44269, p=0.01605). Conclusion : In order to reduce the environmental pollution issue caused by the contact lens which does not decompose at the sewage treatment facility and become micro plastics, it is urgent to provide information about correct disposal methods after using contact lenses and to educate contact lens wearers.

• Journal of Distribution Research
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• v.13 no.1
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• pp.1-33
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• 2008

As the interest in the business-to-business(B2B) electronic commerce is increasing, many companies are participating in the B2B e-Marketplaces. The e-Marketplace is defined as the virtual market that many players take part in to transact. The e-Marketplace has an influenced on the manner in which organizational buyers and sellers interact. As a result, it is important to develop an understanding of the behaviors of firms that use these electronic marketplaces. The purpose of this study is to develop a comprehensive model for trust and commitment of B2B e-Marketplace and empirically to examine their structural relationships. Drawing from trust and commitment theory in the interorganizational relationship and B2B electronic commerce context, this study identifies network externality, interactivity, justice, quality of information sharing, institutional assurance as the determinants of trust and commitment of e-Marketplace. The proposed model hypothesized that (1) trust is a function of network externality, interactivity, justice, quality of information sharing, institutional assurance, (2) attitudinal and behavioral commitment is a function of trust, (3) behavioral commitment is a function of attitudinal commitment. The proposed model is tested using organizational-level survey data from 187 buying organizations that conduct business in MRO e-Marketplaces. The data were tested by reliability test, correlation analysis, exploratory factor analysis, confirmatory factor analysis and covariance structure analysis. The results indicate that (1) trust is influenced by network externality, interactivity, justice, institutional assurance, (2) attitudinal commitment and behavioral commitment is influenced by trust (3) behavioral commitment is influenced by attitudinal commitment. Also, the empirical results confirmed that trust play a strong, central role in determinging e-Marketplace commitment. The key theoretical contribution of this research is that it begins to extend interorganizational information system literature in areas such as B2B Internet e-Marketplace. Managerially, this study contributes tn the understanding of the role of B2B e-Markeplace providers in Internet situation. And Limitations of this study and guidelines for future researches are also discussed.

• Korean Journal of Poultry Science
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• v.45 no.3
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• pp.219-228
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• 2018

This study was conducted twice to investigate egg purchase behavior and perception on animal welfare of Korean consumers. This study included women, who were the main decision makers and caretakers in the household, and men with one-person household. This survey was conducted with by the Computer Assisted Web Interview and Gang Survey methods. On the key considerations factor, the highest response rate was considered to be 'price', and the response rate of considering 'packing date' increased in the second survey. At a reasonable price based on 10 eggs, the response rate was the highest at 53.8% and 42.9% in both the first and second surveys and the appropriate price averages were 2,482 won and 2,132 won, respectively. The highest rate of purchase of egg consumers from 'Large Mart' followed by 'Medium sized supermarket' and 'Chain supermarket'. As for the awareness about animal welfare, the recognition ratio (73.5%) was higher in the result of the second survey than the first. The cognitive period of animal welfare was 59.0% before the insecticide egg crisis and 41.0% thereafter. Regarding whether or not they have ever seen an animal welfare certification mark and an animal welfare animal farm certification mark, 59.6% of respondents said that they saw it for the first time and 37.6% answered that they knew the animal welfare certification mark. On the animal welfare system, the 'free-range' response rate was the highest at 85.8%. The 'free-range' fit response decreased by 34.2%p, while the 'barn' and 'European type' fit response increased by 13.2%p and 24.1%p, respectively. The number of 'I have never seen' and 'I have ever eaten' responses to the recognition and eating experience of animal welfare certified eggs decreased while the number of those who answered 'Have ever seen' and 'Have eaten' increased. The answer of purchasing animal welfare certified eggs at department stores, organic farming cooperatives, and internet shopping malls was higher than that of buying conventional eggs. Of the total respondents, 92.0% were willing to purchase an animal welfare egg before the price was offered, but after offering the prices of animal welfare eggs, the intention to purchase was 62.7%, which was about 30%p lower than before. The reason for purchasing an animal welfare certified egg was the highest score of 71.0% for 'I think it is likely to be high in food safety', and 38.1% for 'I think the price is high' for lack of intention to purchase. In the sensory evaluation of animal welfare eggs, egg color and skin texture of conventional eggs were significantly higher than those of certified welfare eggs (P<0.05), and boiled eggs showed that egg whites of animal welfare certified eggs were more (P<0.05). As a result, the results of this study will contribute to the activation of the animal welfare certification system for laying hens by providing basic data on consumer awareness to animal welfare certified farmers.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.137-148
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• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used