• Economic and Environmental Geology
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• v.51 no.4
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• pp.345-358
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• 2018

In this study, we have performed electron probe micro analyzer (EPMA), X-ray differaction (XRD), inductively coupled plasma spectroscopy (ICP), Fourier transform Raman spectroscopy (FT-Raman), far-infrared (FIR), nuclear magnetic resonance (NMR), and pH-DO Analyses for characterizing medicinal mineralogy aspect of the black tourmaline (Shantung, china), black and pink tourmaline (Minas Geraris, Brazil), black touemaline (Daeyu mine, Korea). In addition, heating effects of the tourmaline sauna as well as the effects of tourmaline powder-added soap on skin troubles have been investigated. It has been revealed that chemical composition of the tourmaline is either high in Fe-, Al-, B-rich types. Ratio of the K-Ca, Na-K, and Fe-B reflects the component change property of solid solution. $CaO/CaO+Na_2O$ and MgO/FeO+MgO ratio show high positive correlation. When tourmaline reacts with distilled water, extended reaction time DO values approximately decrease and it stabilizes at DO = 10. Otherwise, pH values increase until 6 hours and it stabilizes at pH = 8 after 24 hours. Distilled water changes to alkaline when it reacts with tourmaline powder and particles. Tourmaline showed lower absorption spectrum strength and transmittance at short wave, where absorption spectrum wavelength and strength were determined by the content of the composition elements and characteristics of crystallography. Increase of the Fe content has been confirmed to be the cause for the reduction of irradiation. For the chemical composition and spectral property of the tourmaline particle samples, it has been found that Si and Fe contents show positive correlation with Far-Infrared irradiation, while Al and Mg contents show negative correlation. For tourmaline powder, it has been confirmed that $^{17}O-NMR$ FWHM (full width at half maximum) decreases when reacts with distilled water. Tourmaline sauna (approximately $100^{\circ}C$) was found to increase $0.5-1.5^{\circ}C$ of body temperature, average of 12 heartbeat, and 10mg Hg of blood pressure. Tourmaline soap had very good aesthetic effect to skin and was confirmed to have above the average improvements to skin troubles (e.g., allergy or atopy).

• Science of Emotion and Sensibility
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• v.19 no.4
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• pp.21-32
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• 2016

Studies have observed various phenomena regarding the effect of the interaction between type, price, and brand image of a product on consumers' purchase intent and product quality perception. Yet, few have studied the effect of the interaction between product type and manufacturing method on these factors. However, the advent of three-dimensional (3D) printers added a new manufacturing method, 3D printing, to the traditional methods of handicraft and automated machine-based production, and research is necessary since this new framework might affect consumers' purchase intent and product quality perception. Therefore, this study aimed to verify the effects of the interaction between product type and manufacturing method on purchase intent and product quality perception. To achieve this, in our experiment 1, we selected product types with different characteristics (drone vs. violin vs. cup), and measured whether consumers preferred different manufacturing methods for each product type. The results showed that consumers preferred the 3D printing method for technologically advanced products such as drones, the handmade method for violins, and the automated machine-based manufacturing method, which allows mass production, for cups. Experiment 2 attempted to verify the effects of the differences in manufacturing method preferences for each product type on consumers' purchase intent and product quality perception. Our findings are as follows: for drones, the purchase intent was highest when 3D printing was used; for violins, the purchase intent was highest when the violins were handmade; for cups, the purchase intent was highest when machine-based manufacturing was used. Moreover, whereas the product quality perception for drones did not differ across different manufacturing methods, consumers perceived that handmade violins had the highest quality and that cups manufactured with 3D printing had the lowest quality (the purchase intent for cups was also lowest when 3D printing was used). This study is anticipated to provide a wide range of implications in various areas, including consumer psychology, marketing, and advertising.

• Journal of the Korean Society for Library and Information Science
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• v.34 no.1
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• pp.265-295
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• 2000

Education of library and information science must focus on practical education acted upon as a laboratory room in the characteristics of learning, because it cultivates a librarian as an information expert who can conduct professional affairs and services, applying traditional theory to the practical business of library and information. This dissertation suggested a new paradigm of an instructional media center as an advanced laboratory room which faithfully can run the curriculum of a library and information science for cultivating librarians, information experts who can satisfy the 21C information society. To carry out this purpose, I considered the various opinions of professors and librarians, after investigating and analyzing facilities and furnishings of laboratory rooms and teaching and learning data related to departments of library and information science in 32 universities. These contents can be summarized as follows : 1) Constructional media centers connected to education of library and information science sets laboratory rooms for practical classification and cataloging classes; laboratory rooms for film media which can utilize advanced media, listening tools, and practical materials; information management laboratory rooms which can experience the various information research methods through the Internet, cultivate the ability of information application, and teach the curriculum of library and information science related to computers. 2) Arrangement plans linked to laboratory rooms for classification and cataloging, one for film media, and one for information proceedings are as follows: , , and . 3) The size of each room is $162m^2$ (49.1pying); the number of persons to be admitted is about 40 to 50; each room has one media expert and one assistant as operating manager of exclusive responsibility. 4) Instructional & learning data which must be contained as instructional media of library and information science include computers, marginal tools related to it, listening materials, supplies for ordering books, teaching aids containing various equipment and tools, textbooks for practice, books connected to classification and cataloging for practice, and textbooks related to practical subjects and reference books. 5) Industrial media centers belonging to library and information science require for practice, general furnishings like bookshelves, and various material depository boxes.

• 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.

• Information Systems Review
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• v.6 no.2
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• pp.113-135
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• 2004

This paper defines appraisal items and weights of the items for the purpose of developing an appraisal instrument that objectively measures employee's effectiveness of knowledge contribution. Deductive research is used for the development of appraisal items and delphi method for the development of weights of the items. In the deductive research the term, "effectiveness of knowledge contribution" is first defined. Then knowledge contribution activities are classified as "dimension of explicit contribution" and " dimension of tacit contribution" due to the characteristics of knowledge. Each dimension is divided again by components. The dimension of explicit contribution is divided according to the content of knowledge, and the dimension of tacit contribution is divided according to the extent of tacitness of knowledge contribution. The total components of dimensions are 7. The dimension of explicit contribution is composed of factual knowledge and procedural knowledge. The factual knowledge is made up of "procedural knowledge outcome" and "other factual knowledge". The procedural knowledge is made up of "procedural knowledge manual" and "lessons-learned procedural knowledge". The dimension of tacit contribution is composed of "agency", "model" and "Q&A". The basic framework for measuring 7 components of knowledge contribution is quantitative and qualitative approach. This paper is premised on the assumption that the outcomes of employee's knowledge contribution activities are recorded in the knowledge management systems in order to evaluate them objectively. The appraisal items are defined as follows: at the dimension of explicit contribution, in quantitative approach, "the upload number" or "performance number", and in qualitative approach, other employee's "referred number" and other employee's "content and format satisfaction evaluation"; at the dimension of tacit contribution, "demanded number of performance" After the development of appraisal items by the deductive method, delphi method was used for the analysis of the weights of the items with the total degree of knowledge contribution, 100. This research does not include the standard marks of the appraisal items. It is because when companies apply this appraisal instrument, they could use their own standard appraisal marks of the appraisal items considering their present situations and companies' goals. Through this almost desert-like research about the appraisal instrument of employee's knowledge contribution effectiveness, it proposes a cornerstone in the research field of appraisal instrument, which provides a standard for employee's knowledge contribution appraisal, and appraisal items that make organizational knowledge to be managed more systemically in business sites.

• Journal of Distribution Science
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• v.10 no.5
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• pp.37-44
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• 2012

In this paper, we investigate several factors that affect the locational decision of discount stores by using previous studies on the marketing area and the location of commercial facilities. We selected 21 primary variables that are expected to influence the decision of store location and, by factor analysis, grouped them into five underlying factors. Among these, the demographic factor, which shows the potential purchasing power level, had the greatest impact on the locational decision for the store. However, we found individual stores positioned according to unique locational characteristics in addition to the demographic factor. It means that we have to additionally consider if the vicinity of the market is based on any physical properties. Many previous studies proposed four decision factors for store location: the economic factor, the demographic factor, the land utilization factor, and traffic factor. However, the fivefold factors-our distinctive contribution-are more concrete and persuasive according to Korean reality. We show that location preference is based on the following criteria: (1) the area is densely populated, (2) houses stand close together, (3) residents have a high income level, (4) road traffic is developed and easy to access, and (5) public transportation is well developed. The demographic factor has the greatest impact on the location of a discount store. The number of households has a greater relevance to the demographic factor than does the individual consumer. Second, discount stores relatively prefer places where houses are located close together because such places offer easy access to the market. Third, a place whose residents have a high income level will be preferred, with its large cars and excellent traffic conditions. Fourth, a location would be highly rated if the roads around commercial facilities are well developed and their accessibility is good. Finally, discount stores must be located close to bus stops because female consumers, including housewives-the most important customers-evaluate stores based on distance. In this research, the variable of consumer attitude and preference was excluded, and the location factors of discount stores were analyzed according to a microscopic view through physical spatial data. In the future, the opening of new discount stores based on the five factors indicated above will require a comparatively shorter time from the first project feasibility analysis. In addition, the result of our study can be applied to the field of public policy for constructing and attracting large-scale distribution facilities.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.159-172
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• 2010

The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.97-121
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• 2013

With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.69-85
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• 2016

Successful relationship with loving partners is one of the most important factors in life. In psychology, there have been some previous researches studying the factors influencing romantic relationships. However, most of these researches were performed based on statistical analysis; thus they have limitations in analyzing complex non-linear relationships or rules based reasoning. This research analyzes commitment and persistence in heterosexual involvement according to styles of loving using a datamining technique as well as statistical methods. In this research, we consider six different styles of loving - 'eros', 'ludus', 'stroge', 'pragma', 'mania' and 'agape' which influence romantic relationships between lovers, besides the factors suggested by the previous researches. These six types of love are defined by Lee (1977) as follows: 'eros' is romantic, passionate love; 'ludus' is a game-playing or uncommitted love; 'storge' is a slow developing, friendship-based love; 'pragma' is a pragmatic, practical, mutually beneficial relationship; 'mania' is an obsessive or possessive love and, lastly, 'agape' is a gentle, caring, giving type of love, brotherly love, not concerned with the self. In order to do this research, data from 105 heterosexual couples were collected. Using the data, a linear regression method was first performed to find out the important factors associated with a commitment to partners. The result shows that 'satisfaction', 'eros' and 'agape' are significant factors associated with the commitment level for both male and female. Interestingly, in male cases, 'agape' has a greater effect on commitment than 'eros'. On the other hand, in female cases, 'eros' is a more significant factor than 'agape' to commitment. In addition to that, 'investment' of the male is also crucial factor for male commitment. Next, decision tree analysis was performed to find out the characteristics of high commitment couples and low commitment couples. In order to build decision tree models in this experiment, 'decision tree' operator in the datamining tool, Rapid Miner was used. The experimental result shows that males having a high satisfaction level in relationship show a high commitment level. However, even though a male may not have a high satisfaction level, if he has made a lot of financial or mental investment in relationship, and his partner shows him a certain amount of 'agape', then he also shows a high commitment level to the female. In the case of female, a women having a high 'eros' and 'satisfaction' level shows a high commitment level. Otherwise, even though a female may not have a high satisfaction level, if her partner shows a certain amount of 'mania' then the female also shows a high commitment level. Finally, this research built a prediction model to establish whether the relationship will persist or break up using a decision tree. The result shows that the most important factor influencing to the break up is a 'narcissistic tendency' of the male. In addition to that, 'satisfaction', 'investment' and 'mania' of both male and female also affect a break up. Interestingly, while the 'mania' level of a male works positively to maintain the relationship, that of a female has a negative influence. The contribution of this research is adopting a new technique of analysis using a datamining method for psychology. In addition, the results of this research can provide useful advice to couples for building a harmonious relationship with each other. This research has several limitations. First, the experimental data was sampled based on oversampling technique to balance the size of each classes. Thus, it has a limitation of evaluating performances of the predictive models objectively. Second, the result data, whether the relationship persists of not, was collected relatively in short periods - 6 months after the initial data collection. Lastly, most of the respondents of the survey is in their 20's. In order to get more general results, we would like to extend this research to general populations.

• Management & Information Systems Review
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• v.36 no.3
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• pp.151-165
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• 2017

This study investigates the effect of revenue recognition by percentage of completion method on financial analysts' earnings forecasting information in order industry. Specifically, we examines how the analysts' earnings forecast errors and biases differ according to whether or not to report the unbilled revenue account balance and the level of unbilled revenue account balance. The sample consists of 453 firm-years listed in Korea Stock Exchange during the period from 2010 to 2014 since the information on unbilled revenue accounts can be obtained after the adoption of K-IFRS. The results are as follows. First, we find that the firms with unbilled revenue account balances have lower analysts' earnings forecast accuracy than the firms who do not report unbilled revue account balances. In addition, we find that the accuracy of analysts' earnings forecasts decreases as the amount of unbilled revenue increases. Unbilled revenue account balances occur when the revenue recognition of the contractor is faster than the client. There is a possibility that managerial discretionary judgment and estimation may intervene when the contractor calculates the progress rate. The difference between the actual progress of the construction and the progress recognized by the company lowers the predictive value of financial statements. Our results suggest that the analysts' earnings forecasts may be more difficult for the firms that report unbilled revenue balances as applying the revenue recognition method based on the progress criteria. Second, we find that the firms reporting unbilled revenue account balances tend to have higher the optimistic biases in analysts' earnings forecast than the firms who do not report unbilled revenue account balances. And we find that the analysts' earnings forecast biases are increases as the amount of unbilled revenue increases. This study suggests an effort to reduce the arbitrary adjustment and estimation in the measurement of the progress as well as the introduction of the progress measurement method which can reflect the actual progress. Investors are encouraged to invest and analyze the characteristics of the order-based industry accounting standards. In addition, the results of this study empower the accounting transparency enhancement plan for order industry proposed by the policy authorities.