• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.95-108
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• 2011

TThis is a study of the personalization method that intelligently adapts the level of clustering considering purchasing index of a customer. In the e-biz era, many companies gather customers' demographic and transactional information such as age, gender, purchasing date and product category. They use this information to predict customer's preferences or purchasing patterns so that they can provide more customized services to their customers. The previous Customer-Segmentation method provides customized services for each customer group. This method clusters a whole customer set into different groups based on their similarity and builds predictive models for the resulting groups. Thus, it can manage the number of predictive models and also provide more data for the customers who do not have enough data to build a good predictive model by using the data of other similar customers. However, this method often fails to provide highly personalized services to each customer, which is especially important to VIP customers. Furthermore, it clusters the customers who already have a considerable amount of data as well as the customers who only have small amount of data, which causes to increase computational cost unnecessarily without significant performance improvement. The other conventional method called 1-to-1 method provides more customized services than the Customer-Segmentation method for each individual customer since the predictive model are built using only the data for the individual customer. This method not only provides highly personalized services but also builds a relatively simple and less costly model that satisfies with each customer. However, the 1-to-1 method has a limitation that it does not produce a good predictive model when a customer has only a few numbers of data. In other words, if a customer has insufficient number of transactional data then the performance rate of this method deteriorate. In order to overcome the limitations of these two conventional methods, we suggested the new method called Intelligent Customer Segmentation method that provides adaptive personalized services according to the customer's purchasing index. The suggested method clusters customers according to their purchasing index, so that the prediction for the less purchasing customers are based on the data in more intensively clustered groups, and for the VIP customers, who already have a considerable amount of data, clustered to a much lesser extent or not clustered at all. The main idea of this method is that applying clustering technique when the number of transactional data of the target customer is less than the predefined criterion data size. In order to find this criterion number, we suggest the algorithm called sliding window correlation analysis in this study. The algorithm purposes to find the transactional data size that the performance of the 1-to-1 method is radically decreased due to the data sparity. After finding this criterion data size, we apply the conventional 1-to-1 method for the customers who have more data than the criterion and apply clustering technique who have less than this amount until they can use at least the predefined criterion amount of data for model building processes. We apply the two conventional methods and the newly suggested method to Neilsen's beverage purchasing data to predict the purchasing amounts of the customers and the purchasing categories. We use two data mining techniques (Support Vector Machine and Linear Regression) and two types of performance measures (MAE and RMSE) in order to predict two dependent variables as aforementioned. The results show that the suggested Intelligent Customer Segmentation method can outperform the conventional 1-to-1 method in many cases and produces the same level of performances compare with the Customer-Segmentation method spending much less computational cost.

• Journal of Technology Innovation
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• v.25 no.4
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• pp.107-143
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• 2017

This study aims to understand the impact of internal and external environments and innovation efforts on a company's performance. First, the relationships and patterns between variables were determined through an exploratory factor analysis. Afterwards, a cluster analysis was conducted, in which the influential factors summarized in the factor analysis were classified. Finally, structural equation modeling was used to carry out an empirical analysis of the structural relationship between innovation efforts and the company's performance in the classified clusters. 7 factors were derived from the exploratory factor analysis of 40 input variables from external and internal environments. 4 clusters (n=1,022) were formed based on the 7 factors. Empirical analysis of the 4 clusters using structural equation modelling showed the following: Only independent technology development had a positive impact on the company's performance for Cluster 1, which is characterized by sensitivity to a technological/competitive environment and innovativeness. Only independent technology development and joint research had positive impacts on the company's performance for Cluster 2, which is characterized by sensitivity to a market environment and internal orientation. Joint research and the mediating variable of government support program utilization had positive impacts, while the introduction of technology had a negative impact on the company's performance for Cluster 3, which is characterized by sensitivity to a competitive environment, innovativeness, and willingness to cooperate with the government and related institutions. Independent technology development as well as the mediating variables of network utilization and government support program utilization had positive impacts on the company's performance for Cluster 4, which is characterized by openness and external cooperation.

• 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.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.4 no.4
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• pp.89-114
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• 2009

BizCool is an entry-level business education program implemented with a purpose of enhancing the entrepreneurial disposition and capability of the youth through enterprise commencement education of vocational high school students and developing them into economic pillars of future to alleviate the labor shortage crisis of small and medium enterprises and revitalize enterprise commencement. In this study, the factors were deduced and a path analysis was conducted with the purpose of proposing a revitalization plan through an effectiveness analysis of enterprise commencement education for the youth. The result of the analysis revealed that BizCool has effects on the knowledge and understanding of enterprise commencement, and enterprise commencement knowledge also has effects on the understanding of enterprise commencement. In addition, it was found that the enterprise commencement knowledge and the understanding on enterprise commencement have effects on the intention of enterprise commence. In the result of verifying the hypothesis that the understanding of enterprise commencement according to the psychological characteristics of individuals will have a positive effect on the enterprise commencement intention, it was revealed that the risk resignation disposition and patience for ambiguity are having effects but accomplishment desire is not playing a moderating variable role. Through the above path analysis, a conclusion was obtained that the enterprise commencement education has effects on the outcome of enterprise commencement education through the understanding on enterprise commencement. Additionally, the nation needs to actively lead systematic enterprise commencement education within the policy of job creation upon realizing the need for enterprise commencement education of vocational high school, and a revitalization plan was proposed on the five kinds of a conversion of social perception on vocational high school, establishment of institutes specializing in BizCool and cultivation of BizCool specialists, development of various materials and expansion of BizCool program, field-centered lessons, revitalization of enterprise commencement club and personnel and resource support by companies.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.6
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• pp.121-132
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• 2015

This study by the authenticity of the CSV in social contribution activities and not giving a positive effect on job satisfaction of employees, as adjusted by the identification variables in the organization that were neglected during the research for the CSV its positive impact on job satisfaction the purpose is to verify whether this study has been carried out by a survey of employees of some medium-sized enterprises and large corporations to small businesses and worker being served on them, social contributions derived for the research activities of public interest and corporate profit activities classified and divided whether the legitimacy of the employees for social contribution activities that are embedded in its base in the perception of moral legitimacy and practical perceived legitimacy of these four variables were presented, and how these variables presented a positive effect on employee job satisfaction, control Job organizational changes saw equate to verify that controls are effective. As a result, first, the authenticity of the CSV is giving a positive effect on the activity of public interest've found that giving a positive effect on the perception of employees and the moral legitimacy, and job satisfaction of employees has showed that it does not affect, whichIt could not be verified because of the moderating effect between job satisfaction and perceived moral legitimacy. Second, CSVDML authenticity showed that a positive effect on the perception of practical legitimacy by giving employees a positive impact on corporate profit activity, which results significantly affected the job satisfaction of employees. And moderator of the organization identified has been proven that there is a moderating effect between job satisfaction and perceived practical justification. In order to improve employee job satisfaction by the public activities through this research, public service activities can be seen that the need for settlement of corporate culture that can impress an astute awareness of the strategic objectives of companies seeking employees.

• Archives of design research
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• v.13 no.1
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• pp.209-218
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• 2000

The purpose of this study was to improve the curriculum for industrial design department in the junior colleges. In order to achieve the purpose, two methodologies were carried out. First is job analysis of the industrial designers who have worked in the small & medium manufacturing companies, second is survey for the opinions of professors in the junior colleges. Some results were as follows: 1. The period of junior college for industrial designers is 2 years according to present. But selectively 1 year of advanced course can be established. 2. The practice subjects same as computational formative techniques needed to product development have to be increased. In addition kinds of selection subjects same as foreign language, manufacturing process, new product information and consumer behavior investigation have to be extended. 3. The next subjects need to adjust the title, contents and hours. (1) The need of 3.D related subjects same as computer modeling, computer rendering, 3.D modeling was high. The use of computer is required to design presentation subjects. (2)The need of advertising and sale related subjects same as printing, merchandise, package, typography, photography was low, the need of presentation techniques of new product development was high. (3) The need of field practice, special lecture on practice and reading original texts related subjects was same as at present, but these are not attached importance to form. As the designers feel keenly the necessity of using foreign language, the need of language subject was high.

• Cartoon and Animation Studies
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• s.45
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• pp.197-214
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• 2016

Augmented Reality, virtual reality in recently attracted attention throughout the world. and Mix them mixed reality etc., it has had a significant impact on the overall pop culture beyond the scope of science and technology. The world's leading IT company : Google, Apple, Samsung, Microsoft, Sony, LG is focusing on development of AR, VR technology for the public. The many large and small companies developed VR hardware, VR software, VR content. It does not look that makes a human a human operation in the cognitive experience of certain places or situations or invisible through Specific platforms or program is Encompass a common technique that a realization of the virtual space. In particular, out of the three-dimensional image reveals the limitations of the conventional two-dimensional structure - 180, 360 degree images provided by the subjective and objective symptoms such as vision and sense of time and got participants to select it. VR technology that can significantly induce the commitment and participation is Industry as well as to the general public which leads to the attention of colostrum. It was introduced more than 10 related VR works Year 2015 Sundance Film Festival New Frontier program. The appearance VR content : medical, architecture, shopping, movies, animations. Also, 360 individuals can be produced by the camera / video sharing VR is becoming an interactive tunnel between two possible users. Nevertheless, This confusion of values, moral degeneration and the realization of a virtual space that has been pointed out that the inherent. 4K or HUD, location tracking, motion sensors, processing power, and superior 3D graphics, touch, smell, 4D technology, 3D audio technology - It developed more than ever and possible approaches to reality. Thereafter, This is because the moral degeneration, identity, generational conflict, and escapism concerns. Animation is also seeking costs in this category Reality. Despite the similarities rather it has that image, and may be the reason that the animation is pushed back to the VR content creation. However, it is focused on the game and VR technology and the platform that is entertaining, but also seek new points within the animation staying in the flat Given that eventually consist of visual images is clear that VR sought. Finally, What is the reality created in the virtual space using VR technology could be applied to the animation? So it can be seen that the common interest is research on what methods and means applied.

• Clean Technology
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• v.10 no.2
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• pp.73-87
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• 2004

In most of industrial fields, cleaning is employed for removing soils on their products or parts. Halogenated cleaning agents such as CFC-113, 1,1,1-TCE(1,1,1-trichloroethane), MC(methylene chloride) and TCE (trichloroethylene) have been used as cleaning ones in most of companies in the world since their excellent performance of cleaning ability and good material compatibility. However, CFC-113 and 1,1,1-TCE which are ozone destruction substances are not used any more in the advanced countries because of the which are ozone destruction substances are not used any more in the advanced countries because of the Montreal protocol. MC and TCE are now used restrictively at small part of industrial fields in most of countries since they are known to be hazardous or carcinogenic materials. Thus, it is indispensible that the alternative cleaning agents which are environmental-friendly and safe, and show good cleaning ability should be developed or utilized for replacement of the halogenated cleaning agents. Aqueous/semi-aqueous cleaning agents are evaluated to be promising alternative ones among various alternatives in environmental and economical view point. In this study, commercially available 12 aqueous and 6 semi-aqueous cleaning agents were selected and their physical properties, cleaning abilities, rinsing abilities and recycling of contaminated rinse water were measured and analyzed. Aqueous cleaning agents with higher wetting index showed better cleaning ability compared with those with lower wetting index. However wetting index did not have any correlation with cleaning ability in semi-aqueous cleaning agents. It was observed that soil concentration in aqueous and semi-aqueous cleaning agents should be maintained below the certain concentrations which depend on types of clearing agents. More than 70% soils in contaminated rinse water by some of aqueous and semi-aqueous clearing agents could be separated by simple settling method. This means that some cleaning agents with high oil-water separation efficiency will be effiective for recycling oil-contaminated rinse water. It was found that contaminated rinse water with aqueous agents was purified easiy by ultrafiltration method with PAN membrane of 30 kDa.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.195-211
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• 2010

An exhibition is defined as market events for specific duration to present exhibitors' main product range to either business or private visitors, and it also plays a key role as effective marketing channels. Especially, as the effect of the opinions of the visitors after the exhibition impacts directly on sales or the image of companies, exhibition organizers must consider various needs of visitors. To meet needs of visitors, ubiquitous technologies have been applied in some exhibitions. However, despite of the development of the ubiquitous technologies, their services cannot always reflect visitors' preferences as they only generate information when visitors request. As a result, they have reached their limit to meet needs of visitors, which consequently might lead them to loss of marketing opportunity. Recommendation systems can be the right type to overcome these limitations. They can recommend the booths to coincide with visitors' preferences, so that they help visitors who are in difficulty for choices in exhibition environment. One of the most successful and widely used technologies for building recommender systems is called Collaborative Filtering. Traditional recommender systems, however, only use neighbors' evaluations or behaviors for a personalized prediction. Therefore, they can not reflect visitors' dynamic preference, and also lack of accuracy in exhibition environment. Although there is much useful information to infer visitors' preference in ubiquitous environment (e.g., visitors' current location, booth visit path, and so on), they use only limited information for recommendation. In this study, we propose a booth recommendation methodology using Sequential Association Rule which considers the sequence of visiting. Recent studies of Sequential Association Rule use the constraints to improve the performance. However, since traditional Sequential Association Rule considers the whole rules to recommendation, they have a scalability problem when they are adapted to a large exhibition scale. To solve this problem, our methodology composes the confidence database before recommendation process. To compose the confidence database, we first search preceding rules which have the frequency above threshold. Next, we compute the confidences of each preceding rules to each booth which is not contained in preceding rules. Therefore, the confidence database has two kinds of information which are preceding rules and their confidence to each booth. In recommendation process, we just generate preceding rules of the target visitors based on the records of the visits, and recommend booths according to the confidence database. Throughout these steps, we expect reduction of time spent on recommendation process. To evaluate proposed methodology, we use real booth visit records which are collected by RFID technology in IT exhibition. Booth visit records also contain the visit sequence of each visitor. We compare the performance of proposed methodology with traditional Collaborative Filtering system. As a result, our proposed methodology generally shows higher performance than traditional Collaborative Filtering. We can also see some features of it in experimental results. First, it shows the highest performance at one booth recommendation. It detects preceding rules with some portions of visitors. Therefore, if there is a visitor who moved with very a different pattern compared to the whole visitors, it cannot give a correct recommendation for him/her even though we increase the number of recommendation. Trained by the whole visitors, it cannot correctly give recommendation to visitors who have a unique path. Second, the performance of general recommendation systems increase as time expands. However, our methodology shows higher performance with limited information like one or two time periods. Therefore, not only can it recommend even if there is not much information of the target visitors' booth visit records, but also it uses only small amount of information in recommendation process. We expect that it can give real?time recommendations in exhibition environment. Overall, our methodology shows higher performance ability than traditional Collaborative Filtering systems, we expect it could be applied in booth recommendation system to satisfy visitors in exhibition environment.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.85-97
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• 2010

Internet communities are a typical space for knowledge creation and use on the Internet as people discuss their common interests within the internet communities. When we define 'Knowledge Communities' as internet communities that are related to knowledge creation and use, they are categorized into 4 different types such as 'Search Engine,' 'Open Communities,' 'Specialty Communities,' and 'Activity Communities.' Each type of knowledge community does not remain the same, for example. Rather, it changes with time and is also affected by the external business environment. Therefore, it is critical to develop processes for practical use of such changeable knowledge communities. Yet there is little research regarding a strategic framework for knowledge communities as a source of knowledge creation and use. The purposes of this study are (1) to find factors that can affect knowledge creation and use for each type of knowledge community and (2) to develop a strategic framework for practical use of the knowledge communities. Based on previous research, we found 7 factors that have considerable impacts on knowledge creation and use. They were 'Fitness,' 'Reliability,' 'Systemicity,' 'Richness,' 'Similarity,' 'Feedback,' and 'Understanding.' We created 30 different questions from each type of knowledge community. The questions included common sense, IT, business and hobbies, and were uniformly selected from various knowledge communities. Instead of using survey, we used these questions to ask users of the 4 representative web sites such as Google from Search Engine, NAVER Knowledge iN from Open Communities, SLRClub from Specialty Communities, and Wikipedia from Activity Communities. These 4 representative web sites were selected based on popularity (i.e., the 4 most popular sites in Korea). They were also among the 4 most frequently mentioned sitesin previous research. The answers of the 30 knowledge questions were collected and evaluated by the 11 IT experts who have been working for IT companies more than 3 years. When evaluating, the 11 experts used the above 7 knowledge factors as criteria. Using a stepwise linear regression for the evaluation of the 7 knowledge factors, we found that each factors affects differently knowledge creation and use for each type of knowledge community. The results of the stepwise linear regression analysis showed the relationship between 'Understanding' and other knowledge factors. The relationship was different regarding the type of knowledge community. The results indicated that 'Understanding' was significantly related to 'Reliability' at 'Search Engine type', to 'Fitness' at 'Open Community type', to 'Reliability' and 'Similarity' at 'Specialty Community type', and to 'Richness' and 'Similarity' at 'Activity Community type'. A strategic framework was created from the results of this study and such framework can be useful for knowledge communities that are not stable with time. For the success of knowledge community, the results of this study suggest that it is essential to ensure there are factors that can influence knowledge communities. It is also vital to reinforce each factor has its unique influence on related knowledge community. Thus, these changeable knowledge communities should be transformed into an adequate type with proper business strategies and objectives. They also should be progressed into a type that covers varioustypes of knowledge communities. For example, DCInside started from a small specialty community focusing on digital camera hardware and camerawork and then was transformed to an open community focusing on social issues through well-known photo galleries. NAVER started from a typical search engine and now covers an open community and a special community through additional web services such as NAVER knowledge iN, NAVER Cafe, and NAVER Blog. NAVER is currently competing withan activity community such as Wikipedia through the NAVER encyclopedia that provides similar services with NAVER encyclopedia's users as Wikipedia does. Finally, the results of this study provide meaningfully practical guidance for practitioners in that which type of knowledge community is most appropriate to the fluctuated business environment as knowledge community itself evolves with time.