• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.57-63
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• 2009

With an exponential increase in electronic commerce (e-commerce), marketers are attempting to gain a competitive advantage by emphasizing service quality and post interaction service aspects, which leads to customer satisfaction or behavioral consequence. Particularly for apparel, service quality is one of the key determinants in encouraging customer e-loyalty, and hence the success of apparel retailing in the context of electronic commerce. Therefore, this study explores e-service quality (E-SERVQUAL) factors and their unique effects on e-loyalty for apparel online shopping based on Parasuraman et al' s (2005) framework. Specific objectives of this study are to identify underlying dimension of E-SERVQUAL, and analyze a structural model for examining the effect of E-SERVQUAL on e-loyalty for online apparel shopping. For the theoretical framework of service quality in the context of online shopping, literatures on traditional and electronic service quality factors were comparatively reviewed, and two aspects of core and recovery services were identified. This study hypothesized that E-SERVQUAL has an effect on e-loyalty; customer satisfaction has a positive effect on e-service loyalty for apparel online shopping; and customer satisfaction mediates in the effect of E-SERVQUAL on e-loyalty for apparel online shopping. A self-administered questionnaire was developed based on literatures. A total of 252 usable questionnaires were obtained from online consumers who had purchase experience with online shopping for apparel products and reside in standard metropolitan areas, in the United States. Factor analysis (e.g., exploratory, confirmatory) was conducted to assess the validity and reliability and the structural equation model including measurement and structural models was estimated via LISREL 8.8 program. Findings showed that the E-SERVQUAL of shopping websites for apparel consisted of five factors: Compensation, Fulfillment, Efficiency, System Availability, and Responsiveness. This supports Parasuraman (2005)'s E-S-QUAL encompassing two aspects of core service (e.g., fulfillment, efficiency, system availability) and recovery related service (e.g., compensation, responsiveness) in the context of apparel shopping online. In the structural equation model, there are five exogenous latent variables for e-SERVQUAL factors; and two endogenous latent variables (e.g., customer satisfaction, e-loyalty). For the measurement model, the factor loadings for each respective construct were statistically significant and were greater than .60 and internal consistency reliabilities ranged from .85 to .88. In the estimated structural model of the e-SERVEQUAL factors, the system availability was found to have direct and positive effect on e-loyalty, whereas efficiency had a negative effect on e-loyalty for apparel online shopping. However, fulfillment was not a significant predictor for explaining consequences of E-SERVQUAL for apparel online shopping. This finding implies that perceived service quality of system available was likely to increase customer satisfaction for apparel online shopping. However, it was not supported that e-loyalty was determined by service quality, because service quality has an indirect effect on e-loyalty (i.e., repurchase intention) by mediating effect of value or satisfaction in the context of online shopping for apparel. In addition, both compensation and responsiveness were found to have a significant impact on customer satisfaction, which influenced e-loyalty for apparel online shopping. Thus, there was significant indirect effect of compensation and responsiveness on e-loyalty. This suggests that the recovery-specific service factors play an important role in maximizing customer satisfaction levels and then maintaining customer loyalty to the online shopping site for apparel. The findings have both managerial and research implications. Fashion marketers can establish long-term relationship with their customers based on continuously measuring customer perceptions for recovery-related service quality, such as quick responses to problem and returns, and compensation for customers' problem after their purchases. In order to maintain e-loyalty, recovery services play an important role in the first choice websites for consumers to purchase clothing. Given that online consumers may shop anywhere, a marketing strategy for improving competitive advantages is to provide better service quality, maximize satisfaction, and turn to creating customers' e-loyalty for apparel online shopping. From a researcher's perspective, there are some limitations of this research that should be considered when interpreting its findings. For future research, findings provide a basis for the further study of this important topic along both theoretical and empirical dimensions. Based on the findings, more comprehensive models for predicting E-SERVQUAL's consequences can be developed and tested. For global fashion marketing, this study can expand to a cross-cultural approach into e-service quality for apparel by including multinational samples.

• Journal of Technologic Dentistry
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• v.25 no.1
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• pp.203-218
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• 2003

The 3 year graduate school course of the dental technician, which has been enforced since 1994 till the present date, differs from the currently existing 2 year graduate course because of an 8 weeks clinical field training course being newly executed and an imposed curriculum about manufacturing specialized prosthetics like all-ceramic, double prosthetic technology, attachment, and implant. Even though nearly 10 years have passed, the education program of the 18 colleges have still not been standardized and the subjects differing a little, while some are still not following the 3 years graduate course. The goal of this research is to emphasize the qualities of the 3 years graduate program and enable the dental technician to handle clinical models in the dental technical clinic right after graduation by adding clinical field training in the dental technician education program of the 18 colleges. Also in accordance to a national and international increase in esthetical prosthetics, credits, weekly study hours, education practice time of specialized prosthetic dental technology can be analyzed as follows. 1. In the year 2003, currently colleges start clinical practice education starting from the 1st semester of the 2nd year junior year, to the 2nd semester of 3rd year the varying in time with adequate class time, and credits. The average credit is 9.56, and weekly average class time is 18.00 hours. later clinical trainee education will be adjusted to the 3 year graduate school course to 10 credits and 20 hours and the adequate education period should be the 2nd semester of 3rd grade when most basic clinical education has been covered. 2. Currently in the year 2003, all-ceramic education has an average credit of 8.01 in 17 colleges with an exception of Ma-san college. The weekly average theoretical education is 4.94 hours, weekly clinical education of 7.88 hours and currently in 14 colleges porcelain technical class usually starts in the 1st semester of the 2nd year. All-ceramic education is thought to have adequate credits, timing, and weekly study hours. 3. Currently in 2003 implant education is enforced in 11 colleges including Bu-san Catholic university and the education period is usually in the 3rd year. Out of the 11 colleges, only Bu-san Catholic univ., Ma-san and Shinheung college have practice training classes. We knew that Shingu, Dongu, Mokpo science colleges have practice training as a curriculum, namely specific prosthetics laboratory. Out of the 9 colleges enforcing implant education the average credits taken are 2.56, and the average hours of weekly theory education is 2.14, but with the exception of Shinheung college which has an implant practice training course theory and practice classes are not divided. Therefore implant education is thought to start in the 3rd year as a 3 credit course with 3 hours of theory and practice each. 4. Currently in 2003, theoretical attachment education is given in 15 colleges and including practical training it is given in 10 colleges. The education starts 1st semester of the 2nd year till the 2nd semester of the 3rd year. The average credit of attachment theory education in the 15 colleges was 3.64, the average weekly theoretical education was 2.64, and the average weekly practice training out of the schools teaching it was 3.20. Later attachment education is thought to start the 1st semester of the 3rd year as a 3 credit course with 2 hours of theory class and 3 hours of practice training. 5. Double prosthetic technology is currently carried out in Dae-jon Health Science college(2nd year 2nd semester, 2 credits, theory 2hours), Gimcheon college (1 credit, 2 hours of practical training), Bu-san Catholic university (4th year 2nd semester, 4 hours of theory. practice). When the 3 year course is enforced, education will start 1st semester of the 3rd year with 2hours of theory and practice each. 6. The newly installed programs of the 3 year education is clinical field training, and specialized prosthetic manufacturing practice like all-ceramic, double prosthetic technology, attachment, and implant. If such education is to be effectively managed, a primary precursor as systemic basic clinical education is thought to be important. 7. Nationally in the 18 colleges of dental technology the currently executed curriculum course had varying subjects, class time according to the subject, and credits by each college. The curriculum difference between the colleges must be settled.

• Journal of Science Education
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• v.44 no.1
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• pp.92-111
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• 2020

The 2015 revised science curriculum and NGSS (Next Generation Science Standard) suggest computational thinking as an inquiry skill or competency. Particularly, concern in computational thinking has increased since the Ministry of Education has required software education since 2014. However, there is still insufficient discussion on how to integrate computational thinking in science education. Therefore, this study aims to prepare a way to integrate computational thinking elements into scientific inquiry by analyzing the related literature. In order to achieve this goal, we summarized various definitions of the elements of computational thinking and analyzed general problem solving process and scientific inquiry process to develop and suggest the model. We also considered integrated problem solving cases from the computer science field and summarized the elements of the Computational Thinking-Scientific Inquiry (CT-SI) model. We asked scientists to explain their research process based on the elements. Based on these explanations from the scientists, we developed 'Problem-finding' CT-SI model and 'Problem solving' CT-SI model. These two models were reviewed by scientists. 'Problem-finding' model is relevant for selecting information and analyzing problems in the theoretical research. 'Problem solving' is suitable for engineering problem solving process using a general research process and engineering design. In addition, two teachers evaluated whether these models could be used in the secondary school curriculum. The models we developed in this study linked with the scientific inquiry and this will help enhance the practices of 'collecting, analyzing and interpreting data,' 'use of mathematical thinking and computer' suggested in the 2015 revised curriculum.

• Asia pacific journal of information systems
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• v.22 no.2
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• pp.39-69
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• 2012

With the advent of communication technologies including electronic collaborative tools and conferencing systems provided over the Internet, virtual collaboration is becoming increasingly common in organizations. Virtual collaboration refers to an environment in which the people working together are interdependent in their tasks, share responsibility for outcomes, are geographically dispersed, and rely on mediated rather than face-to face, communication to produce an outcome. Research suggests that new sets of individual skill, knowledge, and ability (SKAs) are required to perform effectively in today's virtualized workplace, which is labeled as individual virtual competence. It is also argued that use of online social networking sites may influence not only individuals' daily lives but also their capability to manage their work-related relationships in organizations, which in turn leads to better performance. The existing research regarding (1) the relationship between virtual competence and task performance and (2) the relationship between online networking and task performance has been conducted based on different theoretical perspectives so that little is known about how online social networking and virtual competence interplay to predict individuals' task performance. To fill this gap, this study raises the following research questions: (1) What is the individual virtual competence required for better adjustment to the virtual collaboration environment? (2) How does online networking via diverse social network service sites influence individuals' task performance in organizations? (3) How do the joint effects of individual virtual competence and online networking influence task performance? To address these research questions, we first draw on the prior literature and derive four dimensions of individual virtual competence that are related with an individual's self-concept, knowledge and ability. Computer self-efficacy is defined as the extent to which an individual beliefs in his or her ability to use computer technology broadly. Remotework self-efficacy is defined as the extent to which an individual beliefs in his or her ability to work and perform joint tasks with others in virtual settings. Virtual media skill is defined as the degree of confidence of individuals to function in their work role without face-to-face interactions. Virtual social skill is an individual's skill level in using technologies to communicate in virtual settings to their full potential. It should be noted that the concept of virtual social skill is different from the self-efficacy and captures an individual's cognition-based ability to build social relationships with others in virtual settings. Next, we discuss how online networking influences both individual virtual competence and task performance based on the social network theory and the social learning theory. We argue that online networking may enhance individuals' capability in expanding their social networks with low costs. We also argue that online networking may enable individuals to learn the necessary skills regarding how they use technological functions, communicate with others, and share information and make social relations using the technical functions provided by electronic media, consequently increasing individual virtual competence. To examine the relationships among online networking, virtual competence, and task performance, we developed research models (the mediation, interaction, and additive models, respectively) by integrating the social network theory and the social learning theory. Using data from 112 employees of a virtualized company, we tested the proposed research models. The results of analysis partly support the mediation model in that online social networking positively influences individuals' computer self-efficacy, virtual social skill, and virtual media skill, which are key predictors of individuals' task performance. Furthermore, the results of the analysis partly support the interaction model in that the level of remotework self-efficacy moderates the relationship between online social networking and task performance. The results paint a picture of people adjusting to virtual collaboration that constrains and enables their task performance. This study contributes to research and practice. First, we suggest a shift of research focus to the individual level when examining virtual phenomena and theorize that online social networking can enhance individual virtual competence in some aspects. Second, we replicate and advance the prior competence literature by linking each component of virtual competence and objective task performance. The results of this study provide useful insights into how human resource responsibilities assess employees' weakness and strength when they organize virtualized groups or projects. Furthermore, it provides managers with insights into the kinds of development or training programs that they can engage in with their employees to advance their ability to undertake virtual work.

• Management & Information Systems Review
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• v.35 no.3
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• pp.1-22
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• 2016

We analyzed the international comovements and structural changes in the quarterly real GDP by the Markov-switching vector autoregressive model (MS-VAR) from 1971(1) to 2016(1). The main results of this study were as follows. First, the business cycle phenomenon that occurs in the models or individual time series in real GDP has been grasped through the MS-VAR models. Unlike previous studies, this study showed the significant comovements, asymmetry and structural changes in the MS-VAR model using a real GDP across countries. Second, even if there was a partial difference, there were remarkable structural changes in the economy contraction regime(recession), such as 1988(2) ending the global oil shock crisis and 2007(3) starting the global financial crisis by the MS-VAR model. Third, large-scale structural changes were generated in the economic expansion and/or contraction regime simultaneously among countries. We found that the second world oil shocks that occurred after the first global oil shocks of 1973 and 1974 were the main reasons that caused the large-scale comovements of the international real GDP among countries. In addition, the spillover between Korea and 5 countries has been weak during the Asian currency crisis from 1997 to 1999, but there was strong transmission between Korea and 5 countries at the end of 2007 including the period of the global financial crisis. Fourth, it showed characteristics that simultaneous correlation appeared to be high due to the country-specific shocks generated for each country with the regime switching using real GDP since 1973. Thus, we confirmed that conclusions were consistent with a number of theoretical and empirical evidence available, and the macro-economic changes were mainly caused by the global shocks for the past 30 years. This study found that the global business cycles were due to large-scale asymmetric shocks in addition to the general changes, and then showed the main international comovements and/or structural changes through country-specific shocks.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.33-62
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• 2009

Internet computing is a disruptive IT innovation. Semantic Web can be considered as an IT innovation because the Semantic Web technology possesses the potential to reduce information overload and enable semantic integration, using capabilities such as semantics and machine-processability. How should organizations adopt the Semantic Web? What factors affect the adoption and diffusion of Semantic Web innovation? Most studies on adoption and diffusion of innovation use empirical analysis as a quantitative research methodology in the post-implementation stage. There is criticism that the positivist requiring theoretical rigor can sacrifice relevance to practice. Rapid advances in technology require studies relevant to practice. In particular, it is realistically impossible to conduct quantitative approach for factors affecting adoption of the Semantic Web because the Semantic Web is in its infancy. However, in an early stage of introduction of the Semantic Web, it is necessary to give a model and some guidelines and for adoption and diffusion of the technology innovation to practitioners and researchers. Thus, the purpose of this study is to present a model of adoption and diffusion of the Semantic Web and to offer propositions as guidelines for successful adoption through a qualitative research method including multiple case studies and in-depth interviews. The researcher conducted interviews with 15 people based on face-to face and 2 interviews by telephone and e-mail to collect data to saturate the categories. Nine interviews including 2 telephone interviews were from nine user organizations adopting the technology innovation and the others were from three supply organizations. Semi-structured interviews were used to collect data. The interviews were recorded on digital voice recorder memory and subsequently transcribed verbatim. 196 pages of transcripts were obtained from about 12 hours interviews. Triangulation of evidence was achieved by examining each organization website and various documents, such as brochures and white papers. The researcher read the transcripts several times and underlined core words, phrases, or sentences. Then, data analysis used the procedure of open coding, in which the researcher forms initial categories of information about the phenomenon being studied by segmenting information. QSR NVivo version 8.0 was used to categorize sentences including similar concepts. 47 categories derived from interview data were grouped into 21 categories from which six factors were named. Five factors affecting adoption of the Semantic Web were identified. The first factor is demand pull including requirements for improving search and integration services of the existing systems and for creating new services. Second, environmental conduciveness, reference models, uncertainty, technology maturity, potential business value, government sponsorship programs, promising prospects for technology demand, complexity and trialability affect the adoption of the Semantic Web from the perspective of technology push. Third, absorptive capacity is an important role of the adoption. Fourth, suppler's competence includes communication with and training for users, and absorptive capacity of supply organization. Fifth, over-expectance which results in the gap between user's expectation level and perceived benefits has a negative impact on the adoption of the Semantic Web. Finally, the factor including critical mass of ontology, budget. visible effects is identified as a determinant affecting routinization and infusion. The researcher suggested a model of adoption and diffusion of the Semantic Web, representing relationships between six factors and adoption/diffusion as dependent variables. Six propositions are derived from the adoption/diffusion model to offer some guidelines to practitioners and a research model to further studies. Proposition 1 : Demand pull has an influence on the adoption of the Semantic Web. Proposition 1-1 : The stronger the degree of requirements for improving existing services, the more successfully the Semantic Web is adopted. Proposition 1-2 : The stronger the degree of requirements for new services, the more successfully the Semantic Web is adopted. Proposition 2 : Technology push has an influence on the adoption of the Semantic Web. Proposition 2-1 : From the perceptive of user organizations, the technology push forces such as environmental conduciveness, reference models, potential business value, and government sponsorship programs have a positive impact on the adoption of the Semantic Web while uncertainty and lower technology maturity have a negative impact on its adoption. Proposition 2-2 : From the perceptive of suppliers, the technology push forces such as environmental conduciveness, reference models, potential business value, government sponsorship programs, and promising prospects for technology demand have a positive impact on the adoption of the Semantic Web while uncertainty, lower technology maturity, complexity and lower trialability have a negative impact on its adoption. Proposition 3 : The absorptive capacities such as organizational formal support systems, officer's or manager's competency analyzing technology characteristics, their passion or willingness, and top management support are positively associated with successful adoption of the Semantic Web innovation from the perceptive of user organizations. Proposition 4 : Supplier's competence has a positive impact on the absorptive capacities of user organizations and technology push forces. Proposition 5 : The greater the gap of expectation between users and suppliers, the later the Semantic Web is adopted. Proposition 6 : The post-adoption activities such as budget allocation, reaching critical mass, and sharing ontology to offer sustainable services are positively associated with successful routinization and infusion of the Semantic Web innovation from the perceptive of user organizations.

• Magazine of the Korean Society of Agricultural Engineers
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• v.19 no.1
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• pp.4279-4295
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• 1977

Two types of model were established in order to product the soil moisture content by which information on irrigation could be obtained. Model-I was to represent the soil moisture depletion and was established based on the concept of water balance in a given soil profile. Model-II was a mathematical model derived from the analysis of soil moisture variation curves which were drawn from the observed data. In establishing the Model-I, the method and procedure to estimate parameters for the determination of the variables such as evapotranspirations, effective rainfalls, and drainage amounts were discussed. Empirical equations representing soil moisture variation curves were derived from the observed data as the Model-II. The procedure for forecasting timing and amounts of irrigation under the given soil moisture content was discussed. The established models were checked by comparing the observed data with those predicted by the model. Obtained results are summarized as follows: 1. As a water balance model of a given soil profile, the soil moisture depletion D, could be represented as the equation(2). 2. Among the various empirical formulae for potential evapotranspiration (Etp), Penman's formula was best fit to the data observed with the evaporation pans and tanks in Suweon area. High degree of positive correlation between Penman's predicted data and observed data with a large evaporation pan was confirmed. and the regression enquation was Y=0.7436X+17.2918, where Y represents evaporation rate from large evaporation pan, in mm/10days, and X represents potential evapotranspiration rate estimated by use of Penman's formula. 3. Evapotranspiration, Et, could be estimated from the potential evapotranspiration, Etp, by introducing the consumptive use coefficient, Kc, which was repre sensed by the following relationship: Kc=Kco$.$Ka＋Ks‥‥‥(Eq. 6) where Kco : crop coefficient Ka : coefficient depending on the soil moisture content Ks : correction coefficient a. Crop coefficient. Kco. Crop coefficients of barley, bean, and wheat for each growth stage were found to be dependent on the crop. b. Coefficient depending on the soil moisture content, Ka. The values of Ka for clay loam, sandy loam, and loamy sand revealed a similar tendency to those of Pierce type. c. Correction coefficent, Ks. Following relationships were established to estimate Ks values: Ks=Kc-Kco$.$Ka, where Ks=0 if Kc,=Kco$.$K0$\geq$1.0, otherwise Ks=1-Kco$.$Ka 4. Effective rainfall, Re, was estimated by using following relationships : Re=D, if R-D$\geq$0, otherwise, Re=R 5. The difference between rainfall, R, and the soil moisture depletion D, was taken as drainage amount, Wd. {{{{D= SUM from { {i }=1} to n (Et-Re-I+Wd)}}}} if Wd=0, otherwise, {{{{D= SUM from { {i }=tf} to n (Et-Re-I+Wd)}}}} where tf=2∼3 days. 6. The curves and their corresponding empirical equations for the variation of soil moisture depending on the soil types, soil depths are shown on Fig. 8 (a,b.c,d). The general mathematical model on soil moisture variation depending on seasons, weather, and soil types were as follow: {{{{SMC= SUM ( { C}_{i }Exp( { - lambda }_{i } { t}_{i } )+ { Re}_{i } - { Excess}_{i } )}}}} where SMC : soil moisture content C : constant depending on an initial soil moisture content $\lambda$ : constant depending on season t : time Re : effective rainfall Excess : drainage and excess soil moisture other than drainage. The values of $\lambda$ are shown on Table 1. 7. The timing and amount of irrigation could be predicted by the equation (9-a) and (9-b,c), respectively. 8. Under the given conditions, the model for scheduling irrigation was completed. Fig. 9 show computer flow charts of the model. a. To estimate a potential evapotranspiration, Penman's equation was used if a complete observed meteorological data were available, and Jensen-Haise's equation was used if a forecasted meteorological data were available, However none of the observed or forecasted data were available, the equation (15) was used. b. As an input time data, a crop carlender was used, which was made based on the time when the growth stage of the crop shows it's maximum effective leaf coverage. 9. For the purpose of validation of the models, observed data of soil moiture content under various conditions from May, 1975 to July, 1975 were compared to the data predicted by Model-I and Model-II. Model-I shows the relative error of 4.6 to 14.3 percent which is an acceptable range of error in view of engineering purpose. Model-II shows 3 to 16.7 percent of relative error which is a little larger than the one from the Model-I. 10. Comparing two models, the followings are concluded: Model-I established on the theoretical background can predict with a satisfiable reliability far practical use provided that forecasted meteorological data are available. On the other hand, Model-II was superior to Model-I in it's simplicity, but it needs long period and wide scope of observed data to predict acceptable soil moisture content. Further studies are needed on the Model-II to make it acceptable in practical use.

• International Commerce and Information Review
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• v.15 no.4
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• pp.481-508
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• 2013

The purpose of this study is to research the specific ways of successful localization by analyzing the success and failures case for localization through the theoretical background and the strategic models of localization. The strategic models of localization are divided by management aspects such as the localization of production and sourcing, the localization of human resources, the localization of marketing, the localization of R&D, harmonious relationship with the local community and authority transfer between headquarters and local subsidiaries. And the specific measures of the successful localization are proposed within the framework of the strategic models by comparing and analyzing the success and failures case for localization of individual companies operating in Indonesia. The results indicate that there are successful companies which develop a suitable products for the local climate and failed automobile company which is weak for assembly of complete vehicle in terms of localization of production and sourcing. In case of localization of human resources, most companies recognize the importance of this part and endeavor to secure superior human resource through a related education. It is found that most of the companies perform R & D in their native country. In part of a harmonious relationship with the local community, Korean companies should contribute to the community and be friendly with local residents and make a good image of the company focusing on the cultural environment. In aspect of authority transfer between headquarters and local subsidiaries, there is a tendency to be determined by the head office rather than the joint participation. In the future, in order for Korean enterprise to be successful one in Indonesia market, a highly interdependent and complex forms between headquarters and local subsidiaries shall be performed and an active exchange of information and the selection of best talent regardless of nationality shall be promoted.

• Journal of the Korea Computer Graphics Society
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• v.6 no.4
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• pp.1-7
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• 2000

Traditionally, three dimension model s have been used for building virtual worlds, and a data structure called the "scene graph" is often employed to organize these 3D objects in the virtual space. On the other hand, image-based rendering has recently been suggested as a probable alternative VR platform for its photo-realism, however, due to limited interactivity. it has only been used for simple navigation systems. To combine the merits of these two approaches to object/scene representations, this paper proposes for a scene graph structure in which both 3D models and various image-based scenes/objects can be defined. traversed, and rendered together. In fact, as suggested by Shade et al. [1]. these different representations can be used as different LOD's for a given object. For in stance, an object might be rendered using a 3D model at close range, a billboard at an intermediate range. and as part of an environment map at far range. The ultimate objective of this mixed platform is to breath more interactivity into the image based rendered VE's by employing 3D models as well. There are several technical challenges in devising such a platform : designing scene graph nodes for various types of image based techniques, establishing criteria for LOD/representation selection. handling their transition s. implementing appropriate interaction schemes. and correctly rendering the overall scene. Currently, we have extended the scene graph structure of the Sense8's WorldToolKit. to accommodate new node types for environment maps. billboards, moving textures and sprites, "Tour-into-the-Picture" structure, and view interpolated objects. As for choosing the right LOD level, the usual viewing distance and image space criteria are used, however, the switching between the image and 3D model occurs at a distance from the user where the user starts to perceive the object's internal depth. Also. during interaction, regardless of the viewing distance. a 3D representation would be used, if it exists. Finally. we carried out experiments to verify the theoretical derivation of the switching rule and obtained positive results.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.