• Journal of Information Management
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• v.40 no.4
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• pp.135-150
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• 2009

Existing bibliometric laws have been established on the basis of well defined science journals with a long history. However, the history of technology innovation research in Korea is young and the scope of the research is diverse compared with other fields. The main purpose of this research can be summarized as follows : Can the traditional bibliometric laws be used to explain the young and diverse data derived from technology innovation studies in Korea. Second, we want to compare the explain ability of the power law, compared with the traditional laws in the field. Third, we propose a quasi index related to the well-known impact factor to measure the contribution of a journal or a group of journals to the development of innovation research in Korea. We confirmed Lotka's and Bradford's laws which are used to measure the productivity of researchers, but we could not support the validity of Price's Square Root law as Nicholls (1998) could not. On the citations to journals, Garfield's laws is not observed. However, the power law fits well the citations to author, journal, article, and book. The estimated parameters between 1.6 and 3.5 are similar to the values in the range of 1.5 and 3 in previous studies. Finally the quasi index shows that the influence of international leading journals on innovation research in Korea is weaker than on innovation studies in the world.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• Journal of Technology Innovation
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• v.19 no.3
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• pp.85-114
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• 2011

This paper aims at developing a new index that represents the Korean new growth industries, which is named the Korea Future Technology Index(KOFTI). The KOFTI is designed to provide a reliable and econometric index based on which the Korean government searches for new growth engines. The KOFTI is composed of three individual indexes such as the Economic Impact Index, the Future Strategy Index, and the Technological Influence Index. The KOFTI is applied for 62 star brands, which have been promoted by the Korean government for the korean future industrial competitiveness. The top 13 leading industries are drawn from the calculation of the KOFTI for 62 star brands.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.265-274
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• 2021

This study empirically analyzed the users' experiences with the Netflix thumbnail curation based on the Technology Acceptance Model(TAM). According to the correlation analysis results, the higher the dependence on the thumbnails, the higher the satisfaction with the thumbnail curation. Both Perceived Informational Usefulness(PIU) and Perceived Ease of Use(PEOU) had correlations with the degree of satisfaction with the thumbnail curation. In particular, the factors of relevance in PEOU had the greatest impact on the degree of satisfaction and this result proved that the suitability factors of the thumbnails had significant correlations with the degree of satisfaction. The degree of satisfaction with the thumbnail curation also positively correlated with Netflix's overall degree of satisfaction and behavioral intention to use the Netflix. This study demonstrated the suitability of the TAM as a UX evaluation tool for the Netflix thumbnail curation.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.355-370
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• 2013

This study was aimed at the married immigrant women and was attempted to provide the basic data of the nursing practice useful in identifying the relationship aspects and the influence of resilience factor and promoting the family adaptation. This study was conducted for the married immigrant women who were located in urban-rural complex area around Daejeon city and in Chungnam region, and the multi-cultural families supporting program of community welfare halls among those who had resided over 1 year in Korea. The data was collected from Feb, 2012 to July, 2012 and in the end, 216 questionnaires were made the subjects of data analysis. For the collected data, frequency analysis, percentage, ANOVA, t-test and correlation analysis were conducted using SPSS, LISREL. The overall index of hypothesis model showed a good congruence like ${\chi}^2$ = .06 (p= .812), df=1, ${\chi}^2$(df)=.06, GFI=1.0, AGFI= 1.0, SRMR=.002, NFI= 1.0, NNFI=1.0, RMSEA=0.000, CN=266. Looking at the results of hypothesis testing suggested by the model, the variables which affected the family adaptation were family stress and parenting stress, while social support, family hardness, problem solving communication, and problem solving coping didn't affect the family adaptation. It is considered that based on the results of this study, nursing intervention which helps the family adaptation of the married immigrant women who are in a crisis situation must be done with a program which can help them have a positive view on the stress situation and reduce the stress happening in the family relationship and parenting.

• Korean Journal of Construction Engineering and Management
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• v.11 no.6
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• pp.100-110
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• 2010

The main roots of CM service contracts include existing customer repurchases and those made by new customers by existing ones. The study on customers and loyalty can be factors to strengthen CM's competitiveness. However, there have been little attempt to study customer satisfaction and customer loyalty. Construction Management (CM), the advanced construction management method, was introduced 15 years ago in the mid 1990's in the domestic market. The aim of this research is to build a model that can predict customer loyalty based on how much customers are satisfied with CM service. To measure customer satisfaction and loyalty, this research surveyed 135 decision-makers who have experienced CM services. Customer satisfaction was tested and analyzed according to different phases: planning, designing, procurement, construction, and post construction. Referral intention was tested based on NPS theory. Customer types were divided into detractors, passively satisfied and promoters according to the tested measurement and multinomial logistic regression between the satisfaction by construction phases and customer types. This research resulted to a model that can predict customer types: detractors, passively satisfied and promoters, which were determined according to satisfaction level. The initial planning phase also revealed which factor is most influential for a customer to become promoter. These results can be used to acquire customer loyalty by managing the satisfaction of customers through a project under an Internet-based environment. Such can provide the needed information in quickly exploring positive and negative word-of-mouth feedbacks.

• Management & Information Systems Review
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• v.36 no.3
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• pp.255-268
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• 2017

This study examines whether firms with tax avoidance of Corporate Social Responsibility(CSR) performance is tempered by the extent firms engage in CEO turnovers. Considering the increasing interest in CSR activities of the firm to secure sustainable growth of national economy, this paper investigates the benefit and cost of CSR activities by combining the agency theory using the firm level data. Prior studies document that investors positively value tax avoidance. The rationale for this finding is that tax avoidance provides cash savings that can be used by firm managers to generate future shareholder wealth. Prior studies also show that investors' valuations are sensitive to the risk of future negative tax outcomes. Assuming that many types of CSR performances are low risk, low yielding uses of firm resources, we posit that higher levels of CSR performance may signal to investors that cash generated via tax avoidance has not been fully used to generate a return sufficient to offset the risk associated with aggressive tax planning strategies. Consistent with this argument, we predict and find that the positive association between CSR performance and tax avoidance is significantly weakened when firms have higher positive levels of CEO turnovers. Further, we predict and find that 'philanthropic' types of CSR activities in particular are associated with investor discounting of tax avoidance. We interpret our results as suggesting the equity market views CSR activities to be ostensibly funded through cash savings generated via tax avoidance.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.174-189
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• 2015

The objective of this study was to reconstruct spatial information using the results of the investigation and evaluation of the health of the living organisms, habitat, and water quality at the investigation points for the aquatic ecosystem health of the Nakdong River basin, to support the rational decision making of the aquatic ecosystem preservation and restoration policies of the Nakdong River basin using spatial analysis techniques, and to present efficient management methods. To analyze the aquatic ecosystem health of the Nakdong River basin, punctiform data were constructed based on the position information of each point with the aquatic ecosystem health investigation and evaluation results of 250 investigation sections. To apply the spatial analysis technique, the data need to be reconstructed into areal data. For this purpose, spatial influence and trends were analyzed using the Kriging interpolation(ArcGIS 10.1, Geostatistical Analysis), and were reconstructed into areal data. To analyze the spatial distribution characteristics of the Nakdong River basin health based on these analytical results, hotspot(Getis-Ord Gi, $G^*_i$), LISA(Local Indicator of Spatial Association), and standard deviational ellipse analyses were used. The hotspot analysis results showed that the hotspot basins of the biotic indices(TDI, BMI, FAI) were the Andong Dam upstream, Wangpicheon, and the Imha Dam basin, and that the health grades of their biotic indices were good. The coldspot basins were Nakdong River Namhae, the Nakdong River mouth, and the Suyeong River basin. The LISA analysis results showed that the exceptional areas were Gahwacheon, the Hapcheon Dam, and the Yeong River upstream basin. These areas had high bio-health indices, but their surrounding basins were low and required management for aquatic ecosystem health. The hotspot basins of the physicochemical factor(BOD) were the Nakdong River downstream basin, Suyeong River, Hoeya River, and the Nakdong River Namhae basin, whereas the coldspot basins were the upstream basins of the Nakdong River tributaries, including Andong Dam, Imha Dam, and Yeong River. The hotspots of the habitat and riverside environment factor(HRI) were different from the hotspots and coldspots of each factor in the LISA analysis results. In general, the habitat and riverside environment of the Nakdong River mainstream and tributaries, including the Nakdong river upstream, Andong Dam, Imha Dam, and the Hapcheon Dam basin, had good health. The coldspot basins of the habitat and riverside environment also showed low health indices of the biotic indices and physicochemical factors, thus requiring management of the habitat and riverside environment. As a result of the time-series analysis with a standard deviation ellipsoid, the areas with good aquatic ecosystem health of the organisms, habitat, and riverside environment showed a tendency to move northward, and the BOD results showed different directions and concentrations by the year of investigation. These aquatic ecosystem health analysis results can provide not only the health management information for each investigation spot but also information for managing the aquatic ecosystem in the catchment unit for the working research staff as well as for the water environment researchers in the future, based on spatial information.