• Journal of Technologic Dentistry
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• v.37 no.2
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• pp.79-94
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• 2015

Purpose: The main purposes of this study are to describe the organization effectiveness and to investigate the effects of dental technicians' work ethic on job satisfaction, organization citizen's action, and organizational commitment. Methods: A total of 300 dental technicians working at dental laboratories in the Daegu area were randomly selected and surveyed, 298 of them were used for the statistical analysis. Results: The work ethic sub-items, such as industry, work centrality, morality, time save, independence, and relation with co-worker are independent variables. The organization effectiveness subi-items, such as job satisfaction, organization citizen's action, and organizational commitment are dependent variables. Sociodemographic variables are used for control variables. Findings are as follows: First, in terms of dental technicians' work ethic, the level of relation with coworker was the highest, and work centrality was the lowest. Second, in terms of dental technicians' organization effectiveness, the level of citizen's organizational action was the highest followed by organizational commitment and job satisfaction in order. Third, the effects of industry, work centrality, time save, relation with coworker, and morality showed statistically significant relationships with organizational effectiveness. Fourth, the effects of industry, work centrality, time save, relation with co-worker, and morality statistically significant relationships with job satisfaction. Fifth, in terms of organization citizen's action, the effects of industry, work centrality, and time save were statistically significant. Sixth, work centrality, time save, relation with coworker, and independence were statistically significant with organizational commitment. Conclusion: Some policy implications for the improvement of organizational effectiveness are introduced and discussed. Dental technicians are required to have vocation and work ethic for themselves and the organization, and by doing so, they may contribute to the improvement of national oral health. Policies and educational programs, which can support them may be necessary.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.221-230
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• 2016

This is an experimental study which is designed to identify the joint relationship between communication density and centrality as independent factors to team performance, discovering how they would jointly affect work team performance. Specially different from existing studies, separating team performance into team efficiency and team effectiveness, we identified differential influences to the two independent factors. Findings suggest a competing relationship between communication density and centrality. A framework was proposed to help managers understand the joint effect of density and centrality on performance. Work team has high communication density and low centrality is "Innovating", which is likely to have a great extent of ideas, knowledge and information sharing, and reach high effectiveness. Team with high centrality and low density is characterized as "centralized". Such communication structure may reduce diversity of perspectives and accelerate team decision making. When both density and centrality are low, the team is "Autonomous". To increase external validity, other factors such as leadership, organizational climate influencing on team performance should be reflected in the future research.

• The Journal of Information Systems
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• v.31 no.2
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• pp.19-43
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• 2022

Purpose Due to the COVID-19 pandemic, many companies are building virtual workplaces based on virtual reality technology. Through this study, we intend to identify the trend of convergence and convergence research between virtual reality technology and work space, and suggest future promising fields based on this. Design/methodology/approach For this purpose, 12,250 bibliographic data of research papers related to Virtual Reality (VR) and Workplace were collected from Scopus from 1982 to 2021. The bibliographic data of the collected papers were analyzed using Text Mining and Pathfinder Network, Parallel Neighbor Clustering, Nearest Neighbor Centrality, and Triangle Betweenness Centrality. Through this, the relationship between keywords by period was identified, and network analysis and visualization work were performed for virtual reality-based workplace research. Findings Through this study, it is expected that the main keyword knowledge structure flow of virtual reality-based workplace convergence research can be identified, and the relationship between keywords can be identified to provide a major measure for designing directions in subsequent studies.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2001.05a
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• pp.95-99
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• 2001

This study aims from being meaning of centrality to possibility of space composition in the Contemporary Interior Space os forming of center and way of being. There it is studied analysed architect's work on character of certrality. This study mentiones not as analysis of location and perception aspect on uabanism but as various forming and changing in the contemporary interior space composition. it is definitioned as centrality in architecture space which is base in the course of congiting and organizing and is core space in forming area, It is moaned not as Euclidean plan but as three demeasional vector space in space express architectual space exists except for perception of human and takes center and direction in perculiarly.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.479-491
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• 2008

A "task network" is a type of social network that consists of experts who exchange professional help and advice regarding executing tasks. In this study, we investigate the task network used within the IS department of a national bank in Korea. We identify how this network moderates the influence of computer-mediated communication (CMC) technology on an individual s task performance. Size, density, and centrality were measured as the characteristics of a personal task networks. Size equates to the total number of colleagues who work with a specific member for a certain project. Density is the ratio of the number of actual relationships to the total number of available relationships. Centrality defines whether an individual s position is in the exact center of whole network, and is measured by betweenness centrality, meaning the position one member holds between others in a network. Our findings conclude that the conditions - the larger the size of the task network, the smaller its density and the higher its level of centrality - lead to more benefits of using CMC media. Further, this positive effect of CMC is more noticeable when it provides synchronicity.

• International Area Studies Review
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• v.18 no.3
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• pp.131-145
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• 2014

Abundance of low-wage labor resources, strategic location connecting East-West Asia and business professionals are fluent in English are strength of Bangladesh. Also the business environment changes in China such as the wage increases and labor regulations enhancement acts as searching for replacement of investment where Bangladesh is considered as substitute. At this point there is a need for research of Bangladesh employees at human resource management level. Therefore this study focus on the research of an important component of human resource management, organizational commitment. This study analysis the Bangladesh employees organizational commitment and its antecedent. This study consider four antecedents, role ambiguity, role conflict, voluntary participation and the work centrality and three organizational commitment, affective organizational commitment, continuous organizational commitment and normative organizational commitment. As results show, role ambiguity and role conflict has a negative influence on affective organizational commitment. And voluntary participation and work centrality give positive influence. Role ambiguity showed a negative effect on continuous organizational commitment, however role conflict show positive effect. Voluntary participation and work centrality showed positive effect on normative organizational commitment and role ambiguity showed negative influence. Results of this study give clue to understand Bangladesh employees organizational commitment and its relation among variables. And thus the need for appropriate management presented.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Communications for Statistical Applications and Methods
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• v.18 no.2
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• pp.213-217
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• 2011

For the social network of n nodes, one might be interested in finding k nodes to disseminate the information as quickly as possible or to identify key nodes of high "local centrality". I propose two algorithms for determining k "local centers" of the network and work on a real case.

• Korean Journal of Social Welfare
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• v.49
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• pp.190-224
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• 2002

The purpose of this study was to find out the characteristics of the direct workers and the organizations delivering services to the children in low-income families, and to identify major factors that affect the number and degree centrality of service network. The research sample was 141 organizations. and the data were collected by a survey questionnaire and analyzed by UCINET V and multiple regression. The results show that the classification of organizations, the work-autonomy, the license of social welfare have a significant effect on the number of network organization, and the license of social welfare, the subjective body of organizations, the number of children in charge have a significant effect on the degree centrality of service network, among the independent variables. Based on the research results, implications for the future practice are discussed.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.361-368
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• 2004

The purpose of the study was to explore the potential of the Social Network Analysis as an analytical tool for scientific investigation of learner-learner, or learner-tutor interaction within an Computer Supported Corporative Learning (CSCL) environment. Theoretical and methodological implication of the Social Network Analysis had been discussed. Following theoretical analysis, an exploratory empirical study was conducted to test statistical correlation between traditional performance measures such as achievement and team contribution index, and the centrality measure, one of the many quantitative measures the Social Network Analysis provides. Results indicate the centrality measure was correlated with the higher order learning performance and the peer-evaluated contribution indices. An interpretation of the results and their implication to instructional design theory and practices were provided along with some suggestions for future research.