• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.545-553
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• 2020

Although networking behavior is an effective job search method to students, far too little attention has been paid to mechanisms explaining the antecedents and networking behavior. The goal of this study was to demonstrate the effect of the HEXACO personality dimensions on graduated students' job search networking behavior through their network size. A survey of 773 participants was conducted to assess personality traits, network size, and networking behavior. All constructs in the study were measured by 5-point Likert scales. This study employed a structural equation model to examine the proposed conceptual model and the correlations among variables. Results showed that the personality of emotionality negatively influence students' network size, while extraversion and agreeableness are positively associated with the scope of their social network. Second, the findings confirmed that network size is directly related to the level of looking-for job behavior, particularly networking behavior. Finally, our results explored that network size played the mediating effect on how personality traits affect networking behavior. These findings suggest that network size is a dynamic mechanism that helps to understand the correlation between personality traits and job search networking behavior. The theoretical and practical implication of the study, as well as the future research direction were discussed.

• Journal of Distribution Science
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• v.15 no.6
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• pp.13-24
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• 2017

Purpose - The current study aims to examine the effect of social network factors on travel agency employees' occupational outcomes such as job performance and job satisfaction through innovation behavior in a comprehensive model. Research design, data, and methodology - Based on a theory of social network, the concept of social network was assessed by three factors: a) network size, b) network range, and c) tie strength. To test the proposed hypotheses, structural equation modeling (SEM) was employed based on data from 197 travel agency employees in Korea. Result - The results showed that the associational activity of network size had a positive effect on innovation behavior, while the network range of network size had a significant negative effect on innovation behavior. Subsequently, innovation behavior positively influenced on job performance and job satisfaction, respectively. Conclusions - The results offer some insights into the extended model and have important managerial implications for Korean travel agencies. More specifically, considering diverse domains of social network and organizational research, this study advances critical utility of social network factors in a high facilitating level of innovation behavior, which can help travel agency employees promote their job performance and job satisfaction.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1299-1303
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• 2005

Over the last decade the research of end-to-end behavior on computer network has grown by orders but it has few researching in hop-by-hop behavior. We think if we know hop-by-hop behavior it can make better understanding in network behavior. This paper represent ICMP time stamp request and time stamp reply as tool of network study for learning in hop-by-hop behavior to estimate link bandwidth and link structure. We describe our idea, experiment tools, experiment environment, result and analysis, and our discussion in our observative.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.159-166
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• 2019

In this paper, we propose takes network marketing as a starting point for analysis, uses the theory of purchasing behavior and enterprise performance to analyze the network marketing strategy of artistic products, incorporates the practical problems encountered by some artistic products enterprises in Zhejiang Province in network marketing into theoretical research. The theoretical model of network marketing strategy acting on enterprise performance through the intermediary effect of purchasing behavior is constructed. This paper conducted an in-depth survey of three representative core domestic companies engaged in Internet marketing of artistic products, and analyzed the questionnaires of 357 respondents. The initial model was verified by statistical tools such as SPSS and AMOS, and three conclusions were drawn: Firstly, network marketing strategies of different dimensions have different effects on purchasing behavior: pricing strategy and product strategy have significant positive effects on impulse purchasing behavior, but channel strategy has no significant impact on impulse purchasing behavior; Channel strategy and product strategy have a significant positive impact on repeated purchasing behavior, but pricing strategy has no significant impact on repeated purchasing behavior. Second, user purchasing behavior has a significant positive impact on enterprise performance. Third, network marketing strategies of different dimensions have significant direct and positive impact on enterprise performance.

• Korean Journal of Health Education and Promotion
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• v.19 no.2
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• pp.73-98
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• 2002

This study was carried out to investigate the relationship between social support, social network and health behaviors as surveyed by cross-sectional study in 744 rural people aged above 30 of a community dwelling sample of one county for 6 days of July in 2000. Objectives of this study was in order to establish an effective health promotion. The sample was accrued by face to face interview of direct visiting from clustered sampling method. Interview was conducted by trained medical students with the questionnaire consisted of socio-demographic data, health behavior, social support and social network based on previous literature. The summarized results were as follows: 1. There were significant difference in the level of social support and social network by general characteristic variables except occupation and residency type(p〈0.05). 2. There were significant difference in knowledge about hypertension, smoking status, status of physical exercise, diet patterns by social support and social network in spite of variation of social support and social network subconcept(p〈0.05). And there were significant difference in alcohol drinking status, body weight control and diet pattern according to level of social network(p〈0.05). But smoking status by social support and network results opposite direction(p〈0.05). 3. There were no regular or consistent result in the relationship between social support, social network and health behavior. 4. Major predictors for health behavior on the multiple logistic regression that included general characteristic, social support and social network were age, instrumental social support and worry about health. Significant variables of multiple logistic regression for health behavior that included social support(instrumental and emotional) and social network were instrumental social support and social network. These results suggest that only a instrumental element and social network may be associated with health behavior. Inconsistent with prior research in these some item, a positive consistent relationship was not found between social support, social network and health behavior. So the study should be replicated to determined the reliability of our findings.

• The Research Journal of the Costume Culture
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• v.27 no.3
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• pp.274-284
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• 2019

Research on cosmetic behavior has developed significantly since the 2000s. Reviewing cosmetic behavior research can be meaningful because it can grasp trends in the domestic cosmetics market, and it can also illuminate how domestic consumers' interest in makeup has changed over time. The purpose of this study is to investigate the links between major keywords and the keywords which affect makeup behavior of different age groups through network analysis. In this study we analyzed thesis and journal data based on makeup behavior through network analysis using Nodexl. We analyzed 10 years of journals and theses - from 2000 to 2017, and investigated age-related differences in variables related to makeup behavior. Research subjects were divided into age-based groups: 10, 20-40, and over 50. The total number of theses collected was 82. In order to perform network analysis using the Nodexl program, we extracted the frequency of representative words using the KrKwic program. The extracted core words were analyzed for degree centrality, betweenness centrality and eigenvector centrality using Nodexl. The expected result is that the network analysis using keywords will lead to different variables depending on age and the main goal of the cosmetics market, and it is expected to be used as the basis for follow-up research related to cosmetic behavior.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1540-1551
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• 2020

Aiming at the problem that the existing human behavior recognition algorithm cannot fully utilize the multi-level spatio-temporal information of the network, a human behavior recognition algorithm based on a dense three-dimensional residual network is proposed. First, the proposed algorithm uses a dense block of three-dimensional residuals as the basic module of the network. The module extracts the hierarchical features of human behavior through densely connected convolutional layers; Secondly, the local feature aggregation adaptive method is used to learn the local dense features of human behavior; Then, the residual connection module is applied to promote the flow of feature information and reduced the difficulty of training; Finally, the multi-layer local feature extraction of the network is realized by cascading multiple three-dimensional residual dense blocks, and use the global feature aggregation adaptive method to learn the features of all network layers to realize human behavior recognition. A large number of experimental results on benchmark datasets KTH show that the recognition rate (top-l accuracy) of the proposed algorithm reaches 93.52%. Compared with the three-dimensional convolutional neural network (C3D) algorithm, it has improved by 3.93 percentage points. The proposed algorithm framework has good robustness and transfer learning ability, and can effectively handle a variety of video behavior recognition tasks.

• The Journal of Information Systems
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• v.21 no.4
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• pp.1-29
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• 2012

The purpose of this study was to find about personal information security of internet and social networks by focusing on end users. User competence and subjective criterion, which are the antecedents, are affecting security behaviors For these security behaviors, the study examined the relationship between security behavior intention on internet use and security behavior intention about social network that is actively achieved in many fields. Behaviors of internet and social network were classified into an action of executing security and an action of using a security technology. In addition, this study investigated a theory about motivational factors of personal intention on a certain behavior based on theory of reasoned action in order to achieve the purpose of this study. A survey was conducted on 224 general individual users through online and offline, and the collected data was analyzed with SPSS 12.0 and SmartPLS 2.0 to verify demographic characteristics of respondents, exploratory factor analysis, and suitability of a study model. Interesting results were shown that security behavior intention of social network is not significant in all security behavior execution, which is security performance behavior, and security technology use. Internet security behavior is significant to security technology use but it does not have an effect on behavior execution.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1132-1137
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• 2013

In swarm robot systems, it is vital to maintain network connectivity to ensure cooperative behavior between robots. This paper deals with the behavior control algorithm of the swarm robots for maintaining network connectivity. To do this, we divide swarm robots into search-robots, base-robots, and relay-robots. Using these robots, we propose behavior control algorithm to maintain network connectivity. The behavior control algorithms to maintain network connectivity are proposed for the local path planning using virtual force and global path planning using the Delaunay triangulation, respectively. Finally, we demonstrate the effectiveness and applicability of the proposed method through some simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1450-1463
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• 2019

The problem towards crowd behavior recognition in a serious clustered scene is extremely challenged on account of variable scales with non-uniformity. This paper aims to propose a crowed behavior classification framework based on a transferring hybrid network blending 3D res-net with inception-v3. First, the 3D res-inception network is presented so as to learn the augmented visual feature of UCF 101. Then the target dataset is applied to fine-tune the network parameters in an attempt to classify the behavior of densely crowded scenes. Finally, a transferred entropy function is used to calculate the probability of multiple labels in accordance with these features. Experimental results show that the proposed method could greatly improve the accuracy of crowd behavior recognition and enhance the accuracy of multiple label classification.