• Journal of Fashion Business
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• v.9 no.3
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• pp.22-36
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• 2005

This research is to classify psychological risk perceptions in purchases process at counterfeit at fashion luxury brands, into a risk perception on purchase activity itself and a risk perception on the post-purchase situation, and to analyze types and characteristics at risk reduction behaviors to reduce each risk perception. In this research a qualitative method was employed, and research-related data were collected and analyzed through in-depth interviews. Results were shown that risk reduction behaviors at psychological risk perception on purchase activity itself included rationalization of purchase, accompanied purchase, reduction and discontinuance of purchase, and that risk reduction behaviors of psychological risk perception on the post-purchase situation included information search, establishment of selection criteria, establishment of marginal limit, selective purchase, planned and compared purchase, and reduction and discontinuance of purchase. Previous researches suggested brand loyalty, selection of famous brands, utilization of information agents by marketers, pre-purchase usage and guaranteed purchase, but these risk reduction methods were not utilized, this probably being interpreted as a result of characteristics of counterfeit. In addition, risk reduction behavior of one type tended to reduce risk perception of several other types, and risk reduction behaviors of various types were utilized to reduce a certain type's risk perception. Not only types of risk perception but also levels of risk perception appeared to have exerted influence to risk reduction behaviors.

• Journal of information and communication convergence engineering
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• v.10 no.2
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• pp.149-155
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• 2012

This paper presents mobile robot control architecture of hierarchical behaviors, inspired by biological life. The system is reactive, highly parallel, and does not rely on representation of the environment. The behaviors of the system are designed hierarchically from the bottom-up with priority given to primitive behaviors to ensure the survivability of the robot and provide robustness to failures in higher-level behaviors. Fuzzy logic is used to perform command fusion on each behavior's output. Simulations of the proposed methodology are shown and discussed. The simulation results indicate that complex tasks can be performed by a combination of a few simple behaviors and a set of fuzzy inference rules.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.231-244
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• 2012

Consumer dissatisfaction and complaints make it difficult for online shopping mall to maintain existing customers and attract new customers, which may result in a direct profit loss. The primary purpose of this study is to investigate the relationship between customer dissatisfaction in terms of product-complaints and website complaints and complaint behaviors in terms of individual, public, and 3rd party complaint behaviors. Th results indicate that product-dissatisfaction is significantly related to the public and 3rd party complaint behaviors, but not the individual complaint behavior. Website dissatisfaction was not found to be significantly related to any complaint behavior. The moderate effect of sex and individual attitude on the relationship between customer dissatisfaction and complaint behaviors was also not considerable.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.137-140
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• 2003

This paper proposes a pursuing system utilizing the learning method where multiple cooperating agents emulate social behaviors of animals and insects and realize their group behaviors. Each agent contains sensors to perceive other agents in several directions and decides its behavior based on the information obtained by the sensors. In this paper, a neural network is used fir behavior decision controller. The input of the neural network is decided by the existence of other agents and the distance to the other agents. The output determines the directions in which the agent moves. The connection weight values of this neural network are encoded as genes, and the fitness individuals are determined using a genetic algorithm. Here, the fitness values imply how much group behaviors fit adequately to the goal and can express group behaviors. The validity of the system is verified through simulation.

• Asia pacific journal of information systems
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• v.13 no.3
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• pp.131-149
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• 2003

This paper examines internet shopping mall user's customer satisfaction and their consequent attitude and customer loyalty behaviors. For this purpose, internet shopping mall user's customer satisfaction is proposed to affect trust, and commitment, and consequently to influence customer loyalty behaviors. This study, which used data from customers of internet shopping malls, showed satisfactory data-fit of the proposed model and supported five of the six research hypotheses. The empirical results indicated that customer satisfaction take significant effect on trust, and commitment, and the trust and commitment in turn have strong influence on customer's loyalty behaviors. It was confirmed that both trust and commitment variables are effective mediators linking internet shopping mall user's customer satisfaction and their loyalty behaviors.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.1-9
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• 2022

The influence of information sensitivity during the COVID-19 pandemic on perceived risk and personal preventive behaviors of consumers in China had been investigated. The participants were Chinese individuals experiencing the pandemic as it happened. Participants voluntarily completed an online questionnaire to provide their COVID-19 information sensitivity, their perceived COVID-19 risk, preventive behavior and their respective age. Our study discovered that COVID-19 information sensitivity positively influence perceived risk and preventive behavior. Moreover, young individuals show higher levels of online information sensitivity, which influenced their personal protective behavior when compared to that of middle-aged and elderly participants. Furthermore, Perceived risk significantly affected preventive behaviors. The results of this study may assist the government and marketeers in comprehending information sensitivity which can affect consumers' protective behavior toward reducing COVID-19 infections.

• Proceedings of the Korea Association of Information Systems Conference
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• 2005.12a
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• pp.235-248
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• 2005

This paper examines internet shopping mall e-loyalty behaviors. Conceptually, the paper relied on the relatively established literature on ' traditional ' store image and technology acceptance research. And proposes an integrated model including factors on customer e-loyalty in shopping environment. For this purpose, internet shopping mall user's image is proposed to affect trust, and commitment, and consequently to influence customer loyalty behaviors. The empirical results indicated that shopping mal image take significant effect on trust and customer loyalty behaviors. And commitment variable are effective mediators linking internet shopping mall user's trust and their loyalty behaviors. The proposed model and empirical results would contribute to setting up strategy shopping mall industry, and also to future research in information systems and internet marketing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.659-679
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• 2015

Distributed applications are composed of multiple nodes, which exchange information with individual nodes through message passing. Compared with traditional applications, distributed applications have more complex behavior patterns because a large number of interactions and concurrent behaviors exist among their distributed nodes. Thus, it is difficult to detect anomalous behaviors and determine the location and scope of abnormal nodes, and some attacks and misuse cannot be detected. To address this problem, we introduce a method for detecting anomalous behaviors based on process algebra. We specify the architecture of the behavior detection model and the detection algorithm. The anomalous behavior detection and analysis demonstrate that our method is a good discriminator between normal and anomalous behavior characteristics of distributed applications. Performance evaluation shows that the proposed method enhances efficiency without security degradation.

• Journal of Global Scholars of Marketing Science
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• v.8
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• pp.89-110
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• 2001

The purpose of this study were to examine the types of apparel store, to investigate consumer characteristics related to the apparel store patronage behaviors, and to find out the differences of casual relationships on apparel store patronage behaviors in store types. Data were collected from 451 consumers living in Pusan and analysed by factor analysis, ANOVA and path analysis. The results were as followings : First, the types of apparel store recognized by consumers were composed by five factors such as Casual-wear store, Traditional market store, Neighboring store, Department store, and Small-sized department store. Second, apparel store patronage behaviors have significant differences recreational and economic shopping orientations, Fashionability in store evaluative creteria, social psychologic risks in perceived risks, and observation store information source. Third, there were differences in casual relationships an apparel store patronage behaviors across store types. Casual-wear store patronage behaviors were directly influenced by the information source, and traditional market store patronage behaviors did by the perceived risk. Apparel shopping orientations directly influenced Neighboring store, and department store patronage behaviors. Evaluative creteria of store directly did small-sized department store. That is, consumer characteristics directly influencing to patronage behaviors were different across apparel store types. Therefore, the marketers of apparel store should understand consumer characteristics related to patronage behaviors and affecting variable and then try to encourage consumer's store patronage behavior.

• Journal of Korean Library and Information Science Society
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• v.53 no.3
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• pp.263-285
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• 2022

This study presented the factor analysis on constructing the new factors affecting the middle school students' online learning behaviors from the questionnaires employed among middle school students. A total of 204 students participated and the data were collected in South Korea. The sample of middle school ninth-grade students was selected and used through purposive sampling. Findings from the factor analysis provided evidence for the eight-factor solution for the 35-items accounting for 66.15% of the shared variance. A wide range of factors has been considered to identify students' online learning behaviors. The appropriate experience and use of e-learning in the middle school period is also important as it will be a critical stepstone for future education. This research provides information that has been taken into account for advancing online learning to enhance the quality of e-learning systems for middle school students. The study results provided eight new factors affecting the middle school students' online learning behaviors; that is 1) communication using social media as a learning tool, 2) intention to share information using ICT, 3) addiction of technology, 4) adoption of technology, 5) seeking information using ICT, 6) use of social media learning, 7) information search using ICT, and 8) immersion of technology. This study confirmed that middle school students prefer communication using social media as a learning tool, and value intention to share information using ICT for the most part. The data obtained based on factor analysis can highlight the online learning behaviors towards a mixture of social media learning and ICT to ensure a new educational platform for the future of e-learning. This research expects to be useful for both middle schools of online learning to better understand students' online learning behaviors and design online learning environments and information professionals to better assist students who particularly need digital literacy.