• The Journal of Industrial Distribution & Business
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• v.9 no.1
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• pp.51-65
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• 2018

Purpose - This paper aims to identify factors that influence the users' word-of-mouth intention (WOMI) regarding mobile apps, focussing on the impacts of technology acceptance model (TAM) and social network theory. Research design, data and methodology - Based on TAM, this study integrates social network theory into the research model. The 317 sets of data collected in a survey were tested against the model using SmartPLS. Results - Our findings suggest the following: 1) Personal innovativeness positively influences perceived usefulness (PU), perceived ease of use (PEU) and perceived enjoyment (PE); 2) PEU affects PU and PE; 3) Both PU and Satisfaction are directly correlated with WOMI. Although PEU and PE has no direct impact on WOMI, they may indirectly affect WOMI via Satisfaction, as PU, PEU and PE all positively influence satisfaction; 4) Network density and network centrality both play a mediating role in the relation between PEU and WOMI. Referral Reward Program have a positive moderating effect on the relation between PU and WOMI. Conclusions - The findings of this study illustrate the traits of Apps that can promote users' WOMI, as well as the characteristics of people who are more likely to participate in the word-of-mouth process. The findings provide a theoretical basis for app developers to make word-of-mouth a marketing strategy.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.33-42
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• 2005

In this paper, we propose a new training algorithm for improving pattern classification performance of ART neural network. The proposed train algorithm restricts unnecessary cluster generation and transition, applies the location extraction algorithm, and operates the reset system based on the agreement between the present learning pattern and the initial pattern. As a result, repetitive input of a pattern does not generate a new cluster and mis-recognition rate decreases.

• The Journal of Information Systems
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• v.18 no.3
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• pp.47-70
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• 2009

Social network is one of the representative analytical method of the complexity theory and this research analyzed various and unique strategic alliance model of e-business domain using social network technique. A lot of small and medium firms of e-business field had developed many useful type of strategic alliances for the firms tried to maximize the effect of advertisement, marketing and to make up for their weak points and to compete with huge company with capital strength long before. But it is too rare to analyze the structure of the firm networks and to study the evolution and extension of business model considered the role of each company in the network. Social network analysis helps each firm's network easily visualized and completely modelized. Additionally, this paper cries to analyze the relationship between the role of hub and broke in the firm networks for strategic alliance, and financial performance. We demonstrate the firm with finer business model to the business environment can make higher financial performance. This implies that the firm that can create new finer business model, will lead the network of e-business firms and evolve the industry of e-business.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.20 no.6
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• pp.17-23
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• 2018

The purpose of this study is to suggest 100MPa class ultra high strength concrete mix design model applying neural network theory, in order to minimize an effort wasted by trials and errors method until now. Mix design model was applied to each of the 70 data using binary binder, ternary binder and quaternary binder. Then being repeatedly applied to back-propagation algorithm in neural network model, optimized connection weight was gained. The completed mix design model was proved, by analyzing and comparing to value predicted from mix design model and value measured from actual compressive strength test. According to the results of this study, more accurate value could be gained through the mix design model, if error rate decreases with the test condition and environment. Also if content of water and binder, slump flow, and air content of concrete apply to mix design model, more accurate and resonable mix design could be gained.

• The Journal of Information Systems
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• v.29 no.2
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• pp.221-242
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• 2020

Purpose This study collects data of the recently activated online black market and analyzes it to present a specific method for preparing for a hacking attack. This study aims to make safe from the cyber attacks, including hacking, from the perspective of individuals and businesses by closely analyzing hacking methods and tools in a situation where they are easily shared. Design/methodology/approach To prepare for the hacking attack through the online black market, this study uses the routine activity theory to identify the opportunity factors of the hacking attack. Based on this, text mining and social network techniques are applied to reveal the most dangerous areas of security. It finds out suitable targets in routine activity theory through text mining techniques and motivated offenders through social network analysis. Lastly, the absence of guardians and the parts required by guardians are extracted using both analysis techniques simultaneously. Findings As a result of text mining, there was a large supply of hacking gift cards, and the demand to attack sites such as Amazon and Netflix was very high. In addition, interest in accounts and combos was in high demand and supply. As a result of social network analysis, users who actively share hacking information and tools can be identified. When these two analyzes were synthesized, it was found that specialized managers are required in the areas of proxy, maker and many managers are required for the buyer network, and skilled managers are required for the seller network.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.447-453
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• 2003

Emotion Technology is used in many field such as computer A.I., graphics, robot, and interaction with agent. We focus on the theory, the technology and the features in emotion application. Firstly in the field of theory, there are psychological approach, behavior-based approach, action-selection approach. Secondly in the field of implementation technologies use the learning algorithm, self-organizing map of neural network and fuzzy cognition maps. Thirdly in the field of application, there are software agent, agent robot and entrainment robot. In this paper, we research the case of application and analyze emotion architecture.

• The Journal of Information Systems
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• v.21 no.3
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• pp.163-186
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• 2012

With the development of Internet and transition to information society, social capital is expanding to online from the traditional offline context. Especially with the widespread of social network service(SNS) the number of SNS users is increasing sharply and the importance of online social capital has been more and more significant. Most studies on social capital focused on organizational aspects but few studies have payed attention to personal aspect. Empirical studies on the relation between SNS and social capital were seldom conducted in previous studies. Based on the theory of social capital this study targets on the relationship formed through SNS and analyzes on how the relationship affects the perceived social capital. In this study 'self-presentation', 'playfulness' and 'critical mass' are posited as the antecedent factors of 'SNS usage'. This study proposes a research model to examine the effect of 'SNS usage' on 'relationship reinforcement', 'relationship building' and 'perceived social capital'. According to the results of empirical analysis, 'self-presentation', 'playfulness' and 'critical mass' can generate significant positive influence on 'SNS usage'. It also confirms not only the effect of 'relationship reinforcement' and 'relationship building' formed through SNS on 'perceived social capital' but also relationship between the social capital formation and SNS usage. The outcome obtained in this study can be applied in developing SNS services.

• Informatization Policy
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• v.22 no.4
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• pp.91-104
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• 2015

This study tests the effects of differential association, definitions, differential reinforcement and imitation from social learning theory in the explanation of university students' crimes in social network services. In addition, this study tests the interaction effects between social learning factors and other factors such as low self-control, subcultural environment, and crime opportunity for the integrated approach. Using data from 486 university students in Seoul, results show that both definition and imitation have significant influences on crimes, even though differential association and differential reinforcement factors have no significant influences on crimes in social network services. Results also reveal that there are significant interaction effects between definition and subcultural environment, which meana that definition has a strong effect on crimes in high subcultural environment. In addition, it is found that reinforcement has also a strong effect on crimes in high crime opportunity and that interaction effect between imitation and low self-control is significant, which means that imitation has a strong effect on crimes in low self-control students.

• The Journal of the Korea Contents Association
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• v.15 no.1
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• pp.388-398
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• 2015

This study is to investigate an impact of emotional index, social network, and trust to customers on sales performance with emotional intelligence theory and social relationship theory. We found that the higher is seller's emotional index, the higher are cognitive and affective trust, and the high trust improves sales performance. We also found that the higher emotional index strengthens social network, but does not have an effect on cognitive and affective trust. With these results we provide the sales competency in clothing shop.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.179-189
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• 2016

This aim of this study is identify research trends and intellectual structure in the field of Korean journalism and communication studies. For this purpose, a semantic network analysis was employed to analyze keywords in the abstracts of published articles in the Korean Journal of Journalism and Communication Studies from 2005 to 2015. The results showed that "frame", "Twitter", "content analysis" and "social media" are among the most frequently used keywords in the abstracts during this period. With regards to degree and eigenvector centrality, "social capital", "trust" and "twitter" were among the highest. The findings of the periodic characteristics of research trends revealed that there are more studies that employ the traditional media effect theories including Uses and Gratification Theory, Agenda Setting Theory, and Framing Theory before the year of 2010 while those that focus on the specific new media such as smartphones and twitter after 2011. This study has implications in the sense that it can be used as guidelines for making a curriculum or establishing the research system for Korean journalism and communication studies in the future.