• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.117-139
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• 2020

This research analyzes the factors that affect the consumers' participation of the internet-only banks, and suggests effective financial sales strategies and methods to attract more users. Through prior research review and interviews with experts, the factors affecting the consumers to sign up for the internet banks are identified. The actual user data from the internet banks are used for the analysis, providing more systematic and credible results. The research shows that social media buzz positively affects the user growth, proving Granger Causality relation of increasing social media buzz on K Bank increases K Bank users. The research also shows that marketing activities noticeably impacts K Bank's positive user growth. On the other hand, the event of Kakao Bank's grand opening shows negative effect. The results from the research validates the need for periodical monitoring process of social media buzz. Moreover, the research proves that the integrated analysis of social media buzz and marketing effect is also essential.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.243-254
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• 2022

Customers' perceptions of information about a company's products or services have altered as a result of the development of ICT and social networks. This gives rise to a fact that buzz marketing, which is a marketing technique employed commonly in today's business and communication, has a significant impact on customers' electronic word of mouth intention (e-WOM). However, very few studies about this issue have been conducted so far, which reveal a gap in understanding buzz marketing from an academic perspective. Based on the results of a cross-sectional survey in Binh Duong city, this study investigates the efficiency and effect of buzz marketing on customers' e-WOM intention through mediating variables of message credibility. Data from 367 time-lagged individual samples were collected and analyzed by the structural equation modeling method (SEM). Results showed that creativity, clarity, and humor variables have a positive relationship with message credibility and then impact the intention to conduct e-WOM of social networks' users. Marketing campaigns employing the buzz technique should be launched with easy-to-understand and entertainable messages. Findings from this study also provide managers with a scientific understanding of buzz marketing and the effectiveness of this technique as well as reveal the potential for future studies to explore further in this area.

• Journal of Digital Contents Society
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• v.15 no.2
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• pp.219-225
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• 2014

Competition between corporations is getting more intense, so they need customer feedback in order to fulfill an effective management. Recently, SNS (Social Network Service) such as Twitter and Facebook has grown dramatically because of smart phones. Social media like Twitter and Facebook let customers to express their needs, and using big data such as data on SNS is a very effective method for getting customer's feedback. Collecting and analyzing social big data are operated by Buzz monitoring system. This research suggests how to utilize big data for getting customer's feedback on hotel CRM(Customer Relationship Management), which considers customer itself as asset of business. This paper demonstrates the research of buzz monitoring system that analyzes big data, and presents results of hotel customer reputation using buzz monitoring system. It would analyze the result from the hotel customer reputation, and research the implication in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2439-2446
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• 2013

Recently, SNS (Social Network Service) such as Twitter and Facebook has grown dramatically because of smart phones. Since development of IT has created massive information, social big data extremely increased. Competition between corporations is getting more intense, so they need customer feedback in order to fulfill an effective management. Because social big data plays an important role for getting customer feedback, a lot of corporations are interested in analyzing and applying of social big data. Collecting and analyzing social big data is operated by Buzz monitoring system. This paper demonstrates the research of buzz monitoring system that analyzes big data, and presents examples of customer reputation using buzz monitoring. In the paper, after all, it would analyze the result from the customer reputation, and research the implication.

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.256-261
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• 2018

There are three types of noise generated inside the vehicle: BSR (Buzz, Squeak, Rattle). In this paper, we propose a classifier that automatically classifies automotive BSR noise by using features extracted from deep convolutional neural networks. In the preprocessing process, the features of above three noises are represented as noise-map using STFT (Short-time Fourier Transform) algorithm. In order to cope with the problem that the position of the actual noise is unknown in the part of the generated noise map, the noise map is divided using the sliding window method. In this paper, internal parameter of the deep convolutional neural networks is visualized using the t-SNE (t-Stochastic Neighbor Embedding) algorithm, and the misclassified data is analyzed in a qualitative way. In order to analyze the classified data, the similarity of the noise type was quantified by SSIM (Structural Similarity Index) value, and it was found that the retractor tremble sound is most similar to the normal travel sound. The classifier of the proposed method compared with other classifiers of machine learning method recorded the highest classification accuracy (99.15 %).

• International Journal of Aeronautical and Space Sciences
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• v.13 no.3
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• pp.296-306
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• 2012

A series of numerical simulations are carried out to analyze a supersonic inlet buzz, which is an unsteady pressure oscillation phenomenon around a supersonic inlet. A simple but efficient geometry, experimentally adopted by Nagashima, is chosen for the analysis of unsteady flow physics. Among the two sets of simulations considered in this study, the effects of various throttling conditions are firstly examined. It is seen that the major physical characteristic of the inlet buzz can be obtained by inviscid computations only and the computed flow patterns inside and around the inlet are qualitatively consistent with the experimental observations. The dominant frequency of the inlet buzz increases as throttle area decreases, and the computed frequency is approximately 60Hz or 15% lower than the experimental data, but interestingly, this gap is constant for all the test cases and shock structures are similar. Secondly, inviscid calculations are performed to examine the effect regarding angle of attack. It is found that patterns of pressure oscillation histories and distortion due to asymmetric (or three-dimensional) shock structures are substantially affected by angle of attack. The dominant frequency of the inlet buzz, however, does not change noticeably even in regards to a wide range of angle of attacks.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.617-621
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• 2007

Recent advances in automotive noise control engineering have reduced major sound sources in the vehicle, customers perceive Buzz, Squeak and Rattle (BSR) as one of important indicators of vehicle quality and durability. As the long-term goal, we expect to establish the integrated design cycle for the reduction of BSR noise in the early stage of development, which consist of design, prediction, and evaluation procedures. This is possible only with great bulk of experimental data for BSR noise. In this paper, BSR noise is experimentally identified for vehicle doors, which have been traditionally considered as one of main sources of BSR noise. Based on this result, we proposed method for the prevention of BSR noise in the vehicle doors.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.12
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• pp.1217-1222
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• 2007

With recent advance in automotive noise control engineering reducing major sound sources in the vehicle, customers perceive Buzz, Squeak and Rattle (BSR) as one of important indicators of vehicle quality and durability. As the long-term goal, we expect to establish the integrated design cycle for the reduction of the BSR noise in the early stage of vehicle development. which consist of design, prediction and evaluation procedures. This is possible only with great bulk of experimental data for BSR noise. In this paper, BSR noise is experimentally identified for vehicle doors, which have been traditionally considered as one of main sources of BSR noise. Based on this result, we proposed systematic method for the prevention of BSR noise in the vehicle doors.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.41-51
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• 2013

A lots of social data are distributed, utilized and opened through the social media. They have characterized effectiveness and pleasure of information to the media by social data but it is ignored about excessive exposure of information and damage from collective reply of personal attack type. In this paper, we study about analysis of opinion social data on the SNS (Social Network Service) by analyzing of collective damage reply. It is analysed by diverse measurement method for distribution and disuse of the amount of Buzz data that is analysed data from structured social network.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.6
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• pp.195-200
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• 2013

Road loads data are indispensable in the evaluation of BSR (Buzz, Squeak, and Rattle) of automotive parts/modules. However, there are uncertainties on the best measurement locations for representative body motion and for seat systems. In the present study, we measure road loads at four different locations of a body. A-pillars on the driver and passenger sides and left and right frame fronts of the front passenger seat mountings are selected to study the acceleration behavior at different locations. The measurements are conducted with passenger cars driving local roads at 50km/hr. The measured time-acceleration data are then transformed into PSD (power spectral density) data to compare the characteristics of local accelerations. By defining the deviated acceleration components from rigid body motion, the stiffness of vehicle body could be simply expressed in a quantitative basis. Measured data from two different vehicles are presented to demonstrate their relative vehicle body stiffness.