• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.66-76
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• 2021

The quality of the E-learning education in Saudi Arabia has been a major concern by many academicians, especially, and people in general as this platform has not been a priority for education. Not until recently, the world has been impacted by the Covid-19 pandemic, which makes every education institution shifted to the online platform to continue the education for the students. Thus, many studies on the perceptions on the online learning have been carried out, and though many are focusing on the perceptions by the education institutions' faculty and administration, there is a lack in the amount of study performed to analyse the students' perceptions of online learning during the pandemic time. The current study is conducted by utilising qualitative methods in order to collect information and investigate the students' perception regarding online learning during the pandemic Covid-19, based on their individual experiences. A number of fifteen (15) students were selected as respondents for the study, in which structured interviews were conducted by using a convenient sampling technique for data collection. Through the discussion, all of the positive and negative perceptions of online learning, as well as the factors contributing to those perceptions were identified. The results of the study found that the positive perceptions were contributed based on the flexibility, cost-effectiveness, availability of the electronic research databases, and well-designed online classroom interfaces. For the negative perceptions from using online learning platforms, the respondents informed that they were contributed by the lecturer's delayed feedback, lack of technical support by lecturers, low in self-esteem and self-motivation, feel isolated, one-way of educational methods, and poorly-designed class materials. Through the findings, the school's administration and lecturers would be able to know the struggles experienced by the students, and eventually come out with better solutions to improve their teaching methods.

• Management & Information Systems Review
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• v.30 no.3
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• pp.153-167
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• 2011

This study conducts to examine the effect of purchase intention on social shopping by connection density and centrality which is a structural characteristic of social network. Furthermore, this study suggests and analyses the difference of social shopping purchase intention between online community which focuses on a group and SNS(social network service) which focuses on an individual. To examine these reason, this study proposes hypotheses that reflects structural characteristic then analyses them. The result of analysis shows that the purchase intention on social shopping seems to be high when the density of connection is high and the purchase intention seems to be high when the centrality is high as well. Moreover, there is difference in the purchase intention on social shopping between online community and SNS and it is found that both cases where the connection density is high in the online community and the connection centrality is high in SNS have significant impact on the purchase intention. Based on these results, this study provides an implication on the importance on network structure in social network and social shopping and to increase the purchase intention of social shopping, this study suggests the implication on the importance and direction which understands the structure of social network type.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.29
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• pp.173-196
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• 2006

Online game business has emerged as the most lucrative entertainment industry, with over 10 million players in South Korea and over 30 million in Japan in 2005. The popularity of online games can be attributed to the availability of broadband network, pushing online games into the mainstream entertainment culture. The age distribution of online game players is expanding and a variety of new games are under development to target certain age groups. While the interactive entertainment market continues to expand, with many new online game publishers entering the Japan, relatively little is known about which factors influence online game players' behavioral intentions to play continuously in this area. This study investigates major factors which influence the acceptance of online game services based on the theoretical backgrounds of the technology acceptance model(TAM) and the flow theory. This paper extended the Davis' TAM model by including the flow concept as another major factor toward the intention to play online game. Based on data collected from online questionnaire survey, we show that the proposed model provides an adequate fit to the data, and that the flow experience is another important factor influencing the intention to play online game, as well as the perceived ease of use.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.116-130
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• 2019

This study investigates passenger-authored online reviews of airline services using social network analysis to compare the differences in customer perceptions between full service carriers (FSCs) and low cost carriers (LCCs). While deriving words with high frequency and weight matrix based on the text analysis for FSCs and LCCs respectively, we analyze the semantic network (betweenness centrality, eigenvector centrality, degree centrality) to compare the degree of connection between words in online reviews of each airline types using the social network analysis. Then we compare the words with high frequency and the connection degree to gauge their influences in the network. Moreover, we group eight clusters for FSCs and LCCs using the convergence of iterated correlations (CONCOR) analysis. Using the resultant clusters, we match the clusters to dimensions of two types of service quality models ($Gr{\ddot{o}}nroos$, Brady & Cronin (B&C)) to compare the airline service quality and determine which model fits better. From the semantic network analysis, FSCs are mainly related to inflight service words and LCCs are primarily related to the ground service words. The CONCOR analysis reveals that FSCs are mainly related to the dimension of outcome quality in $Gr{\ddot{o}}nroos$ model, but evenly distributed to the dimensions in B&C model. On the other hand, LCCs are primarily related to the dimensions of process quality in both $Gr{\ddot{o}}nroos$ and B&C models. From the CONCOR analysis, we also observe that B&C model fits better than $Gr{\ddot{o}}nroos$ model for the airline service because the former model can capture passenger perceptions more specifically than the latter model can.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3057-3075
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• 2020

End-to-end network delay plays an vital role in distributed services. This delay is used to measure QoS (Quality-of-Service). It would be beneficial to know all node-pair delay information, but unfortunately it is not feasible in practice because the use of active probing will cause a quadratic growth in overhead. Alternatively, using the measured network delay to estimate the unknown network delay is an economical method. In this paper, we adopt the state-of-the-art matrix completion technology to better estimate the network delay from limited measurements. Although the number of measurements required for an exact matrix completion is theoretically bounded, it is practically less helpful. Therefore, we propose an online adaptive sampling algorithm to measure network delay in which statistical leverage scores are used to select potential matrix elements. The basic principle behind is to sample the elements with larger leverage scores to keep the traits of important rows or columns in the matrix. The amount of samples is adaptively decided by a proposed stopping condition. Simulation results based on real delay matrix show that compared with the traditional sampling algorithm, our proposed sampling algorithm can provide better performance (smaller estimation error and less convergence pressure) at a lower cost (fewer samples and shorter processing time).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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• pp.966-972
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• 2007

This paper presents position control of nonlinear three-dimensional crane systems using neural network approach. Such crane system generally includes very complicated characteristic dynamics and mechanical framework such that its mathematical model is expressed by strong nonlinearity. This leads difficulty in control design for the systems. We linearize the nonlinear system model to construct PID control applying well-known linear control theory and then neural network is utilized to compensate system perturbation due to linearization. Thus, control input of the crane system is composed of nominal PID and neural output signals respectively. Our method illustrates simple design procedure, but system perturbation and modelling error are overcome through a neural compensator. As well. adaptive neural control is constructed from online learning. Computer simulation demonstrates our control approach is superior to the classic control systems.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.444-452
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• 2008

We propose an intelligent predictive control approach for a nonlinear networked control system (NCS) with time-varying delay and random observation. The control is given by the sum of a nominal control and a corrective control. The nominal control is determined analytically using a linearized system model with fixed time delay. The corrective control is generated online by a neural network optimizer. A Markov chain (MC) dynamic Bayesian network (DBN) predicts the dynamics of the stochastic system online to allow predictive control design. We apply our proposed method to a satellite attitude control system and evaluate its control performance through computer simulation.

• Journal of Digital Convergence
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• v.1 no.1
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• pp.147-164
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• 2003

The use of electronic mail and messenger software tools has been increased rapidly over a decade. Compared to the variety of research related to the relationship between personal psychological traits and communication modes, effects of human psychology on online activities have only recently become a focus of interest. This research analyzed the relationship between personal psychological type and online connectivity. We employed network analysis methodology and collected and analyzed data from 146 subjects. Significant differences in network measures were found among groups with different psychological style. Findings of the research can provide several implications for managerial activities regarding social connectivity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8B
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• pp.764-768
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• 2006

Over the years, the widespread proliferation of multimedia services has necessitated the development for an efficient network management. In this paper, we investigate the role of adaptive online pricing mechanism in order to manage effectively the network congestion problem. Our on-line approach is dynamic and flexible that responds to current network conditions. With a simulation study, we demonstrate that our proposed scheme enhances network performance and system efficiency simultaneously under widely diverse traffic load intensities.