• Asia pacific journal of information systems
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• v.19 no.1
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• pp.147-165
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• 2009

Virtual community(VC) will increasingly be organized as commercial enterprises, with the objective of earning an attractive financial return by providing members with valuable resources and environment. For example, Cyworld.com in Korea uses several community services to enable customers of Cyworld to take control of their own value as potential purchasers of products and services. Although initial adoption is important for online network service success, it does not necessarily result in the desired managerial performance unless the initial usage is continuously related to the continuous usage and purchase. Particularly, the customer who receives relevant online services and is well equipped with online network services, will trust the online service provider and perceive less risk and experience more activities such as continuous usage and purchase. Thus, how to promote continued online service usage or, alternatively, how to prevent discontinuance is a critical issue for VC service providers to consider. By aggregating a wide range of information and online environments for customers and providing trust to its members, the service providers of virtual communities help to reduce the perceived risk of continuous usage and purchase. Drill down, online service managers realize that achieving strong and sustained customers who continuously use online service and purchase on it is crucial. Therefore, the research into this online service continuance will identify the relationship between the initial usage and the continuous usage and purchase. The research of continuous usage or post adoption has recently emerged as an important issue in the IS literature. Individuals' information systems(IS) continuous usage decisions are congruent with consumers' repeat purchase decisions. The TAM(Technology Acceptance Model) paradigm has been strongly confirmed across a wide range from product purchase on EC to online service usage contexts. The analysis of IS usage based on TAM has proven to be successful across almost online service contexts. However, most of previous studies have focused on only an area (i.e., VC or EC). Just little research has tried to analyze the relationship between VC and EC. The effect of some factors on user intention, captured through several theories such as TAM, has been demonstrated. Yet, few studies have explored the salient relationships of VC users' EC acceptance. To fill this gap between VC and EC research, this paper attempts to develop a research model that extends the TAM perspective in view of the additional contributions of trust in the service provider and trust in members on some factors that affect EC and VC adoption. In this extension, we applied the TAM-to-TAM(T2T) model, and analyzed the transfer effect of trust between these two TAMs. The research model was empirically tested on the context of a social network service. The model was to extend TAM with the trust concept for the virtual community environment from the perspective of tasks. By building an extended model of TAM and examining the relationships between trust and the existing variables of TAM, it is aimed to explain a user's continuous intention to use VC and purchase on EC. The unit of analysis in this paper is an individual user of a virtual community. The population of interest is the individual with the experiences in virtual community. The data for this paper was made available via a Web survey of VC users. In total, 281 cases were gathered for about one week, but there were some missing values in the sample and there were some inappropriate cases. Thus, only 248 cases were finally analyzed. We chose the structural equation analysis to test the hypotheses and it is better suited for explaining complex relationships than the other methods. In this test, AMOS was used to test the Structural Equation Model (SEM). Noticeable results have been found in the T2T model regarding the factors affecting the intention to use of virtual community and loyalty. Our result showed that trust transfer plays a key role in forming the two adoption beliefs. Overall, this study preliminarily confirms the salience of trust transfer in online service.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.43-49
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• 2014

Paradigm shift in government services means the evolution to the service with active participation based on information technology. Opening public information proceeds to an extent that private sector participation can be a basis and driving force, and extends to a stage that free and practical use is possible for private sector. Therefore, the government is preparing for legal and institutional foundation for various fields. The government needs to build open network from user-oriented point of view rather than provider-centric point of view, improve communication, and change the way of working due to the fact that flexible and rapid business process is required. It is time to prepare development plans for public the functions of platform-type government that public sector can participate in the role of government, create new value, and give rise to innovation in order to change the functionality of the government and meet the new needs of citizen. This study tries to analyze platform-type government and to study efficient role allocation for sharing resources including informant and system between the government and the private sector, focusing on innovation of public information sharing.

• 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 Economic Geographical Society of Korea
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• v.14 no.4
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• pp.583-602
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• 2011

Based on the survey, this paper examines entrepreneurs' attitude toward corporate lending in Pusan region. The results show that the relationships of manufacturing firmswith banks are different from those of non-manufacturing firms. These are mainly due to the differences in the operational grounds between them. The non-manufacturing firms have their operational ground in Pusan, thus they have local banks as their mainbanks and depend heavily on mainbanks' credits. However the business network of the local banks is not broad enough to satisfy the manufacturing firms financial service needs. Therefore, the manufacturing firms maintain close relationship with not only regional local banks but also other banks. The results of the study demand the local banks to produce information of the regional firms and to monitor them more widely and tightly. One of the important contributions of this paper is that it has succeeded in making clear the importance of relationship banking of the local banks.

• Management & Information Systems Review
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• v.36 no.1
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• pp.41-57
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• 2017

The previous studies have investigated the effect of social capital on innovation performance. However, the previous studies investigating the relationship between social capital and innovation performance have assumed a black box in the linkage. According to the knowledge based view, firms with inter-dependent relationship can make innovation through sharing processes of knowledge. In other words, social capital as intangible resource results in knowledge management activities which can increase innovation performance. And increasing innovation can make relationship satisfaction promoting relationship investment gradually. Therefore, research hypotheses are made from social capital to relationship investment. From the empirical results, except for the effect of knowledge sharing on both product innovation and relationship satisfaction, almost all hypotheses are reported to be significant. And product innovation performance positively affects relationship satisfaction, and relationship investment is positively affected by relationship satisfaction. From this study, we can know the importance of knowledge management activities in strategic management view.

• International Commerce and Information Review
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• v.12 no.1
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• pp.3-33
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• 2010

Paperless trade is a new trade paradigm that has innovated on traditional trade procedures, which relied on manual work in the past, and applied an IT-based e-document standard. To realize paperless trade in Korea, a lot of efforts have been made. Korea has overcome many difficulties, a lack of awareness, trials and errors, etc. at the initial introduction stage and strived to establish a stable infrastructure through the government's policy support and active cooperation with the trade business communities and related organizations. Now, Korea became a well-known leader in IT industry, especially in the paperless trade infrastructure and strategic policies. The one-stop trading system named 'uTradeHub' is operated by a paperless trade service provider, Korea Trade Network(KTNET). uTradeHub includes trade finance and settlement, customs clearance and export and import logistics, improving trading procedures and reducing related expenses. Private-Public joint efforts from Korean government and private sectors which have respectively fulfilled their role and function with market-oriented practical policies and strategies has lead Korea a world leading country in paperless trade. Moreover, Korea expended its efforts to the global areas. Korea has started to activate multi-national paperless trade alliances such as PAA(Pan-Asia e-Commerce Alliance), ASEAL(Asia Europe Alliance for Paperless Trading) as well as established the bilateral cooperative networks with China and Taiwan. The one-stop trading system, uTradeHub should keep close cooperations between nations since trade itself is implemented in a cross-border ways. In the near future, it is expected uTradeHub can achieve best results in the simplification of procedures and cost savings when an international linkage is completely established with international cooperations.

• The KIPS Transactions:PartA
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• v.11A no.3
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• pp.115-128
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• 2004

The proliferation of Information Technology and Business Automation become the mainstay of the growth of world printer market. Especially the demand for high speed printers increases drastically as the need for printing service station in networked computing environment grows. However outstanding research activities are seldom reported. Only efforts are currently focused on the printing quality and development of application programs for low or midium speed printers. This stimulates the research for high-speed printers. In this paper, we first defined the architectural components of high-speed printers so that the performance requirements can be satisfied. The individual impacts of each module on overall throughput are then elaborately analysed. Based on this result, we accomplished well-tuned system architecture which presents up to 163.52 PPM. Another contribution of this paper can be found in that this is one of the first articles that deal with the architecture and the performance of high-speed printers.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.26
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• pp.285-313
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• 2005

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 Japan, relatively little is known about which factors influence online game players' behavioral intentions to play continuously in this area. It appears that in this extremely attractive and growing services segment, academics, as well as practitioners, would benefit from investigating the difference, among the types of players, in demographic and social trends, perceptions related to game-design factors, and attitude toward the games. Based on data collected from online questionnaire survey, the differences between hardcore and casual players have been analyzed, and interesting conclusions have been provided concerning the online-game design and development strategies for Japan online-game players.