• The Journal of Society for e-Business Studies
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• v.25 no.4
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• pp.33-60
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• 2020

Along with the rapid advance in internet technologies, ubiquitous mobile device usage has enabled consumers to access real-time information and increased interaction with others through various social media. Consumers can now get information more easily when making purchase decisions, and these changes are affecting the brand landscape. In a digitally connected world, brand image is not communicated to the consumers one-sidedly. Rather, with consumers' growing influence, it is a result of co-creation where consumers have an active role in building brand image. This explains a reality where people no longer purchase products just because they know the brand or because it is a famous brand. However, there has been little discussion on the matter, and many practitioners still rely on the traditional measures of brand indicators. The goal of this research is to present the limitations of traditional definition and measurement of brand and brand image, and propose a more direct and adequate measure that reflects the nature of a connected world. Inspired by the proverb, "A man is known by the company he keeps," the proposed measurement offers insight to the position of brand (or brand image) through co-purchased product networks. This paper suggests a framework of network analysis that clusters brands of cosmetics by the frequency of other products purchased together. This is done by analyzing product networks of a brand extracted from actual purchase data on Amazon.com. This is a more direct approach, compared to past measures where consumers' intention or cognitive aspects are examined through survey. The practical implication is that our research attempts to close the gap between brand indicators and actual purchase behavior. From a theoretical standpoint, this paper extends the traditional conceptualization of brand image to a network perspective that reflects the nature of a digitally connected society.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.4
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• pp.67-79
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• 2013

A meta-analysis is a statistical literature synthesis method that provides the opportunity to view the research context by combining and analyzing the quantitative results of many empirical studies. The technology acceptance model (TAM) has been the subjects of a great deal of MIS research in the last two decades and now also has been continuously studied. Recently, the convergence of knowledge information society and information telecommunication technologies has a rapid impact on politics, economics and various fields. The biggest issue in the information communication and information systems fields is smart. Therefore, we conducted a meta-analysis research on the behavioral intention of smart phone users based on technology acceptance model. Also, this study was targeted a total of 50 research papers that are setting up the causal relationship in TAM among the research papers published in domestic academic journals since 2005. The result of the meta analysis, showed that the effect size was 0.48 in the path from perceived usefulness to behavioral intention, it showed that the effect size was 0.46 in the path from perceived ease of use to behavioral intention. And, it showed that the effect size was 0.46 in the path from perceived ease of use to perceived usefulness. Also, it showed that the effect size was 0.61 in the path from attitude to behavioral intention. Based on the results, it was discussed the difference through comparative analysis with previous research.

• Journal of the Korea Computer Industry Society
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• v.5 no.1
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• pp.131-146
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• 2004

As Electronic Commerce(EC) has been emerged and has developed, many researchers have tried to establish EC framework for automated contract and negotiation using agent technologies. Traditional researches, however, often had limitations. They often enforced the user's participations during the automated contract process of agents. They also could only consider a few of the user's requirements for a specific goods and did not have supported the procedures and methodologies for making the best contract. In this paper, we propose business model on EC based on multiagents to overcome the defects of the previous researches. We apply CSP techniques to brokerage process to satisfy various preferential requirements from the user. We also propose efficient negotiation mechanism using negotiation model of game theory. The contract candidates automatically negotiate and mediate in terms of their benefits through the proposed negotiation mechanism. For the optimal brokerage and automated negotiation, the agents process activities for contract on three layers, which are called competition layer, constraint satisfaction layer and negotiation layer in the proposed model. We also design the message driven communication protocol to support the automated contract among the agents. Finally, we have implemented prototype systems applying the proposed model and have shown the various experimental results for efficiency of the proposed model.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.177-193
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• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.

• Information Systems Review
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• v.17 no.2
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• pp.29-48
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• 2015

This study proposes an integrated operational model of branches with customer center at stock brokerage firms and suggests ways to improve existing systems. This suggested integrated model of branches and customer centers can increase customer satisfaction and customer values for the specific services at each channel. This integrated model also enables customers to make transactions at a desired specific time, make it possible to inquire whatever the customer wished to ask, and select desired contact channels. In addition, the firms can bring in improved effectiveness of internal resources by integrating all the resources the firm has. Personal resources and system resources are distributed by the characteristics of channels that can be selected by the customers. Then agents also can provide more speedy and accurate responses to the engaged customer interactions matching to his/her job in charge. Also, the model makes it possible to collect the latest customer and transaction information at the moment of each interactions, by which the firm can provide customized services specifically tailed to each customers' preferences. However, systematic interactions between branches and customer center, and completed system should be equipped with in order to provide the highest quality services.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• Management & Information Systems Review
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• v.37 no.4
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• pp.175-193
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• 2018

As a new type of business model in the market competition situation of tour companies, this study has developed to the online form of the travel industry to the business form which is the combination of the electronic commerce function and the mobile service process in the provision of the simple web-site, This study explores the difficulties of change for the development of the travel industry from the point of view that recognition is not a simple marketing strategy diversification means but a change of recognition as a business model for expanding new markets or creating new markets. The factors affecting the choice of online travel agent (OTA) and the factors that influence the choice of online travel agency were analyzed. Were used for the empirical survey. The purpose of this study is to investigate the factors influencing the choice of online travel agents who have experience with or experience using online travel agency (OTA), what factors are important to them, and how they differ in importance when visiting again. The results of this study are as follows: First, there was a significant difference between the first and second visitors of online travel agencies. The results of this study were as follows: Attitude toward resolving complaints, convenience of change and cancellation, delivery of tickets and documents, convenience of complaints, The emphasis should be on establishing and strengthening service environments such as the speed of updating the latest information, the simplicity of the booking procedure, the degree of satisfaction of the past, the ability of employees to handle their work, the safety of various payment methods and settlement, The results of this study are as follows: First, the satisfaction of the online travel agency is influenced by the selection factors of the selected online tour agency, and the A/S such as the convenience of prompt delivery, Environmental factors contributed to satisfaction. It is suggested that the systematic service structure such as customer satisfaction and ease of use is a necessary marketing strategy for survival and development of online travel agencies. It is suggested that the marketing concentration strategy with the first visitors as the target market is effective and this is a part of the marketing strategy for the survival of online travel agencies.

• Information Systems Review
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• v.12 no.3
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• pp.49-73
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• 2010

The lack of customer satisfaction and trust remains a key barrier to electronic commerce. From the standpoint of online merchants, it is critical to build consumer trust by lessening sources of apprehensions and uneasiness associated with online transactions. This paper explores the relationships between customer satisfaction and intermediary's trustworthiness factors in B2C e-marketplaces. It also aims at examining the effects of consumer characteristics, including propensity to trust and Internet shopping self-efficacy, upon trust and purchase intentions. To meet the research objectives, an empirical study has been conducted by surveying 223 active e-marketplace buyers in Korea. The findings of the present research indicate that customer satisfaction positively affects all the three attributes of trustworthiness (i.e., competence, benevolence, and integrity), and more specifically it has a quite strong association with benevolence. In addition, propensity to trust has no significant influence on trust or purchasing intentions, and only affects benevolence and integrity with no direct effect on competence. Finally, Internet shopping self-efficacy was found to affect both trust and purchasing intentions, suggesting that e-marketplaces seek an online strategy designed to strengthen loyalty for customers with high self-efficacy, while they use a strategy to improve the usability and usefulness of their website to attract customers with low self-efficacy. The paper concludes with implications and directions for future research.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.100-116
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• 2018

Recently, with the US protection trade trend, South Korea 's exports to the US have shrunk and the need to pioneer emerging markets in Eurasia has increased. Due to the bankruptcy of Hanjin Shipping, a large Korean national shipping company, the necessity of securing transportation that can replace the Asian - European shipping route has emerged. Moreover, as the international trade and logistics environment is rapidly changing due to the spread of electronic commerce, it is time to prepare for the environment where IT technology is applied to international logistics activities. Therefore, this study was carried out to establish information strategy of Eurasia logistics information sharing platform from Korean perspective through comparison of logistics information level of Eurasian countries. This study aims at standardization direction for supporting logistics activities between Eurasian countries, providing customs clearance and logistics services without interruption, providing information for expanding business of trade companies, and building information linkage infrastructure for expanding cooperation between logistics companies across countries. Through this study, it is expected that logistics activities through information sharing among countries will be actively carried out.

• Information Systems Review
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• v.26 no.1
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• pp.385-407
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• 2024

This study explains consumers' showrooming which refers to the activities of visiting offline stores to check products in person and obtaining information offline and online via mobile devices before making the final decision to buy. More specifically, this study verifies key determinants of showrooming based on two dimensions of the mobile technology and user characteristics. Furthermore, the study examines the relationship of showrooming and purchase intentions and the moderating effect of perceived risks on the relationship. The key findings are as follows: firstly, service connectivity and time convenience of the mobile technology characteristics are positively related to showroming. Secondly, as the user characteristics, need for touch and personal innovativeness increase showrooming while impulsiveness does not. Thirdly, showrooming contributes to the increase of purchase intentions. Finally, moderating effect of perceived risks has turned out to be insignificant. This study has implications by providing the understanding of key determinants of showrooming and further proving the positive relationship of showrooming and purchase intentions.