• Information Systems Review
• /
• v.22 no.1
• /
• pp.59-72
• /
• 2020

Artificial Intelligence is establishing itself as a familiar tool from an intractable concept. In this trend, financial sector is also looking to improve the problem of existing system which includes Fraud Detection System (FDS). It is being difficult to detect sophisticated cyber financial fraud using original rule-based FDS. This is because diversification of payment environment and increasing number of electronic financial transactions has been emerged. In order to overcome present FDS, this paper suggests 3 types of artificial intelligence models, Generative Adversarial Network (GAN), Deep Neural Network (DNN), and Convolutional Neural Network (CNN). GAN proves how data imbalance problem can be developed while DNN and CNN show how abnormal financial trading patterns can be precisely detected. In conclusion, among the experiments on this paper, WGAN has the highest improvement effects on data imbalance problem. DNN model reflects more effects on fraud classification comparatively.

• Information Systems Review
• /
• v.25 no.1
• /
• pp.93-110
• /
• 2023

Recently, attempts have been made to convert unstructured text into vectors and to analyze vast amounts of natural language for various purposes. In particular, the demand for analyzing texts in specialized domains is rapidly increasing. Therefore, studies are being conducted to analyze specialized and general-purpose documents simultaneously. To analyze specific terms with general terms, it is necessary to align the embedding space of the specific terms with the embedding space of the general terms. So far, attempts have been made to align the embedding of specific terms into the embedding space of general terms through a transformation matrix or mapping function. However, the linear transformation based on the transformation matrix showed a limitation in that it only works well in a local range. To overcome this limitation, various types of nonlinear vector alignment methods have been recently proposed. We propose a vector alignment model that matches the embedding space of specific terms to the embedding space of general terms through end-to-end learning that simultaneously learns the autoencoder and regression model. As a result of experiments with R&D documents in the "Healthcare" field, we confirmed the proposed methodology showed superior performance in terms of accuracy compared to the traditional model.

• Information Systems Review
• /
• v.20 no.4
• /
• pp.79-96
• /
• 2018

This study started by focusing on the internalization of the technology appraisal model into the credit rating model to increase the discriminative power of the credit rating model not only for SMEs but also for all companies, reflecting the items related to the financial stability of the enterprises among the technology appraisal items. Therefore, it is aimed to verify whether the technology appraisal model can be applied to identify high-stability SMEs in advance. We classified companies into industries (manufacturing vs. non-manufacturing) and the age of company (initial vs. non-initial), and defined as a high-stability company that has achieved an average debt ratio less than 1/2 of the group for three years. The C5.0 was applied to verify the discriminant power of the model. As a result of the analysis, there is a difference in importance according to the type of industry and the age of company at the sub-item level, but in the mid-item level the R&D capability was a key variable for discriminating high-stability SMEs. In the early stage of establishment, the funding capacity (diversification of funding methods, capital structure and capital cost which taking into account profitability) is an important variable in financial stability. However, we concluded that technology development infrastructure, which enables continuous performance as the age of company increase, becomes an important variable affecting financial stability. The classification accuracy of the model according to the age of company and industry is 71~91%, and it is confirmed that it is possible to identify high-stability SMEs by using technology appraisal items.

• Information Systems Review
• /
• v.18 no.4
• /
• pp.43-67
• /
• 2016

Although many studies have stressed the importance of technology in service innovation, the roles of technology in service innovation are at the center of debates in the service innovation literature. One major research stream regards technology as a trigger for other innovation based on resource advantage theory. Conversely, another major stream considers it as an enabler of other innovations based on complementary theory. The contradictory situation induces the necessity to better understand the role of technology in service innovation. Therefore, this study aims to identify the role of technology in service innovation. This study investigates the role of technology in service innovation based on a service innovation orientation framework. Four service innovation orientations (i.e., service creation, service delivery, customer interaction, and technology) are identified on the basis of Den Hertog's 4D model. This study proposes a research model that examines the indirect effect of technology orientation on innovation performance through the service creation and service delivery orientations, and the effect of technology orientation on firm performance as a moderator between customer interaction orientation and firm performance. Based on empirical data from 193 knowledge-intensive business service firms in Korea, we explain the role of technology in service innovation. The results indicate that technology orientation influences both service creation and service delivery orientations as an antecedent but customer interaction orientation as an enabler. The three service innovation orientations, which are directly and indirectly influenced by technology orientation, positively affect firm performance. The findings also show that the role of technology is different depending on the type of service innovation orientation in this study.

• Information Systems Review
• /
• v.19 no.3
• /
• pp.127-154
• /
• 2017

This study aims to identify various service innovation patterns in the service industry and understand the main differences among them. We attempt to create a new typology of service innovation by analyzing its patterns based on the four major dimensions of service innovation (i.e., service concept, service delivery, customer interaction, and technology). We then investigate whether firms pursuing different service innovation patterns significantly differ from one another in terms of their performance (high and low performance). Based on empirical data collected from 198 Korean firms in the knowledge-intensive business service sector, four major clusters composed of different service innovation dimensions are identified. These four clusters can be interpreted as specific service innovation patterns, including "technology based high customer interaction," "high technology based high service delivery," "service delivery and high customer interaction-integrated," and "strongly balanced" innovators. High firm performance does not depend on the individual service innovation dimension but on the specific configurations of such service dimensions. Customer interaction also has an important role in achieving innovation success and improving firm performance, while technology has a key role in enhancing firm performance. This study sheds new light on service innovation research by developing a new typology of service innovation, identifying four major clusters as service innovation patterns, and exploring the relationship between service innovation patterns and firm performance.

• Information Systems Review
• /
• v.21 no.4
• /
• pp.197-220
• /
• 2019

This study aims to identify consumer motivations of open innovation project participation from digital transformation perspective. By extending a traditional intrinsic/extrinsic motivation framework, we propose a three-dimensional perspective of the self-driven, firm-driven, and sociality-driven motivations. This reveals the significance of the social effects of open innovation projects as an example of digital transformation by categorizing the motivations based on the 'influencer' of the motivation building and by highlighting the importance of sociality as an influencer. As a result, self-efficacy is identified as a key motivation when the influencer exists internally. Economic incentive and firm reputation are identified when the influencer exists externally. Finally, competition, peer evaluation and social contributions are identified when the influencer exists socially. The role of knowledge type sought through innovation projects is further introduced to explain its moderating effects on motivations. The study is validated in two steps. First, we investigate four cases of open innovation projects and examine what motivations are highlighted in each context. Second, we collect survey data from 203 online game users and ask them on their motivations. The results confirm most of our hypotheses and highlight the significance of sociality in the knowledge-seeking process in open innovation projects. This study largely contributes to digital transformation literature by extending the view of motivation and examining the moderating role of knowledge involved in the projects.

• Information Systems Review
• /
• v.19 no.2
• /
• pp.115-136
• /
• 2017

Online communities have become substantial aspects of people's daily lives. However, only a few communities succeed and attract the majority of users, whereas the vast majority struggle for survival. When various communities coexist, important factors should be identified and examined to maintain attraction and achieve success. The concept of coexistence as been extensively explored in organizational ecology literature. However, given the similarities and differences between online communities and traditional organizations, the direct application of organizational theories to online contexts should be cautiously explored. In this study, we follow the roadmap proposed by Davis et al. (2007) in conducting agent-based modeling and simulation study to develop a novel theory based on the previous literature. In the case of two coexisting communities, we find that community size and participation costs can significantly affect the development of a community. A large community can attract a high number of active members who frequently log in. By contrast, low participation costs can encourage the reading and posting behaviors of members. We also observe the important influence of the distribution of interests on the topic trends of communities. A community composed of a population that focuses on only one topic can quickly converge on the topic regardless of whether the initial topic is broad or focused. This simulation model provides theoretical implications to literature and practical guidance to operators of online communities.

• Information Systems Review
• /
• v.20 no.2
• /
• pp.21-37
• /
• 2018

Under ubiquitous work environment, innovative changes occur in work process with ICT. The work process for collaboration through mobile devices and network should be investigated. The research model consists of two major antecedents: autonomy and interdependence as a task characteristic and job satisfaction as ultimate consequence followed by work design theory. To elaborate work design theory, smartwork application (app) use, communication extent, and work-life balance were reviewed from the literature. Data were collected from three ICT firms, which adopted certain smartwork app, and a partial least squares analysis was made on 175 data points. The analysis results show that task interdependence exerts a statistically significant effect on the level of smartwork app usage. Communication extent directly affects job satisfaction and work-life balance. The remarkable point is that smartwork app usage does not affect employees' work-life balance; the former can only affect the latter indirectly by increasing communication extent. This study attempts to explain the organizational impact by considering smartwork app and the effects simultaneously. We proposed and empirically tested the extended work design theory including information technology and its environment. Based on the results, other theoretical and practical contributions are discussed at the end with limitations and further studies.

• Information Systems Review
• /
• v.25 no.2
• /
• pp.77-101
• /
• 2023

Due to COVID-19, paid virtual live-stream concerts have emerged as an alternative format and a new revenue model for in-person live concerts. Despite the increasing scholarly and practical interest in how participants experience paid virtual live-stream concerts, few studies examined participants' consumption and participation experiences. Thus, this study aims to provide insights into consumers' virtual live-stream concert experience by employing social representations theory (SRT). We explore the features of paid virtual live-stream concerts based on the C-P-N-D (Content-Platform-Network-Device) framework and the consumers' cognitive and affective perception. To this end, an SRT-based core-periphery analysis was conducted based on 239 responses to the open-ended survey questions. The results show that network-and device-level features of virtual live concerts and participants' overall perception are presented as core elements of paid virtual live-stream concerts, whereas content- and platform-level features are peripheral elements. This finding provides an in-depth understanding of the emergence of paid virtual live-stream concerts as an alternative concert format, thereby providing an invaluable understanding of a virtual live concert experience and theoretical and practical insights.

• Information Systems Review
• /
• v.25 no.2
• /
• pp.205-227
• /
• 2023

Recently, Virtual Human(VH) has begun to appear in various media, not only on social media, but also in advertisements, music sources, and dramas. Virtual human has become a primary marketing tool for companies, but there also exist concerns when the companies do not disclose the identities of virtual humans. Accordingly, it is necessary to examine users' responses toward content that features virtual humans. This study aimed to examine how the exposure of virtual humans in the content affects users' perceptions. Therefore, the study defined the concept of 'VH Disclosure(VHD)', referring to the exposure of the virtual human's identity, and explored the impact of VH disclosure on attitude toward the ad (Hedonism, Utilitarianism, and Interestingness) and source credibility (Trustworthiness and Expertise). The study conducted an experimental survey with 302 respondents. Regardless of when the ad featured a VH or a human, the results showed that there was no significant difference between users' attitudes and source credibility. The results revealed that it was more effective to disclose the VH in social media feeds than directly reveal the VH's identity in the content. Therefore, this study utilizes a new concept of 'VH Disclosure(VHD)' to enhance the understanding of VH and contributes to establishing marketing strategies optimized for consumers in the creation of virtual human-related content.