• Journal of Korean Society for Quality Management
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• v.37 no.3
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• pp.10-17
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• 2009

This study developed a new model for evaluating effects about the success of six sigma activities. This model consists of four constructs such as success of six sigma, employee's success experience, customer satisfaction, and business performance. Structural Equation Modeling (SEM) is used to analyze causality among the four constructs. Hypothesis were tested through a field study conducted for one hundred and thirty-one project leaders, who were asked to evaluate their experiences of six sigma projects. The results indicate that six hypothesis are statistically significant. As a result, the success of six sigma doesn't influence the customer satisfaction directly, but it influences customer satisfaction indirectly through employee's success experience. We find out that control for employee's success experience is important as well as success of six sigma in business innovation. Otherwise business performance is influenced directly by success of six sigma, that is business performance isn't influenced directly by employee's success experience but influenced indirectly through customer satisfaction. This study found that the change management raising employee's success experience is important in Six Sigma.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.126-132
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• 2006

Recently, business environments have been changing quickly. To establish competitive advantage, most enterprises have been using information systems such as Enterprise Resource Planning (ERP), Supply Chain Management (SCM) and Customer Relationship Management (CRM). Many consider Business Process Management (BPM) a new innovative solution for enterprise-wide processes. As the BPM system is used more widely and matures, new techniques and functions will be developed by commercial vendors. However, they mainly focus on correctly executing process models, and user convenience has not been considered. In this paper, we have developed a new method of designing business processes, which provides users with an easy modeling interface. The method is based on version management. Version management of a process enables a history of the process model to be recorded. In order to prevent wasted storage, not all of the process versions are stored. An initial version and changes to each process are stored by automatically detecting changes. Our method enhances the convenience of the modeling business processes and thus helps the process designer. A prototype system is presented to verify the effectiveness of our method.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.79-93
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• 2012

Despite growing interest and attention from researchers and practitioners in management studies, empirical research has been limited on how factors that influence an organization's business performance are affected by certain characteristics of enterprise information systems (IS), such as maturity and infrastructure. This study reports on an empirical analysis of survey data to identify relationships among the informatization level, the business environment, and IS maturity and infrastructure related to business performance-based on financial and non-financial performance measurements-from the perspective of 136 Taiwan firms. The survey questionnaire respondents were drawn from individuals in each of these firms who were typically working in divisions related to business performance functions. Structural equation modeling was used to test the hypotheses that came from the research model in this study.

• Asia pacific journal of information systems
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• v.32 no.4
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• pp.945-963
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• 2022

With the widespread use of social media, online social platforms like Twitter have become a place of rapid dissemination of information-both accurate and inaccurate. After the COVID-19 outbreak, the overabundance of fake information and rumours on online social platforms about the COVID-19 pandemic has spread over society as quickly as the virus itself. As a result, fake news poses a significant threat to effective virus response by negatively affecting people's willingness to follow the proper public health guidelines and protocols, which makes it important to identify fake information from online platforms for the public interest. In this research, we introduce an approach to detect fake news using deep learning techniques, which outperform traditional machine learning techniques with a 93.1% accuracy. We then investigate the content differences between real and fake news by applying topic modeling and linguistic analysis. Our results show that topics on Politics and Government services are most common in fake news. In addition, we found that fake news has lower analytic and authenticity scores than real news. With the findings, we discuss important academic and practical implications of the study.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.817-837
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• 2019

The medical industry is rapidly evolving into a combination of artificial intelligence (AI) and ICT technology, such as mobile health, wireless medical, telemedicine and precision medical care. Medical artificial intelligence can be diagnosed and treated, and autonomous surgical robots can be operated. For smart medical services, data such as medical information and personal medical information are needed. AI is being developed to integrate with companies such as Google, Facebook, IBM and others in the health care field. Telemedicine services are also becoming available. However, security issues of medical information for smart medical industry are becoming important. It can have a devastating impact on life through hacking of medical devices through vulnerable areas. Research on medical information is proceeding on the necessity of privacy and privacy protection. However, there is a lack of research on the practical measures for protecting medical information and the seriousness of security threats. Therefore, in this study, we want to confirm the research trend by collecting data related to medical information in recent 5 years. In this study, smart medical related papers from 2014 to 2018 were collected using smart medical topics, and the medical information papers were rearranged based on this. Research trend analysis uses topic modeling technique for topic information. The result constructs topic network based on relation of topics and grasps main trend through topic.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.121-133
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• 2015

This tutorial presents an approach to perform the covariance based structural equation modeling using the R. For this purpose, the tutorial defines the criteria for the covariance based structural equation modeling by reviewing previous studies, and shows how to analyze the research model with an example using the "lavaan" which is the R package supporting the covariance based structural equation modeling. In this tutorial, a covariance-based structural equation modeling technique using the R and the R scripts targeting the example model were proposed as the results. This tutorial will be useful to start the study of the covariance based structural equation modeling for the researchers who first encounter the covariance based structural equation modeling and will provide the knowledge base for in-depth analysis through the covariance based structural equation modeling technique using R which is the integrated statistical software operating environment for the researchers familiar with the covariance based structural equation modeling.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1143-1150
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• 2017

The objective of this study is to examine the trends in information systems research. The abstracts of 1,245 articles were extracted from three leading Korean journals published between 2002 and 2016: Asia Pacific Journal of Information Systems, Information Systems Review, and The Journal of Information Systems. Time series analysis and topic modeling methods were implemented. The topic modeling results showed that the research topics were mainly "systems implementation", "communication innovation", and "customer loyalty". The time series regression results indicated that "customer satisfaction", "communication innovation", "information security", and "personal privacy" were hot topics, and on the other hand, "system implementation" and "web site" were the least popular. This study also provided suggestions for future research.

• The Journal of Society for e-Business Studies
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• v.10 no.2
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• pp.21-41
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• 2005

An Enterprise Architecture (EA) Framework is a tool which supports implementation of the Enterprise architecture that is used to enhance the interoperability of the IT components. In this paper, we propose a framework named as ENAE (ENterprise Architecture Framework) which combines enterprise architecture unit (AU), reference model, and association relationship between domain model. Architecture Unit is defined as a minimum set of a business process and its associated components such as application system and technical components. An EA can be designed and implemented by the aggregating the related AUs including association relationship between Architecture Units. Because UML model has limitations to describe business domain semantics because it is designed for general purpose, we adapt the DSM (Domain Specific Modeling) concept. We describe association relationship between Architecture Units designed by Domain Specific Modeling through Topic Map. Session 2 describes related works about Enterprise Architecture frameworks, Domain Specific Modeling, and Topic Map, while Session 3 explains components of the ENAF. Finally Session 4 shows the case study for implementation of the new Framework called ENAF.

• Korean Journal of Construction Engineering and Management
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• v.11 no.3
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• pp.80-88
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• 2010

The construction industry concentrates their efforts on construction information technology (IT) including construction CALS. However, the actual circumstances for construction IT focuses on building hardware and it neglects importance of business process reengineering (BPR) for construction tasks. A systematic process modeling method and a computerized model by process concept need for building construction BPR. This study develops a generalized BPR procedure for construction projects, and then suggests a new process modeling method for construction BPR that consists of object-related process model (ORPM). Finally, this study develops a web-based ORPM Builder (ORPMB) based on the ORPM methodology, and the applicability of the developed system is verified by a case study with practical construction processes.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.217-225
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• 2019

The Latent Growth Modeling(LGM) is known as the typical analysis method of longitudinal data and it could be classified into unconditional model and conditional model. It is common to assume that the growth trajectory of unconditional model of LGM is linear. In the case of quasi-linear, the methodology for improving the model fitness using Sequential Pattern of Association Rule Mining is suggested. To do this, we divide longitudinal data into quintiles and extract periodic changes of the longitudinal data in each quintiles and make sequential pattern based on this periodic changes. To evaluate the effectiveness, the LGM module in SPSS AMOS was used and the dataset of the Youth Panel from 2001 to 2006 of Korea Employment Information Service. Our methodology was able to increase the fitness of the model compared to the simple linear growth trajectory.