• The Journal of Information Systems
• /
• v.9 no.1
• /
• pp.157-188
• /
• 2000

Today a knowledge management systems (KMS) is an enabler for gaining competitive position in the market environments. However, it is just recognized as a conceptual management paradigm not as realistic management philosophy in an organization. A firm just accustomed to deal with tangible assets such as inventory and buildings based on the cumulated experiences. However, the firm often struggle with how to define and apply the knowledge management system into its real business activities such as business strategy and productivity. For example, one of textile company, E-land, in Korea found the way how the firm utilize intelligent assets of its employees to overcome the performance differences among the employees in an organization to increase their ability. Managers in an organization should fully understand and try to figure out the concept of knowledge management systems to implement KMS more efficiently and effectively. Even though lots of previous knowledge management literature proposed several unique knowledge management process models, they have their own terms, process sequences, or different approaches. There are three common knowledge management processes： knowledge creation, knowledge store and search, knowledge sharing process. In this study, a new KM process theoretical framework based on the previous researches is developed. This study will guide to those who will adopt or implement of KMS in the organization in near future.

• Journal of Fashion Business
• /
• v.16 no.3
• /
• pp.78-94
• /
• 2012

This study devised and drew custom sleeve patterns by using a regression equation with the data from 7 models along with the sleeve that was slightly modified to make the general-purpose sleeve pattern. To devise a general-purpose sleeve pattern, the sleeve pattern was drawn as an object for comparison by applying the Bunka drafting system (sleeve pattern by the Bunka drafting system) to the basic upper garment. Actual sleeves, made by using the three types of patterns above, were created and tested by models. Next, 30 panel members participated in a sight test of the compatibility of the sleeves to examine the validity of the sleeve drafting method acquired using the regression equation. The test proved that the custom sleeve pattern and the general-purpose sleeve pattern were more suitable for the characteristics of arm structures. Thus, the new sleeve-cap part drafting method using the regression equation was shown to have validity. As a result, since a very significant correlation was obtained for the body measurement figures and the basic pattern of the adequate basic pattern of the sleeves, this study concludes that it is possible to come up with primary data that can be widely used by increasing the number of subjects.

• Journal of Korean Society for Quality Management
• /
• v.36 no.4
• /
• pp.102-116
• /
• 2008

The most widely used models to study the quality of service are the SERVQUAL and SERVPERF models that measure service mechanisms. This paper is to estimate service efficiency and consistency for Retail Industry. We tried to measure the service quality and overall satisfaction by using DEA and PCI, degree of combination and top2box which is a little bit different methodology from traditional ones. Rather than using the usual method of converting the service quality index by mean value, the Service Efficiency Index(SEI) and Service Quality Consistency Index(SQCI) are used to measure the efficiency and consistency level, which in turn can be used as the new service quality indices. The result of SEI and SQCI show the efficiency frontier in retail industry that 6 DMUs are analyzed relative efficient DMUs, 12DMUs are inefficient DMUs and retail Industry consistency level appeared low(0.35-0.47) Also, there is a significant difference in terms of efficiency and consistency in the each retail industry. Finally, we showed the summarized result as the Effi-Con Matrix.

• YAKHAK HOEJI
• /
• v.55 no.2
• /
• pp.98-105
• /
• 2011

To search the minimum structural requirement of tricyclic isoxazole analogues (1~30) as new class potent antidepressant, thee-dimensional quanti- tative-structure relationship (3D-QSAR) models between substituents ($R_1{\sim}R_5$) of tricyclic isoxazoles and their antidepressant activity against medetomidine-induced loss of righting were performed and discussed quantitatively using comparative molecular field analysis (CoMFA) and comparative molecular similarity indies analysis (CoMSIA) methods. The correlativity and predictability ($r^2$=0.484 and $q^2$=0.947) of CoMSIA-2 model were higher than those of the rest models. The inhibitory activity against medetomidine-induced loss of righting was dependent on electrostatic field (43.4%), hydrophobic field (35.3%), and steric field (21.2%) of tricyclic isoxazoles. From the CoMSIA-2 contour maps, it is predicted that the antidepressant activity of potent antidepressants against medetomidine-induced loss of righting will be able to increase by the substituents ($R_1{\sim}R_5$) which were in accord with CoMSIA field.

• The Journal of Information Systems
• /
• v.30 no.2
• /
• pp.105-126
• /
• 2021

Purpose The purpose of this study is to implement a optimal machine learning model about the cancellation prediction performance in car sales business. It is to apply the data set of accumulated contract, cancellation, and sales information in sales support system(SFA) which is commonly used for sales, customers and inventory management by imported car dealers, to several machine learning models and predict performance of cancellation. Design/methodology/approach This study extracts 29,073 contracts, cancellations, and sales data from 2015 to 2020 accumulated in the sales support system(SFA) for imported car dealers and uses the analysis program Python Jupiter notebook in order to perform data pre-processing, verification, and modeling that is applying and learning to Machine learning model after then the final result was predicted using new data. Findings This study confirmed that cancellation prediction is possible by applying car purchase contract information to machine learning models. It proved the possibility of developing and utilizing a generalized predictive model by using data of imported car sales system with machine learning technology. It can reduce and prevent the sales failure as caring the potential lost customer intensively and it lead to increase sales revenue by predicting the cancellation possibility of individual customers.

• Journal of Intelligence and Information Systems
• /
• v.12 no.2
• /
• pp.167-183
• /
• 2006

Since data mining attempts to find unknown facts or rules by dealing with also vaguely-known data sets, it always suffers from high error rate. In order to reduce the error rate, many researchers have employed multiple models in solving a problem. In this research, we present a new type of multiple models, called DyMoS, whose unique feature is that it classifies the input data and applies the different model developed appropriately for each class of data. In order to evaluate the performance of DyMoS, we applied it to a real customer churn problem of an automobile insurance company, The result shows that the DyMoS outperformed any model which employed only one data mining technique such as artificial neural network, decision tree and case-based reasoning.

• The Journal of Fisheries Business Administration
• /
• v.52 no.4
• /
• pp.13-28
• /
• 2021

The purpose of this study is to compare short-term price predictive power among ARMA ARMAX and VAR forecasting models based on the MDM test using monthly consumer price data of frozen mackerel. This study also aims to help policymakers and economic actors make reasonable choices in the market on monthly consumer price of frozen mackerel. To analyze this study, the frozen wholesale prices and new consumer prices were used as variables while the price time series data were used from December 2013 to July 2021. Through the unit root test, it was confirmed that the time series variables employed in the models were stable while the level variables were used for analysis. As a result of conducting information standards and Granger causality tests, it was found that the wholesale prices and fresh consumer prices from the previous month have affected the frozen consumer prices. Then, the model with the highest predictive power was selected by RMSE, RMSPE, MAE, MAPE, and Theil's inequality coefficient criteria where the predictive power was compared by the MDM test in order to examine which model is superior. As a result of the analysis, ARMAX(1,1) with the frozen wholesale, ARMAX(1,1) with the fresh consumer model and VAR model were selected. Through the five criteria and MDM tests, the VAR model was selected as the superior model in predicting the monthly consumer price of frozen mackerel.

• Korean Medical Education Review
• /
• v.18 no.2
• /
• pp.51-57
• /
• 2016

This literature review explores artificial intelligence (AI) technology trends and IBM Watson health and medical references. This study explains how healthcare will be changed by the evolution of AI technology, and also summarizes key technologies in AI, specifically the technology of IBM Watson. We look at this issue from the perspective of 'information overload,' in that medical literature doubles every three years, with approximately 700,000 new scientific articles being published every year, in addition to the explosion of patient data. Estimates are also forecasting a shortage of oncologists, with the demand expected to grow by 42%. Due to this projected shortage, physicians won't likely be able to explore the best treatment options for patients in clinical trials. This issue can be addressed by the AI Watson motivation to solve healthcare industry issues. In addition, the Watson Oncology solution is reviewed from the end user interface point of view. This study also investigates global company platform business to explain how AI and machine learning technology are expanding in the market with use cases. It emphasizes ecosystem partner business models that can support startup and venture businesses including healthcare models. Finally, we identify a need for healthcare company partnerships to be reviewed from the aspect of solution transformation. AI and Watson will change a lot in the healthcare business. This study addresses what we need to prepare for AI, Cognitive Era those are understanding of AI innovation, Cloud Platform business, the importance of data sets, and needs for further enhancement in our knowledge base.

• Design Convergence Study
• /
• v.16 no.3
• /
• pp.69-84
• /
• 2017

Service blueprint is used to show the interaction between each service element at a glance and to understand the flow of the whole service centering on the customer at the stage of proposing a new service system. It was proposed in the 1980s before online business was developed. However, current services are changing in a way that provides various forms and channels, and the service blueprint seems to be not enough. To reflect this problem consciousness, we selected PSS among diversified service business models and propose a service blueprint type optimized for each business. After collecting 137 PSS cases to be used in the research, we made a business matrix and classified the cases and selected two representative cases to conduct two experiments. As a result, six types of service blueprint corresponding to the matrix could be derived: online service type, online remote support type, self rental type, online order type, traditional type, and offline support type. The validity of the proposed types of service blueprint was verified to confirm the suitability of those types.

• Journal of Information Technology Applications and Management
• /
• v.19 no.1
• /
• pp.25-36
• /
• 2012

Social Commerce recently attracted the attention of academic and industry researchers. Social Commerce aims to make a transactional environment which is beneficial to three parties-social commerce service provider, buyer and seller by way of using the platform of SNS. As Social Commerce is a new technology issue, there is no existing conceptual framework, e.g. appropriate classification the business types, that help to understand the nature of Social Commerce. This study suggests one classification framework and tries to verify whether it works.