• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.221-241
• /
• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.20 no.44
• /
• pp.425-446
• /
• 1997

In recent years, a scholars and a managers in business have taken a more interest on the effects of corporate culture on the organization effectiveness. The corporate culture has been recognized as one of the way to promote the organization performance and cope with the changes of the business environment. Edgar H. Shein defins the corporate culture as the that the pattern of basic assumptions that a given group has invented, discovered or developed in learning to cope with its problems of external adaptation and internal integration. The organization effectiveness is differently defined as the job satisfaction, job involvement, organizational commitment, organizational performance etc. The business culture help the employee (1) understand the values, the tradition, and the different management systems(decision-making basis, promotion, reward, behavior etc.) of the company, (2) make the performance-oriented decison and doings. Consequently, the excellent corporate culture would improve the organizational effectiveness. The purpose of this study is (1) to examine theoretically the content on the corporate culture and the organizational effectiveness, (2) to suggest the direction of the corporate culture management for both the management md the scholars.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
• /
• v.50
• /
• pp.187-212
• /
• 2011

Third party logistics research is searching for increasing its logistics efficiency of organization. Perspective of resource-based theory, this study is to reveal the exploratory relation between integrated capabilities, organzaiton knowledge, and service performance. To develop the relational model, this study conducted a theoretical survey on Shang(2009)'s 3PL service providers research model and Synder & Cumming(1998)'s learning of organization knowledge. According to the result of correlation analysis, Integrated organization knowledge is positively correlated with service diversity advantage (correlation coefficient= .670, p-value= .000) and service quality advantage (correlation coefficient= .575, p-value= .000). The thesis argued that Korean companies try to apply integrated organization abilities and service performance for cutting their export expense.

• Structural Engineering and Mechanics
• /
• v.16 no.1
• /
• pp.83-99
• /
• 2003

The aim of this paper is to develop the ISCOSTFUN (Intelligent System for Prediction of Concrete Strength by Functional Networks) in order to provide in-place strength information of the concrete to facilitate concrete from removal and scheduling for construction. For this purpose, the system is developed using Functional Network (FN) by learning functions instead of weights as in Artificial Neural Networks (ANN). In serial functional network, the functions are trained from enough input-output data and the input for one functional network is the output of the other functional network. Using ISCOSTFUN it is possible to predict early strength as well as 7-day and 28-day strength of concrete. Altogether seven functional networks are used for prediction of strength development. This study shows that ISCOSTFUN using functional network is very efficient for predicting the compressive strength development of concrete and it takes less computer time as compared to well known Back Propagation Neural Network (BPN).

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2002.07b
• /
• pp.1121-1124
• /
• 2002

Currently, the regulation system on controlling EMI has been strengthened throughout the world and this system has emerged as another invisible barrier from the advanced countries. Such a regulation is likely to expand in many various ways depending on the objective and type, and there has to be a fundamental EMI measure to respond this movement. This study is aimed at learning the EMI technology of communication system through the shielding material. It introduces the selection of appropriate shielding material and method of use, and it introduces the cases that resolved the actual EMI problem of the system that is manufactured by the company.

• Nuclear Engineering and Technology
• /
• v.9 no.3
• /
• pp.151-163
• /
• 1977

Being based on the Segal method, calculation was carried out for the natural uranium nuclear fuel cost with Zircaloy-4 cladding having design Parameters of Wolsung Nuclear Power Plant, CANDU-PHWR (Unit 1) , currently under construction in Korea aiming at its completion in 1982. An attempt was also made for tile sensitivity analysis of each fuel component; j. e., depreciation of fuel manufacturing plant caused by its life time, its load factor, production scale expansion of plant facilities, variations of construction and operating costs of fuel manufacturing plant, fluctuation of interest rates, extent of uranium ore price increases and effect of learning factor.

• Asia pacific journal of information systems
• /
• v.9 no.3
• /
• pp.127-142
• /
• 1999

There have been strong arguments that the best organizational type for the information society is a network organization which is intelligent and learning-oriented as well as has problem solving capacities rather than a traditional passive organization which strictly follows standard operating procedures. In this perspective, integrated information work environment emerges as attractive work environment for the 21st century. Integrated information work environment is defined as an integrated electronic environment that is available to and readily accessible be each employee and is structured to provide immediate, individualized on-line access to the full range of information, software, guidance, advice and assistance, data, images, tools, and assessment and monitoring systems to permit job performance with minimal support and intervention by others. Case study was performed to measure the productivity improvement by implementing integrated information work environment in life insurance company. The results show that there is a number of indications of strong work productivity improvements.

• Knowledge Management Research
• /
• v.8 no.1
• /
• pp.15-28
• /
• 2007

In the age where the Internet changes everything, even the earth has become flat. The boarders between nations, locations, times, and industries are not meaningful, and no single company can do the whole process well. Therefore, various types of 'Value network' and 'Relation web' emerge for moving first and learning fast. Both the relationship maturity model (RMM) proposed and the partnership management initiatives at SKT demonstrate that the concept is important, and that the final goal can be reached only through a series of critical outcome at each phase. In particular, recognizing as core infrastructures various online/offline channels, deep trust, and rich communications is an important finding for a successful relationship management. Also, related literatures suggest the following key factors to be influential in more than two phases: professionalism including expertise, similarity, channel infrastructure, trustful/trustworthy, and absorptive capacity. Based on these findings, future efforts need to be put on the research & development of related measurement and management tools. It is hoped that more dance with their partners through these efforts.

• Journal of Korean Society for Quality Management
• /
• v.29 no.4
• /
• pp.38-53
• /
• 2001

In resolving industrial quality control problems, a vector of multiple quality characteristic variables is involved rather than a single variable. However, it is not guaranteed that a multivariate control chart based on statistical methods can monitor abnormal signal in case that small changes of relationship between each variables causes abnormal production process. Hence a quality control system for real-time monitoring of the multi-dimensional quality characteristic vector under a multivariate normal process is needed to enhance tile production system quality performance. A pattern analysis approach based on self-organizing map (SOM), an unsupervised learning technique of neural network, is applied to the design of such a quality control system. In this study we present a new material quality control system based on pattern analysis approach and illustrate the effectiveness of proposed system using actual electronic company material data.

• Journal of the Korea Safety Management & Science
• /
• v.7 no.1
• /
• pp.199-210
• /
• 2005

Customer segmentation prediction has attracted a lot of research interests in previous literature, and recent studies have shown that artificial neural networks (ANN) method achieved better performance than traditional statistical ones. However, ANN approaches have suffered from difficulties with generalization, producing models that can overfit the data. This paper employs a relatively new machine learning technique, support vector machines (SVM), to the customer segmentation prediction problem in an attempt to provide a model with better explanatory power. To evaluate the prediction accuracy of SVM, we compare its performance with logistic regression analysis and ANN. The experiment results with real data of insurance company show that SVM superiors to them.