• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.10-20
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• 2017

The proportion of software in the automotive industry is steadily increasing due to the rapid technological development of automobile E/E parts. Because the automotive E/E technology is now on the basis of intelligent automobile and advanced safety automobile technology. The purpose of this study is to investigate the effect of organizational capability (organizational resource capability and management capability), process capability (process capability, customer Requirement management capability), performance dimension (motivation, participation level). In this study, we conducted questionnaires and statistical analysis on engineers (members of the Korea Advanced Automotive Technology Association) who perform research and development activities in the R&D organization of the automotive E/E part in South Korea. ANOVA is applied for the verification of the difference in performance measured by organizational capability, process maturity, and motivation participation level according to company characteristics (level of processing : supply chain configuration, annual sales, total SW development ratio). According to the results of this study, in order to improve the performance of ASPICE or ISO 26262-related consulting project, a different consulting approach strategy considering the characteristics of organization and personnel is needed. In summary, the analysis results for the three main treatment levels are as follows. The difference in organizational capacity, process capability and performance was found to be statistically significant according to supply chain configuration and annual sales, but it was found that the difference of response according to the proportion of total SW was not significant.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.5
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• pp.77-90
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• 2016

This study is to examine the importance of site selection and service quality in franchise business as food service franchise became one of the fastest-growing service industries today. The chief finding of this study is as follows: First, a survey in locational and service quality factors affecting food service franchise shows that responders are more concerned with hygiene and visibility of the store than proximity and transportation advantages which reflects low statistical significance, thus the distance did not seem to be a big problem for the responders in the context that they mostly visit nearby food franchise. Second, the examination of the influence by the service quality factors and customer satisfaction shows significant positive relation with customer response, speed and accuracy, and accuracy factors which reveals that the responders prefer prompt response and swift judgment toward the customer's needs and expectations, professional knowledge services to the credibility factors in which little correlation with the customer satisfaction were found. Third, the examination of the influence by the service quality factors, locational factors, and re-visit reveals that customer response and specialty showed statistically significant correlation with intention of WOM (Word of Mouth) and revisit, which suggests that swift judgment and response toward the customer's needs and expectations, professional knowledge services is of great importance to both customer satisfaction and revisit. The study on the aspects of locational and service quality factors affecting franchise industry's customer satisfaction was conducted as above, an investigation in both factors' influence on the customer satisfaction was made, and based on the results of the analysis, this research seeks an optimal operation strategy of a franchise business. Food service franchise are relatively very competent to business adminstration and reaction capability to consumption changes due to the already established market, and there are stores springing up everywhere inspired by the founders who are too confident of their success in the franchise business. However, it is necessary for the franchise beginners to figure out a zone oriented, regular customer oriented business strategy than just complying with the head office manual. Owing to an increasing trend of opening medium to large sized stores and investments in the wake of converting to multiple business type Korean food franchise, there is growing need to set up new concept of store development and operational management strategy in order to overcome the excessive competition and limited sales volume of the old-fashioned small sized, small capital franchise stores. Furthermore, as most business category of food service franchise serve very similar menus, from a product differentiation point of view, it is required to map out flexible sales concept including the adoption of competitive and low-price strategy. In conclusion, as is shown in the analytical research, the customers' optimal choice fluctuate over their preferences like customer convenience and circumstances rather than insisting on specific brand, thus it will be necessary for the franchise stores to draw up aggressive strategy and planning in running food service franchise to maximize their profits.

• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.234-240
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• 2004

Now that the e-commerce users are explosively increasing, there is always followed by a sharp increase in load from the e-commerce system and the heavy traffic on the network, where leads to the delayed service for the client's request. The natural consequences contain decreasing customer satisfaction and weakening the business's competitive position in markets. Therefore, we'll need to study the e-commerce system in due consideration of the operational efficiency and response speed. This study includes a design of e-commerce system, with a hierarchical structure based on the local server, which has the capability of caching necessary to distribute the system load, makes a proposal concerning a split web-cache algorithm devoted to the local web server to finally give an analysis of the performance through the appropriate trial.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.4
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• pp.83-97
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• 2008

Recently, as managing organization's stakeholders become important, a viewpoint of corporate social responsibility (CSR) has been changed. Unlike in the past, organizations have performed CSR in their active and strategic point of view. Previous studies about the effect of social responsibility generally focused on customer response, social performance, and financial performance, and studies about the influence on business processes and organizational members are relatively not sufficient. In particular, there is few studies about the relationship among CSR, organization's innovation capability, and non-financial performance. The purpose of this study is to examine the effect of CSR to knowledge management and organizational performance by using multiple regression analysis. Specifically, from the empirical result of this study with 256 Korean finns in diverse industries including the manufacturing, we identified that CSR has positive influence on knowledge management and organizational performance.

• Information Systems Review
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• v.19 no.4
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• pp.183-209
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• 2017

With changes in information technology (IT), many innovative IT-based services, such as AirBnB, have become popular. Switching behavior toward new and innovative services become a major issue for managers who want to attract many customers. In response, many researchers have investigated why customers switch service providers. However, little research has been conducted on the processes of switching behavior for a hedonic service. To fill this research gap, this study aimed to identify the stages of switching behavior based on transtheoretical model. Furthermore, the factors affecting the service switching behavior in stages were identified on the basis of service provider switching model. This study also hypothesized the customer's switching behavior in accommodation sharing economy service and analyzed it empirically. Results showed that the factors affecting switching behavior differ across five stages. The present results can provide a basis to prevent switching behavior and reduce churn by analyzing the difference in switching behavior among stages. This study also helps managers who want to improve organizational performance by enhancing customer retention capability.