• 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.

• Korean Journal of Computational Design and Engineering
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• v.16 no.6
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• pp.414-423
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• 2011

The collaboration hub has been developed since 2004 as an online collaboration space, which supports the various collaborative works amongst small and medium enterprises using information sharing, collaboration project management, and project history management. Because of the change of manufacturing environment and rapid development of information technologies, it should be evolved from the existing version called Collaboration Hub 1.0. Recently, a lot of manufacturing enterprises know the importance of business process management(BPM) and start to introduce BPM systems. Our research group has developed the new version of Collaboration Hub 1.0 called Collaboration Hub 2.0 which contains the BPM concept, the consistent product data management, and the specialized functions overcoming the various variation of manufacturing. This study scrutinizes the meaning and role of the Collaboration Hub 2.0 and introduces an application study of it to the value chain of automobile module development consisted of a leading company and subcontractors. The case study covers the definition, execution and monitoring of collaboration process, the specialized functions overcoming the manufacturing variation and the key performance index of collaboration business.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.154-161
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• 2018

This study conducted to predict the stock market prices based on the assumption that internet news articles might have an impact and effect on the rise and fall of stock market prices. The internet news articles were tested to evaluate the accuracy by comparing predicted values of the actual stock index and the forecasting models of the companies. This paper collected stock news from the internet, and analyzed and identified the relationship with the stock price index. Since the internet news contents consist mainly of unstructured texts, this study used text mining technique and multiple regression analysis technique to analyze news articles. A company H as a representative automobile manufacturing company was selected, and prediction models for the stock price index of company H was presented. Thus two prediction models for forecasting the upturn and decline of H stock index is derived and presented. Among the two prediction models, the error value of the prediction model (1) is low, and so the prediction performance of the model (1) is relatively better than that of the prediction model (2). As the further research, if the contents of this study are supplemented by real artificial intelligent investment decision system and applied to real investment, more practical research results will be able to be developed.

• Korean small business review
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• v.40 no.3
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• pp.1-24
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• 2018

The purpose of this study is verifying with corporate financial data that the required investment amount flow shows a similar pattern as times passed, in new product development by start-up company. In the previous paper, the same authors proposed the required investment amount flow as a 'New Product Investment Curve (NPIC)'. In this study, we have studied further in various types of companies. The samples used are accounting data of 462 companies selected from 5,873 Korean companies which were finished external audit in 2015. The results of this study are as follows; The average investment period was 3 years for the listed companies, while 6 years for the unlisted companies. The investment payback period was 6 years for listed companies, while 17 years for unlisted companies. The investment payback period of the company supported by big affiliate company (We call 'greenhouse company') was 14~15 years, while 17 years for real venture companies. When we divide all companies into 4 groups in terms of R&D cost and variable cost ratio, NPIC explanatory power of 'high R&D and high variable cost ratio group (Automobile Assembly Business) is best. Among the eight investment cost indexes proposed to estimate the investment amount, the 'cash 1' (operating cash flow+fixed asset excluding land & building+intangible asset, deferred asset change)/year-end total assets) turned out to be the most effective index to estimate the investment flow patterns. The conclusion is that NPIC explanatory power is somewhat reduced when we estimate all companies together. However, if we estimate the sample companies by characteristics such as listed, unlisted, greenhouse, and venture company, the proposed NPIC was verified to be effective by showing the required investment amount pattern.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.17-32
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• 2019

Sales representatives of automobile company play a key role in the circulation system. Given the characteristics of the good, consumers demand high-quality information and guides from the salespersons when they decide to purchase an automobile. Sales representatives provide service to the customers in accordance with their needs to help purchase decision-making process. Therefore, a sales representative's personal competence have a significant effect on sales performance. Based on this hypothesis, we assumed that personal competence of a salesperson has a positive correlation with sales performance. An empirical analysis was conducted to test the hypothesis. This study classifies personal competence into 4 independent variables((1) sales technique professionalism (2) salesperson's attitude and relationship with customers (3) emotion utilization (4) emotion control) and measures the correlation with the dependent variable(sales performance). To verify the relationship, we set and modified the hypothesis based on the precedent studies and researches. In addiction, a survey was conducted targeting 300 local salespersons from Gyeonggi-Gangwon region. 268 valid samples were used and analyzed with SPSS WIN24.0 statistical program. As a result of an empirical analysis, it turned out that sales technique professionalism and emotion utilization have positive correlation with sales performance. However, the result failed to support the assumption that sales representative's attitude and relationship with customers and emotion control have positive correlation with sales performance. At last the result revealed that personal competence should be considered as an important determinant of recruitment specification for sales representatives.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.146-155
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• 2022

The purpose of this study is to investigate the recyclability of Shenlong in China using SWOT. The main analysis results are as follows. First, provided that the company's current capacity utilization rate is seriously insufficient, reducing staff is one among the effective ways. Second, Shenlong should open a web store to cater to young people's online shopping behavior, and further expand the brand visibility using national mainstream media and online shopping platforms like Taobao and JingDong to market Dongfeng Peugeot and Dongfeng Citroen on the whole network. Third, under the premise of maintaining the present best-selling models, Shenlong should appropriately reduce the amount of models, adjust the assembly capacity ratio of every model and every displacement in real time per the newest market trends, increase the agility of auto companies' production, and timely meet the wants of domestic consumers. Fourth, dual-brand coordination and channel integration are very necessary, and also the profitability and profitability of dealers are going to be further improved, thereby increasing sales. Fifth, target building new energy leading products of Shenlong, strive to attain the forefront of the industry within the sales of recent energy vehicles within 5 years, and gradually expand new energy vehicle products from passenger vehicles to passenger vehicles and commercial vehicles. Finally, the marketing field of Shenlong Automobile should achieve "three major changes", that is, change from a goal-driven type to a demand-driven type, cancel the bundling of outlet invoicing goals and delivery incentive tiers; start from basic capabilities, and set pragmatic and challenging goals; focus Channels, to realize following the activation of outlets, and single store sales increase.

• Journal of the Korea Safety Management & Science
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• v.15 no.2
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• pp.193-204
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• 2013

The growing logistics strategy of a company is to optimize their vehicle route scheduling in their supply chain system. It is very important to analyze for continuous pickups and delivery vehicle scheduling. This paper is a computational study to investigate the effectiveness of continuous pickups and delivery vehicle routing problems. These scheduling problems have 3 subproblems; Inbound Vehicle Routing Problem with Makespan and Pickup, Line-haul Network Problem, and Outbound Vehicle Routing Problem with Delivery. In this paper, we propose 5 heuristic Algorithms; Selecting Routing Node, Routing Scheduling, Determining Vehicle Type with Number and Quantity, and Modification Selecting Routing Node. We apply these Algorithms to S vehicle company. The results of computational experiments demonstrate that proposed methods perform well and have better solutions than other methods considering the basic time and due-date.

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

• Journal of Korean Society for Quality Management
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• v.31 no.4
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• pp.226-238
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• 2003

Recently, The problems with which our country's company is confronted for business of manufacturing goods. This study set the hypothesis to develop the method that was analysis and application of A reliability evaluation method of environmental material for circuit components in Computer, Color TV, Monitor, Microwave oven, Electric Refrigerator, Automobile parts, other goods. Especially, this study emphasis on regulate export of the EU and North America that it's a environmental material's hazards problem. In this process, this study set the pattern of practical application. Therefore, this study emphasis on the application of A reliability evaluation method of environmental material and the use of other parameters by environmental reliability test data. The result of this study is as follows. 1) There is relationship between regulate material and technical protecting system. 2) Characteristics of hazard materials is operating a healthcare damage factor as well as regulate environmental factors.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.271-280
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• 2002

Recently, many companies have applied data mining techniques to promote competitive power in the field of their business market. In this study, we address how data mining, that is a technique to enable to discover knowledge from a deluge of data, Is used in an executed project in order to support decision making of an enterprise. Also, we develope scoring model on customer attrition probability for automobile-insurance company using data mining techniques. The development of scoring model in domestic insurance is given as an example concretely.