• Journal of Korean Society for Quality Management
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• v.40 no.4
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• pp.599-614
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• 2012

Purpose: We measure service quality based on service process, and examine relationships among product quality, product and service loyalty. Methods: We develop a construct to evaluate process based service quality. We collect data from customers of auto maintenance centers to measure perceived product quality, service and product quality. We test relationships between constructs using structural equation model and regression analysis. Results: Relationships among perceived-product quality, service quality, service loyalty, and product loyalty are all significant. Conclusion: Perceived-product quality has a indirect impact through service quality and loyalty in addition to a direct impact on product loyalty.

• Proceedings of the Korean Society for Quality Management Conference
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• 2010.04a
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• pp.55-61
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• 2010

Many enterprises are looking for counterproposals to be survival through innovation activities and to be held on their continuous businesses for their business management environments nowadays. One of the innovation activities is an improvement of Loss and reinforcement of business structure through Lean, TPM. Another one is an improvement of these innovation activities and have achieved lots of outcomes (profits). But most these activities have been applied for only the industries in Automobile, Semiconductor, Aviation, Construction with large enter in Korea. And most of minor cable enterprises don't even try to import these innovation activities excluding some how the small and medium cable enterprise can import the LEAN / 6 Sigma activities effectively with some of sample in real small and medium cable company.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.177-182
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• 2013

More and more medium and small enterprises do business across the world according to generalization of online shopping mall such as eBay and Amazon. But high export and import transportation cost make weak the price competitive power of medium and small enterprises products. Then this paper deals with the development of new business model which can reduce the transportation cost for global logistics through efficiently overcoming the constraints as length, size, and weight of product. We explain this model with application for company which export the automobile parts. We can expect the transportation cost reduction by 50%.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.170-174
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• 2003

While related with electronic commerce and supply chain management, the concept of ERP is more extended. Even information technology makes it more important to achieve company competence Automobile material industry in which there are the variety of suppliers and materials, has to relate with external information such as supply chain information in order to induct efficient ERP system. This study focuses on the induction policies of ERP system through data sharing within supply chain, and performed both case study and statistical analysis through the interviews to the suppliers of automobile materials. To the better induction of ERP through information sharing of SCM, we have to consider the needs of partner of which information sharing is being done well. This study suggests that organizational change management, business process, information technology are orderly taken into account as the analytical results.

• Journal of Distribution Science
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• v.17 no.6
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• pp.65-75
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• 2019

Purpose - Vietnamese customers have a crowd psychology when choosing and buying cars, they believe the advice and comments of those who have used the product. This paper aims to explore how factors in the relation between employees and customers affect to the customer's positive word of mouth (WOM) through customer satisfaction. Research design, data, and methodology - A survey was conducted with 250 customers. This research focus on six factors: (1) familiarity, (2) care, (3) personal connection, (4) employee competence, (5) customer satisfaction, (6) positive WOM. By using Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM), this research determined the impact of relation between eployees and customers to the customer satisfaction in order to have the positive WOM to another customers. Results - This result shows that 3 factors: care, personal connection and service quality, have positive effects to customer satisfaction. Moreover, the similar relationship is found between customer satisfaction and positive WOM. The familiarity is not significant in this research. Conclusions - The research results indicate that positive WOM has an important impact of market development for automobile business enterprises in Vietnam. Therefore, administrators should have appropriate strategies to encourage positive WOM to customers.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.193-198
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• 2013

Warehouse Management System was a helper of business in past, but it is perceived as a core competitive power and a tool for generating new business. It have been come out some new prospects for WMS due to generalization of global outsourcing and extension of the range of supply chain. In China, H automobile company construct the new WMS for providing the production extension and increment of part demand for A/S. This paper deals with the location management in warehouse, warehouse management, delivery management of goods from a warehouse, inventory management organizing WMS for construction of A/S warehouse in H motor in China. Then we identified the several problems of existing warehouse and constructed the driving organization and methods for overcoming these problems. We continually gather data for analysing the effects of new A/S warehouse and WMS construction.

• Korean Journal of Artificial Intelligence
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• v.9 no.1
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• pp.9-14
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• 2021

This paper predicted a model that indicates whether to buy a car based on primary health insurance customer data. Currently, automobiles are being used to land transportation and living, and the scope of use and equipment is expanding. This rapid increase in automobiles has caused automobile insurance to emerge as an essential business target for insurance companies. Therefore, if the car insurance sales are predicted and sold using the information of existing health insurance customers, it can generate continuous profits in the insurance company's operating performance. Therefore, this paper aims to analyze existing customer characteristics and implement a predictive model to activate advertisements for customers interested in such auto insurance. The goal of this study is to maximize the profits of insurance companies by devising communication strategies that can optimize business models and profits for customers. This study was conducted through the Microsoft Azure program, and an automobile insurance purchase prediction model was implemented using Health Insurance Cross-sell Prediction data. The program algorithm uses Two-Class Logistic Regression and Two-Class Boosted Decision Tree at the same time to compare two models and predict and compare the results. According to the results of this study, when the Threshold is 0.3, the AUC is 0.837, and the accuracy is 0.833, which has high accuracy. Therefore, the result was that customers with health insurance could induce a positive reaction to auto insurance purchases.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.141-156
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• 2008

Market structure analysis is a very useful tool to analyze the competition boundary of the brand or the company. But most of the studies in market structure analysis, the concern lies in nondurable goods such as candies, soft drink and etc. because of the their availability of the data. In the field of durable goods, the limitation of the data availability and the repurchase time period constrain the study. In the analysis of the automobile market, those of views might be more persuasive. The purpose of this study is to analyze the structure of automobile market based on some idea suggested by prior studies. Usually the buyers of the automobile tend to buy upper tier when they buy in the next time. That kind of behavior make it impossible to analyze the structure of automobile market under the level of automobile model. For that reason I tried to analyze the market structure in the brand or company level. In this study, consideration data was used for market structure analysis. The reasons why we used the consideration data are summarized as following. Firstly, as the repurchase time cycle is too long, brand switching data which is used for the market analysis of nondurable good is not avaliable. Secondly, as we mentioned, the buyers of the automobile tend to buy upper tier when they buy in the next time. We used survey data collected in the U.S.A. market in the year of 2005 through questionaire. The sample size was 8,291. The number of brand analyzed in this study was 9 among 37 which was being sold in U.S.A. market. Their market share was around 50%. The brands considered were BMW, Chevrolet, Chrysler, Dodge, Ford, Honda, Mercedes, and Toyota. �� ratio was derived from frequency of the consideration set. Actually the frequency is different from the brand switch concept. In this study to compute the �� ratio, the frequency of the consideration set was used like a frequency of brand switch for convenience. The study can be divided into 2 steps. The first step is to build hypothetical market structures. The second step is to choose the best structure based on the hypothetical market structures, Usually logit analysis is used for the choice best structure. In this study we built 3 hypothetical market structure. They are type-cost, cost-type, and unstructured. We classified the automobile into 5 types, sedan, SUV(Sport Utility Vehicle), Pickup, Mini Van, and Full-size Van. As for purchasing cost, we classified it 2 groups based on the median value. The median value was $28,800. To decide best structure among them, maximum likelihood test was used. Resulting from market structure analysis, we find that the automobile market of USA is hierarchically structured in the form of 'automobile type - purchasing cost'. That is, result showed that automobile buyers considered function or usage first and purchasing cost next. This study has some limitations in the analysis level and variable selection. First, in this study only type of the automobile and purchasing cost were as attributes considered for purchase. Considering other attributes is very needful. Because of the attributes considered, only 3 hypothetical structure could be analyzed. Second, due to the data, brand level analysis was tried. But model level analysis would be better because automobile buyers consider model not brand. To conduct model level study more cases should be obtained. That is for acquiring the better practical meaning, brand level analysis should be conducted when we consider the actual competition which occurred in the real market. Third, the variable selection for building nested logit model was very limited to some avaliable data. In spite of those limitations, the importance of this study lies in the trial of market structure analysis of durable good.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.58-72
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• 2021

In July 2021, UNCTAD classified Korea as a developed country. After the Korean War in the 1950s, economic development was promoted despite difficult conditions, resulting in epoch-making national growth. However, in order to respond to the rapidly changing global economy, it is necessary to continuously study the domestic industrial ecosystem and prepare strategies for continuous change and growth. This study analyzed the industrial ecosystem of the automobile industry where it is possible to obtain transaction data between companies by applying complexity spatial network analysis. For data, 295 corporate data(node data) and 607 transaction data (link data) were used. As a result of checking the spatial distribution by geocoding the address of the company, the automobile industry-related companies were concentrated in the Seoul metropolitan area and the Southeastern(Dongnam) region. The node importance was measured through degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality, and the network structure was confirmed by identifying density, distance, community detection, and assortativity and disassortivity. As a result, among the automakers, Hyundai Motor, Kia Motors, and GM Korea were included in the top 15 in 4 indicators of node centrality. In terms of company location, companies located in the Seoul metropolitan area were included in the top 15. In terms of company size, most of the large companies with more than 1,000 employees were included in the top 15 for degree centrality and betweenness centrality. Regarding closeness centrality and eigenvector centrality, most of the companies with 500 or less employees were included in the top 15, except for automakers. In the structure of the network, the density was 0.01390522 and the average distance was 3.422481. As a result of community detection using the fast greedy algorithm, 11 communities were finally derived.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.4
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• pp.123-130
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• 2012

The automobile industry has been rapidly developing and the manufacturers in Korea as well as auto makers in other advanced countries are putting every ounce of their energies in securing their competitive edges in technology and in marketing. To that purpose, each company focuses on (i) reducing costs and (ii) improving productivity. We believe that the improved productivity can be capitalized by a set of various factors including improved organization-internal environment and employees' job satisfaction. The present research aims to identify how the internal elements contribute and lead to improved productivity. The present paper is a report of an empirical survey performed to 161 employees working in small and medium-sized firms in the automobile industry. After testing reliability and validity of the collected data, we have performed structural equation analysis using Amos of SPSS and tested a set of research hypotheses and models. The reported results will clarify the factors that influence productivity and job satisfaction and also shed light on the directions for strategic polices to keep up with the ever changing climate of the industry.