• Journal of Ocean Engineering and Technology
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• v.11 no.3
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• pp.200-211
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• 1997

Most recently, offshore Engineering & Construction field is concerned about integration management technology such as CIM(Computer Integrated Manufacturing), PDM(Product Data Management) and Enterprise Information Engineering in order to cope with the rapid change of engineering and manufacturer specification as per owner's requirement during construction stage of the project. System integration and integrated data modeling with relational database in integration management technology improve the quality of product and reduce the period of the construction project by reason of owing design information jointly. This paper represents the design methodology of system integration using Business Process Reengineering by the case study. The case study is about the offshore plant material information process from front end engineering design to detail engineering for the construction and the basis of monitoring system by integrating and sharing the design information between the 2D intelligent P&ID and 3D plant modeling using relational database. As a result of the integrated data modeling and system integration, it is possible to maintain the consistency of design process in point of view of the material balancing and reduce the design assumption/duration. Near future, this system will be expanded and connected with the MRP(Material Requirement Planing) and the POR (Purchase Order Requisition) system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.69-77
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• 2019

As information technology advances, the penetration of smart devices connected to the Internet, such as smart phone and tablet PC, has rapidly expanded, and as sensor prices have fallen the Internet of Things has begun to be introduced in the industry. Today's industry is rapidly changing and evolving, requiring companies to respond to the new paradigm of business. In this situation, companies need to actively manage and maintain customer relationships in order to acquire loyal customers who bring them a high return. The purpose of this study is to suggest a method to manage customer relationship using real time IoT data including IoT product usage data, customer characteristics and transaction data. This study proposes a method of segmenting customers through RFM analysis and transition index analysis. In addition, a real-time monitoring through control charts is used to identify abnormalities in product use and suggest ways of differentiating marketing for each group. In the study, 44 samples were classified as 9 churn customers, 10 potential customers, and 25 active customers. This study suggested ways to induce active customers by providing after-sales benefit for product reuse to a group of churn customers and to promote the advantages or necessity of using the product by setting the goal of increasing the frequency of use to a group of potential customers. Finally, since the active customer group is a loyal customer, this study proposed an one-on-one marketing to improve product satisfaction.

• Journal of Technology Innovation
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• v.16 no.2
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• pp.65-94
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• 2008

There has been rapid diffusion of digital innovation technology(DIT) such as 3 D CAD, CAE, simulation software which enable firms to see the future results of intended product designs through 3 D diagram and simulated results. This technology helps firms to reduce trial and error process by solving later stage problems in earlier stages. The DIT being the technology reflecting the real world, as a tool representing the simplified form of the real world, the degree of reflecting the real world(fidelity) is important in utilizing the DIT. This study is an exploratory research examining the process of reviewing the fidelity of the DITs and developing the complementary process necessary for utilizing the DIT with 'not good enough' fidelity. This study could draw out, from its case study, an exploratory hypothesis about the process of developing the complementary process. In the process, there is an analysis of the corresponding relationship between the actual data and the output data of the DIT, e.g. simulated result. Then the input data or output data are adjusted on the basis of the analysis of the corresponding relationship so that the discrepancy between the actual data and the expected interpretation of the output data, through the adjustment, of the DIT, can be reduced. This process is sometimes accompanied by the process of generating experimental data, which reflect the unique situation of the product development process of a company, to be put to the data base of DIT. The complementary process is the process requiring knowledge sharing and adjustment activities across different divisions. This study draw outs implications for effective management of the fidelity of DIT tools.

• Journal of Distribution Science
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• v.17 no.10
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• pp.17-26
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• 2019

Purpose - This research investigates the old marketing mix approach to satisfaction and loyalty from the perspective of research subjects of Samsung brand smartphone cases through empirical testing involving product quality, price, distribution channel variables as antecedent variables. Research design, data, and methodology - This study emphasizes the empirical/quantitative concept by using a survey as a data collection tool. The number of samples used was 179 eligible respondents who used Samsung smartphone devices for more than five years. Statistical testing tools use PLS with several testing stages such as the classical assumption test to the hypothesis testing stage. Results - The nine hypotheses proposed, as many as two hypotheses were proposed, namely intervening relationships involving Price and Distribution channel variables on customer satisfaction and customer loyalty. Conclusions - Product quality is the essential component affecting customer satisfaction and loyalty while distribution channel is a complementary component that is no less important to measure the extent to which customer satisfaction expectations and customer loyalty are realized for the product quality of the products that have been produced and marketed. The price component is not the only reason to make consumers satisfied and loyal.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.6
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• pp.543-553
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• 2008

Shipbuilding is a kind of ETO(Engineering To Order) industry which designs and produces a product in accordance to various requirement of customers, rules and regulations. Recently, the number of ordered ships has been increased by up to two or three times in each domestic shipyards. Most shipyards have been adopted 3D ship CAD, ERP(Enterprise Resource Planning) and APS(Advanced Planning System) to get an efficient product development and manufacturing system. However, not only the effective operation of 3D ship CAD, ERP and APS but also the production efficiency can be achieved only if product information management which can manages the product data is implemented in an integrated environment. Present study has suggested a systematic approach to implement a PLM system to manage the product data in early design shipbuilding. Also, a prototype of PLM is implemented to manage the product data in a basic ship-design. In the prototype system, a product structure and architecture of PLM is considered.

• The Korean Journal of Franchise Management
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• v.11 no.3
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• pp.7-18
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• 2020

Purpose: Recently, information on 'Delicious Restaurants (Mat-zip)' and 'Famous Bakeries' can be obtained through various media such as TV, Internet search, and SNS, and the culture of finding and sharing them has become a trend. Since PZB's SERVQUAL, there have been many studies measuring service quality, leading to hotels, restaurants and coffee shops. These studies of service quality include product quality in the service quality dimension. Hotels, restaurants, and coffee shops are provided with intangible services while customers visit and stay, but 'Delicious Restaurants (Mat-zip)' and 'Famous Bakeries' often stop by to buy products and return home. Therefore, the study on the effect of quality on customer behavior on 'Delicious Restaurants (Mat-zip)' should consider product quality separately. In this study, we want to study how each quality element affects the perceived value and response of customers by separating product quality and service quality. Research design, data, and methodology: This study tested the structural model of how the quality of products and services of famous bakeries affect customers' perceived value and response. As the quality factors, products, tangible services, and employee services were adopted, and perceived values adopted utilitarian and hedonic values, and customer responses adopted customer satisfaction and behavior intention. For this study, 203 survey data with experience using famous bakeries were analyzed using SPSS 22.0 and AMOS 22.0. Result: The research results are as follows. First, product quality positively influenced utilitarian value, hedonic value, and customer satisfaction, tangible service quality positively influenced utilitarian value, and employee service quality positively influenced hedonic value. Second, utilitarian value had a positive effect on behavioral intention, and hedonic value had a positive effect on customer satisfaction. Conclusions: In a famous bakery, it is basic that product quality should be given priority, and for customer satisfaction, employee service quality is half as important. In addition, for Behavior Intension (revisit by the customer), in addition to product quality, the quality of tangible services and employee services should be maintained at a quarter level.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.857-862
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• 2005

MND(Ministry of National Defense) has developed MND AF(Ministry of National Defense Architecture Framework) and CADM(Core Architecture Data Model to guarantee interoperability among defense information systems. But, it is very difficult to manage architecture product documented through MND AF and CADM. So, there Is necessity for development of modeling tool and repository system which can develop architecture products and manage architecture product informations in common repository In this paper, we developed architecture product management system which supports development and management of meta model and architecture product of MND AF and CADM. Through architecture product management system architect of each agency can construct architecture product in a more effective and efficient way with modeling method and a user can search and refer useful architecture product informations using query function. Also, architecture product management system provides the basis for system integration and interoperability with integration, analysis and comparison of architecture product.

• Korean Management Science Review
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• v.19 no.1
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• pp.189-196
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• 2002

Data clustering is often one of the first steps in data mining analysis. It Identifies groups of related objects that can be used as a starling point for exploring further relationships. This technique supports the development of population segmentation models, such as demographic-based customer segmentation. This paper Purpose to present the development of two phase hierarchical clustering algorithm for group formation. Applications of the algorithm for product-customer group formation in customer relationahip management are also discussed. As a result of computer simulations, suggested algorithm outperforms single link method and k-means clustering.

• Information Systems Review
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• v.23 no.1
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• pp.155-172
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• 2021

With the recent increase in online product purchases, a recommender system that recommends products considering users' preferences has still been studied. The recommender system provides personalized product recommendation services to users. Collaborative Filtering (CF) using user ratings on products is one of the most widely used recommendation algorithms. During CF, the item-based method identifies the user's product by using ratings left on the product purchased by the user and obtains the similarity between the purchased product and the unpurchased product. CF takes a lot of time to calculate the similarity between products. In particular, it takes more time when using text-based big data such as review data of Amazon store. This paper suggests a hybrid recommendation system using a 2-phase methodology and text data mining to calculate the similarity between products easily and quickly. To this end, we collected about 980,000 online consumer ratings and review data from the online commerce store, Amazon Kinder Store. As a result of several experiments, it was confirmed that the suggested hybrid recommendation system reflecting the user's rating and review data has resulted in similar recommendation time, but higher accuracy compared to the CF-based benchmark recommender systems. Therefore, the suggested system is expected to increase the user's satisfaction and increase its sales.

• Asia Pacific Journal of Business Review
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• v.1 no.1
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• pp.1-22
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• 2016

The prediction of prices of agricultural products in the agriculture IT sector plays a significant role in the economic life of consumers and anyone engaged in agricultural business, and as these prices fluctuate more often than do other prices, the prediction of these prices holds a great deal of research promise. For this reason, academic literature has provided studies on the factors influencing the prices of agricultural products and the price index. However, as these factors vary, they are difficult to predict, resulting in the challenge of acquiring quantitative data. China is one example of a country without a reliable prediction system for prices of agricultural products. Fortunately, disclosed heterogeneous data can be found on the Internet, which allows for the effective collection of factors related to the prediction of these product prices through the use of text mining. The data provided online is valuable in that they reflect the opinions of the general public in real-time. Accordingly, this study aims to use heterogeneous data from the Internet and suggest a model predicting the prices of agricultural products before functional analyses. Toward this end, data analyses were conducted on the Chinese agricultural products market, one of the largest markets in the world.