• Journal of Korean Society for Quality Management
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• v.40 no.2
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• pp.145-155
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• 2012

The purpose of this study is to suggest the direction of improving service quality in the defense logistics support. For this, this study compares and analyzes the perceived service quality between customer(using unit) and defense logistics support unit by using SERVPERF model. Supply, military meals, and maintenance are carrying out the mission as core function of defense logistics support and also encounter with customer. In this empirical analysis, the service quality is composed of four factors, and there are significant difference in perception level of service quality between them. Also, the relationship between factors of service quality and revisit intention shows significant difference statistically, and the customer orientation and responsiveness are key affecting factors on revisit intention.

• Asia pacific journal of information systems
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• v.20 no.2
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• pp.23-37
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• 2010

Conventional Support Vector Machines (SVMs) have been utilized as classifiers for binary classification problems. However, certain real world problems, including corporate bond rating, cannot be addressed by binary classifiers because these are multi-class problems. For this reason, numerous studies have attempted to transform the original SVM into a multiclass classifier. These studies, however, have only considered nominal classification problems. Thus, these approaches have been limited by the existence of multiclass classification problems where classes are not nominal but ordinal in real world, such as corporate bond rating and multiclass customer classification. In this study, we adopt a novel multiclass SVM which can address ordinal classification problems using ordinal pairwise partitioning (OPP). The proposed model in our study may use fewer classifiers, but it classifies more accurately because it considers the characteristics of the order of the classes. Although it can be applied to all kinds of ordinal multiclass classification problems, most prior studies have applied it to finance area like bond rating. Thus, this study applies it to a real world customer level classification case for implementing customer relationship management. The result shows that the ordinal multiclass SVM model may also be effective for customer level classification.

• Proceedings of the Korean Reliability Society Conference
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• 2001.06a
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• pp.277-278
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• 2001

The successful operation of a product In service depends upon the effective provision of logistic support in order to achieve and maintain the required levels of performance and customer satisfaction. Logistic support encompasses the activities and facilities required to maintain a product (hardware and software) in service. Logistic support covers maintenance, manpower and personnel, training, spares, technical documentation and packaging handling, storage and transportation and support facilities.The cost of logistic support is often a major contributor to the Life Cycle Cost (LCC) of a product and increasingly customers are making purchase decisions based on lifecycle cost rather than initial purchase price alone. Logistic support considerations can therefore have a major impact on product sales by ensuring that the product can be easily maintained at a reasonable cost and that all the necessary facilities have been provided to fully support the product in the field so that it meets the required availability. Quantification of support costs allows the manufacturer to estimate the support cost elements and evaluate possible warranty costs. This reduces risk and allows support costs to be set at competitive rates.Integrated Logistic Support (ILS) is a management method by which all the logistic support services required by a customer can be brought together in a structured way and In harmony with a product. In essence the application of ILS:- causes logistic support considerations to be integrated into product design;- develops logistic support arrangements that are consistently related to the design and to each other;- provides the necessary logistic support at the beginning and during customer use at optimum cost.The method by which ILS achieves much of the above is through the application of Logistic Support Analysis (LSA). This is a series of support analysis tasks that are performed throughout the design process in order to ensure that the product can be supported efficiently In accordance with the requirements of the customer.The successful application of ILS will result in a number of customer and supplier benefits. These should include some or all of the following:- greater product uptime;- fewer product modifications due to supportability deficiencies and hence less supplier rework;- better adherence to production schedules in process plants through reduced maintenance, better support;- lower supplier product costs;- Bower customer support costs;- better visibility of support costs;- reduced product LCC;- a better and more saleable product;- Improved safety;- increased overall customer satisfaction;- increased product purchases;- potential for purchase or upgrade of the product sooner through customer savings on support of current product.ILS should be an integral part of the total management process with an on-going improvement activity using monitoring of achieved performance to tailor existing support and influence future design activities. For many years, ILS was predominantly applied to military procurement, primarily using standards generated by the US Government Department of Defense (DoD). The military standards refer to specialized government infrastructures and are too complex for commercial application. The methods and benefits of ILS, however, have potential for much wider application in commercial and civilian use. The concept of ILS is simple and depends on a structured procedure that assures that logistic aspects are fully considered throughout the design and development phases of a product, in close cooperation with the designers. The ability to effectively support the product is given equal weight to performance and is fully considered in relation to its cost.The application of ILS provides improvements in availability, maintenance support and longterm 3ogistic cost savings. Logistic costs are significant through the life of a system and can often amount to many times the initial purchase cost of the system.This study provides guidance on the minimum activities necessary to Implement effective ILS for a wide range of commercial suppliers. The guide supplements IEC60106-4, Guide on maintainability of equipment Part 4: Section Eight maintenance and maintenance support planning, which emphasizes the maintenance aspects of the support requirements and refers to other existing standards where appropriate. The use of Reliability and Maintainability studies is also mentioned in this study, as R&M is an important interface area to ILS.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.181-195
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• 2010

This study intends to find the empirical relationship between influential factors of CRM realization and performance. The purpose of this study is to analyze effect of managerial support factors on customer orientation, work performance, and customer performance in the banking institutions. First, it is analyzed to find what kind of effects the major factor of CRM system may have on customer orientation. Then, the impacts of the customer orientation on the performance are to be analyzed. Lastly, it is analyzed that the work performance affects the customer performance.

• IE interfaces
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• v.18 no.3
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• pp.317-326
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• 2005

Staff scheduling is an important area, both from an academic and industrial point of view. It has become increasingly important as business becomes more service oriented and cost conscious in a global environment. There has been a lot of study to develop new and efficient staff scheduling models and methods. The purpose of this paper is not to develop new theoretical results but to develop a comprehensive user-friendly staffing model that can be applied to the real-world practice. The developed staffing software, OptStaff, provides the optimal configuration of the customer support center including the selection of customer support center locations, the allocation of staffs to each selected location, and schedules of staffs, so as to minimize the total cost while maximizing the customer satisfaction level. OptStaff also has capability to do scenario analysis by varying the levels of parameters and to create a variety of graphs and reports with user-friendly interfaces.

• The Journal of Industrial Distribution & Business
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• v.10 no.2
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• pp.39-49
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• 2019

Purpose - Customer loyalty and citizenship behavior are key success factors of franchise system. They make the management of franchisee more effective and efficient. Prior studies, however, mainly dealt with only acquisition utility of customer, such as perceived product/service quality and brand reputation to explain customer loyalty and citizenship behavior, which explains only on one side. We tried to investigate the effect of exchange utility of customer, such as relationship strength and psychological obligation together with the acquisition utility. In addition, we tried to investigate the relationship between customer loyalty and citizenship behavior in franchise context. Research design, data, and methodology - This study used data collected from the dining franchisee managers of 342 franchisors in South Korea. The franchisors consist of more than ten franchisees, the majority of which participated directly in the transaction with franchisor and have worked for more than six months. To test the hypotheses, the study used structural equation model analysis. Results - H1-1, 1-2, 1-3 predicted that acquisition utility would increase customer loyalty to franchisee. In support of H1-1, 1-2, 1-3, the results indicated that acquisition utilities such as perceived product value, perceived service value, and franchise brand reputation had positive effects on customer loyalty. H2-1, 2-2 predicted that exchange utility would increase customer loyalty to franchisee. In support of H2-2, the result indicated that psychological obligation had positive effects on customer loyalty like other acquisition utilities. However, H2-1 was not supported. Relationship strength had no significant effect on customer loyalty. H3 predicted that customer loyalty would increase customer citizenship behavior. In support of H3, the results indicated that customer loyalty had positive effect on customer citizenship behavior. Overall, the evidences generally supported the hypotheses. Conclusion - The results of the study show that not only acquisition utility but also exchange utility increases customer loyalty to franchisee and also show that customer loyalty increases customer citizenship behavior. Interestingly, however, relationship strength has no significant effect on customer loyalty. These results have two implications. The one is that increasing exchange utility can improve customer loyalty as acquisition utility can. The other one is that both of customer utilities can improve customer citizenship via customer loyalty.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.26-32
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• 2020

There are many airline customer evaluation data, but they are insufficient in terms of predicting customer satisfaction in practice. In particular, they are generally insufficient in case of verification of data value and development of a customer satisfaction prediction model based on customer evaluation data. In this paper, airline customer satisfaction analysis is conducted through an experiment of correlation analysis between customer evaluation data provided by Google's Kaggle. The difference in accuracy varied according to the three types, which are the overall variables, the top 4 and top 8 variables with the highest correlation. To build an airline customer satisfaction prediction model, they are applied to three classification algorithms of Random Forest, SVM, DNN and conduct a classification experiment. They are divided into training data and verification data by 7:3. As a result, the DNN model showed the lowest accuracy at 86.4%, while the SVM model at 89% and the Random Forest model at 95.7% showed the highest accuracy and performance.

• Information Systems Review
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• v.4 no.1
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• pp.33-45
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• 2002

With the advance of information technology, it is possible to build the interactive communication channel among relationship participants with low cost, and this channel makes ties between consumers and company by enabling information sharing and exchange. In order to maintain customer relationship, it is necessary to support customer information that includes of-the-customer, for-the-customer, and by-the-customer information. From the three types of customer information, the proper information for the relationship management like the level and type of commitment can be extracted. Customer Information System (CIS), which includes database, communication channel, application program, should be designed to facilitate the customer relationship management. Since lots of investments to information system are required, it is not easy to implement. This paper develops a framework of dynamic customer relationship management and suggests an effective information technology strategy to support that.

• The Journal of Information Systems
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• v.26 no.4
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• pp.17-37
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• 2017

Purpose Customer Loyalty is the most important factor of customer relationship management (CRM). Especially in retailing industry, where customers have many options of where to spend their money. Classifying loyal customers through customers' data can help retailing companies build more efficient marketing strategies and gain competitive advantages. This study aims to construct classification models of distinguishing the loyal customers within a Korean retailing company using data mining techniques with R language. Design/methodology/approach In order to classify retailing customers, we used combination of support vector machines (SVMs) and other classification algorithms of machine learning (ML) with the support of recursive feature elimination (RFE). In particular, we first clean the dataset to remove outlier and impute the missing value. Then we used a RFE framework for electing most significant predictors. Finally, we construct models with classification algorithms, tune the best parameters and compare the performances among them. Findings The results reveal that ML classification techniques can work well with CRM data in Korean retailing industry. Moreover, customer loyalty is impacted by not only unique factor such as net promoter score but also other purchase habits such as expensive goods preferring or multi-branch visiting and so on. We also prove that with retailing customer's dataset the model constructed by SVMs algorithm has given better performance than others. We expect that the models in this study can be used by other retailing companies to classify their customers, then they can focus on giving services to these potential vip group. We also hope that the results of this ML algorithm using R language could be useful to other researchers for selecting appropriate ML algorithms.

• Journal of Korea Port Economic Association
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• v.25 no.4
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• pp.225-250
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• 2009

The purpose of this paper is to clarify the movement of customer satisfaction factor of port like marketing and customer support factors and set up new strategy for customer satisfaction with the factors of control by Port Authority. It was researched to Terminal operation and shipping companies of main clients of Container Terminals of Busan Port. The Score of customer satisfaction is 4.62, it is almost average score to consider Likert Scale 7 for Research measurement. For Customer satisfaction measurement score, the factor is named Port Facility, Port Cost, Marketing Activity and Customer Support with 20 elements. It is verified suitable model by Structural Equation Method. It is effect customer satisfaction by Marketing Activity and Customer Support factor instead of Port Facility and Port Cost. So Port Authority has to plan new strategy for customer satisfaction to consider its effect factors.