• Title/Summary/Keyword: Customer Knowledge Management

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A Case Study on Forecasting Inbound Calls of Motor Insurance Company Using Interactive Data Mining Technique (대화식 데이터 마이닝 기법을 활용한 자동차 보험사의 인입 콜량 예측 사례)

  • Baek, Woong;Kim, Nam-Gyu
    • Journal of Intelligence and Information Systems
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    • v.16 no.3
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    • pp.99-120
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    • 2010
  • Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.

A PageRank based Data Indexing Method for Designing Natural Language Interface to CRM Databases (분석 CRM 실무자의 자연어 질의 처리를 위한 기업 데이터베이스 구성요소 인덱싱 방법론)

  • Park, Sung-Hyuk;Hwang, Kyeong-Seo;Lee, Dong-Won
    • CRM연구
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    • v.2 no.2
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    • pp.53-70
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    • 2009
  • Understanding consumer behavior based on the analysis of the customer data is one essential part of analytic CRM. To do this, the analytic skills for data extraction and data processing are required to users. As a user has various kinds of questions for the consumer data analysis, the user should use database language such as SQL. However, for the firm's user, to generate SQL statements is not easy because the accuracy of the query result is hugely influenced by the knowledge of work-site operation and the firm's database. This paper proposes a natural language based database search framework finding relevant database elements. Specifically, we describe how our TableRank method can understand the user's natural query language and provide proper relations and attributes of data records to the user. Through several experiments, it is supported that the TableRank provides accurate database elements related to the user's natural query. We also show that the close distance among relations in the database represents the high data connectivity which guarantees matching with a search query from a user.

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Hand Biometric Information Recognition System of Mobile Phone Image for Mobile Security (모바일 보안을 위한 모바일 폰 영상의 손 생체 정보 인식 시스템)

  • Hong, Kyungho;Jung, Eunhwa
    • Journal of Digital Convergence
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    • v.12 no.4
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    • pp.319-326
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    • 2014
  • According to the increasing mobile security users who have experienced authentication failure by forgetting passwords, user names, or a response to a knowledge-based question have preference for biological information such as hand geometry, fingerprints, voice in personal identification and authentication. Therefore biometric verification of personal identification and authentication for mobile security provides assurance to both the customer and the seller in the internet. Our study focuses on human hand biometric information recognition system for personal identification and personal Authentication, including its shape, palm features and the lengths and widths of the fingers taken from mobile phone photographs such as iPhone4 and galaxy s2. Our hand biometric information recognition system consists of six steps processing: image acquisition, preprocessing, removing noises, extracting standard hand feature extraction, individual feature pattern extraction, hand biometric information recognition for personal identification and authentication from input images. The validity of the proposed system from mobile phone image is demonstrated through 93.5% of the sucessful recognition rate for 250 experimental data of hand shape images and palm information images from 50 subjects.

Collaboration Framework based on Social Semantic Web for Cloud Systems (클라우드 시스템에서 소셜 시멘틱 웹 기반 협력 프레임 워크)

  • Mateo, Romeo Mark A.;Yang, Hyun-Ho;Lee, Jae-Wan
    • Journal of Internet Computing and Services
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    • v.13 no.1
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    • pp.65-74
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    • 2012
  • Cloud services are used for improving business. Moreover, customer relationship management(CRM) approaches use social networking as tools to enhance services to customers. However, most cloud systems do not support the semantic structures, and because of this, vital information from social network sites is still hard to process and use for business strategy. This paper proposes a collaboration framework based on social semantic web for cloud system. The proposed framework consists of components to support social semantic web to provide an efficient collaboration system for cloud consumers and service providers. The knowledge acquisition module extracts rules from data gathered by social agents and these rules are used for collaboration and business strategy. This paper showed the implementations of processing of social network site data in the proposed semantic model and pattern extraction which was used for the virtual grouping of cloud service providers for efficient collaboration.

Case Study on Dynamics of RDA PLA Model with Agri-SMEs (농업인 참여식 실천학습모델 개발과 성과분석 -농촌진흥청 강소농 사업을 중심으로-)

  • Kim, Sa Gyun;Lee, Mi Hwa;Park, Heun Dong
    • Journal of Agricultural Extension & Community Development
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    • v.19 no.3
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    • pp.551-579
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    • 2012
  • This case study aims to explore how RDA PLA model affects the agri-SMEs' empowerment. As an agri-business management renovation program from main workshop it was conducted on March to December 2011 with agri-SMEs and extension officials nationwide by RDA. Especially, as a packaged action learning process in the model used participatory action research. This study collected data with participants observation, interviews, situational analysis and systematic review of discourse in qualitative method. For the validity and identifying empirical results, this study used statistic analysis as a mixed method. Further including various pedagogic methods and business coaching skills, this model was conducted from workshop in RDA, in turn, on-farm business coaching as follow-up, CoPs' activities, and local ATCs extension services by each actors. The dynamic process and effects of each process led some change for farmers' innovative knowledge, skills, attitude, practice and aspiration on their farm business. RDA PLA model development based on the previous practices and research, which provided a configurated picture in the holistic action learning process. In statistic research, this study focused on 279 farmers as respondents who had participated in the program. It shows that their income and benefits increased from their renovative practices on farm business. Following the sampling group, it was surveyed by four indicators - products, customer, quality and cost. The level of contribution of education on economic impact 15% is quoted from previous paper. Even in some limitations of public sector, RDA PLA model actively suggests the paradigm shift of agricultural HRD and development of alternative extension-service system.

A Study on Possible Construction of Big Data Analysis System Applied to the Offline Market (오프라인 마켓에 적용 가능한 빅데이터 분석 시스템 구축 방안에 관한 연구)

  • Lee, Hoo-Young;Park, Koo-Rack;Kim, Dong-Hyun
    • Journal of Digital Convergence
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    • v.14 no.9
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    • pp.317-323
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    • 2016
  • Big Data is now seen as a major asset in the company's competitiveness, its influence in the future is expected to grow. Companies that recognize the importance are already actively engaged with Big Data in product development and marketing, which are increasingly applied across sectors of society, including politics, sports. However, lack of knowledge of the system implementation and high costs are still a big obstacles to the introduction of Big Data and systems. It is an objective in this study to build a Big Data system, which is based on open source Hadoop and Hive among Big Data systems, utilizing POS sales data of small and medium-sized offline markets. This approach of convergence is expected to improve existing sales systems that have been simply focusing on profit and loss analysis. It will also be able to use it as the basis for the decisions of the executive to enable prediction of the consumption patterns of customer preference and demand in advance.

Developing the Linkage System Between Statistical Quality Control and ISO 9000 Series (통계적 품질관리와 ISO 9000 시리즈와의 연결시스템 개발)

  • 김형준;오성균
    • Journal of the Korea Society of Computer and Information
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    • v.3 no.4
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    • pp.174-192
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    • 1998
  • These day in the Quality Assurance System, it required that computer system is able to utilize SQC and ISO 9000 series, just then. However. because SQC is necessary to special branch of statistical experience, it is very hard to use and have a bound in that apply to practical business. Therefor in this paper, we proposed the software system which is control, at the same time, SQC and ISO 9000 series, in addition to avail without statistical knowledge. For the shake of this point, the substance of this study is largely separated dual part that ISO 9000 system for which is limited to use design of basic system, test, experiment, tracking incongruent part, analysis condemned goofs, and SQC system for which is to limited to use control chart, estimate, statistical testing, design of experiment(DOE) which used to commonly in Quality Control System. Expected efficiency of this paper is to set Qualify Management System, transfer qualify consciousness, satisfy the customer, increase reliability, in particular, it is expected that it is very useful to minor enterprises of manufacturing-centered.

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The Leadership of CEO and the Building up of Strategic Information Systems: THEFACESHOP Korea Case (CEO의 리더십과 전략적 정보화 시스템의 구축: 더페이스샵 코리아 사례를 중심으로)

  • Lee, Mi-Young;Park, Yang-Kyu;Kim, Woo-Bong;Ahn, Ji-Hyun
    • Information Systems Review
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    • v.11 no.2
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    • pp.183-207
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    • 2009
  • In general, the introduction of information technology to domestic small and middle size firms is depending on the governmental supporting policy. However, even under this situation there is also a case that the building up of information technology is initiated by the management of small and middle size firms. An accumulated know-how for information technology and powerful leadership in such firms are considered as success factors. This study attempts to analyze a case for 'THEFACESHOP', in which MIS is successfully built. To achieve corporate goals, the CEO of THEFACESHOP based on the extensive knowledge of information technology drove to build up information system. Also, the board of directors supported him, and employees committed to their organization. Through the strong leadership of the CEO, the information system of THEFACESHOP became sufficient and efficient. And it led the organization and the information system to be competitive. In particular, the systematic approach of THEF ACESHOP reinforcing its competitiveness can be summarized as follows: First, it tried to construct basic information systems as like ERP etc. to increase work-efficiency. Second, it completed CRM related systems for analysis to maximize its customer orientation and marketing effect. Third, the last step can be stated as the building up of operation related CRM systems to improve the responsiveness of target marketing activities and the profitability of its agencies. Such endeavors of THEFACESHOP contributed to increase productivity and performance of the organization. As a result, THEFACESHOP has had its own 'Natural Story' and price competitiveness. For that reason THEFACESHOP became the best of brand-shop cosmetic firms. This success based on the strong leadership and the systematic investment on the information system.

A Study on Philosophy-based Human Resource Model in the Service Economy Era (철학기반의 서비스경제시대 인재상 연구)

  • Kim, JeaYoung;Kim, Hyunsoo
    • Journal of Service Research and Studies
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    • v.10 no.3
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    • pp.119-138
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    • 2020
  • Unlike the era of manufacturing-oriented industrial economy in the past, the era of service economy has characteristics intangible goods center, knowledge universalization, and expansion of needs, and many things that are of the economy are changing. In the past, the change in the environment was not fast, so even after analyzing the changed environment and deriving the talent needed for the company, it was possible to maintain a talent for the organization for a long time, so it is not proactive to build and apply talent. It became difficult to manage effectively. Therefore, in this paper, we conducted a normative study for deriving a desirable talent model rather than a descriptive human resource model. Human resources image suitable for the modern service economy era, the modern economic society and modern spirit were analyzed and reflected. The model in which the two opposing members of the organization, managers and employees, interact intensely and balance dialectically. A desirable talent in a modern organization must play the role of a manager, and the management and talent models in a modern organization can be said to be connected to each other like the front and back sides of a coin. The philosophy of human resources was presented in five dimensions: human, historical, social, economic, and management. The human resource model from eight factors: mastery, rationality, wisdom, customer orientation, innovation, flexibility, autonomy, collaboration. This study suggested that general talent model may vary depending on the company's type, empirical follow-up studies are needed the talents in each company in the future.

The Effects of Virtual Reality Advertisement on Consumer's Intention to Purchase: Focused on Rational and Emotional Responses (가상현실(Virtual Reality) 광고가 소비자 구매의도에 미치는 영향: 이성적인 반응과 감성적인 반응의 통합)

  • Cha, Jae-Yol;Im, Kun-Shin
    • Asia pacific journal of information systems
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    • v.19 no.4
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    • pp.101-124
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    • 2009
  • According to Wikipedia, virtual reality (VR) is defined as a technology that allows a user to interact with a computer-simulated environment. Due to a rapid growth in information technology (IT), the cost of virtual reality has been decreasing while the utility of virtual reality advertisements has dramatically increased. Nevertheless, only a few studies have investigated the effects of virtual reality advertisement on consumer behaviors. Therefore, the objective of this study is to empirically examine the effects of virtual reality advertisement. Compared to traditional online advertisements, virtual reality advertisement enables consumers to experience products realistically over the Internet by providing high media richness, interactivity, and telepresence (Suh and Lee, 2005). Advertisements with high media richness facilitate consumers' understanding of advertised products by providing them with a large amount and a high variety of information on the products. Interactivity also provides consumers with a high level of control over the computer-simulated environment in terms of their abilities to adjust the information according to their individual interests and concerns and to be active rather than passive in their engagement with the information (Pimentel and Teixera, 1994). Through high media richness and interactivity, virtual reality advertisements can generate compelling feelings of "telepresence" (Suh and Lee, 2005). Telepresence is a sense of being there in an environment by means of a communication medium (Steuer, 1992). Virtual reality advertisements enable consumers to create a perceptual illusion of being present and highly engaged in a simulated environment, while they are in reality physically present in another place (Biocca, 1997). Based on the characteristics of virtual reality advertisements, a research model has been proposed to explain consumer responses to the virtual reality advertisements. The proposed model includes two dimensions of consumer responses. One dimension is consumers' rational response, which is based on the Information Processing Theory. Based on the Information Processing Theory, product knowledge and perceived risk are selected as antecedents of intention to purchase. The other dimension is emotional response of consumers, which is based on the Attitude-Structure Theory. Based on the Attitude-Structure Theory, arousal, flow, and positive affect are selected as antecedents of intention to purchase. Because it has been criticized to have investigated only one of the two dimensions of consumer response in prior studies, our research model has been built so as to incorporate both dimensions. Based on the Attitude-Structure Theory, we hypothesized the path of consumers' emotional responses to a virtual reality advertisement: (H1) Arousal by the virtual reality advertisement increases flow; (H2) Flow increases positive affect; and (H3) Positive affect increases intension to purchase. In addition, we hypothesized the path of consumers' rational responses to the virtual reality advertisement based on the Information Processing Theory: (H4) Increased product knowledge through the virtual reality advertisement decreases perceived risk; and (H5) Perceived risk decreases intension to purchase. Based on literature of flow, we additionally hypothesized the relationship between flow and product knowledge: (H6) Flow increases product knowledge. To test the hypotheses, we conducted a free simulation experiment [Fromkin and Streufert, 1976] with 300 people. Subjects were asked to use the virtual reality advertisement of a cellular phone on the Internet and then answer questions about the variables. To check whether subjects fully experienced the virtual reality advertisement, they were asked to answer a quiz about the virtual reality advertisement itself. Responses of 26 subjects were dropped because of their incomplete answers. Responses of 274 subjects were used to test the hypotheses. It was found that all of six hypotheses are accepted. In addition, we found that consumers' emotional response has stronger impact on their intention to purchase than their rational response does. This study sheds much light into practical implications for both IS researchers and managers. First of all, while most of previous research has analyzed only one of the customers' rational and emotional responses, we theoretically incorporated and empirically examined both of the two sides. Second, we empirically showed that mediators such as arousal, flow, positive affect, product knowledge, and perceived risk play an important role between virtual reality advertisement and customer's intention to purchase. In addition, the findings of this study can provide a basis of practical strategies for managers. It was found that consumers' emotional response is stronger than their rational response. This result indicates that advertisements using virtual reality should focus on the emotional side, and that virtual reality can be served as an appropriate advertisement tool for fancy products that require their online advertisements to give an impetus to customers' emotion. Finally, even if this study examined the effects of virtual reality advertisement of cellular phone, its findings could be applied to other products that are suited for virtual experience. However, this research has some limitations. We were unable to control different kinds of consumers and different attributes of products on consumers' intention to purchase. It is, therefore, deemed important for future research to control the consumer and product types for more reliable results. In addition to the consumer and product attributes, other variables could affect consumers' intention to purchase. Thus, the future research needs to find ways t control other variables.