• Title/Summary/Keyword: Customer performance

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An Exploratory Analysis of IT Implementation: A Case Study of Construction Companies (건설기업 정보화 추진 방안: 대형 건설사 사례를 중심으로)

  • Han, Jeong-Sook;Kim, Young-Shin;Lee, Seung-Chan
    • Information Systems Review
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    • v.6 no.2
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    • pp.209-225
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    • 2004
  • This study shows the field of construction which was less developed in the aspect of information system in comparison to other areas needs to introduce construction information system and suggests it can make more value linked with company performance through the system. For the first step, it emphasizes the integrated enterprise approach not optimization of each sector in a company. This paper extracts the current issues of construction information from the core process of construction area and implies a driving plan and the future development plan for construction information. Antecedent studies for this drew the information structure model and the construction information-driving model of a construction company. Hence, case studies with management companies that implemented the construction information system successfully tested validity. This research brings the cases of PMS, the integrated finance system, and CRM system as successful ones.

A Framework for Success of Industrial Clusters: The Fusion of Online and Offline Businesses (온라인과 오프라인이 융합된 성공적 산업클러스터의 프레임워크)

  • Yi Jung-Sub;Jang Hyeong-Wook
    • Journal of Korea Society of Industrial Information Systems
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    • v.11 no.3
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    • pp.96-107
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    • 2006
  • This paper explores the benefits provided by the adoption and implementation of electronic commerce in a particular SME-intensive productive environment: the geographical cluster. This study develops a conceptual framework that highlights the six types of benefits obtained by integrating online business with offline business. Using data from 73 traditional companies in Korean port clusters, factor analysis was used to figure out six benefits including sharing information, cost savings, value-added service, customer relationship, enhanced trust, and marketing efficiency. The six empirically derived critical benefit factors were then used to examine how they improve management performance of the traditional offline companies in the cluster measured by Balanced Scorecard(BSC). According to the results, we concluded that the offline firms in the cluster can take advantages of extending to online business.

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State Transition Diagram을 이용한 신규 정보통신 서비스의 대체/보완관계 분석: 와이브로(WiBro) 서비스를 중심으로

  • An Jae-Hyeon;Kim Mun-Gu;Han Sang-Pil;Park Bong-Won;Lee Sang-Yun;Bang Yeong-Seok
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.10a
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    • pp.304-316
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    • 2004
  • When new services are introduced, one of the drivers for market performance of them is the interactions among existing and new services. They are characterized by the substitution or complementary effects among existing and new service or the cannibalization of existing services by new services. This paper analyzes these issues in the telecommunications service industry context. To analyze them, a simple graphical tool or State Transition Diagram(STD) is developed and used. The diagram helps to clearly represent and explain the substitution, complement and cannibalization impact. Then, using the face-to-face survey of 1,200 people, a new wireless internet access service or WiBro is analyzed to identify the substitution/complement and cannibalization impacts in relation with the other competing services. Additionally, the important factors explaining customer subscription and substitution behavior are identified. The analysis results indicate that males, students or on-line game users are more likely to subscribe WiBro. Also, among the potential WiBro subscribers, customers who are less satisfied with the existing fixed line broadband internet access services are more likely to stop subscribing the fixed line service, which implies substitution by a new service. Additionally, this raises the issue of cannibalization if the existing and new services are provided by the same company. In fact we find the cannibalization effect is more serious for the cost sensitive group. We believe that our tool, approach, analysis results and their implications would be very helpful to devise a winning strategy for the new services in the highly uncertain telecommunications business environment.

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A Study on the Evaluation of the Work-Net, a Web-based Public Employment Information System (웹 기반 공공고용정보시스템 워크넷(Work-Net)평가에 관한 연구)

  • Kim, Soon-Won
    • Journal of the Korean Society for information Management
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    • v.20 no.2
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    • pp.93-112
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    • 2003
  • A public information system is being expanded, along with the advance of information technology, to strengthen national competitiveness and provide people with better services. And there also is a growin need for the better performance of that system, as a tremendous amount of public financial resources is invested in that. To address that need, it's required to make an evaluation of its efficiency on a regular basis to identify its problems and make it work better. The purpose of this study was, accordinglu, to examine the quality of data and services provided by the Work-Net, a Web-based public employment information system. The subjects in this study were 102 users of it, and the system was evaluated in terms of content, accuracy, timeliness, display format, ease of use and customer support. For data analysis, t-test and one-way ANOVA were implemented to find out the general characteristics of the users, and to see Whether or not their view was different according to the type of information they searched for. The findings of this study are expected to lay some foundation for intensifying the efficiency of the public and private employment information systems.

A Study on Improvement of the Logistic System in Social Commerce using Simulation (시뮬레이션을 활용한 소셜커머스의 물류시스템 개선방안 연구)

  • Gu, Seung-Hwan;Noh, Seung-Min;Jang, Seong-Yong
    • Journal of the Korea Society for Simulation
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    • v.22 no.3
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    • pp.25-33
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    • 2013
  • The research focuses on the method to improve the Logistics considering investigating the present state of the fast growing social commerce. The improving Logistics is the jointed transport system, which proposes the concept of the packaged delivery for customers in same area and the condition-specific benefits as the transport cost and delay period. Customers in this system will obtain the advantage as the decrease of transport cost and social commerce companies will make the effect about growing the number of customer and the sales by the lowest price in the online markets. There are 7 scenarios for simulation. The performance assessment of the results from simulation is carried out by total number of orders, finished number of orders, sales, delivery times, delivery cost, earlier rate of delivery, and fluctuation of number of wrong delivery. The results of the research show that the total number of orders, finished number of orders and sales are increased, while the times and cost of delivery are decreased.

Practical Intelligent Cleaning Robot Algorithm Based on Grouping in Complex Layout Space (복잡한 공간에서 그룹화 기반의 실용적 지능형 청소 로봇 알고리즘)

  • Jo Jae-Wook;Noh Sam-H.;Jeon Heung-Seok
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.5
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    • pp.489-496
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    • 2006
  • The random-based cleaning algorithm is a simple algorithm widely used in commercial vacuum cleaning robots. This algorithm has two limitations, that is, cleaning takes a long time and there is no guarantee that the cleaning will cover the whole cleaning area. This has lead to customer dissatisfaction. Thus, in recent years, many intelligent cleaning algorithms that takes into consideration information gathered from the cleaning area environment have been proposed. The plowing-based algorithm, which is the most efficient algorithm known to date when there are no obstacles in the cleaning area, has a deficiency that when obstacle prevail, its performance is not guaranteed. In this paper, we propose the Group-k algorithm that is efficient for that situation, that is, when obstacle prevail. The goal is not to complete the cleaning as soon as possible, but to clean the majority of the cleaning area as fast as possible. The motivation behind this is that areas close to obstacles are usually difficult for robots to handle, and hence, many require human assistance anyway In our approach, obstacles are grouped by the complexity of the obstacles, which we refer to as 'complex rank', and then decide the cleaning route based on this complex rank. Results from our simulation-based experiments show that although the cleaning completion time takes longer than the plowing-based algorithm, the Group-k algorithm cleans the majority of the cleaning area faster than the plowing algorithm.

Collaborative Filtering for Credit Card Recommendation based on Multiple User Profiles (신용카드 추천을 위한 다중 프로파일 기반 협업필터링)

  • Lee, Won Cheol;Yoon, Hyoup Sang;Jeong, Seok Bong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.4
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    • pp.154-163
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    • 2017
  • Collaborative filtering, one of the most widely used techniques to build recommender systems, is based on the idea that users with similar preferences can help one another find useful items. Credit card user behavior analytics show that most customers hold three or less credit cards without duplicates. This behavior is one of the most influential factors to data sparsity. The 'cold-start' problem caused by data sparsity prevents recommender system from providing recommendation properly in the personalized credit card recommendation scenario. We propose a personalized credit card recommender system to address the cold-start problem, using multiple user profiles. The proposed system consists of a training process and an application process using five user profiles. In the training process, the five user profiles are transformed to five user networks based on the cosine similarity, and an integrated user network is derived by weighted sum of each user network. The application process selects k-nearest neighbors (users) from the integrated user network derived in the training process, and recommends three of the most frequently used credit card by the k-nearest neighbors. In order to demonstrate the performance of the proposed system, we conducted experiments with real credit card user data and calculated the F1 Values. The F1 value of the proposed system was compared with that of the existing recommendation techniques. The results show that the proposed system provides better recommendation than the existing techniques. This paper not only contributes to solving the cold start problem that may occur in the personalized credit card recommendation scenario, but also is expected for financial companies to improve customer satisfactions and increase corporate profits by providing recommendation properly.

Analysis of User Requirements Prioritization Using Text Mining : Focused on Online Game (텍스트마이닝을 활용한 사용자 요구사항 우선순위 도출 방법론 : 온라인 게임을 중심으로)

  • Jeong, Mi Yeon;Heo, Sun-Woo;Baek, Dong Hyun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.43 no.3
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    • pp.112-121
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    • 2020
  • Recently, as the internet usage is increasing, accordingly generated text data is also increasing. Because this text data on the internet includes users' comments, the text data on the Internet can help you get users' opinion more efficiently and effectively. The topic of text mining has been actively studied recently, but it primarily focuses on either the content analysis or various improving techniques mostly for the performance of target mining algorithms. The objective of this study is to propose a novel method of analyzing the user's requirements by utilizing the text-mining technique. To complement the existing survey techniques, this study seeks to present priorities together with efficient extraction of customer requirements from the text data. This study seeks to identify users' requirements, derive the priorities of requirements, and identify the detailed causes of high-priority requirements. The implications of this study are as follows. First, this study tried to overcome the limitations of traditional investigations such as surveys and VOCs through text mining of online text data. Second, decision makers can derive users' requirements and prioritize without having to analyze numerous text data manually. Third, user priorities can be derived on a quantitative basis.

Building credit scoring models with various types of target variables (목표변수의 형태에 따른 신용평점 모형 구축)

  • Woo, Hyun Seok;Lee, Seok Hyung;Cho, HyungJun
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.1
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    • pp.85-94
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    • 2013
  • As the financial market becomes larger, the loss increases due to the failure of the credit risk managements from the poor management of the customer information or poor decision-making. Thus, the credit risk management also becomes more important and it is essential to develop a credit scoring model, which is a fundamental tool used to minimize the credit risk. Credit scoring models have been studied and developed only for binary target variables. In this paper, we consider other types of target variables such as ordinal multinomial data or longitudinal binary data and suggest credit scoring models. We then apply our developed models to real data and random data, and investigate their performance through Kolmogorov-Smirnov statistic.

Extended Information Entropy via Correlation for Autonomous Attribute Reduction of BigData (빅 데이터의 자율 속성 감축을 위한 확장된 정보 엔트로피 기반 상관척도)

  • Park, In-Kyu
    • Journal of Korea Game Society
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    • v.18 no.1
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    • pp.105-114
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    • 2018
  • Various data analysis methods used for customer type analysis are very important for game companies to understand their type and characteristics in an attempt to plan customized content for our customers and to provide more convenient services. In this paper, we propose a k-mode cluster analysis algorithm that uses information uncertainty by extending information entropy to reduce information loss. Therefore, the measurement of the similarity of attributes is considered in two aspects. One is to measure the uncertainty between each attribute on the center of each partition and the other is to measure the uncertainty about the probability distribution of the uncertainty of each property. In particular, the uncertainty in attributes is taken into account in the non-probabilistic and probabilistic scales because the entropy of the attribute is transformed into probabilistic information to measure the uncertainty. The accuracy of the algorithm is observable to the result of cluster analysis based on the optimal initial value through extensive performance analysis and various indexes.