• Title/Summary/Keyword: Data Value Chain

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Simulation Study of Two Supply Chain Collaboration Programs: Consignment and VMI

  • Ryu, Chung-Suk
    • Journal of Distribution Science
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    • v.14 no.4
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    • pp.21-31
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    • 2016
  • Purpose - This study examines how consignment and Vendor-Managed Inventory perform as supply chain collaboration programs. By using three key collaborative features, this study defines the collaboration programs and develops theoretical models of different supply chain systems. Research design, data and methodology - This study conducts sophisticated analysis on the supply chain systems by applying simulation modeling based on time-phased operations. The simulation model represents a two-stage supply chain system where a supplier sells a single item to a buyer, and it incorporates various operations. Results - In general, the simulation outcomes support that more advanced collaboration programs outperform less advanced ones. The analysis on the simulation outcomes identifies the significant value of information sharing in both collaboration programs. The specific conditions where the particular collaboration system outperforms the others are recognized. Conclusions - The outcome of this study supports that the supply chain system can improve its performance by having more collaborative features. This study provides business practitioners with guidelines to identify the circumstances that the specific collaboration program can fully exploit its advantages.

Prediction of extreme rainfall with a generalized extreme value distribution (일반화 극단 분포를 이용한 강우량 예측)

  • Sung, Yong Kyu;Sohn, Joong K.
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.4
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    • pp.857-865
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    • 2013
  • Extreme rainfall causes heavy losses in human life and properties. Hence many works have been done to predict extreme rainfall by using extreme value distributions. In this study, we use a generalized extreme value distribution to derive the posterior predictive density with hierarchical Bayesian approach based on the data of Seoul area from 1973 to 2010. It becomes clear that the probability of the extreme rainfall is increasing for last 20 years in Seoul area and the model proposed works relatively well for both point prediction and predictive interval approach.

A Study on the Effect of Win-win Growth Policies on Sustainable Supply Chain and Logistics Management in South Korea

  • KIM, Ki-Hyung;SONG, Sang Hwa
    • The Journal of Industrial Distribution & Business
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    • v.10 no.12
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    • pp.7-14
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    • 2019
  • Purpose: In Korea, win-win growth policy has been successfully implemented in supply chain and logistics management. In the policy, it is recommended to support supply chain partners with various mechanisms including financial and technical aids. This study attempts to scientifically analyze the effects of direct and indirect win-win growth policy factors on supply chain and logistics management performance through partnership factors. Research design, data and methodology: This study builds a structural equation model reflecting the relationship between the win-win growth policy, partnership and performance factors. The proposed model is verified with the PLS (Partial Least Squares regression) methodology. Data from shipper and logistics companies were collected and analyzed by the PLS model. Results: The analysis showed that both direct and indirect policy factors are meaningful to improve supply chain and logistics performance. Indirect support factors including R&D, management innovation, human resources development and educational supports have positive impacts on partnership factors. Direct support factors including financial aids and fairness also have positive impacts on the performance. Conclusions: This study is meaningful in that it suggests a turning point in which supply chain Win-win growth and partnership efforts are perceived as new value-creating mechanism rather than unilateral cost reduction for logistics industry.

A Research on Value Chain Structure on TV Programs Focused on Means-End Chain theory on News, Drama, and Comedy (텔레비전 프로그램 시청 행위의 가치 사슬 구조 연구 국내 수도권 지역 대학생의 뉴스, 드라마, 코미디 프로그램 시청을 중심으로)

  • Kweon, Sang-Hee;Cha, Min-Kyung
    • Korean journal of communication and information
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    • v.71
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    • pp.194-223
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    • 2015
  • This study explores a value chain structure of TV program including news, drama, and comedy. The purpose of this research focused on factor analysis and the relationship among viewer's program selection motivations. This research explores correlation between personal value and viewing motivation. This study was to identify the value structure of respondent on TV program(news, drama, comedy) based on means-end chain theory. The research used structured APT laddering questions and 251 data was analysed. Through such analysis, category difference by stage and relationship difference were identified and hierarchical value map was compared. There are four different value ladders: first is attributes, functional consequences, psychological consequences, and final value. The result shows that on news program the basic function is viewers are want to visual factor and quickly acquire social news and they pursue a value of personal social relationship. Whereas, on drama program, the viewers are reflected by around person, and they selected a program based on closed related person. In addition, the viewers are influenced by program's social nomination, production's brand in drama, and performer's nomination, producer and program prominence on comedy. The program selection is highly correlated on program selection's credibility, vital energetic life, and social relationship. The results shows that there was no significant difference between low involvement group and high involvement group for main category involvement group respondents.

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A Study on Intelligent Value Chain Network System based on Firms' Information (기업정보 기반 지능형 밸류체인 네트워크 시스템에 관한 연구)

  • Sung, Tae-Eung;Kim, Kang-Hoe;Moon, Young-Su;Lee, Ho-Shin
    • Journal of Intelligence and Information Systems
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    • v.24 no.3
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    • pp.67-88
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    • 2018
  • Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

A study on Classification of Insider threat using Markov Chain Model

  • Kim, Dong-Wook;Hong, Sung-Sam;Han, Myung-Mook
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.4
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    • pp.1887-1898
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    • 2018
  • In this paper, a method to classify insider threat activity is introduced. The internal threats help detecting anomalous activity in the procedure performed by the user in an organization. When an anomalous value deviating from the overall behavior is displayed, we consider it as an inside threat for classification as an inside intimidator. To solve the situation, Markov Chain Model is employed. The Markov Chain Model shows the next state value through an arbitrary variable affected by the previous event. Similarly, the current activity can also be predicted based on the previous activity for the insider threat activity. A method was studied where the change items for such state are defined by a transition probability, and classified as detection of anomaly of the inside threat through values for a probability variable. We use the properties of the Markov chains to list the behavior of the user over time and to classify which state they belong to. Sequential data sets were generated according to the influence of n occurrences of Markov attribute and classified by machine learning algorithm. In the experiment, only 15% of the Cert: insider threat dataset was applied, and the result was 97% accuracy except for NaiveBayes. As a result of our research, it was confirmed that the Markov Chain Model can classify insider threats and can be fully utilized for user behavior classification.

Evaluation of Competitiveness of Domestic Aircraft Manufacturing Enterprises Using Data Mining Techniques

  • Ok, Juseon;Park, Chanwoo
    • Journal of Aerospace System Engineering
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    • v.15 no.6
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    • pp.26-32
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    • 2021
  • The global aircraft-manufacturing industry ecosystem is characterized by the international division of labor through the worldwide supply chain and by the concentration of value added at the top of the supply chain. As a result, the competition for entry into the top supply chain and for order expansion is becoming increasingly intensive. To increase their orders, domestic aircraft manufacturing enterprises need to enhance their competitiveness by evaluating and analyzing it. However, most domestic aircraft manufacturing companies are unaware of the need to quantitatively evaluate their competitiveness. It is challenging to perform such an evaluation, and there are few research cases. In this study, we quantitatively evaluated and analyzed the competitiveness of domestic aircraft manufacturers by using data mining techniques. Thereby, implications for enhancing their competitiveness could be identified.

Effect of Perceived Value on Customer's Repurchase Intention in a Coffee Chain Context: Focused on Utilitarian, Hedonic, and Social Value (커피 전문점의 인지된 가치가 재구매 의도에 미치는 영향: 실용적, 유희적, 사회적 가치를 중심으로)

  • Kim, Byoungsoo
    • The Journal of the Korea Contents Association
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    • v.16 no.4
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    • pp.195-203
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    • 2016
  • This study examined customer's purchase decision-making processes in a coffee chain context. We posit customer satisfaction, brand image, and perceive value as key drivers of forming customer's repurchase intention. From the perspective of multidimensional perceived value concept, the effects of utilitarian, hedonic, and social value on customer's decision-making processes were investigated. The proposed model was empirically tested by using survey data collected from 232 university students who often visit several coffee chains. LISREL has been used to perform these analysis. The proposed theoretical model accounts for 67% of the variance in repurchase intention and 73% of the variance in customer satisfaction. The analysis results indicate that customer satisfaction and brand image play an important role in forming customer's repurchase intention. Further, utilitarian and hedonic values significantly affect customer's repurchase intention, whereas social value negatively influences it.

Information, Knowledge, Wisdom: A Progressive a Value Added Chain

  • Satija, Mohinder Partap
    • International Journal of Knowledge Content Development & Technology
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    • v.5 no.2
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    • pp.65-74
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    • 2015
  • The paper lists problems in defining information and knowledge and also in differentiating between the two. It separately describes physical, economic and cognitive properties of information and knowledge. A long drawn comparative chart of the nature, characteristics and properties of knowledge and information is given. In addition it explains their relation with wisdom. The paper emphasizes that knowledge is only a human preserve. Also it finds common grounds and mutual dependence between information, knowledge and wisdom. The purpose is to clear confusion between knowledge and information, and find their relation with wisdom and tradition by placing these in value added and evolutionary chain: Signals--data-- Information--Knowledge--Wisdom--Tradition.

The Impact of Traditional Market Properties and Relationship Quality on Customer Value : Approach from the viewpoint of the Means-end Chain Theory

  • Cho, Hee-Young;Han, Sang-Ho;Yang, Hoe-Chang
    • Journal of Distribution Science
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    • v.12 no.1
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    • pp.13-19
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    • 2014
  • Purpose - This study investigated relationship quality and/or loyalty, from the viewpoint that merchants and consumers could develop the traditional market. It reorganized variables to find the conditions of values that could stimulate consumers' motives to revive the traditional market. Research Design, data, and methodology - This study employed 202 copies of effective questionnaires, based on the data of Yang & Ju (2012), to conduct correlation, regression, and structured equation modeling (SEM). Results - The results emphasized product and store atmosphere as store selection attributes to consider in the minimum error correction (MEC) model; service factor was not significant. Further, consumers valued relationship quality in the test of mediated effects of the sub-factors of store selection attributes, including consumers' social and emotional value. The relationship quality significantly influenced consumers' value in traditional markets that needed to improve and develop using several variables. Conclusions - This study revealed connections between attributes, consequences, and values using the causal relation model, to generate an optimal model based on a practical and theoretical background and proposed ways to obtain consumer-related information easily.