• Title/Summary/Keyword: Value network

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Identification of resources and competences for value co-creation in the relationship network of high-tech B2B firm (첨단 기술 기반 B2B 회사의 관계 네트워크에서의 공동 가치 창출을 위한 자원 및 역량 도출)

  • Park, Changhyun;Lee, Heesang
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.7
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    • pp.4191-4197
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    • 2014
  • Value co-creation is an important business strategy these days in both the business-to-business (B2B) and business-to-consumer (B2C) markets. The aim of this study was to identify specialized resources and competences for value co-creation in the relationship network within a high-tech B2B market. A case of Taiwan Semiconductor Manufacturing Company Limited (TSMC) with customers and partners was chosen as the study case. Based on the observations, contents analysis of the secondary data and unstructured interviews with former TSMC employees, 4 critical resource types (financial, knowledge, efficiency and intellectual resource) and 6 competence types (relational, collaboration, strategic, innovation, managing and service capability), were performed as the principal factors for value co-creation in the relationship network. A research framework that can analyze the value co-creation phenomena in the relationship network was established.

DeepPurple : Chess Engine using Deep Learning (딥퍼플 : 딥러닝을 이용한 체스 엔진)

  • Yun, Sung-Hwan;Kim, Young-Ung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.5
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    • pp.119-124
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    • 2017
  • In 1997, IBM's DeepBlue won the world chess championship, Garry Kasparov, and recently, Google's AlphaGo won all three games against Ke Jie, who was ranked 1st among all human Baduk players worldwide, interest in deep running has increased rapidly. DeepPurple, proposed in this paper, is a AI chess engine based on deep learning. DeepPurple Chess Engine consists largely of Monte Carlo Tree Search and policy network and value network, which are implemented by convolution neural networks. Through the policy network, the next move is predicted and the given situation is calculated through the value network. To select the most beneficial next move Monte Carlo Tree Search is used. The results show that the accuracy and the loss function cost of the policy network is 43% and 1.9. In the case of the value network, the accuracy is 50% and the loss function cost is 1, respectively.

Evolution and Development Process of Customer Value Research Using Network Analysis In Marketing : Focusing on SSCI Rank 20 Journals Using Author Co-Citation Analysis (연결망 분석을 이용한 마케팅 분야의 고객가치 연구의 진화 및 발전과정에 관한 연구 : 저자 동시 인용 분석방법을 이용한 SSCI 상위 20위권 저널을 대상으로)

  • Yoo, Kyungok;Kim, Hyang Mi;Kim, Jae Wook
    • Journal of the Korean Operations Research and Management Science Society
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    • v.38 no.2
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    • pp.1-24
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    • 2013
  • The research about customer value has developed over the past years in the marketing field. On the other hand, the stream of the idea has not fully been structured yet. It is the purpose of this research to present the process of development together with the intellectual structure in the field of customer value researches using "Author Co-citation Analysis" (ACA). For the purpose of the research, authors chosen were ranked in order of frequency according to their citations which were used for network analysis. Further, it was of advantage in finding the development process for this research from 1996 to 2011. The trend were set into three time-line groups/trends (1996~2000, 2001~2005, and 2006~2011) that were respectively analyzed. In conclusion, the research represents the intellectual structure of customer value in each period. The research having been tried, influenced a variable field in other marketing researches. While still, many researches limit their focus on a "one-way customer value, used by companies in the past and some in the present, many researches now have a wider perspective about the value and relationship of their customer and their company, together with the society at large.

Determinants of Users' Perceived Value on Mobile Contents Service (모바일 콘텐츠 서비스에 대한 인지된 사용자 가치 결정요인에 관한 연구)

  • Park, Sang-Cheol;Kim, Jong-Uk
    • Journal of Information Technology Applications and Management
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    • v.15 no.4
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    • pp.221-245
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    • 2008
  • Recently, mobile internet technologies are enabling the possibility of radically new computing services which can share information and communicate with others on the move. In this situation, prior studies have attempted to identify of what factors make people use mobile internet. However, prior researches focused on investigating the factors affecting users' adoption to Mobile Internet. In order to offer beneficial materials to mobile internet companies, we investigated important factors to increase mobile users' value from the viewpoints of customer. In particular, this study was progressed how characteristics of mobile contents affect users' intrinsic attributes and how perceived users' network effects affect users' value in the mobile computing environments. To empirically test proposed hypotheses, we have analyzed 285 survey data gathering from mobile internet users and verified hypotheses by using SEM (structural equation modeling). Based on the results of this study, we found that content accessibility and content quality have significant impacts on users' intrinsic attributes such as perceived usefulness and perceived enjoyment. In addition, this study also revealed that perceived usefulness and perceived enjoyment were positively related to users' emotional value. Moreover, this study found that perceived users' network effects could affect users' monetary value by mediating expected benefits. Based on our findings, we can understand that this perspective can provide a deeper understanding of the mobile users' value adoption by bridging the gap between mobile internet studies and actual practice.

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Analysis of Marketing Channel Competition under Network Externality (네트워크 외부성을 고려한 마케팅 채널 경쟁 분석)

  • Cho, Hyung-Rae;Rhee, Minho;Lim, Sang-Gyu
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.1
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    • pp.105-113
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    • 2017
  • Network externality can be defined as the effect that one user of a good or service has on the value of that product to other people. When a network externality is present, the value of a product or service is dependent on the number of others using it. There exist asymmetries in network externalities between the online and traditional offline marketing channels. Technological capabilities such as interactivity and real-time communications enable the creation of virtual communities. These user communities generate significant direct as well as indirect network externalities by creating added value through user ratings, reviews and feedback, which contributes to eliminate consumers' concern for buying products without the experience of 'touch and feel'. The offline channel offers much less scope for such community building, and consequently, almost no possibility for the creation of network externality. In this study, we analyze the effect of network externality on the competition between online and conventional offline marketing channels using game theory. To do this, we first set up a two-period game model to represent the competition between online and offline marketing channels under network externalities. Numerical analysis of the Nash equilibrium solutions of the game showed that the pricing strategies of online and offline channels heavily depend not only on the strength of network externality but on the relative efficiency of online channel. When the relative efficiency of online channel is high, the online channel can greatly benefit by the network externality. On the other hand, if the relative efficiency of online channel is low, the online channel may not benefit at all by the network externality.

Blending Precess Optimization using Fuzzy Set Theory an Neural Networks (퍼지 및 신경망을 이용한 Blending Process의 최적화)

  • 황인창;김정남;주관정
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1993.10a
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    • pp.488-492
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    • 1993
  • This paper proposes a new approach to the optimization method of a blending process with neural network. The method is based on the error backpropagation learning algorithm for neural network. Since the neural network can model an arbitrary nonlinear mapping, it is used as a system solver. A fuzzy membership function is used in parallel with the neural network to minimize the difference between measurement value and input value of neural network. As a result, we can guarantee the reliability and stability of blending process by the help of neural network and fuzzy membership function.

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Network Structure and Centrality Analysis of Global Value Chains in Electrical and Electronic Industries (전기·전자산업의 중간재 글로벌가치사슬 네트워크 구조와 중심성 분석)

  • Seog-Min Kim
    • Korea Trade Review
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    • v.46 no.1
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    • pp.113-134
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    • 2021
  • This study analyzed the centrality of the GVCs network and the value-added-based production structure of the electrical and electronic industries using ADB-MIRO and social network analysis methods. According to the analysis, the centrality and power of the GVSc intermediate goods network were differentiated into China, the United States, and the EU due to the advancement of industrial structure in Asia. In the 2000 network, the United States and Japan had a very strong influence in all aspects, including connectivity and strength. However, in 2017, China's power index rose to number one among 62 countries in the network. Furthermore, this study presented strategic implications of the Korean electrical and electronic industries to respond to the reorganization of GVSs based on the analysis results.

Realization of Intelligence Controller Using Genetic Algorithm.Neural Network.Fuzzy Logic (유전알고리즘.신경회로망.퍼지논리가 결합된 지능제어기의 구현)

  • Lee Sang-Boo;Kim Hyung-Soo
    • Journal of Digital Contents Society
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    • v.2 no.1
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    • pp.51-61
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    • 2001
  • The FLC(Fuzzy Logic Controller) is stronger to the disturbance and has the excellent characteristic to the overshoot of the initialized value than the classical controller, and also can carry out the proper control being out of all relation to the mathematical model and parameter value of the system. But it has the restriction which can't adopt the environment changes of the control system because of generating the fuzzy control rule through an expert's experience and the fixed value of the once determined control rule, and also can't converge correctly to the desired value because of haying the minute error of the controller output value. Now there are many suggested methods to eliminate the minute error, we also suggest the GA-FNNIC(Genetic Algorithm Fuzzy Neural Network Intelligence Controller) combined FLC with NN(Neural Network) and GA(Genetic Algorithm). In this paper, we compare the suggested GA-FNNIC with FLC and analyze the output characteristics, convergence speed, overshoot and rising time. Finally we show that the GA-FNNIC converge correctly to the desirable value without any error.

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Improving the Performance of Cellular Network by Controlling SIP Retransmission Time Interval and Implementing Home Network (셀룰러 망에서 SIP 재전송 간격조절에 의한 성능 개선과 이를 이용한 홈 네트워크 구현)

  • Kwon, Kyung-Hee;Kim, Jin-Hee;Go, Yun-Mi
    • The Journal of the Korea Contents Association
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    • v.8 no.2
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    • pp.67-73
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    • 2008
  • Recently, due to the rapid advances of mobile communication, multimedia service can be provided by mobile devices. Cellular network tends to uses SIP as a call setup protocol in order to provide various multimedia service to consumers. Cellular network holds the characteristic of higher BER(Bit Error Rate), narrower bandwidth than the wired network. The value of SIP RTI(Retransmission Time interval) based on the wired network decreases a network efficiency and increases a call setup delay over cellular network. By using NS-2 simulator, we show new SIP RTI value adequate over cellular network. We design and implement home network by using the modified SIP that is suitable for cellular network.

A Study on the Evaluation of the Hand Value of Korean Fabrics using the Artificial Neural Network (인공신경망을 이용한 한복지 태의 평가에 관한 연구)

  • Moon, Myeong-Hee
    • Korean Journal of Human Ecology
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    • v.12 no.1
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    • pp.63-73
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    • 2003
  • The purpose of this study was to quantify the hands of fabrics for the Korean folk clothes using both a KES-FB and an artificial neural network. In order to select the proper input parameters, we calculated the correlation using step-wise regression between mechanical properties and the hand value of fabrics. For the classification, the primary hand values and total hand value, five neural networks with three-layered structure were constructed using the error back propagation algorithm and, in order to reduce errors and to speed up learning, the momentum method was selected. From the analysis of the primary and total hands using a self-constructed artificial intelligence system, the error rates of sleekness, stiffness, silkiness, and roughness compared with the judgement of expert panels were found to be 3.3%, 3.3%, 1.6%, and 4.9%, respectively, while that of the total hand was 9.83%.

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