• 제목/요약/키워드: network value

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서비스지배논리하에서 가치공동창출 매커니즘과 기업성과간의 관계에 대한 연구 (Understanding the Relationship between Value Co-Creation Mechanism and Firm's Performance based on the Service-Dominant Logic)

  • 남기찬;김용진;임명성;이남희;조아라
    • Asia pacific journal of information systems
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    • 제19권4호
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    • pp.177-200
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    • 2009
  • AIn the advanced - economy, the services industry hasbecome a dominant sector. Evidently, the services sector has grown at a much faster rate than any other. For instance, in such developed countries as the U.S., the proportion of the services sector in its GDP is greater than 75%. Even in the developing countries including India and China, the magnitude of the services sector in their GDPs is rapidly growing. The increasing dependence on service gives rise to new initiatives including service science and service-dominant logic. These new initiatives propose a new theoretical prism to promote the better understanding of the changing economic structure. From the new perspectives, service is no longer regarded as a transaction or exchange, but rather co-creation of value through the interaction among service users, providers, and other stakeholders including partners, external environments, and customer communities. The purpose of this study is the following. First, we review previous literature on service, service innovation, and service systems and integrate the studies based on service dominant logic. Second, we categorize the ten propositions of service dominant logic into conceptual propositions and the ones that are directly related to service provision. Conceptual propositions are left out to form the research model. With the selected propositions, we define the research constructs for this study. Third, we develop measurement items for the new service concepts including service provider network, customer network, value co-creation, and convergence of service with product. We then propose a research model to explain the relationship among the factors that affect the value creation mechanism. Finally, we empirically investigate the effects of the factors on firm performance. Through the process of this research study, we want to show the value creation mechanism of service systems in which various participants in service provision interact with related parties in a joint effort to create values. To test the proposed hypotheses, we developed measurement items and distributed survey questionnaires to domestic companies. 500 survey questionnaires were distributed and 180 were returned among which 171 were usable. The results of the empirical test can be summarized as the following. First, service providers' network which is to help offer required services to customers is found to affect customer network, while it does not have a significant effect on value co-creation and product-service convergence. Second, customer network, on the other hand, appears to influence both value co-creation and product-service convergence. Third, value co-creation accomplished through the collaboration of service providers and customers is found to have a significant effect on both product-service convergence and firm performance. Finally, product-service convergence appears to affect firm performance. To interpret the results from the value creation mechanism perspective, service provider network well established to support customer network is found to have significant effect on customer network which in turn facilitates value co-creation in service provision and product-service convergence to lead to greater firm performance. The results have some enlightening implications for practitioners. If companies want to transform themselves into service-centered business enterprises, they have to consider the four factors suggested in this study: service provider network, customer network, value co-creation, and product-service convergence. That is, companies becoming a service-oriented organization need to understand what the four factors are and how the factors interact with one another in their business context. They then may want to devise a better tool to analyze the value creation mechanism and apply the four factors to their own environment. This research study contributes to the literature in following ways. First, this study is one of the very first empirical studies on the service dominant logic as it has categorized the fundamental propositions into conceptual and empirically testable ones and tested the proposed hypotheses against the data collected through the survey method. Most of the propositions are found to work as Vargo and Lusch have suggested. Second, by providing a testable set of relationships among the research variables, this study may provide policy makers and decision makers with some theoretical grounds for their decision making on what to do with service innovation and management. Finally, this study incorporates the concepts of value co-creation through the interaction between customers and service providers into the proposed research model and empirically tests the validity of the concepts. The results of this study will help establish a value creation mechanism in the service-based economy, which can be used to develop and implement new service provision.

Concept Drift Based on CNN Probability Vector in Data Stream Environment

  • Kim, Tae Yeun;Bae, Sang Hyun
    • 통합자연과학논문집
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    • 제13권4호
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    • pp.147-151
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    • 2020
  • In this paper, we propose a method to detect concept drift by applying Convolutional Neural Network (CNN) in a data stream environment. Since the conventional method compares only the final output value of the CNN and detects it as a concept drift if there is a difference, there is a problem in that the actual input value of the data stream reacts sensitively even if there is no significant difference and is incorrectly detected as a concept drift. Therefore, in this paper, in order to reduce such errors, not only the output value of CNN but also the probability vector are used. First, the data entered into the data stream is patterned to learn from the neural network model, and the difference between the output value and probability vector of the current data and the historical data of these learned neural network models is compared to detect the concept drift. The proposed method confirmed that only CNN output values could be used to reduce detection errors compared to how concept drift were detected.

A hybrid singular value decomposition and deep belief network approach to detect damages in plates

  • Jinshang Sun;Qizhe Lin;Hu Jiang;Jiawei Xiang
    • Steel and Composite Structures
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    • 제51권6호
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    • pp.713-727
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    • 2024
  • Damage detection in structures using the change of modal parameters (modal shapes and natural frequencies) has achieved satisfactory results. However, as modal shapes and natural frequencies alone may not provide enough information to accurately detect damages. Therefore, a hybrid singular value decomposition and deep belief network approach is developed to effectively identify damages in aluminum plate structures. Firstly, damage locations are determined using singular value decomposition (SVD) to reveal the singularities of measured displacement modal shapes. Secondly, using experimental modal analysis (EMA) to measure the natural frequencies of damaged aluminum plates as inputs, deep belief network (DBN) is employed to search damage severities from the damage evaluation database, which are calculated using finite element method (FEM). Both simulations and experimental investigations are performed to evaluate the performance of the presented hybrid method. Several damage cases in a simply supported aluminum plate show that the presented method is effective to identify multiple damages in aluminum plates with reasonable precision.

암호화폐 가치 특성이 투자 의도에 미치는 영향에 관한 실증적 연구 : 가치 기반 수용모델을 중심으로 (An Empirical Study on the Impact of Cryptocurrency Value Characteristics on Investment Intention : Focusing on the Value-based Adoption Model (VAM))

  • 김상일;서재석;김정욱
    • 디지털산업정보학회논문지
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    • 제20권2호
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    • pp.141-157
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    • 2024
  • This study examines the impact of cryptocurrency value characteristics on cryptocurrency investment intention. Stock craze and information provided through various media, including YouTube, play an essential role in helping investors recognize the value of cryptocurrency and develop positive investment intentions. In this study, we applied the Value-Based Adoption Model (VAM) to verify the relationship between cryptocurrency value characteristics and investment intention. We surveyed 500 cryptocurrency investors to assess network externalities, awareness, compatibility, cost benefits (fees), technicality, security, perceived value, and investment intentions. SEM (Structural Equation Modeling) using AMOS 26.0 was used for data analysis. Results show that network externalities, awareness, compatibility, cost benefits (fees), security, and perceived value significantly impact investment intention. This study provides insights that help investors accurately perceive cryptocurrencies and develop strategies to increase investment intentions. It also contributes to improving investors' decision-making ability. This comprehensive approach will foster the growth of the cryptocurrency market and strengthen investor confidence.

SK텔레콤 가치네트워크의 역동적 진화에 관한 장기사례분석 (The Longitudinal Case Study on the Dynamically Evolving Value Network of SK Telecom)

  • 장용호;박종구
    • 한국산학기술학회논문지
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    • 제14권5호
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    • pp.2150-2156
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    • 2013
  • 새로운 가치를 창출하기 위한 자원 확보는 기술과 시장의 불확실성이 높은 융합시장에서 기업이 살아남기 위한 필수조건이다. 이 연구는 융합환경에 직면한 이동통신사가 새로운 가치창출을 위해 필요한 자원들의 연결체인 가치네트워크를 어떻게 재구성해왔는지를 밝혀내고자 했다. 이를 위해 SK텔레콤을 분석 사례로 선정하여 1999년부터 2008년까지 SK텔레콤의 출자구조에 대한 측정을 통해 자원구성관점에서 SK텔레콤의 가치네트워크가 융합환경에 어떻게 적응해왔는지를 실증적으로 분석하였다. 연구결과 이동통신망의 고도화에 기반한 융합서비스 제공은 SK텔레콤의 수입원천에 구조적인 변화를 가져왔으며, 사업영역의 확장을 통해 SK텔레콤이 미디어기업으로 자리매김할 수 있는 원동력으로 작동하였다. 이 과정에서 출자구조로 측정된 SK텔레콤의 가치네트워크는 새로운 가치창출을 위해 동종 산업뿐만 아니라 이종 산업에 존재하는 보완적 자산을 역동적으로 재구성해가며 가치 지향적으로 진화했다.

신경망을 이용한 콘크리트의 압축강도 및 슬럼프값 추정 (The Prediction of Compressive Strength and Slump Value of Concrete Using Neural Networks)

  • 최영화;김종인;김인수
    • 한국산업융합학회 논문집
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    • 제5권2호
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    • pp.103-110
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    • 2002
  • An artificial neural network is applied to the prediction of compressive strength, slump value of concrete. Standard mixed tables arc trained and estimated, and the results are compared with those of experiments. To consider the varieties of material properties, the standard mixed tables of two companies of Ready Mixed Concrete are used. And they are trained with the neural network. In this paper, standard back propagation network is used. For the arrangement on the approval of prediction of compressive strength and slump value, the standard compressive strength of 210, $240kgf/cm^2$ and target slump value of 12, 15cm are used because the amount of production of that range arc the most at ordinary companies. In results, in the prediction of compressive strength and slump value, the predicted values are converged well to those of standard mixed tables at the target error of 0.10, 0.05, 0.001 regardless of two companies.

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Security Clustering Algorithm Based on Integrated Trust Value for Unmanned Aerial Vehicles Network

  • Zhou, Jingxian;Wang, Zengqi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권4호
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    • pp.1773-1795
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    • 2020
  • Unmanned aerial vehicles (UAVs) network are a very vibrant research area nowadays. They have many military and civil applications. Limited bandwidth, the high mobility and secure communication of micro UAVs represent their three main problems. In this paper, we try to address these problems by means of secure clustering, and a security clustering algorithm based on integrated trust value for UAVs network is proposed. First, an improved the k-means++ algorithm is presented to determine the optimal number of clusters by the network bandwidth parameter, which ensures the optimal use of network bandwidth. Second, we considered variables representing the link expiration time to improve node clustering, and used the integrated trust value to rapidly detect malicious nodes and establish a head list. Node clustering reduce impact of high mobility and head list enhance the security of clustering algorithm. Finally, combined the remaining energy ratio, relative mobility, and the relative degrees of the nodes to select the best cluster head. The results of a simulation showed that the proposed clustering algorithm incurred a smaller computational load and higher network security.

클라이언트-서버기반 분산가상환경에서의 지연예측을 통한 효율적 공유상태관리 (An Effective Shared-Slate Management using Network Delay Estimation in Client-Sewer-Based Networked Virtual Environment)

  • 심광현;최병태;김종성;오원근
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 추계종합학술대회 논문집(3)
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    • pp.189-192
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    • 2000
  • This paper presents a new DR(Dead Reckoning) algorithm in client-server-based networked virtual environment using network delay estimation. In the algorithm, a new update packet is sent to server (or client) whenever the difference of current real value and tracking value after network delay is larger than threshold. To confirm the proposed algorithm, a test network game was implemented. Through iterative field tests, we knew that this algorithm provides fair service and stability.

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A Study on The Optimization Method of The Initial Weights in Single Layer Perceptron

  • Cho, Yong-Jun;Lee, Yong-Goo
    • Journal of the Korean Data and Information Science Society
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    • 제15권2호
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    • pp.331-337
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    • 2004
  • In the analysis of massive volume data, a neural network model is a useful tool. To implement the Neural network model, it is important to select initial value. Since the initial values are generally used as random value in the neural network, the convergent performance and the prediction rate of model are not stable. To overcome the drawback a possible method use samples randomly selected from the whole data set. That is, coefficients estimated by logistic regression based on the samples are the initial values.

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초 고 탄소 저합금강의 경도와 인성에 미치는 열간단조의 영향 (Effect of Hot Forging on the Hardness and Toughness of Ultra High Carbon Low Alloy Steel)

  • 김종백;강창룡
    • 동력기계공학회지
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    • 제17권6호
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    • pp.115-121
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    • 2013
  • This study was carried out to investigate the effect of hot forging on the hardness and impact value of ultra high carbon low alloy steel. With increasing hot forging ratio, thickness of the network and acicular proeutectoid cementite decreased, and than were broken up into particle shapes, when the forging ratio was 80%, the network and acicular shape of the as-cast state disappeared. Interlamellar spacing and the thickness of eutectoid cementite decreased with increasing forging ratio, and were broken up into particle shapes, which then became spheroidized. With increasing hot forging ratio, hardness, tensile strength, elongation and impact value were not changed up 50%, and then hardness rapidly decreased, while impact value rapidly increased. Hardness and impact value was greatly affected by the disappeared of network and acicular shape of proeutectoid cementite, and became particle shape than thickness reduction of proeutectoid and eutectoid cementite.