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    사회 네트워크 상의 기술 확산 경쟁에서 확산 시작 지점의 중심성에 따른 확산 경쟁의 결과

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    https://www.riss.kr/link?id=A101549801

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    Diffusion of innovation is the process in which an innovation is communicated through certain channels over time among the members of a social system. The literatures have emphasized the importance of interpersonal network influences on individuals in convincing them to adopt innovations and thereby promoting its diffusion. In particular, the behavior of opinion leaders who lead in influencing others’ opinion is important in determining the rate of adoption of innovation in a system. Centrality has been recognized as a good indicator that quantifies a node’s influences on others in a given network. However, recent studies have questioned its relevance on various different types of diffusion processes. In this regard, this study aims at examining the effect of a node exhibiting high centrality on expediting diffusion of innovations. In particular, we considered the situation where two innovations compete with each other to be adopted by potential adopters who are personally connected with each other. In order to analyze this competitive diffusion process, we developed a simulation model and conducted regression analyses on the outcomes of the simulations performed. The results suggest that the effect of a node with high centrality can be substantially reduced depending upon the type of a network structure or the adoption thresholds of potential adopters in a network.
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    Diffusion of innovation is the process in which an innovation is communicated through certain channels over time among the members of a social system. The literatures have emphasized the importance of interpersonal network influences on individuals in...

    Diffusion of innovation is the process in which an innovation is communicated through certain channels over time among the members of a social system. The literatures have emphasized the importance of interpersonal network influences on individuals in convincing them to adopt innovations and thereby promoting its diffusion. In particular, the behavior of opinion leaders who lead in influencing others’ opinion is important in determining the rate of adoption of innovation in a system. Centrality has been recognized as a good indicator that quantifies a node’s influences on others in a given network. However, recent studies have questioned its relevance on various different types of diffusion processes. In this regard, this study aims at examining the effect of a node exhibiting high centrality on expediting diffusion of innovations. In particular, we considered the situation where two innovations compete with each other to be adopted by potential adopters who are personally connected with each other. In order to analyze this competitive diffusion process, we developed a simulation model and conducted regression analyses on the outcomes of the simulations performed. The results suggest that the effect of a node with high centrality can be substantially reduced depending upon the type of a network structure or the adoption thresholds of potential adopters in a network.

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    목차 (Table of Contents)

    • Abstract
    • 1. 서론
    • 2. 연구배경
    • 3. 경쟁확산 프로세스
    • 4. Research Design
    • Abstract
    • 1. 서론
    • 2. 연구배경
    • 3. 경쟁확산 프로세스
    • 4. Research Design
    • 5. 결론 및 토의
    • 참고문헌
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    참고문헌 (Reference)

    1 홍정식, "확산이론 관점에서 로지스틱 모형과 Bass 모형의 비교" 한국경영과학회 37 (37): 113-125, 2012

    2 김도훈, "양면시장형 산업생태계에서 플랫폼 경쟁에 관한 진화게임 모형" 39-69, 2010

    3 최대헌, "네트워크 외부효과를 고려한 두 단계 공급체인에서의 신기술 도입과 확산속도에 대한 연구 : 구매자-공급자간 관계 요인에 대한 모형" 한국경영과학회 38 (38): 51-70, 2013

    4 Weitzel, T, "Unified Economic Model of Standard Diffusion : The Impact of Standardization Cost, Network Effects, and Network Topology" 30 (30): 489-514, 2006

    5 Bantel, K.A, "Top management and innovations in banking : does the composition of the top team make a difference?" 10 : 107-124, 1989

    6 Granovetter, M, "Threshold models of collective behavior" 83 (83): 1420-1443, 1978

    7 Centola, D, "The Spread of Behavior in an Online Social Network Experiment" 329 (329): 1194-1197, 2010

    8 Carter Jr., F.J, "Technological innovations :a framework for communicating diffusion effects" 38 : 277-287, 2001

    9 Katz, M.L, "Systems Competition and Network Effects" 8 : 93-113, 1994

    10 Farrell, J, "Standardization, Compatibility, and Innovation" 16 (16): 70-83, 1985

    1 홍정식, "확산이론 관점에서 로지스틱 모형과 Bass 모형의 비교" 한국경영과학회 37 (37): 113-125, 2012

    2 김도훈, "양면시장형 산업생태계에서 플랫폼 경쟁에 관한 진화게임 모형" 39-69, 2010

    3 최대헌, "네트워크 외부효과를 고려한 두 단계 공급체인에서의 신기술 도입과 확산속도에 대한 연구 : 구매자-공급자간 관계 요인에 대한 모형" 한국경영과학회 38 (38): 51-70, 2013

    4 Weitzel, T, "Unified Economic Model of Standard Diffusion : The Impact of Standardization Cost, Network Effects, and Network Topology" 30 (30): 489-514, 2006

    5 Bantel, K.A, "Top management and innovations in banking : does the composition of the top team make a difference?" 10 : 107-124, 1989

    6 Granovetter, M, "Threshold models of collective behavior" 83 (83): 1420-1443, 1978

    7 Centola, D, "The Spread of Behavior in an Online Social Network Experiment" 329 (329): 1194-1197, 2010

    8 Carter Jr., F.J, "Technological innovations :a framework for communicating diffusion effects" 38 : 277-287, 2001

    9 Katz, M.L, "Systems Competition and Network Effects" 8 : 93-113, 1994

    10 Farrell, J, "Standardization, Compatibility, and Innovation" 16 (16): 70-83, 1985

    11 Valente, T.W, "Social network thresholds in the diffusion of innovations" 18 : 69-89, 1996

    12 Abrahamson, E, "Social network effects on the extent of innovation diffusion: A computer simulation" 8 (8): 2389-2390, 1997

    13 Burt, R.S, "Social contagion and innovation :cohesion versus structural equivalence" 92 (92): 1287-1335, 1987

    14 Lee, E, "Reconsideration of the Winner-Take-All Hypothesis : Complex Networks and Local Bias" 52 (52): 1838-1865, 2006

    15 Katz, E, "Personal influence : the part played by people in the flow of mass communications" Free Press 1955

    16 Reagans, R, "Networks, Diversity, and Productivity : The Social Capital of Corporate R&D Teams" 12 (12): 502-517, 2001

    17 Valente T.W, "Network Models of the Diffusion of Innovations" Hampton Press 1995

    18 Katz, M.L, "Network Externality, Competition and Compatibility" 75 (75): 424-440, 1985

    19 Rosenkopf, L, "Modeling reputational and informational influences in threshold models of bandwagon innovation diffusion" 5 (5): 361-384, 1999

    20 Bala, V, "Learning from neighbours" 65 (65): 595-621, 1998

    21 Farrell, J, "Installed Base and Compatibility : Innovation, Product Preannouncements, and Predation" 76 (76): 940-955, 1986

    22 Watts, D.J, "Influentials, Networks, and Public Opinion Formation" 34 (34): 441-458, 2007

    23 Arthur, W.B, "Increasing Returns and the Two Worlds of Business" 74 (74): 100-109, 1996

    24 Kiss, C, "Identification of influencer : measuring influence in customer networks" 47 : 233-253, 2008

    25 허원창, "Dynamics of Technology Adoption in Markets Exhibiting Network Effects" 한국경영정보학회 20 (20): 127-140, 2010

    26 Kim, J, "Diffusion of competing innovations in influence networks" 8 (8): 109-124, 2013

    27 Rogers, E.M, "Diffusion of Innovations" FreePress 2003

    28 Ancona, D.G, "Demography and design : Predictors of new product team productivity" 3 (3): 321-341, 1992

    29 Arthur, W.B, "Competing technologies, increasing returns, and lock-in by historical events" 99 (99): 116-131, 1989

    30 Freeman, L.C, "Centrality in valued graphs : a measure of betweenness based on network flow" 13 : 141-154, 1991

    31 Freeman, L.C, "Centrality in networks : I. Conceptual clarification" 1 : 215-239, 1979

    32 Borgatti, S.P, "Centrality and network flow" 27 : 55-71, 2005

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    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 0.66 0.66 0.69
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    0.69 0.66 1.157 0.2
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