• Title/Summary/Keyword: Innovation Diffusion

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Qualitative Analysis of Tele-healthcare Systems based on the Diffusion of Innovation Model (혁신확산모델에 근거한 원격건강관리시스템의 질적 분석)

  • Kwon, Myung Soon;Jang, Ji Hye
    • Research in Community and Public Health Nursing
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    • v.28 no.2
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    • pp.129-143
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    • 2017
  • Purpose: The purpose of this study is to explore factors which influence adoption, implementation and continued use of tele-healthcare systems. Methods: Qualitative research was conducted by in-depth interviews with 17 professionals from various fields of organizations involved in developing and implementing tele-healthcare systems. Data were analysed thematically, using a conceptual model of diffusion of innovations. Results: The system users were reacted positively to the 3 attributes out of 9 which decided the adoption of innovation. In addition, it is required to redesign the tele-health care system simpler and easier so that the system users can access to the system much more easily regardless of space and time limitations. From the design stage on an individual level, it is necessary to conduct detailed needs analysis and listen to users who are at the center of innovation diffusion. On an organizational level, it is necessary to actively prepare for possible problems during system implementation, educate the users and build communication channels continuously. Conclusion: This study has identified the factors affecting the innovation of tele-health care systems and contributed to the understanding of the operation of tele-health care systems by the diffusion of innovation theory in community health posts.

A Study on Impact of Introduction Characteristics of ERP Systems on Innovation Diffusion and Business Performance in Public Enterprise (공기업의 ERP시스템 도입특성요인이 혁신확산 및 성과에 미치는 영향에 관한 연구)

  • Lee, Pan-Soo;Shim, Joung-Taek
    • Journal of Korea Society of Industrial Information Systems
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    • v.12 no.5
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    • pp.133-145
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    • 2007
  • This study investigated the relationship between introduction characteristics of ERP system, innovation diffusion and business performance in public enterprise. This study tried to suggest plans that can adapt and use critical impact factors on public enterprise performance though diffusion of ERP systems. This study suggests that introduction characteristics affect on vertical innovation diffusion and organizational performance, directly and indirectly.

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Spatial effect on the diffusion of discount stores (대형할인점 확산에 대한 공간적 영향)

  • Joo, Young-Jin;Kim, Mi-Ae
    • Journal of Distribution Research
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    • v.15 no.4
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    • pp.61-85
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    • 2010
  • Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown

    . In a result of the Bass model(I), the estimates of innovation coefficient(p) and imitation coefficient(q) are 0.017 and 0.323 respectively. While the estimate of market potential is 384. A result of the Bass model(II) for each district shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. A result of the Bass model(II) shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. In a result of spatial diffusion model(IV), we can notice the changes between coefficients of the bass model and those of the spatial diffusion model. Except for GJ, the estimates of innovation and imitation coefficients in Model IV are lower than those in Model II. The changes of innovation and imitation coefficients are reflected to spatial coefficient(${\gamma}$). From spatial coefficient(${\gamma}$) we can infer that when the diffusion in the vicinity of the diffusing center occurs, the diffusion is influenced by one in the diffusing center. The difference between the Bass model(II) and the spatial diffusion model(IV) is statistically significant with the ${\chi}^2$-distributed likelihood ratio statistic is 16.598(p=0.0023). Which implies that the spatial diffusion model is more effective than the Bass model to describe diffusion of discount stores. So the research question (1) is supported. In addition, we found that there are statistically significant relationship between similarity of retail environment and spatial effect by using correlation analysis. So the research question (2) is also supported.

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  • The Effect of Social Networks on the Diffusion of Innovation (사회네트워크가 혁신확산에 미치는 영향)

    • 이규현;오장균
      • Journal of Korea Technology Innovation Society
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      • v.3 no.2
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      • pp.33-47
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      • 2000
    • We focus on the investigations of the effect of social networks on the diffusion of innovations, in order to successfully bring innovations into markets. We begin with consideration of social system from Rogers(1995)' perspective, which includes the fifty-year sequential tradition of diffusion studies, and expand the conceptualization into a framework for thinking about the effect of social networks on the diffusion of innovations. We draw upon basic ideas from the research traditions of social network theory in sociology, and social identity theory in social psychology. Finally, we offer propositions for the future empirical researches. A better understanding of social networks can complement research on the diffusion of innovations and help in the development of a universal model of consumer response to innovations.

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    An Empirical Study on the Factors Affecting Diffusion of Objeccl-Oriented Technology (객체지향 기술의 확산에 영향을 주는 요인에 관한 경험적 연구)

    • 이민화
      • The Journal of Information Systems
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      • v.10 no.1
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      • pp.97-126
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      • 2001
    • Object-orientation has been proposed as a promising software process innovation to improve software productivity and quality. It has not been understood clearly, however, what factors influences the diffusion of object-oriented technology in organizations. A research model was formulated and hypotheses were generated based on the literature of information technology implementation and software process innovation. To test the research hypotheses, a questionnaire survey was conducted. The results based on 121 responses from Korean companies revealed that project characteristics, use of external experts, and number of development projects are significantly related to the diffusion of object-oriented analysis and design and object-oriented programming. Innovation champion is positively related to the diffusion of object-oriented analysis and design, whereas it is not related to the diffusion of object-oriented programming language. Only project complexity was significantly related to the diffusion of visual programming language. On the other hand, organizational size was not significantly related to any object-oriented technology in this study.

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    Adoption of RFID Household-based Waste Charging System in Gangnam and Seocho in Seoul:Based on Technology Hype Curve Model

    • Lee, Sabinne
      • International Journal of Contents
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      • v.15 no.2
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      • pp.1-12
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      • 2019
    • Despite their various similarities, Seoul's' Gangnam and Seocho districts showed different patterns in the adoption of the RFID household-based waste charging system. Gangnam, one of the 25 wealthiest districts in Seoul, first adopted the RFID system in 2012, but decided abandon it a year later due to inconvenience, sanitation, budget limitations, and management related issues. Unlike Gangnam, Seocho, a largely similar district to Gangnam, started to implement the RFID system in 2015 and successfully adopted this innovation. In this paper, we explain the adoption behaviors of these two districts using a Technology Hype Curve Model with 5 stages. Unlike traditional technology adoption theory, the Hype Curve Model concentrates on the big chasm between early majorities and late majorities, which is a core reason for discontinuity in innovation diffusion. Based on our case study result, the early majority easily gave up adoption due to immature technological and institutional infrastructure. However, Seocho district, who waited until the deficiencies had been sufficiently fixed since late majorities, succeeded at incremental diffusion. Since its invention by Gartner cooperation, the Hype Curve Model has not received enough attention in academia. This paper demonstrates its explanatory power for innovation diffusion. Similarly, this paper focuses on the importance of institutional framework in the diffusion of innovation. Lastly, we compare the behavior of two local governments in supporting and diffusing RFID systems to draw relevant policy implications for innovation diffusion.

    An Analytical Study of ICT Adoption based on Diffusion Innovation Theory (혁신확산이론을 바탕으로 한 정보통신기술의 수용요인에 관한 분석적 실증연구)

    • Lee Sang-Gun;Kang Min-Cheol;Kim Bo-Youn
      • The Journal of Information Systems
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      • v.14 no.2
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      • pp.257-276
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      • 2005
    • This study adopts diffusion of innovation theory and analyses product life cycle on two different information communication technology (ICT) products. One is telematics located on introduction and the other one is MP3 located on maturity. The analytical results were mixed. ordinary least square (OLS) result showed that adoption of MP3 player is affected by white noise error ($\varepsilon$) and telematics is influenced by innovation effect (p coefficient) rather than imitation effect (q coefficient) or white noise error. However, nonlinear least square (NLS) result showed that adoption of MP3 player is affected by imitation effect (q coefficient) rather than innovation effect (p coefficient). In addition, the ratio of imitation effect/innovation effect of MP3 player is larger than that of telematics.

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    Technological Innovation Capacity Evaluation And Technology Diffusion Analysis Using Patent Data (특허정보를 이용한 기술혁신능력 평가 및 기술 확산 분석)

    • Nam, Ki-Woong;Park, Sang-Sung;Shin, Young-Geun;Jang, Dong-Sik
      • Proceedings of the KAIS Fall Conference
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      • 2009.05a
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      • pp.319-324
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      • 2009
    • Lately, knowledge-based society comes, it is important for enterprises to creatively utilize knowledge of technology for technological innovation. So, Technological innovation capacity of enterprises is important factor of business success. To improve technological innovation capacity, enterprises should well utilize their internal knowledges and external knowledges which come from technological diffusion. To well utilize external knowledges of enterprises they should well understand external knowledge flow. Especially knowledge flow also occurs frequently between nations, understanding of knowledge flow which occurs between nations is important to improve nation`s technological innovation capacity. So this paper presents comparison of technological innovation capacity and knowledge diffusion flow between nations.

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    Technology Innovation in Korean Manufacturing Firms: Intra-Firm Knowledge Diffusion and Market Strategy in Patent Production

    • Hong, Chang-Soo;Jung, Jin-Hwa
      • Asian Journal of Innovation and Policy
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      • v.1 no.1
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      • pp.50-70
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      • 2012
    • This paper analyzes the factors that determine technology innovation in Korean manufacturing firms, focusing on the role of intra-firm knowledge diffusion and market strategy in patent production. For empirical analysis, zero-inflated negative binomial (ZINB) regression is applied to the 2009 Human Capital Corporate Panel data. The empirical findings confirm the critical role of intra-firm knowledge-sharing processes in technology innovation; firms with a market-leading strategy oriented to new product development also tend to be prolific in patent production.

    An Empirical Study on the EDI Diffusion and Performance (EDI 시스템의 확산과 성과에 관한 실증적 연구)

    • Lee, Jae-Won;Lee, Young-Hwan
      • Asia pacific journal of information systems
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      • v.10 no.4
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      • pp.1-20
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      • 2000
    • Electronic Data Interchange(EDI) has the potential to improve business operations by expediting the exchange of business documents. It will also provide substantive operational and strategic benefits to the trading firms. However, the successful implementation of EDI systems requires the mutual trust and cooperation between the trading firms. The extent of EDI diffusion and performance depends on inter-organizational, intra-organizational, as well as innovation factors. Researches based on the sociopolitical process framework in the use of IT, organizational theory, resource dependence theory, and innovation diffusion theory have identified 3 inter-organizational variables(transaction climate, dependence, external IS expert support) and 4 intra-organizational variables(strategic IS planning, infrastructure, top management support, education/training,), and 3 innovation variables(compatibility, relative advantage, cost) that affect EDI diffusion. In this study, a multi-dimensional measure on EDI diffusion has been developed to capture the external and internal integration. Then, the influence of these 10 variables on the extent to which the EDI adopting firms pursue diffusion has been examined. Whether more diffusion leads to superior performance has also been studied. International trade managers from 107 firms in the trade industry participated in a field survey. The results based on a structural equation model(SEM), developed using AMOS, provide quite a strong support for the hypothesized relations. Both education/training and IT infrastructure influenced external and internal diffusion of EDI systems. Internal diffusion of EDI enables the adopting firms to improve operational and strategic performance, whereas external diffusion contributes only to operational performance.

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