• Title/Summary/Keyword: Technology Hype Curve Model

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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.

A System Simulation for Investigation of IT and Society Co-evolution Dynamics and Its Policy Implications (시스템 시뮬레이션을 통한 기술과 사회 공진화의 동태성 고찰)

  • Kim, Sang-Wook;Jung, Jae-Lim
    • Korean System Dynamics Review
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    • v.9 no.1
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    • pp.171-197
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    • 2008
  • By applying Systems Simulation technique, this paper aims to investigates the dynamics underlying the coevolution of IT(information technology) and the society. Particularly, a series of basic questions are explored to answer by developing a simulation model for the mechanisms underlying the 'hype curve' ever occurring in the course of technology diffusion into society: First, why hype curve appears in the process of technology and society coevolution. Second, how to enhance the tapering level at the final stage of coevolution. Third, what are the key policy leverages and when is the right time for the policy intervention. As now, inflated expectations regarding ubiquitous information technology (u-IT) are growing very fast and higher than those for the previous technologies, which would result in overshoot followed by collapse of visibility and thus incur tremendous amount of social costs. In this regard implications drawn from this study perhaps give some insights not necessarily to the academics but also to the practitioners and policy makers facing the advent of u-IT as a new emerging horizon of information society.

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An Study of Demand Forecasting Methodology Based on Hype Cycle: The Case Study on Hybrid Cars (기대주기 분석을 활용한 수요예측 연구: 하이브리드 자동차의 사례를 중심으로)

  • Jun, Seung-Pyo
    • Journal of Korea Technology Innovation Society
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    • v.14 no.spc
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    • pp.1232-1255
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    • 2011
  • This paper proposes a model for demand forecasting that will require less effort in the process of utilizing the new product diffusion model while also allowing for more objective and timely application. Drawing upon the theoretical foundation provided by the hype cycle model and the consumer adoption model, this proposed model makes it possible to estimate the maximum market potential based solely on bibliometrics and the scale of the early market, thereby presenting a method for supplying the major parameters required for the Bass model. Upon analyzing the forecasting ability of this model by applying it to the case of the hybrid car market, the model was confirmed to be capable of successfully forecasting results similar in scale to the market potential deduced through various other objective sources of information, thus underscoring the potentials of utilizing this model. Moreover, even the hype cycle or the life cycle can be estimated through direct linkage with bibliometrics and the Bass model. In cases where the hype cycles of other models have been observed, the forecasting ability of this model was demonstrated through simple case studies. Since this proposed model yields a maximum market potential that can also be applied directly to other growth curve models, the model presented in the following paper provides new directions in the endeavor to forecast technology diffusion and identify promising technologies through bibliometrics.

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A Study on Co-evolution on the Formation Process of Space and Network focused on Knowledge Intensive Industry (지식집약산업의 공간과 네트워크 형성과정에 대한 공진화적 고찰)

  • Choi, HaeOk
    • Journal of the Economic Geographical Society of Korea
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    • v.15 no.4
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    • pp.628-641
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    • 2012
  • This research investigates a dynamic mechanism underlying the co-evolution between network and space by applying hype-curve model, typical phenomenon which shows how new technologies and ideas initially adapted in the society. This study analysis the knowledge intensive industry of digital contents using social network analysis (SNA) in terms of structural, spatial, and temporal aspects, year of 2000, 2005, and 2010 focused on Seoul area. First of all, network and space establish 'inter-feedback' as a result of evolution and differentiation process. Second, it happen temporal 'delay' through the learning process stage of 'peak of inflated expectation' and 'trough of disillusionment.' As a result, Seoul develops with the technology commercialized-orient strategy affect government policy. This trend changes to technology-oriented development in Seoul area in the late of 2000 established 'self-organization' with geographical proximity organizations through learning process.

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