• 기술혁신연구
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• 제9권1호
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• pp.95-120
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• 2001

One of the systematic attempts for technological forecasting is Delphi Method that externalizes and manipulates unformalized experts opinion in a particular problem or subject. It has, however, a critical shortcoming that it can not reflect the degree of interaction that exists among forecast events or subject. Gordon and Hayward(1969) criticize that when the forecast events are strongly interrelated, a totally unrealistic consensus may result. They proposed a new forecasting method that considers the interaction of events, that is, Cross Impact Analysis (CIA). A number of related models have been developed after them. In this study, we examine a variety of research results related to CIA obtained by literature survey and propose the limitation and future research direction. This analysis would be expected to help us to create a strategic scenario on future technology development at the government and firm level.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 1997년도 제11회 하계학술발표회 논문집
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• pp.175-194
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• 1997

The competitive power of technologies is required for survival of enterprises in the social environments that change rapidly. So the strategy of technology development becomes more and more important. For the establishment of strategy, the situational analysis and the forecasting analysis are executed and they include the technology assessment and the technological forecasting. The technology assessment is systematical examination and analysis of the present status of technology. Among the various methods of technology assessment, Matrix Method is one of the usual methods. This research is intended to find out the problems and the difficulties in the current Matrix Method, and to improve the method, finally to help the R&D departments of enterprises applying the method. This suggested matrix(TSM Technology Shift Matrix) method is designed so that one can judge the current situation of technology and future expectation, by moving the matrix which is placed to the upside of the basic matrix.

• Smart Structures and Systems
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• 제21권5호
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• pp.705-713
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• 2018

High-speed rail (HSR) has been in operation and development in many countries worldwide. The explosive growth of HSR has posed great challenges for operation safety and ride comfort. Among various technological demands on high-speed trains, vibration is an inevitable problem caused by rail/wheel imperfections, vehicle dynamics, and aerodynamic instability. Ride comfort is a key factor in evaluating the operational performance of high-speed trains. In this study, online monitoring data have been acquired from an in-service high-speed train for condition assessment. The measured dynamic response signals at the floor level of a train cabin are processed by the Sperling operator, in which the ride comfort index sequence is used to identify the train's operation condition. In addition, a novel technique that incorporates salient features of Bayesian inference and time series analysis is proposed for outlier detection and change detection. The Bayesian forecasting approach enables the prediction of conditional probabilities. By integrating the Bayesian forecasting approach with time series analysis, one-step forecasting probability density functions (PDFs) can be obtained before proceeding to the next observation. The change detection is conducted by comparing the current model and the alternative model (whose mean value is shifted by a prescribed offset) to determine which one can well fit the actual observation. When the comparison results indicate that the alternative model performs better, then a potential change is detected. If the current observation is a potential outlier or change, Bayes factor and cumulative Bayes factor are derived for further identification. A significant change, if identified, implies that there is a great alteration in the train operation performance due to defects. In this study, two illustrative cases are provided to demonstrate the performance of the proposed method for condition assessment of high-speed trains.

• 한국산학기술학회논문지
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• 제18권2호
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• pp.177-184
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• 2017

기술의 확산 현상의 추세 및 발생 동인에 대한 정확한 이해는 새로운 기술을 예측하고 기술 혁신의 과정을 이해하는데 매우 유용하다. 본 연구에서는 기술의 진화 속도가 빠른 반도체 산업 32nm, 22nm, 14nm 로직 기술의 실증적 사례에 대해 기술적 성능 향상 및 경제성 지표를 고려한 정량적 추세 분석을 적용하여 기술 확산 현상의 추세 및 발생 동인을 분석하였다. 기술적 성능 향상을 고려한 기술 확산 곡선은 S곡선의 성숙기, 쇠퇴기 형태를 보였고, 경제성 기반 기술 확산 곡선은 학습효과곡선의 형태를 보였다. 기술 확산 곡선은 2년의 수명주기를 보였고, 기술 세대별 기술적 성능향상 또는 칩 제조비용의 변화 정도가 정량적으로 관찰되었다. 또한 제품구조혁신은 경제적 발생동인보다 기술적 발생동인이 더 지배적인 영향을 미침을 확인할 수 있었다. 본 연구결과는 첨단기술기반의 반도체 산업에 대한 기술 확산 현상의 추세 및 발생 동인에 대한 실증연구로 시사점이 있으며, 기술 예측 또는 기술 전략 수립에 활용될 수 있으므로 실무적으로도 의의가 크다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.122-125
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• 2000

The Analytic Hierarchy Process (AHP), a decision making model, which is more applicable than other methods to R&D project selection, particularly when it is applied to intangibles. The objective of this paper is to develop an extended model of the AHP which Is linked to Cross Impact Analysis to assist in the ranking of a large number of technological alternatives. In this study, we developed a priority setting algorithm which considers the cross-impact of the future technology alternatives and thus developed an integrated cross-impact hierarchical decision-making model, which sets the priority by considering technological forecasting and technology dependency

• 한국컴퓨터정보학회논문지
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• 제20권2호
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• pp.113-120
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• 2015

Technology analysis is to analyze technological data such as patent and paper for a given technology field. From the results of technology analysis, we can get novel knowledge for R&D planing and management. For the technology analysis, we can use diverse methods of statistics. Time series analysis is one of efficient approaches for technology analysis, because most technologies have researched and developed depended on time. So many technological data are time series. Time series data are occurred through time. In this paper, we propose a methodology of technology forecasting using the dynamic time warping (DTW) of time series analysis. To illustrate how to apply our methodology to real problem, we perform a case study of patent documents in target technology field. This research will contribute to R&D planning and technology management.

• ETRI Journal
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• 제45권6호
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• pp.982-995
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• 2023

Technological innovation generates products, services, and processes that can disrupt existing industries and lead to the emergence of new fields. Distributed ledger technology, or blockchain, offers novel transparency, security, and anonymity characteristics in transaction data that may disrupt existing industries. However, research attention has largely examined its application to finance. Less is known of any broader applications, particularly in Industry 4.0. This study investigates academic research publications on blockchain and predicts emerging industries using academia-industry dynamics. This study adopts latent Dirichlet allocation and dynamic topic models to analyze large text data with a high capacity for dimensionality reduction. Prior studies confirm that research contributes to technological innovation through spillover, including products, processes, and services. This study predicts emerging industries that will likely incorporate blockchain technology using insights from the knowledge structure of publications.

• 전자통신동향분석
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• 제39권2호
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• pp.93-102
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• 2024

As the scale of research and development (R&D) increases, countries and companies are consistently establishing R&D directions to meet strategic goals and market demands as well as roadmaps to increase efficiency through concentration and selection. However, establishing an effective roadmap and discovering promising technologies are challenging under the current numerous technological possibilities and uncertainties. The importance of discovering promising technologies to secure future technological competitiveness is recognized worldwide, and Europe, the United States, and Japan are establishing processes to identify promising future technologies and support related R&D. Methods for discovering promising future technologies can be classified into future social needs analysis, forecasting, surveys, use of expert opinions, and data analysis. We describe the types and limitations of technology roadmaps and investigate the status of domestic and foreign organizations using weak signal search through quantitative data analysis.

• 한국전자거래학회지
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• 제17권2호
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• pp.63-72
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• 2012

2000년대 초반부터 한국의 이동통신시장은 급속하게 팽창해 왔으며, 최근 들어 그 성장 속도가 둔화되고 있으나 성장은 계속 진행 중에 있다. 이와 같은 환경에서 4세대 이동통신 서비스가 2011년 10월부터 시작되어 3세대 서비스와 4세대 서비스가 함께 존재하고 이를 통해 이동통신시장의 경쟁구도가 더욱 복잡하고 치열한 상황이 되었다. 본 연구는 다세대 확산 모형을 활용하여 3세대 및 4세대 이동통신 서비스 가입자 규모를 예측하는데 목적이 있다. 이를 위해 세 개의 파라미터, 즉 Norton and Bass 모형[11]에서 사용되는 혁신계수, 모방계수 및 포화수준계수의 값을 추정하기 위해 3세대에서 4세대로 대체되는 서비스 대체의 유사 사례를 역추적하는 방법을 사용하였다. 시뮬레이션 결과, 다세대 확산모형과 유사사례 추론을 통해 신규서비스인 4세대 이동통신서비스 시장규모를 성공적으로 예측할 수 있었다는 결론을 얻었다.

• 한국도서관정보학회지
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• 제35권4호
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• pp.361-375
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• 2004

본 연구는 도서관이 미래의 변화를 감지하고 예측하여 변화에 능동적으로 대처해야 한다는 전제아래 미래예측기법의 하나인 시나리오기법을 통하여 도서관 서비스의 미래를 예측한 것이다. 이 목적을 달성하기 위하여 문헌연구와 도서관 홈페이지의 내용 분석, 전문사서와의 인터뷰를 실시하고, 그 결과 나타난 추세를 근거로 시나리오를 동하여 도서관 서비스의 중기 미래(5년-10년후)를 예측하였다. 본 연구의 결과, 얻어진 결론은 다음과 같다. 첫째, 미래의 정보 환경은 모바일과 유비쿼터스 환경으로 대표되며, 이들을 통해서 언제, 어디서나, 어떠한 기기를 이용하더라도 다양한 미디어를 활용할 수 있게 된다. 둘째, 정보기술의 발전에 따른 시간적 지체, 단말기의 보급 속도, 도서관 서비스의 자세와 대응 속도, 저작권 문제 등이 미래 도서관의 불확실 요인으로 대두된다. 셋째, 기술의 보급 속도와 도서관 서비스의 발전 속도에 따라서 또한, 기술의 보급 속도와 저작권 문제의 해결 속도에 따라서 다양한 시나리오가 만들어진다. 넷째, 도서관은 끊임없이 변하는 정보기술의 추이를 상시적으로 분석하여 불확실 요인을 찾아내야 하며, 예측 가능한 시나리오를 개발하여 미래상황에 대처할 수 있는 전략적 방안을 개발하여야 한다.