Technology forecasting-tv look-ahead

Wilmotte, Raymond M.

doi:10.1109/mspec.1976.6369117

Cited by 3 publications

(1 citation statement)

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“…Through literature review in Compendex and Web of Science, this article investigates the first attempt to forecast technological change of TV, which was made by Feinleib (1971) by using morphological forecast and trend analysis. Wilmotte (1976), as a consultant, also discusses various technological change, broadcasting service and standards associated with TV, based on the report of "technological boundaries of TV" funded by Federal Communications Commission in late 1974. Thereafter, over the past several decades, surprisingly little efforts have been made on the forecast of TV technologies in literature, even though TV, in the consumer area, is not only one of the best selling products in the world with large number of annual shipments but also one that accounts for a significant residential electricity consumption.…”

Section: Literature Reviewmentioning

confidence: 99%

OLED TV technology forecasting using technology mining and the Fisher-Pry diffusion model

Cho

Daim

2016

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Purpose Due to rapid technological evolution driven by display manufacturers, the television (TV) market of flat panel displays has been fast growing with the advancement of digital technologies in broadcasting service. Recently, organic light-emitting diode (OLED) successfully penetrated into the large-size TV market, catching up with light-emitting diode (LED)-liquid-crystal display (LCD). This paper aims to investigate the market penetration of OLED technologies by determining their technology adoption rates based on a diffusion model. Design/methodology/approach Through the rapid evolution of information and communication technology, as well as a flood of data from diverse sources such as research awards, journals, patents, business press, newspaper and Internet social media, data mining, text mining, tech mining and database tomography have become practical techniques for assisting the forecaster to identify early signs of technological change. The information extracted from a variety of sources can be used in a technology diffusion model, such as Fisher-Pry where emerging technologies supplant older ones. This paper uses a comparison-based prediction method to forecast the adoption and diffusion of next-generation OLED technologies by mining journal and patent databases. Findings In recent years, there has been a drastic reduction of patents related to LCD technologies, which suggests that next-generation OLED technology is penetrating the TV market. A strong industry adoption for OLED has been found. A high level of maturity is expected by 2026. Research limitations/implications For OLED technologies that are closely tied to industrial applications such as electronic display devices, it may be better to use more industry-oriented data mining, such as patents, market data, trade shows, number of companies or startups, etc. The Fisher-Pry model does not address the level of sales for each technology. Therefore, the comparison between the Bass model and the Fisher-Pry model would be useful to investigate the market trends of OLED TVs further. Another step for forecasting could include using industry experts and a Delphi model for forecasting (and further validation). Originality/value Fisher-Pry growth curves for journal publications and patents follow the expected sequence. Specially, journal publications and patents growth curves are close for OLED technologies, indicating a strong industry adoption.

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Section: Literature Reviewmentioning

confidence: 99%

OLED TV technology forecasting using technology mining and the Fisher-Pry diffusion model

Cho

Daim

2016

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Forecasting OLED TV technology using bibliometrics and Fisher-Pry diffusion model

Cho

Daim

Sklar³

2015

2015 Portland International Conference on Management of Engineering and Technology (PICMET)

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The market of flat panel displays is experiencing rapid growth with the advancement of digital technologies in broadcasting service. The next challenge of LCD is OLED in TV market. The study attempts to investigate the trends in advanced or emerging technologies by determining their technology diffusion rates due to the lack of experiential data. With the development of information and communication technology, one of the recent methods to assist in technology forecasting is data mining in bibliometric or textual data from various sources such as patents, journals, and research awards. The information extracted from diverse sources can be employed in technology diffusion models such as Fisher-Pry where emerging technologies substitute older ones. The study uses web of science and compendex for bibliometric analysis to forecast the growth of next-generation OLED technologies based on the analogous growths of LCD technologies.

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A Practical Narrow-Band Television System: Sampledot

Stone

1976

IEEE Trans. on Broadcast.

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Technology forecasting-tv look-ahead

Cited by 3 publications

References 0 publications

OLED TV technology forecasting using technology mining and the Fisher-Pry diffusion model

OLED TV technology forecasting using technology mining and the Fisher-Pry diffusion model

Forecasting OLED TV technology using bibliometrics and Fisher-Pry diffusion model

A Practical Narrow-Band Television System: Sampledot

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