Cited 22 time in
Forecasting technology substitution based on hazard function
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Jeong, Yujin | - |
| dc.contributor.author | Park, Inchae | - |
| dc.contributor.author | Yoon, Byungun | - |
| dc.date.accessioned | 2024-08-08T05:30:34Z | - |
| dc.date.available | 2024-08-08T05:30:34Z | - |
| dc.date.issued | 2016-03 | - |
| dc.identifier.issn | 0040-1625 | - |
| dc.identifier.issn | 1873-5509 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/18579 | - |
| dc.description.abstract | The failing to prepare for forecasting along with an excessive focus on incumbent technology may lead to failure in coping with emerging technology. This, in turn, results in entering the market late. Although identifying technology substitution in advance has become increasingly important, there have only been a few attempts to forecast technology substitution. These forecasts have only tried to explain the phenomenon of substitution by focusing on the diffusion of products. Therefore, this paper aims to suggest an approach to forecasting substitution from incumbent technology and emerging technology by applying a hazard rate that originates in equipment placement in reliability engineering. A candidate for emerging technology with a high possibility to substitute existing dominant technology is chosen first. Second, we have developed a model that includes the bathtub-curve to estimate the hazard rate for technologies. This model considers uncertainty, risk, and utility when developing technology. Based on the model, the hazard rate of the dominant technology is estimated by using patent data. After estimating the hazard rate in the form of the bathtub, inflection points and several factors will define an appropriate time point for the substitution. This proposed approach is a novel approach that applies the critical concepts in reliability engineering to technological substitution. Based on a mathematical theory, this method can be used as a derision-making tool for deciding when to develop a technology and apply for patents. (C) 2016 Elsevier Inc All rights reserved. | - |
| dc.format.extent | 14 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | ELSEVIER SCIENCE INC | - |
| dc.title | Forecasting technology substitution based on hazard function | - |
| dc.type | Article | - |
| dc.publisher.location | 미국 | - |
| dc.identifier.doi | 10.1016/j.techfore.2016.01.014 | - |
| dc.identifier.scopusid | 2-s2.0-84958779044 | - |
| dc.identifier.wosid | 000372381700022 | - |
| dc.identifier.bibliographicCitation | TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, v.104, pp 259 - 272 | - |
| dc.citation.title | TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE | - |
| dc.citation.volume | 104 | - |
| dc.citation.startPage | 259 | - |
| dc.citation.endPage | 272 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | ssci | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Business & Economics | - |
| dc.relation.journalResearchArea | Public Administration | - |
| dc.relation.journalWebOfScienceCategory | Business | - |
| dc.relation.journalWebOfScienceCategory | Regional & Urban Planning | - |
| dc.subject.keywordPlus | SUCCESSIVE GENERATIONS | - |
| dc.subject.keywordPlus | OPTIMAL ADOPTION | - |
| dc.subject.keywordPlus | RATE MODELS | - |
| dc.subject.keywordPlus | FAILURE | - |
| dc.subject.keywordPlus | DIFFUSION | - |
| dc.subject.keywordPlus | WEIBULL | - |
| dc.subject.keywordPlus | INNOVATIONS | - |
| dc.subject.keywordPlus | GROWTH | - |
| dc.subject.keywordPlus | TIME | - |
| dc.subject.keywordAuthor | Technology substitution | - |
| dc.subject.keywordAuthor | Hazard function | - |
| dc.subject.keywordAuthor | Technology forecasting | - |
| dc.subject.keywordAuthor | Reliability engineering | - |
| dc.subject.keywordAuthor | Bathtub-shaped curve | - |
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