Model-based approaches for technology planning and roadmapping: Technology forecasting and game-theoretic modeling

Yuskevich, Ilya; Smirnova, K. V.; Vingerhoeds, Rob A.; Golkar, Alessandro

doi:10.1016/j.techfore.2021.120761

Cited by 13 publications

(6 citation statements)

References 31 publications

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“…With sustained input of efforts, technology roadmapping methods are continuously evolving. One notable fraction is model-based technology roadmapping, approaches, in which game theory [46], or meta model [47] are integrated. The application of these model-based methods usually requires well-established industrial datasets like Car Specs Database [46].…”

Section: Technology Roadmappingmentioning

confidence: 99%

“…One notable fraction is model-based technology roadmapping, approaches, in which game theory [46], or meta model [47] are integrated. The application of these model-based methods usually requires well-established industrial datasets like Car Specs Database [46]. Since such datasets are always in short supply, the applicability of these model-based approaches is thereby be constrained.…”

Section: Technology Roadmappingmentioning

confidence: 99%

“…Owning to their relevance with technological developments, patents and scientific papers are the primary resources of quantitative technology forecasting [12,54,55]. Other textual resources such as blogs [56], hyperlinks [57], and product specifications [46,58] have also been employed in technology forecasting. Increasing data resources further stimulate the incorporation of big data analytics like data fusion [51], topic analysis [59], semantic analysis [60], and machine learning [61] in technology forecasting, as these techniques not only improve the performance of the existing methods, but also facilitate the development of novel approaches [62].…”

Section: Technology Forecastingmentioning

confidence: 99%

“…Second, the extant methods are based on defective resources; qualitive approaches have to endure personal biases, while quantitative approaches can only be based on limited and lagged publication records, in particular patents and scientific papers. Although big data analytical techniques have been extensively discussed in the literature of technological assessment, the use of big data is rarely discussed, as most of the works are still based on conventional datasets such as patents [54], publications [36,79], and product specifications [46,58]. But the used data resources tend to be more specific, have poor timeliness, and sometimes are costly or even impossible to access.…”

Section: Literature Summarymentioning

confidence: 99%

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Feature Distributions of Technologies

Zhu,

Deng,

Pan

et al. 2024

Preprint

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The development of one technology can be portrayed by common methods like Gartner’s hype cycle or S-curve, however, there is no method to characterize the feature distributions of multiple technologies within a specific domain. This study proposes a big data-based method in terms of four proposed features, namely versatility, significance, commerciality, and disruptiveness, to characterize the technologies within a given domain. The features of technologies are quantitively portrayed using the representative keywords and volumes of returned search results from Google and Google Scholar in two-dimensional analytical spaces of technique and application. We demonstrate the applicability of this method using 452 technologies in the domain of intelligent robotics. The results of our assessment indicate that the versatility values are normally distributed, while the values of significance, commerciality, and disruptiveness follow power-law distributions, in which few technologies possess higher feature values. We also show that significant technologies are more likely to be commercialized or causing potential disruption, as such technologies have higher scores in these features. Further, we validly prove the robustness of our approach via comparing historical trends with literature and characterizing technologies in reduced analytical spaces. Our method can be widely applied in analyzing feature distributions of technologies in different domains, and it can potentially be exploited in decisions like investment, trade, and science policy.

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Section: Technology Roadmappingmentioning

confidence: 99%

Section: Technology Roadmappingmentioning

confidence: 99%

Section: Technology Forecastingmentioning

confidence: 99%

Section: Literature Summarymentioning

confidence: 99%

See 2 more Smart Citations

Feature Distributions of Technologies

Zhu,

Deng,

Pan

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…( Li et al, 2019 ) combine the expert opinion with trend analysis approach for forecasting the trend of a technology. In this context, trend extrapolation as a numerical method that combines different approaches is able to overcome the limitations associated to the adoption of a single techniques and in turn to enrich the results of the analysis ( Yuskevich et al, 2021 ). Data Envelop Analysis might also be suitable for carrying out estimations on the technology rate of change ( Anderson et al, 2002 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Experts' opinions about lasting innovative technologies in City Logistics

Zenezini

Mangano

Marco

2022

Research in Transportation Business & Management

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Model‐based user experience‐focused roadmapping

Yuskevich,

Hein,

Doufene

et al. 2024

Systems Engineering

Self Cite

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Technology roadmapping is an important yet challenging strategic process involving inter‐disciplinary knowledge and requiring key decision‐makers participation. To improve and facilitate this activity, a concept of model‐based technology roadmapping has been proposed in the literature as an application of model‐based systems engineering practices to the strategic planning domain. At the same time, many modern complex technical systems are required to be not only functional, efficient, and reliable, but also useful, usable, and desirable, which shifts the focus of planning to the user experience (UX). In this paper, we developed a Domain‐specific language that uniformly represents key concepts related to the four levels essential for strategic planning in the user‐oriented business context: market, UX design, engineering design, and technology. A collaborative interactive software was developed to support the proposed methodology. As a case study, a sustainable transformation of the automotive sector was tested and implemented in the software.

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Model-based approaches for technology planning and roadmapping: Technology forecasting and game-theoretic modeling

Cited by 13 publications

References 31 publications

Feature Distributions of Technologies

Feature Distributions of Technologies

Experts' opinions about lasting innovative technologies in City Logistics

Model‐based user experience‐focused roadmapping

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