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@article{Zhao2021,

title = {Is coronavirus-related research becoming more interdisciplinary? A perspective of co-occurrence analysis and diversity measure of scientific articles},

author = {Yi Zhao and Lifan Liu and Chengzhi Zhang},

doi = {https://doi.org/10.1016/j.techfore.2021.121344},

year  = {2021},

date = {2021-11-08},

urldate = {2021-11-08},

journal = {Technological Forecasting and Social Change},

volume = {121344},

abstract = {The outbreak of coronavirus disease 2019 (COVID-19) has had a significant repercussion on the health, economy, politics and environment, making coronavirus-related issues more complicated and difficult to adequately address by relying on a single field. Interdisciplinary research can provide an effective solution to complex issues in the related field of coronavirus. However, whether coronavirus-related research becomes more interdisciplinary still needs corroboration. In this study, we investigate interdisciplinary status of the coronavirus-related fields via the COVID-19 Open Research Dataset (CORD-19). To this end, we calculate bibliometric indicators of interdisciplinarity and apply a co-occurrence analysis method. The results show that co-occurrence relationships between cited disciplines have evolved dynamically over time. The two types of co-occurrence relationships, Immunology and Microbiology & Medicine and Chemical Engineering & Chemistry, last for a long time in this field during 1990–2020. Moreover, the number of disciplines cited by coronavirus-related research increases, whereas the distribution of disciplines is uneven, and this field tends to focus on several dominant disciplines such as Medicine, Immunology and Microbiology, Biochemistry, Genetics and Molecular Biology. We also measure the disciplinary diversity of COVID-19 related papers published from January to December 2020; the disciplinary variety shows an upward trend, while the degree of disciplinary balance shows a downward trend. Meanwhile, the comprehensive index 2Ds demonstrates that the degree of interdisciplinarity in coronavirus field decreases between 1990 and 2019, but it increases in 2020. The results help to map the interdisciplinarity of coronavirus-related research, gaining insight into the degree and history of interdisciplinary cooperation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Robinson2018,

title = {Innovation pathways in additive manufacturing: Methods for tracing emerging and branching paths from rapid prototyping to alternative applications},

author = {Douglas K.R. Robinson and Axel Lagnau and Wouter P.C. Boon},

url = {https://doi.org/10.1016/j.techfore.2018.07.012},

year  = {2018},

date = {2018-07-26},

journal = {Technological Forecasting and Social Change},

abstract = {In recent years, the Forecasting Innovation Pathway approach (FIP) has shown to be a promising set of tools to capture potential developments in emerging fields through capturing indications of endogenous futures. However, the FIP approach is reliant on a clear demarcated area to study, a challenge for emerging technology fields where uncertainty and rhetoric abound. This paper presents an addition to the FIP toolbox that helps characterise and demarcate boundaries of emerging fields to allow for deeper analysis through other FIP methods. We illustrate this approach through an exercise for 3D printing technology (also known as Additive Manufacturing). We show that 3D printing can be represented by a dominant design: a tri-partite configuration of printer, material and digital design software. In the past decade we have seen significant branching from applications in rapid-prototyping to medical, fashion, aeronautics and supply chain management with a variety of elements coming together in tri-partite configurations. The paper adds to the current FTA literature an approach building on evolutionary theories of technical change to help with such situations – emerging, evolving and branching ‘innovation pathways’. Moreover, we developed a methodology to construct these innovation paths.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}