Order in Innovation
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| Accesso online: | |
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| _version_ | 1866913518653014016 |
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| author | Ho, Martin Price, Henry CW Evans, Tim S O'Sullivan, Eoin |
| author_facet | Ho, Martin Price, Henry CW Evans, Tim S O'Sullivan, Eoin |
| contents | Is calendar time the true clock of innovation? By combining complexity science with innovation economics and using vaccine datasets containing over three million citations and eight regulatory authorisations, we discover that calendar time and network order describe innovation progress at varying accuracy. First, we present a method to establish a mathematical link between technological evolution and complex networks. The result is a path of events that narrates innovation bottlenecks. Next, we quantify the position and proximity of documents to these innovation paths and find that research, by and large, proceed from basic research, applied research, development, to commercialisation. By extension, we are able to causally quantify the participation of innovation funders. When it comes to vaccine innovation, diffusion-oriented entities are preoccupied with basic, later-stage research; biopharmaceuticals tend to participate in applied development activities and clinical trials at the later-stage; while mission-oriented entities tend to initiate early-stage research. Future innovation programs and funding allocations would benefit from better understanding innovation orders. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2302_13076 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Order in Innovation Ho, Martin Price, Henry CW Evans, Tim S O'Sullivan, Eoin Physics and Society General Economics Economics Is calendar time the true clock of innovation? By combining complexity science with innovation economics and using vaccine datasets containing over three million citations and eight regulatory authorisations, we discover that calendar time and network order describe innovation progress at varying accuracy. First, we present a method to establish a mathematical link between technological evolution and complex networks. The result is a path of events that narrates innovation bottlenecks. Next, we quantify the position and proximity of documents to these innovation paths and find that research, by and large, proceed from basic research, applied research, development, to commercialisation. By extension, we are able to causally quantify the participation of innovation funders. When it comes to vaccine innovation, diffusion-oriented entities are preoccupied with basic, later-stage research; biopharmaceuticals tend to participate in applied development activities and clinical trials at the later-stage; while mission-oriented entities tend to initiate early-stage research. Future innovation programs and funding allocations would benefit from better understanding innovation orders. |
| title | Order in Innovation |
| topic | Physics and Society General Economics Economics |
| url | https://arxiv.org/abs/2302.13076 |