A Context Similarity-Based Analysis of Countries’ Technological Performance
This work contributes to the literature in the field of innovation by proposing a quantitative approach for the prediction of the timing and location of patenting activity. In a recent work, it was shown that focusing on couples of technological codes allows for the formation of testable predictions...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-10-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/20/11/833 |
| _version_ | 1798039823384051712 |
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| author | Andrea Napoletano Andrea Tacchella Luciano Pietronero |
| author_facet | Andrea Napoletano Andrea Tacchella Luciano Pietronero |
| author_sort | Andrea Napoletano |
| collection | DOAJ |
| description | This work contributes to the literature in the field of innovation by proposing a quantitative approach for the prediction of the timing and location of patenting activity. In a recent work, it was shown that focusing on couples of technological codes allows for the formation of testable predictions of innovation events, defined as the first time two codes appear together in a patent. In particular, the construction of the vector space of codes and the introduction of the <i>context similarity</i> metric allows for a quantitative analysis of technological progress. Here, we move from that result and we show that, through <i>context similarity</i>, it is possible to assign to countries a score which measures the probability of being the first to patent a potential innovation. In other words, we show that we can not only estimate the likelihood that a potential innovation will be patented in the imminent future, but also forecast where it will be patented. |
| first_indexed | 2024-04-11T21:59:00Z |
| format | Article |
| id | doaj.art-e9fec217e0a04a6da28a9a477cd931e9 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-11T21:59:00Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-e9fec217e0a04a6da28a9a477cd931e92022-12-22T04:01:01ZengMDPI AGEntropy1099-43002018-10-01201183310.3390/e20110833e20110833A Context Similarity-Based Analysis of Countries’ Technological PerformanceAndrea Napoletano0Andrea Tacchella1Luciano Pietronero2Institute for Complex Systems—CNR, Via dei Taurini 19, 00185 Rome, ItalyInstitute for Complex Systems—CNR, Via dei Taurini 19, 00185 Rome, ItalyInstitute for Complex Systems—CNR, Via dei Taurini 19, 00185 Rome, ItalyThis work contributes to the literature in the field of innovation by proposing a quantitative approach for the prediction of the timing and location of patenting activity. In a recent work, it was shown that focusing on couples of technological codes allows for the formation of testable predictions of innovation events, defined as the first time two codes appear together in a patent. In particular, the construction of the vector space of codes and the introduction of the <i>context similarity</i> metric allows for a quantitative analysis of technological progress. Here, we move from that result and we show that, through <i>context similarity</i>, it is possible to assign to countries a score which measures the probability of being the first to patent a potential innovation. In other words, we show that we can not only estimate the likelihood that a potential innovation will be patented in the imminent future, but also forecast where it will be patented.https://www.mdpi.com/1099-4300/20/11/833innovationeconomic studiesmachine learning |
| spellingShingle | Andrea Napoletano Andrea Tacchella Luciano Pietronero A Context Similarity-Based Analysis of Countries’ Technological Performance Entropy innovation economic studies machine learning |
| title | A Context Similarity-Based Analysis of Countries’ Technological Performance |
| title_full | A Context Similarity-Based Analysis of Countries’ Technological Performance |
| title_fullStr | A Context Similarity-Based Analysis of Countries’ Technological Performance |
| title_full_unstemmed | A Context Similarity-Based Analysis of Countries’ Technological Performance |
| title_short | A Context Similarity-Based Analysis of Countries’ Technological Performance |
| title_sort | context similarity based analysis of countries technological performance |
| topic | innovation economic studies machine learning |
| url | https://www.mdpi.com/1099-4300/20/11/833 |
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