Name
Title | ||
|---|---|---|
How to foster innovation: A data-driven approach to measuring economic competitiveness. |
Abstract | ||
|---|---|---|
Innovation is a key factor driving economic growth in countries worldwide. However, innovation is hard to define and, therefore, even harder to measure. To help policy makers and business leaders better understand how to foster innovation, we need robust ways to quantify innovation at local and global scales. In this work, we use a data-driven, machine-learning approach for measuring innovation. A... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1147/JRD.2017.2741820 | IBM Journal of Research and Development |
Keywords | Field | DocType |
Technological innovation,Economics,Predictive models,Measurement,Government policies,Modeling,Globalization,Machine learning | Data-driven,Computer science,Engineering management,Electronic engineering | Journal |
Volume | Issue | ISSN |
61 | 6 | 0018-8646 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Caitlin Kuhlman | 1 | 12 | 3.24 |
| Karthikeyan Natesan Ramamurthy | 2 | 163 | 31.33 |
| Prasanna Sattigeri | 3 | 85 | 17.23 |
| Aurelie C. Lozano | 4 | 145 | 20.21 |
| Lei Cao | 5 | 72 | 15.88 |
| C. Reddy | 6 | 19 | 2.22 |
| Aleksandra Mojsilovic | 7 | 288 | 39.15 |
| Kush R. Varshney | 8 | 368 | 55.80 |