Parallel or Intersecting Lines? Intelligent Bibliometrics for Investigating the Involvement of Data Science in Policy Analysis
| Autor: | Denise Chiavetta, Alan L. Porter, Yi Zhang, Nils C. Newman, Scott W. Cunningham |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
business.industry
Computer science Strategy and Management Perspective (graphical) Information technology Bibliometrics 08 Information and Computing Sciences 09 Engineering 15 Commerce Management Tourism and Services Policy analysis Data science Task (project management) ZA4050 Business & Management Related research Research questions Electrical and Electronic Engineering ZA4450 business Set (psychology) |
| Zdroj: | IEEE Transactions on Engineering Management. 68:1259-1271 |
| ISSN: | 1558-0040 0018-9391 |
| DOI: | 10.1109/tem.2020.2974761 |
| Popis: | Efforts to involve data science in policy analysis can be traced back decades but transforming analytic findings into decisions is still far from straightforward task. Data-driven decision-making requires understanding approaches, practices, and research results from many disciplines, which makes it interesting to investigate whether data science and policy analysis are moving in parallel or whether their pathways have intersected. Our investigation, from a bibliometric perspective, is driven by a comprehensive set of research questions, and we have designed an intelligent bibliometric framework that includes a series of traditional bibliometric approaches and a novel method of charting the evolutionary pathways of scientific innovation, which is used to identify predecessor-descendant relationships in technological topics. Our investigation reveals that data science and policy analysis have intersecting lines, and it can foresee that a cross-disciplinary direction in which policy analysis interacting with data science has become an emergent area in both communities. However, equipped with advanced data analytic techniques, data scientists are moving faster and further than policy analysts. The empirical insights derived from our research should be beneficial to academic researchers and journal editors in related research communities, as well as policy-makers in research institutions and funding agencies. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|