Approaches in the concept of convergence. A critical review of the literature
Bibliographic Data
| ID | 15070576 |
|---|---|
| Authors | Federico Stezano (0000-0001-5450-6339, Economic Commission for Latin America and the Caribbean (ECLAC), Subregional Headquarters in Mexico, Economic Development Unit, Mexico City, Mexico, corresponding author) |
| Year | 2024 |
| Volume | 37 |
| Issue | 2 |
| Pages | 534-550 |
| Publication date | 2024-04-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Innovation The European Journal of Social Science Research (JOURNAL) |
| Journal identifiers | ISSN: 1351-1610 • E-ISSN: 1469-8412 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/13511610.2021.1919506 |
| OpenAlex | W3165123741 |
| Language | EN |
| References cited | 63 |
This article explores the existence of two main perspectives on the concept of convergence. The first view assumes convergence as an epistemological, methodological and heuristic issue resulting from the confluence of scientific disciplines and technological fields. The second view emphasizes the importance of technology management and industrial application development as strategies for analyzing the technical challenges and risks associated with convergence processes in the firm. To differentiate between the two visions, 59 specialized bibliographic works selected from a theoretical sample are analyzed. The main finding of this review is the characterization of these two perspectives that, although contradictory, are part of a common conceptualization of convergence as an umbrella notion. These findings provide relevant insights for a field of knowledge under construction: policy agendas focused on fostering technological convergence should start from the differentiation of these two analytical and conceptual levels
Conceptualization · Economics · Epistemology · Heuristic · Management science · Sociology · Technological convergence · Vision · Computer Science · Innovation and Knowledge Management · Mathematics · Technology Assessment and Management · University-Industry-Government Innovation Models
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| Highly cited | No |
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