
Recent literature suggests there is a natural connection between innovation and digital transformation, two key topics of interest in management and organization that have spawned large, independent and well-defined areas of study. While this connection might be analytically straightforward and notable examples are not hard to find, in everyday life, it materializes in a multiplicity of ways. A need emerges, then, to better understand the interaction between innovation and digital transformation so that it can be explored and exploited by actors in academia and the public, private and third sectors. In this article, we use a co-word analysis, a text mining technique that permits to systematically map the intellectual structure of a research field, to characterize the most notable dynamics of ‘innovation-driven digitalization’ and ‘digitalized innovation’— the two major dimensions of interaction between innovation and digital transformation. The text identifies the relevant themes, subthemes and concepts that appear in the literature, as well as their relationship and level of development. It, then, aggregates them in a taxonomy that, on the one hand, readily displays their connection and, on the other hand, (i) informs about current or potential controversies, (ii) gaps, (iii) lines for novel and further research, and (iv) alternatives to bridge to other areas of study.
Digital transformation, digitalized innovation, industry 40, innovation-driven digitalization, COVID-19, co-word analysis, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Digital transformation, digitalized innovation, industry 40, innovation-driven digitalization, COVID-19, co-word analysis, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 10 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
