Adoption and Diffusion of Digital Technologies: A Firm-level Analysis
| Autor: | Hollenstein, Heinz |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | KOF Working Papers, 504 |
| Popis: | The study provides evidence with respect to some topics of inter- and intra-firm diffusion of digital technology so far neglected in research. The analysis is based on a slightly extended version of the encompassing model of Battisti et al. (2009). We use a unique dataset that provides for the entire business sector information on the diffusion of 24 digital technologies ranging from old ones up to others developed only in recent years. We use the model, firstly, to analyse the determinants of the inter- and intra-firm diffusion of the entire set of digital technologies. Secondly, we do the same for six subfields of digital technology we identified by use of a factor analysis. Thirdly, we examine the effect of in-house learning on the intra-firm diffusion of digital technology. We distinguish between “cross-learning” (learning from previous experience with such technologies in subfields other than that considered) and “cumulative learning” (effect of previous application of relatively “old” digital technologies on the intensity of usage of advanced technology in the same or a closely related subfield). Finally, we analyse the determinants of a firm’s decision to digitalise a particular combination of two or more functional fields of its activity (fabrication, storage, marketing, etc.). The findings of this paper strongly support the underlying model in the case of the first and the second topic, whereas the evidence is somewhat weaker with regard to the third and the fourth element of the study. Finally, we find that complementing the “Battisti model” with variables representing firm-specific anticipated benefits is highly sensible, as these are powerful drivers of adoption and diffusion, which points to a strong forward-looking behaviour of firms in the diffusion process. KOF Working Papers, 504 |
| Databáze: | OpenAIRE |
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