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Innovation researchers have known for some time that a new technology may be widely acquired, but then only sparsely deployed among acquiring firms. When this happens, the observed pattern of
cumulative adoptions will vary depending on which event in the assimilation process (i.e., acquisition or deployment) is treated as the adoption event. Instead of mirroring one another, a widening gaptermed
here an assimilation gapwill exist between the cumulative adoption curves associated with the alternatively conceived adoption events. When a pronounced assimilation gap exists, the common practice of using
cumulative purchases or acquisitions as the basis for diffusion modeling presents an illusory picture of the diffusion processleading to potentially erroneous judgments by vendors and prospective adopters
about the robustness of the diffusion process already observed, and the technology's future prospects. This study develops the assimilation gap concept,
describes the circumstances under which assimilation gaps are most likely, proposes techniques for the measurement and analysis of assimilation gaps, and applies these techniques in a study of three
innovations in software development process technology: relational database management systems (RDBs), general purpose fourth generation languages (4GLs), and computer aided software engineering tools
(CASE). Analysis based on graphical techniques showed that, as expected, CASE had a pronounced assimilation gap, while RDBs and 4GLs had more moderate gaps. Further analysis based on survival analysis
techniques revealed that the differences in the size of the gaps for the three technologies were statistically significant, and that each gap was large enough in absolute terms to be of practical interest.
For researchers, these results suggest that, where the strong possibility of an assimilation gap exists, the time of deployment should be captured instead of, or in addition to, time of acquisition as the
basis for diffusion modeling. For managers, the results suggest that they be guarded about concluding, based on impressive sales data, that an innovation is necessarily destined to become widely used. |
