Abstract
New technologies are permanently developed and introduced into markets. Although their adoption process is extremely volatile and varies from case to case, it is of extreme interest to companies to somehow plan and especially to estimate the development. For these estimations so-called diffusion models are utilized. A well-known and often used one is the Bass model, which incorporates different parameters and their specific influences. Our paper analyzes what kind of parameters (e.g., coefficient of innovation, underlying distribution) have what kind of influence (e.g., number of adoptions, standard deviation from adoption time) on the diffusion estimations. For the analysis the market of electric vehicles with its politically motivated objectives and current sales quantities serves as an application example. For the analysis itself, a factorial design with synthetically generated and disturbed data is applied.
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Brusch, M., Fischer, S., Szuppa, S. (2015). The Bass Model as Integrative Diffusion Model: A Comparison of Parameter Influences. In: Lausen, B., Krolak-Schwerdt, S., Böhmer, M. (eds) Data Science, Learning by Latent Structures, and Knowledge Discovery. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44983-7_20
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DOI: https://doi.org/10.1007/978-3-662-44983-7_20
Publisher Name: Springer, Berlin, Heidelberg
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