Understanding early diffusion of digital wireless phones
There is increasing empirical evidence from academic research and strong recognition among policymakers that wide diffusion and innovative uses of digital wireless phones are important sources of a country's economic growth and social development. Adopters do not necessarily adopt digital wireless phones at the same time though. Although the diffusion of innovation theory suggests five adopter categories according to their degree of innovativeness, this approach lacks theoretical justification and, more importantly, it makes a critical assumption of a normal distribution of adopters that needs empirical validation. This study investigates the basis for defining different adopter categories and factors that affect adoption decisions of digital wireless phones using the aggregate data on 46 developed and developing countries from 1992 to 2002. This paper utilizes a two-step analysis approach. The first step evaluates the distribution of adopters over time using various diffusion models. The second step uses iterative survival analysis to examine the patterns of influential factors on adoption behavior by evaluating the survival models using a 1% increment of cumulative penetration as the targeted events. The results of the best-fitting diffusion models indicate that digital wireless phone adoption patterns did not follow a normal distribution and did not map exactly into Rogers five adopter categories. The results from the iterative survival analysis suggest four adopter categories (innovators, early adopters, breakthrough adopters, and mainstream adopters) among the first 30% of adopters. Different factors are observed to influence various adopter categories adoption decisions. The results offer insights to support telecommunication operators to develop strategies to attract these adopters. It also supports policymakers efforts to design effective regulatory frameworks.
early diffusion digital wireless phones adopter categories survival analysis growth curve modeling public policy technology adoption technology diffusion