As world culture continues to thrive on new technology and innovation, one of the critical challenges companies and organizations face is the adoption of that technology; many struggle with the effectiveness of offering or deploying something new, as well as the speed at which the adoption can be influenced. One approach to better understanding these issues is to look at the personalities of the adopting populations, to ascertain their propensity for technology adoption. In this paper, Vishwanath shares a study examining this idea. Due to the nature of empirical studies, if readers are interested in replicating the work or validating the approach, knowledge of statistics is required. The method, approach, conclusions, and reflections are all easily absorbed, however, and can prove informative for all readers.

Vishwanath introduces an information processing model that asserts that “technological innovativeness” is influenced by the individual’s inclination to have “innovative decisions,” regardless of what others are doing, a characteristic referred to as global innovativeness. He identifies two findings of note: first, there is some support that links technological innovativeness to an individual’s proclivity for sophisticated search, and past technology acquisitions. Second, technology adoption can be strongly predicted by an individual’s technological innovativeness, and his or her exposure to television, the Internet, radio, and print; the higher the technological innovativeness of people, and the higher their exposure to media, the more readily they adopt new technology.

Three key areas are outlined to help readers understand the validity of the study’s results: first, global innovativeness, as defined by Rogers [1], includes more than tolerance for uncertainty; this was the only filter used to determine global innovativeness. Second, the sample population was made up of students, which limits the population variation. Third, the study is a point in time report using a single process. These are significant issues to overcome, and, as Vishwanath suggests, future studies would be required to validate his findings.

Moore is well known for his ideas about the technology adoption life cycle, and the chasm that exists between early adopters and the early majority [2]. Research into the definitions of people in the life cycle (innovators, early adopters, early majority, late majority, and laggards) seems to yield characteristics of different populations; this type of inquiry would provide an attractive opportunity to determine the impacts of personality on technology adoption.

Vishwanath does introduce links between media and early adopters, and further study exploring the relationship early adopters have with the media might be of additional interest. For example, innovators want to live (identify, echo, and proliferate) the messages they perceive as leading edge, while early adopters simply want to know that they own the leading edge. How does the relationship that each has with the media influence his or her proclivity to adopt? Does it change with the adopter’s age? Is it the same for all media venues?

Vishwanath proposes a somewhat intricate method for understanding his 131 usable responses: he looks at likelihood to adopt technology, prior ownership of technology, the degree to which the person is cosmopolitan, social networks, information search, media use, global innovativeness, and tolerance for novelty, complexity, and insolubility. The degree to which any one of these aspects might impact another, or contribute meaningfully to understanding the results, is unclear. Furthermore, the population size, and the knowledge that only students (most likely from the same institution) were used to build this data set, leaves a cloud of skepticism over Vishwanath. The one finding that was strong is that people who are technologically innovative, and exposed to mass media, have a high probability of adopting technology. I wonder how much of that has to do with the media, as opposed to their own innate innovative sense.