The Interplay between Psychometric and Sociometric Data and the Willingness to Adopt New Products
|Publikationsart:||Articles in Refereed Journals (National)|
|erschienen in:||Zeitschrift für Betriebswirtschaft (ZfB)|
|Weitere Quellenangabe:||81(1), 29-59|
Due to high failure rates of new products, marketers are seeking ways to actively manage the diffusion of innovations. It is well accepted that individuals, who exert a remarkably strong influence on others and are usually called opinion leaders, play an important role in the diffusion process. In marketing, such opinion leaders are typically identified by self-designation, which can be biased. A second option to identify opinion leaders is the use of sociometric data which becomes increasingly available. In this paper we examine the effect of social position on the perceived opinion leadership and the resulting behavioral intention in terms of adoption behavior. In an empirical study, we examine the adoption of a new drug called “Byetta” and find that sociometric opinion leadership is an antecedent of the psychometric characteristic. Our results also confirm that such opinion leaders are more likely to adopt innovations. We also find that opinion seekers, individuals who often sought information or opinions from interpersonal sources, can be more easily identified with psychometric data. They are more restrictive in terms of adoption. Interestingly, both types are active as market mavens and thus may either advocate the adoption of the innovation or may be frankly conservative regarding the new product adoption. If opinion seekers can, however, be persuaded to adopt the innovation, they may also serve as an important multiplier. This has several implications for pharmaceutical firms that try to optimize their sales force—influencing opinion leaders may indeed start and fasten the adoption process of innovative products. But it is also necessary to allay opinion seekers’ doubts since they might slow down the adoption process. The identification of opinion leaders might not only be based on difficult to obtain psychometric data, but also on sociometric data from social networks, which is becoming more and more available.