Social Networks and Problem-solving in the Context of Biopharmaceutical Research and Development

Abstract

Problem-solving is a vital aspect of scientific innovation. It is especially important in the biopharmaceutical field which, despite its innovative reputation, faces high project failure rates. To cope with research obstacles, these organizations utilize an evolving matrix structure with structured turnover of cross-functional (interdisciplinary) research teams. Problem-solving becomes social and relies on scientists’ ability to activate network contacts. What kind of social network contact facilitates problem-solving? Two different theoretical perspectives set different expectations. The needs perspective suggests specific types of resources are useful at different problem-solving phases. Different types of resources are locked into different types of social network ties. As problem-solving progresses and the required resources change, profiles of network contacts change. Turnover should be greatest between problem-identification, which calls for interpersonal support and familiarity, and problem-understanding, which calls for new knowledge and formal authority. In contrast, what I call the strong core perspective posits a stable core of multi-purpose network contacts. In terms of the types of network contacts, the needs perspective expects problem-solving phases to be independent; the strong core perspective expects path dependence. To explore network contact characteristics associated problem-solving phases and test for path dependence, I surveyed members of the American Association of Pharmaceutical Scientists, the largest pharmaceutical professional organization, about the contacts they utilized while dealing with the most serious research obstacle they encountered in the past year and which contacts were useful for identification and understanding. A multi-level path model copes with the nested data structure and tests for path-dependence. Results support the strong core perspective; strong path dependence indicates that scientists utilize contacts associated with strong tie strength and competence-based trust for both problem-identification and problem-understanding. Scientists form stable sets of social contacts during nascent problem-solving phases.