Coopetition between frenemies–interrelations and effects of seven collaboration problems in research clusters

Abstract

AbstractPrincipal Investigators in research clusters find themselves in a Janus-faced situation: if they want to achieve their common research goals, fulfil their overarching function of integrative knowledge production and thus secure the continuity of their collaboration, they are required to cooperate closely. At the same time, they compete with each other for scientific recognition or third-party funding. Taking this as a background, the article explores the effects and interrelationships of seven collaboration problems that arise in the context of the tension between cooperation and competition. Based on the state of research, a club-theoretical heuristic is developed that captures the effects and interrelationships of seven collaboration problems. The specified hypothesis model is tested with the help of a structural equation model using data from a large-scale online survey of PIs and spokespeople involved in research collaborations. The data analysis confirms the assumption that especially conflictual personal relationships between the partners in a research collaboration (relationship problems) form a central node in the network of collaboration problems: A lack of reciprocity of costs and benefits (fairness problems) as well as the self-interested behaviour of the spokesperson of a research cluster (management problems) promote relationship problems between the partners in a research team. Likewise, relationship problems in turn promote an erosion of communication between collaboration partners (communication problems), of goal progress evaluation (certainty problems), of cross-disciplinary exchange (difference problems) and of partners’ commitment to the common goals of the research collaboration (goal commitment problems). The structural equation model thus supports the widely held, but by no means trivial view in cooperation research that trusting and fair interaction between cooperating PIs in a research cluster is a necessary, if not sufficient, condition for their joint success.