In the previous chapter, we defined multidisciplinarity and interdisciplinarity, but why and when would we need to employ an interdisciplinary research approach instead of a multidisciplinary or a monodisciplinary one? To answer this question, it is necessary to understand that a scientist may respond to several kinds of motivations or ‘drivers’ in undertaking interdisciplinary projects. The National Academy of Sciences (2005) identifies four drivers of interdisciplinary research: 1) The inherent complexity of nature and society; 2) The drive to explore basic research problems at the interfaces of disciplines; 3) The need to solve societal problems; and 4) The stimulus of generative technologies. Interestingly, these drivers share an important characteristic that cuts across disciplines: complexity. Complexity is widely recognized as one of the main themes in science today. As British physicist Stephen Hawking said: “This century is the century of complexity, and complexity and its associated technologies and theories of artificial life, agent-based models, self-organization and the science of networks will revolutionize the way science is done.” Problems and phenomena that require an interdisciplinary approach all somehow show the characteristics of complex (adaptive) systems, which are explained in this chapter.

Before describing the drivers of interdisciplinary research as defined by the NAS and embraced by our Institute for Interdisciplinary Studies’ approach, and consequently employed in this handbook, we need a basic understanding of complexity. This chapter explains complexity and related concepts and sets out its various manifestations, which can be translated into the drivers of interdisciplinary research. These drivers will be described later in this chapter. In the academic world, there is much debate about the definition of complexity. On the one hand, complexity science studies complex systems and their dynamics in a mathematical way; on the other hand, the notion of complexity is used in a broader sense. In the social sciences, complexity is also used to describe the inherent uncertainty of large-scale societal issues (such as ‘wicked problems’, which lack a definitive formulation or solution – these will be explained later on p. 39). It is important to note that interdisciplinary research in many cases addresses problems derived from complex systems, but does not necessarily study the dynamics of those systems. However, we think it is crucial to have an idea of the dynamics within complex systems when engaging in interdisciplinary research.