In sociology and distributed artificial intelligence, researchers are investigating two different ways of scaling. On the one hand, there is qualitative scaling, meaning that (social) complexity is increased, introducing regular practices of action, institutions, new fields of social action and requiring new dimensions in perception and decision making. On the other hand, researchers are interested in investigating quantitative scalability, i.e. how goals can be achieved under the constraints imposed by a growing population.
Our argument is structured as follows: firstly, we want to establish that organizations and interorganizational networks are an important cornerstone for the analysis of qualitative scaling. Secondly, we show by empirical evaluation that an elaborate theoretical concept of such networks increases the quantitative scalability of multiagent systems.