Complexity: On the Way to Mathematical Foundations of Organization Science

The roots of organization science are intimately tied to complexity. Individuals and organizations operate in environments that are too complex, and too unknown, to be dealt with using global optimization schemes. While Economics by and large still tries to find such optimization schemes, organization science took a radical departure from this view of rationality and decision making. The notion of bounded rationality, as proposed by Herbert Simon is at its core an understanding of how individuals and organizations successfully reduce complexity. Individuals and organizations need to cope with environments that are largely more complex than internal representations, hold by managers or distributed in organizations, could capture. Yet some individuals and organizations are successful to operate in, and shape such environments. This raises fundamental questions, that are only partially answered: What exactly is complexity? When is the reduction of complexity successful? Are there general principles that can be described in mathematical form?

These questions lead us into a theoretical realm that may seem to be somewhat detached from organization science. In fact, questions like ``what is complexity, how to define and measure it?'' have been debated in physics, computer science, mathematics for many decades, and have also been the subject of a lot of interdisciplinary work. An entire institute, the Santa Fe Institute for the Sciences of Complexity, has been founded to address such questions, and over the years, this institute has inspired many other initiatives. Likewise, a group of European researchers from various disciplines has founded the European Complex Systems Society which has inspired a lot of further activities.

It is time to take stock. We ask what these theoretical debates and insights can offer for organization science. What new perspectives can offer complexity science for the issues of bounded rationality, decisions under uncertainty, creating innovations for an unknown future, and perhaps thereby also shaping that future? And in turn, what impetus can organization science give to complexity research? Can this bring the abstract debates back to earth?

There are various theoretical concepts of complexity; they usually address one of the following issues

• How difficult it is to generate or to describe a system/structure. This is the constructive aspect.
• How difficult it is to understand a system/structure. Understanding requires the detection and utilization of regularities, rules, principles inherent in that structure. This is the representational aspect.
• To what extent a system is more than the sum of its parts. This is the structural aspect, focussing on relations between collections of elements that are not inherent in those ellements themselves or smaller subcollections of them.

These issues are not independent of each other. Seeing regularities helps to construct new structures. Analogies transfer structures from one system to another. The crucial regularities of a system may be contained in its web of relations.

Complexity is not negative. Of course, on one hand, we want to simplify things. On the other hand, however, we want to build more complex structures. A crucial dialectical insight is that the two processes, simplification and complexification, go hand in hand. Only by simplification can we identify possibilities for complexification. Only when we understand the regularities of existing structures, we can use them to build more complex ones. Only when the interactions in a system are simple or standardized enough, we can generate collective momentum at a higher level.

And there is another insight from constructivism and social science. Complex systems develop their own internal schemes of rationality, their standardized mode of operation. This is often hard to grasp or to appreciate from outside the system, but that is what keeps the system running, enablint it to transform incoherent external input or perturbations into coherent internal processes.

From the perspective of organization science, there is the individual aspect and the institutional one. The individual may wish to reduce complexity, to find its way through complicated situations by simple rules, like heuristics, and coordinate its behavior with others by simple mechanisms. It wants to reduce mental effort, at least for its daily tasks, but it may then want to use its free capacities for innovations. The organization wants to make its internal procedures simple and efficient, in order to avoid frictions and save resources. Towards the outside world, however, it wants to be competitive, generate innovations, move into new domains, but also be intransparent and unpredictable for competitors.

So, can insights from complexity sciences help us to understand these issues at a deeper level? Can it shed light on the relationship between individuals and organizations/institutions? And more concretely, can it provide a deeper understanding of the issue of bounded rationality? And still more concretely, can it detect systematic mechanisms behind acts of creativity, innovation, and by bringing those to light, can it help to make the search for innovations more efficient?

Despite 50 years of research into bounded rationality and complexity, we only have partial answers to these questions. This workshop will use the opportunity to merge leading research groups into the sciences of complexity, the groups of Jürgen Jost and Nihat Ay, with leading complexity scholars from organization science. The workshop thus can be seen as a revisit of the initial complexity vision of Herbert Simon, who made clear that human organization and principles of complexity are indeed closely related.

Format of Sessions and Tracks

The workshop will contain both plenary sessions and sessions in six tracks that comprise of six teams that work on particular topics. At the end of the workshop, the track results are presented in plenum (expect for the teams that are given longer time slots in the plenum earlier during the workshop). The teams will either work on topics of joint interest that are close to the theme of the workshop, or they will continue working on topics that emerged in the first three workshops in the same series. Richard Bettis (University of North Carolina at Chapel Hill) and Shyam Sunder (Yale University) participate via video.

• Team 1: Unawareness in Value Based Business Strategy: Kevin Bryan, Michael Ryall and Burkhard Schipper
• Team 2: Complexity: Nihat Ay, Jürgen Jost and Thorbjørn Knudsen
• Team 3: The Uncertainty and Complexity Vision: Timo Ehrig, David Good, Lenny Smith, David Tuckett
• Team 4: Heuristics and Reciprocal Bounded Rationality: Florian Artinger, Davide Marchiori, Rosemarie Nagel, Jens Schmidt
• Team 5: Heuristics and Routines: Pantelis Analytis, Markus Becker, Nils Bertschinger, Eckehard Olbrich
• Team 6: Human Action Explained by Physical Principles: Shabnam Mousavi, Shyam Sunder