A Coevolutionary Revision of Decision Making Processes: An Analysis of Port Extensions in Germany, Belgium and the Netherlands

Article excerpt

INTRODUCTION

Decision making is often embedded in the implicit or explicit assumption that human decision makers have considerable freedom to steer the system they want to change. This type of thinking is dominant in decision making over physical systems such as rivers, coastal zones, nature parks, etc. Considerable resources are spent on research and planning procedures in order to develop a comprehensive plan for an area. As long as the physical system responds in predictable ways, there are no obvious reasons to challenge this assumption. But often, the responses are erratic and, sometimes, unfavorable (cf. Gunderson, 2001).

Although unfavorable consequences are often attributed to poor planning strategies and faulty decision making, they are not a proof that decision makers have made intentional errors. Rather, it shows that decision making take place in a capricious world that is prone to ignore steering incentives. This is manifestly so in the case of decision making over physical systems such as ports and their maritime access. From the case studies presented in this article, it appears that decision makers are often surprised by the outcomes of their decisions, sometimes unpleasantly. The first step in understanding how seemingly sound decisions can lead to unintended or even unwanted effects on physical systems is to understand that decisions and the actors who make these decisions are an integral part of a chain of causes and consequences that drives physical change (cf. Hook, 1999; Turner 2000). This calls for a contingent analysis of the dynamics of steering physical systems.

The purpose of this article is to analyze that chain of causes and consequences in order to explain unexpected outcomes in decision making over physical systems. Central to this analysis is the concept of coevolution. This concept forms the heart of a conceptual model of decision making processes that is presented in the following section. This model is then used to analyze two case studies about decision making over seaport extensions in fragile estuaries in Germany, Belgium and the Netherlands. The longitudinal analysis of the cases shows that decisions made under pressure backfire in the long run. This analysis leads to the formulation of five propositions about complex decision making processes in the final section of this article.

A COMPLEX SYSTEMS PERSPECTIVE

There is ample research about the workings of physical systems such as the estuaries discussed in this article. However, public decision making is still generally regarded as a black box from the perspective of natural sciences as little is understood about the dynamics of decision making and the impact of those dynamics on physical systems. On the other hand, while the dynamics of decision making are the core subjects in Public Administration, less is known from that perspective about the physical effects of decisions on the systems and how these effects in turn influence decision makers. In Public Administration, it is the physical system that is the black box.

A number of authors identify the need to understand the connections and dynamic interactions between physical systems and public decision making processes but a thorough empirical understanding of these relationships has hitherto been lacking (Folke, 2006; Gual & Norgaard, 2010; Kalis & Norgaard, 2010; Kotchen & Young, 2007; O'Sullivan, Manson, Messina, & Crawford, 2006). In order to understand these relations, one has first to assume a systemic point of departure for analysis. Unintended changes may occur as a result of an incorrect decision but could also be caused by a (physical) development elsewhere in the environment or a combination of factors. Isolating the object of research from its context is unhelpful as this context is necessary for a better understanding of the relationships. Secondly, such an analysis should take into account that the causal relationships between systems are circular as systems respond to changes from other systems, i. …