Suchergebnisse

Big data sets in conjunction with self-learning algorithms are becoming increasingly important in public administration. A growing body of literature demonstrates that the use of such technologies poses fundamental questions about the way in which predictions are generated, and the extent to which such predictions may be used in policy making. Complementing other recent works, the goal of this article is to open the machine's black box to understand and critically examine how self-learning algorithms gain agency by transforming raw data into policy recommendations that are then used by policy makers. I identify five major concerns and discuss the implications for policy making.

Collective decision making seems a straightforward matter: people come together and decide. But why is it that today's winners can turn into tomorrow's losers? Why can't you always get what you want? How does the interaction between the decision makers influence the outcome? And are opportunists better off than stubborn decision makers? This book takes a refreshing look at collective decision making by using models of evolutionary biology and naturalistic decision making to analyse real-world cases. These cases include the rise and fall of the Dutch high-speed railway project and the unexpected effects of introducing public-private partnerships to connect the new Thai national airport to Bangkok. Gerrits and Marks successfully guide the reader towards an in-depth understanding through rich empirical research and uncover the beautiful complexity of collective decision making. Understanding Collective Decision Making will be of great interest to academics working in public administration, political science and evolutionary theory. Public managers will also find this book helpful to understand why and how collective decisions are formed

We assess to what extent a (co)evolutionary macro level approach enhances our understanding of learning in governance processes. We ask the question: in what ways do actors learn to improve their chances of long-term survival in complex governance processes? We deploy a model of collective decision making moulded upon fitness landscapes to analyze a longitudinal case study of collective (political and administrative) decision making, namely the process of developing and acquiring the F35 Lightning II fighter jet. The study demonstrates that actors learn how to ensure survival over time but create a failing megaproject in the process.

This paper examines the use of Problem-Based Learning (PBL) in teaching the complexity sciences to students in public administration, policy, and management. We will discuss the background of the method, as well as demonstrate how it is used in some of our courses. We conclude that, while the method is not applicable in every situation, it does perform very well in bridging the gap between concepts and theories from complexity on the one hand, and more mainstream theories in public administration on the other. It performs equally very well in bridging the gap between theory and practice, as such preparing students in developing a complexity-informed approach to policy issues.

As the contributions in this special issue show, there are ample examples of teaching programs at the nexus of complexity and public administration and its sub-fields. However, the examples discussed in this issue do not give us an indication of the extent to which complexity theory or the complexity sciences are taught in curricula worldwide. This contribution presents the results of a thorough internet search to identify those academic programs in political science, public administration and business administration, where complexity sciences are taught in conjunction with all matters public. The search across 193 countries led to selection of 108 programs that corresponded to some or all the defined criteria. We will present characteristics of the selected programs regarding quality of fit, level of studies, field of studies, and type of information about the complexity science approach available on the programs' websites.

As the contributions in this special issue show, there are ample examples of teaching programs at the nexus of complexity and public administration and its sub-fields. However, the examples discussed in this issue do not give us an indication of the extent to which complexity theory or the complexity sciences are taught in curricula worldwide. This contribution presents the results of a thorough internet search to identify those academic programs in political science, public administration and business administration, where complexity sciences are taught in conjunction with all matters public. The search across 193 countries led to selection of 108 programs that corresponded to some or all the defined criteria. We will present characteristics of the selected programs regarding quality of fit, level of studies, field of studies, and type of information about the complexity science approach available on the programs' websites.

Early in 2014, the Dutch railway system spiralled out of control after traffic management was confronted with the decision to take four double switches and two rail tracks out of service. A lack of coordination between the responsible teams resulted in the decision to stop all traffic in one of the busiest parts of the network during the rush hour. In this study we aim to understand why the teams in the Dutch railway system were not able to adopt a coordinated approach to reschedule rail services. To answer this question, we used a mixed-method approach by combining dynamic network analysis (DNA) with sensemaking. Our analyses show that a diverging framing of the situation accumulated over time, leading to inconsistent actions, incorrect assumptions and a lack of effective communication. Informal and indirect communication spurred uncertainty and promoted negative emotions, which eventually resulted in a conflict between the actors. We discuss the difficulties of managing ambiguous events in multi-team systems.