Lasse Gerrits and Peter Marks, Understanding Collective Decision Making—A Fitness Landscape Model Approach (Cheltenham, UK: Edward Elgar, 2017). 240 pp. $92.00 (hardback), ISBN: 9781783473144

• Published date: 01 November 2018
• Date: 01 November 2018
• DOI: http://doi.org/10.1111/puar.13000
• Author: Göktuğ Morçöl

926 Public Administration Review • Novem ber | Dece mber 2 018

Public Administration Review,

Vol. 78, Iss. 6, pp. 926–928. © 2018 by

The American Society for Public Administration.

DOI: 10.1111/puar.13000.

Reviewed by: Göktug˘ Morçöl

Penn State Harrisburg

Lasse Gerrits and Peter Marks, Understanding Collective

Decision Making—A Fitness Landscape Model Approach

(Cheltenham, UK: Edward Elgar, 2017). 240 pp. $92.00

(hardback), ISBN:9781783473144

Book Reviews

Galia Cohen, Editor

Göktug˘ Morçöl is a professor of

public policy and administration at Penn

State Harrisburg. He has authored books

and articles. He is an editor-in-chief of

the journal

Complexity, Governance and

Networks

.

E-mail: gxm27@psu.edu

This is a remarkable book that deserves

in-depth scrutiny and critique. The authors

make significant contributions by addressing

the conceptual and methodological problems in

the applications of complexity theory in public

administration and policy studies. Complexity

theory has a relatively long history in mathematics,

information sciences, physics, and evolutionary

biology. Its applications in public administration and

policy can be traced back to the early 1990s (Kiel

2014). Many of these applications are descriptive and

metaphorical, but there are some that made significant

conceptual and methodological clarifications as well.

Gerrits and Marks’s book falls into the latter category.

The core problem of the complexity theory applications

in the social sciences is the micro–macro problem

(or, the agency-structure problem), which has kept

sociologists busy for almost a century now (Sawyer

2005). This problem is actually composed of three

questions (Morçöl 2012): (How) Do collective

outcomes emerge for the interactions of individual actors

(micro to macro)? Once emerged, do macro structures

constitute distinct entities? (irreducibility) (How) Do

macro structures affect individual behaviors (macro to

micro)? It is a daunting task to properly conceptualize

and empirically answer any of these three questions,

let alone all three. But to develop a comprehensive

understanding of social life, they all should be answered.

Giddens (1984) offers a meta-theoretical framework

that integrates these questions into one problem:

structuration. His elegant conceptualization is difficult

to empirically investigate, however. In Understanding

Collective Decision Making, Gerrits and Marks make

a valiant and praiseworthy effort to answer two of

the questions; they refine the conceptualizations of

micro to macro processes and macro to micro effects

and propose a method to empirically investigate these

conceptualizations in case studies.

The authors use the concept of “fitness landscapes,”

which has its origins in evolutionary biology, to

illustrate how the micro and macro levels interact

in policy systems. People make decisions in what

Gerrits and Marks call the “fog of uncertainty.” It has

been long and well known that human beings make

decisions under uncertainty, due to the lack of full

knowledge of their environments and the boundedness

of their cognitive capabilities (Simon 1972). Gerrits

and Marks observe that the uncertainty is exacerbated

by the fact that decision makers are not independent

of their environmental conditions or other decisions

makers. Decision-making actors and their landscapes

are mutually dependent: As an actor traverses a terrain

to reach a mountain’s peak, the landscape changes

because of their movement. Gerrits and Marks use this

analogy to describe how as individuals and collective

actors move to reach a peak in public projects (i.e.,

completing the project) they change the landscape.

Along the way, the actors find out that the terrain has

changed and other peaks emerge. Consequently, they

end up constantly adapting to the landscape they have

contributed to change.

Other authors have used the fitness landscapes model

in the social sciences before, but mostly as an analogy,

a heuristic tool. Gerrits and Marks do more than

that: They propose a model, describe it conceptually

and mathematically, illustrate its applications in case

studies, and provide an open source software that can

be used by other researchers (available at un-code.org).

After the general introduction and overview in

chapter1, the authors narrate the history of the

applications of the fitness landscapes model in

evolutionary biology and the social sciences in

chapter2. Gerrits and Marks’s model is an adaptation

of Kauffman’s (1993) NK model, which is a model

that describes the relationships between an organism

and its environment in a biological evolutionary

process. The authors point out the potential

epistemological pitfalls in the applications of the

NK model in the social sciences and argue that such

applications should be based on an “unambiguous

ontology and epistemology.” Also, the data used in

such an application should be real (not simulated),