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development of opinions is to consider it a diffusion process. Such diffusion is
characterized as a process where change is communicated through certain chan-
nels amongst members of a social system [1]. Diffusion embraces aspects such
as learning, contagion, mimicry, trust, reputation, etc. [2]. The modeling of dif-
fusion opinions has attracted a strong academic interest since the early 1960s
especially to simulate market response to new products or services [3]. In spatial
sciences research on the diffusion of opinion is very limited. Hagerstrand [4] was
amongst the first to define clustered growth as spatial diffusion. More recent
examples can be found in the work of Berger [5] who models the diffusion of new
agricultural practices.
Traditionally, the diffusion process is modeled in an aggregated manner. For
example, the acceptance of innovations is often modeled following the Bass model
based on the theory of Rogers [1]. Important drawbacks of these aggregate mod-
els are that they cannot deal with heterogeneity within the population and with
the spatial environment, are not behavioral based, and as such do not explain so-
cial change and social processes and are mainly good in explaining past behavior
rather than forecasting future behavior [3].
To overcome these drawbacks Agent Based Modeling (ABM) is suggested.
ABM differs fundamentally from aggregated approaches by not taking the system
itself as the elementary modeling unit but the individual entities making up the
system. ABM is a widely used technique to simulate land use change while taking
into account the diversity in actors and various spatial and temporal scales. [6, 7].
Although most of current agent based land use simulation deal rather good with
the spatial heterogeneity and scale issues on the behavior of agents, the social
and behavioral processes itself are still underdeveloped. Most ABM apply simple
reactive rules applied on the environment and other agents, they are however
lacking theoretical grounded concepts of elementary processes like negotiation,
formation of opinions, development of reputations and trust etc.
This paper describes a first attempt to implement a more elaborated model
of opinion dynamics in the realm of spatial planning. Focus is on the dynamics
of opinion as it can been seen as the most important driver for actors to accept
a proposed change. The first part of this paper gives a brief overview of existing
models of opinion dynamics. The second part describes a conceptual models of
the development of opinions based on, an innovation diffusion approach, within
a multi-actor, multi-goal spatial planning system. This model is implemented for
a hypothetical case study of an area in the south-east of the Netherlands. The
last sections presents an discussion on the results.
2 Background
Opinion dynamic models describe the change in opinion of an actor through
time under influence of other actors. Most current models of opinion dynamics
are somehow developed in analogy to physical models. Such a “socio-physics”
approach can be beneficial for understanding the complexity of unknown pro-
cesses. Simulating meaningful patters at this stage is more important than more
