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Community coalitions are an important part of the public milieu and subject to similar external pressures as other publicly funded organizations – including changes in required strategic orientation. Many US government agencies that fund efforts such as community-based social marketing initiatives have shifted their funding agenda from program development to policy development. The Florida Prevention Research Center at the University of South Florida (Tampa, Florida, USA) created community-based prevention marketing (CBPM) for policy development framework to teach community coalitions how to apply social marketing to policy development. This paper aims to explicate the framework’s theory of change.

The research question was: “How does implementing the CBPM for Policy Development framework improve coalition performance over time?” The authors implemented a case study design, with the “case” being a normative community coalition. The study adhered to a well-developed series of steps for system dynamics modeling.

Results from computer model simulations show that gains in community coalition performance depend on a coalition’s initial culture and initial efficiency, and that only the most efficient coalitions’ performance might improve from implementing the CBPM framework.

Practical implications for CBPM’s developers and users are discussed, namely, the importance of managing the early expectations of academic-community partnerships seeking to shift their orientation from downstream (e.g. program development) to upstream social marketing strategies (e.g. policy change).

The purpose of this paper is to show how non-linear causal modelling knowledge, already accumulated by other disciplines, is central to unravelling wicked problem scoping and definition in social marketing.

The paper is an illustrative case study approach, highlighting three real-world exemplars of causal modelling for wicked problem definition.

The findings show how the traditional linear research methods of social marketing are not sensitive enough to the dynamics and complexities of wicked problems. A shift to non-linear causal modelling techniques and methods, using interaction as the unit of analysis, provides insight and understanding into the chains of causal dependencies underlying social marketing problems.

This research extends the application of systems thinking in social marketing through the illustration of three non-linear causal modelling techniques, namely, collective intelligence, fuzzy cognitive mapping and system dynamics modelling. Each technique has the capacity to visualise structural and behavioural properties of complex systems and identify the central interactions driving behaviour.

Non-linear causal modelling methods provide a robust platform for practical manifestations of collaborative-based strategic projects in social marketing, when used with participatory research, suitable for micro, meso, macro or systems wide interventions.

The paper identifies non-linear causality as central to wicked problem scoping identification, documentation and analysis in social marketing. This paper advances multi-causal knowledge in the social marketing paradigm by using fuzzy, collective and interpretative methods as a bridge between linear and non-linear causality in wicked problem research.