Academic journal article The Innovation Journal

A Next Step in Collaborative Policy Innovation Research: Analysing Interactions Using Exponential Random Graph Modelling

Academic journal article The Innovation Journal

A Next Step in Collaborative Policy Innovation Research: Analysing Interactions Using Exponential Random Graph Modelling

Article excerpt

Introduction

Many OECD governments are challenged by increasingly complex and seemingly untamable policy problems (OECD, 2014). Wicked issues like global warming, ageing society and immigration can no longer be solved by traditional policy responses solely, as these daunting problems typically transcend conventional organizational and governmental boundaries in the public sector (Ney, 2009). Hence, academics have, under the slogan of collaborative policy innovation, proposed a new form of organizing innovation in policy processes as the cure for the alleged policy-making problem of the public sector (Carstensen and Bason, 2012; Agger and Sorensen, 2014; Sorensen and Waldorff, 2014).

We interpret collaborative policy innovations as processes in which a multitude of actors intentionally work together to develop, realize and propagate enriched policy solutions that are radically different from their predecessors in terms of policy understanding, program theory, objectives, and strategies in order to tame unmet societal challenges. Such a kind of collaborative processes are expected to boost innovation, as more stakeholders and thus more knowledge, information, resources and experiences are included in the decision making (Nambisan, 2008: 11; Ansell and Torfing, 2014: 10).

Collaborative policy innovation is a relatively new strand of research, and an emerging theme, in the public innovation literature (Sorensen and Waldorff, 2014). As a result, the research foci and thereby the findings of scholars have been rather diffuse. For that reason, this paper aims to cluster and (concisely) summarize the contemporary state of the art of the research niche, and identify possible venues for future research. With regard to the latter, we will make two specific claims. First of all, we will contend that the research niche of collaborative policy innovation is in need of more research on the interactive dynamics among actors in collaborative policy innovation processes; particularly, concerning practices of resource-sharing, commitment building and learning. Second, we will argue that the statistical network method of Exponential Random Graph Modelling (ERGM) is a useful tool to analyze and make inferences about these interactive dynamics between actors in collaborations that are used as vehicles for the promotion of policy innovations. Yet, before we do so, we elaborate on the definition of the concept of collaborative policy innovation.

The Concept of Collaborative Policy Innovation

So far, various scholars have worked with the concept of collaborative policy innovation. Nonetheless, not many of them have actually defined the concept. In fact, we could only retrieve one definition from the literature, which is the definition of Agger and Sorensen (2014: 189). They write:

...collaborative policy innovation can be understood as the formulation, implementation and diffusion of new contested normative visions of goals and strategies for realizing a good society through collaborative processes involving relevant stakeholders.

More researchers have, in contrast, indicated what they understand with the term policy innovation, and how collaboration can contribute to the development, realization and propagation of policy innovations. Sorensen and Waldorff (2014: 3-4), for example, state:

...policy innovation is the formulation, realization and diffusion of new policy understandings, new political visions and strategies for solving problems. collaboration can enhance policy innovation in three ways: by creating new and more nuanced understandings of a policy problem; by formulating new political visions for society, and problem-solving strategies; and by enabling and mobilizing relevant audiences to adapt, realize and diffuse these problem definitions and policy ideas.

Scholars related to the more generic literature of collaborative innovation, which looks at the collaborations between relevant stakeholders irrespective of the type of innovation outcome1 in the public sector, have put more effort in formulating a definition. …

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