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Actor-network analysis

Actor-network analysis (ANA) examines how human and non-human actors, i.e. technologies and policies, influence complex systems. It reveals power structures and the dynamic nature of interactions and changes within the network, making it valuable for evaluating the long-term effects of CAP interventions.

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Basics

In a nutshell

What is the actor-network analysis (ANA) method?

ANA is a qualitative research methodology rooted in actor-network theory (ANT). It challenges conventional social science approaches by recognising the influence of both human and non-human entities, or ‘actants’, in shaping social processes. ANA seeks to understand the complex interplay between these actants within a network, and how they interact and influence one another to achieve their shared goals.

ANT emphasises that ‘facts’ and ‘artefacts’ are not objective nor simply given but are the products of intricate, dynamic relationships within a network. ANT examines how networks are constructed and maintained through a process of ‘translation’, where actors (both human and non-human) influence and negotiate with one another to achieve their aims. This involves:

  • Identifying all entities (key actors) that contribute to the network, including individuals, organisations, technologies, regulations and even physical spaces.
  • Visualising the connections (relationships and interactions) between actors, paying attention to how they influence one another and how these interactions shape the network's dynamics.
  • Analysing how actors translate their interests and goals to align with those of others, forge alliances and mobilise resources to achieve collective action.

ANA asks questions about who is linked to whom, the content of the linkages, the pattern they form, the relationship between the pattern and behaviour, and the relationship between the pattern and other societal factors. It helps identify the actors involved and their possible roles, as well as some of the opportunities and risks associated with involving these actors.

Pros and cons

Advantages Disadvantages
  • ANA offers a holistic perspective of the evaluation context by considering both human and non-human actors, including technologies, policies and even physical spaces. This helps to understand the complex interplay between different elements and avoids overly simplistic interpretations.
  • ANA emphasises the dynamic nature of the evaluation context, highlighting how relationships and interactions evolve over time. This provides a more nuanced understanding of the evaluation process and can identify potential barriers and opportunities that other static approaches might miss.
  • ANA reveals how power is distributed and negotiated within the evaluation context, showing how different actors influence each other and shape outcomes. This can be particularly helpful in understanding how power imbalances can affect the evaluation process and identifying ways to mitigate their impact.
  • By including non-human actors, ANA offers a more inclusive analysis that captures the full spectrum of influences within the evaluation context. This approach accounts for the role of technologies, policies and other non-human factors that may not be considered in traditional evaluations.
  • ANA enables an analysis of how the evaluation context evolves over time, providing insights into the dynamic nature of interactions and changes within the network. This can be crucial for understanding the long-term effects of interventions and adapting evaluation strategies as the context evolves.
  • Analysing actor networks can be complex and time-consuming, requiring meticulous data collection and analysis, which is particularly challenging in resource-constrained settings.
  • Gathering accurate and relevant data for all actors, especially non-human ones, can be difficult, particularly when dealing with complex or sensitive information.
  • The inclusion of diverse actors and the focus on relationships can make the analysis difficult to interpret and apply in practice, hence requiring expertise in ANT and the ability to navigate complex interactions.
  • ANT can be challenging to apply in practice due to its abstract theoretical framework, which can make it difficult to translate concepts into concrete evaluation tools and methods.
  • The emphasis on non-human actors can sometimes overshadow the role of individual human agency and decision-making, which can lead to an incomplete or biased understanding of the evaluation context.

When to use?

ANA can provide a unique perspective for evaluating the CAP, particularly when seeking a deeper understanding of the intricate interplay between human and non-human actors involved in its implementation and intended outcomes. This method is effective for evaluating complex interventions involving various actors and dynamic environments, such as Agricultural Knowledge and Innovation Systems (AKIS), LEADER and CAP Networks.

ANA proves particularly valuable when the evaluation aims to:

  • Uncover hidden complexities in interactions with a diverse range of actors, technologies, policies and social contexts. Traditional evaluation methods might miss the nuances of these interrelationships, while ANA can reveal the interconnectedness of human and non-human actors in shaping outcomes.
  • Analyse long-term effects that require understanding how actors and networks evolve over time. ANA can effectively track how actors, interests, and networks shift and adapt, revealing the cascading effects of policy interventions.
  • Address power dynamics of involved actors with different levels of power and influence. ANA can help understand how power dynamics shape policy decisions, how power imbalances might affect outcomes and how to mitigate these imbalances.
  • Understand the role of innovation by identifying how technological innovations interact with other actors and networks, how they are adopted, and how they ultimately affect the agricultural and rural development landscape.
  • Evaluate the impact of non-human actors as the effectiveness of strategic approaches, strategies and systems is influenced not only by human actors but also by technologies, regulations, policies and physical spaces. ANA acknowledges the role of these non-human actors in shaping outcomes, revealing the broader context in which the CAP operates.

Preconditions

A clear understanding of the evaluation objectives and scope is crucial. This involves defining the questions ANA aims to address and the actors, networks and processes that will be analysed.

A deep understanding of the context is essential, including the relevant policy framework, historical background and specific socioeconomic landscape. 

Resources include time, data collection tools, ANT and qualitative data analysis expertise.

Involving stakeholders in the evaluation process – such as farmers, policymakers, researchers, and other actors, can enrich the analysis and ensure that the evaluation remains relevant and actionable. This engagement can involve interviews, workshops, and other participatory methods.

Step-by-step

The process for applying ANA in practice, specifically in the context of evaluating the CAP:

Step 1 – Define the evaluation objectives and scope

  • Identify the key questions the evaluation seeks to answer.
  • Specify the scope of the evaluation.
  • Clearly define the evaluation's overall goals.

Step 2 – Contextualise the evaluation

  • Develop a deep understanding of the policy framework by identifying the intervention's objectives, principles and mechanisms e.g. the AKIS strategic approach.
  • Research the historical background. How has the policy evolved over time? What were the key drivers behind its changes?
  • Analyse the socioeconomic landscape. What are the major trends? What are the key challenges and opportunities facing the sector?

Step 3 – Identify key actors

  • Identify all relevant actors involved in the implementation. This includes human actors (e.g. farmers, policymakers, researchers, NGOs and consumers) and non-human actors (e.g. technologies, regulations, policies and physical spaces).
  • Develop a detailed understanding of the roles and interests of each key actor. What are their motivations? What are their stakes?
  • Consider the power dynamics between actors. Who has the most influence? Are there any power imbalances that might affect the evaluation?

Step 4 – Map relationships and interactions

  • Create a network diagram or chart to visually represent the actors' connections. Show how they influence each other and how their interactions shape the network's dynamics.
  • Use arrows or lines to depict the direction and strength of the influence between actors. For example, a thick arrow might represent a strong influence, while a dotted line might represent a weaker or indirect influence.
  • Consider using different colours or symbols to represent different types of actors. This can help to highlight the various roles and interests within the network.

Step 5 – Analyse the process of translation

  • Trace how actors translate their interests and goals to align with those of others. How do they negotiate, forge alliances and mobilise resources to achieve shared objectives?
  • Identify key moments of translation (i.e. problematisation, interessement, enrolment, mobilisation) within the network.
  • Examine the outcomes of translation. Did it lead to successful implementation? Did it result in unanticipated consequences?

Step 6 – Interpret the findings

  • Draw conclusions based on the analysis of the actor network. What are the key factors influencing the implementation and outcomes?
  • Consider the implications of findings for future policy development and evaluation. What adjustments could be made to improve the effectiveness?

Step 7 – Engagement with stakeholders

  • Present findings to key stakeholders. This might involve presenting a report, holding a workshop or conducting interviews.
  • Seek feedback and input from stakeholders. This can help refine the analysis and ensure it is relevant and actionable.

Step 8 – Document the evaluation

  • Write a detailed report that summarises findings and recommendations, which also includes the network diagram with key actor profiles and the analysis of the translation process.

Be transparent about the limitations of evaluation. Highlight any potential biases or areas where further research might be needed.

Main takeaway points

  • ANA is unique in that it recognises the influences of both human and non-human actors in complex systems. It considers not only individuals, but also technologies, policies and even physical spaces as key actors.
  • ANA is valuable for evaluating long-term effects and complex interventions, such as AKIS, LEADER or CAP Networks.
  • It helps to uncover hidden complexities within the interconnectedness of actors and networks while shedding light on how they shape outcomes. This allows for a more nuanced understanding of the evaluation context.
  • ANA focuses on understanding the process of ‘translation’ – how actors negotiate and align their interests to achieve collective action. This dynamic process reveals how power dynamics shape policy decisions and how different actors influence each other.
  • Engaging with stakeholders throughout the evaluation process is essential for enriching the analysis, ensuring its relevancae and making it actionable.
  • ANA can provide valuable insights into the CAP's effectiveness, highlighting potential areas for improvement and contributing to more informed decision-making for policymakers, farmers and other stakeholders.

Learning from experience

Further reading