The Triangulation Technique

As stated above, the use of different non-equivalent narratives and methods to address energy and material efficiency in production and consumption should be understood as a way to strengthen the results of the investigation by broadening its basis. This includes showing the different aspects and extracting different but inherent meanings from the data collected and the indicators calculated, to generate a stronger and more comprehensive basis for discussion, policy and conflict prevention. In so doing, “integration” does not mean “synthesis”, creating a “one-size-fits-all” method. Instead it refers to a way to point out potentially divergent results, to highlight the diversity of points of view, to double-check the starting point, the structure of the model, the complexity of the system and the results achieved, and finally to generate synergies from deeper understanding.

Such a procedure is known in data and evaluation science as “triangulation”, a “… research technique that facilitates the cross-verification using more than two sources. In particular, it refers to the application and combination of several research methodologies in the study of the same phenomenon (Bogdan and Biklen, 2006). By combining multiple observers, theories, methods, and empirical data, researchers aim at overcoming the weaknesses, intrinsic biases and the prob-lems that are often found in single method, single-observer and single-theory studies.” (Carugi, 2016). The rationale is that either a study’s finding is more solid if different methods lead to the same result. Alternatively, if some methods contradict each other, comparison among their assumptions and results can help understanding where the narrative is not appropriate and suggest that the question needs to be reframed, methods reconsidered, or both. Four types of tri-angulation have been identified (Denzin, 1970) which can be used in isolation or in combination like in Earth Observation science where data from satellite images via remote sensing to local interviews are combined, each with their own agents and theoretical bases:

1. Methodological triangulation: using more than one method to gather data (interviews, observations, questionnaires, focus groups and documents);
2. Data triangulation: collecting data related to different locations, times and people;
3. Observer triangulation: involving multiple researchers with different sensitivity to potential aspects;

Theoretical triangulation: interpreting results based on different theoretical frameworks, hypotheses and theories. Under a “triangulation” point of view, the different methods applied in the EUFORIE project provide a richness of diversity to the investigator instead of converging to one integrated but necessarily simplifying approach, avoiding hypocognition. The challenge is then how to exploit this rich diversity in the different steps of the policy cycle: goal setting, data collection and pro-cessing, interpretation of results, comparison with different expectations of stakeholders, search for suitable policy actions that take diversity into account, and back to goal refinement.