Knowledge Platform

Analysis of Preferences and behaviour

In this group we include methods aimed at collecting information about actors' behaviour in connection to preferences, perception or attitudes statements as well as explaining and interpreting such behaviour or preferences in relation to background determinants. Here we exclude those methods generating monetary values or yielding multi-criteria evaluations.

General Purpose and Application

New information coming from survey is very relevant in a data poor environment such as landscape-related analyses. Statistical and econometric models can provide sound basis to relationships and hypotheses that often are only based on claims by some parties in the policy debate. This type of models provide a statistical framework to test hypotheses about relationships, but have some limits due to the involvement of a large number of parameters that need to be estimated, which implies also needs for large samples.

Statistical and econometric models can yield interpretations and provide corroboration/falsification to expected relationships/determinants about preferences. Different models may be used depending on the nature and mathematical properties of the considered variables and of the specific purposes of the study. For example, latent variable models can be used to analyse data in presence of unobservable variables. These models are particularly useful when the user is interested in studying theoretical constructs that cannot be directly observed (such as the relevance attributed to landscape or to promotional activities related to landscape or willingness to use landscape services).

Lessons learned

The analysis of preferences and behaviour has been widely applied in the CLAIM project. Experiences of the project point at a number of important aspects to be considered.

  1. Careful analysis may change expectations and may be useful to understand the latent mechanisms through which variables affect each other.
  2. Need to consider the heterogeneity of the groups of landscape users,
  3. Distinction between actual users and potential users related to neighbouring points of attraction may be relevant (seaside vs. countryside) may be of relevance.
  4. The survey of rose producers and processing companies in Güneykent town in Isparta (Turkey) also revealed difficulties, as the concept of landscape was not so clear for the rose producers. Results of a survey of vine growing holdings in the Pazardjik district (Bulgaria) reveals a different level of awareness and the ability to cover a wider range of issues, which is typical of individual at an intermediate stage of the chain. An important issue that can help focusing future research is that managed assets are key drivers for the creation and utilization of landscape compositions.
  5. Potential for joint analysis of basic economic parameters, preferences and vision analysis. As several results from the project hint at the role of food chains as a key component of landscape valorisation, this case provides a useful example of the use of explorative questionnaires on this type of actors.