Water quality indices aim at turning several complex indicators into a single synthesized value that describes the water quality of a particular source, and which is understandable by a wide audience including non-experts like the public or decision and policy-makers.
It is known that going beyond measuring simple routines requires more complex indicators, however, the greater the complexity of the indicators used, the greater the difficulties of interpretation involved [ 35, 36].
On the basis of these complex indicators, the interviewees were classified into groups which are characterised by a different attitude to technology.
The literature usually recommends that a company first begins with simple, easy-to-implement measures of resource efficiency before moving into more complex indicators (Krajnc and Glavič 2003).
Following the hypothesis that ecosystems are complex indicators for combinations of causal factors [3], future research is needed to analyse relations between landscape-specific factors and the concentrations of a broader range of metals in moss and soil samples.
We used only simple and easy to-implement indicators, but wheasy to-implementnces indicatorsssary to move towards more complex indicators (Escrig-Olmedo et al. 2017; Krajnc and Glavič 2003).
It can be recommended to start using simple and easy to implement strategies of compliance and resource efficiency and later move towards more complex indicators, addressing environmental and social effects, supply chain, and lifecycle impacts [23].
In this analysis, using principal component analysis (PCA) the 13 psychometric questions were grouped so as to specify complex indicators that might identify the way individuals relate to certain issues.
Therefore, mosses were proved to serve as biological indicators for atmospheric depositions and ecologically defined land classes could be identified as more complex indicators which allow relating exposure monitoring with effects assessment.
However, complex indicators may provide more insight and there use may be warranted in finer analyses particularly when oddities surface that need to be investigated further.
A distinguishing feature of mean travel time is that unlike complex indicators, it is based on simple concepts and can therefore be easily interpreted.
