I’m getting more and more excited about the possibilities of fuzzy set qualitative comparative analysis (fsQCA). Last week I have analysed a set of 35 cases that I have studied in Australia, the Netherlands, and the United States. All these are examples of voluntary environmental programmes that seek to improve the environmental and resource sustainability of buildings and cities.
What makes this particular analysis of interest is that I have looked at two different outcomes that such programs seek to achieve, and whether particular characteristics of these programs help or hamper goal achievement.
The first outcome of interest is to what extent these programmes are successful in attracting participants. After all, if no one is interested in joining a programme, then there is little chance that they help to improve environmental and resource sustainability at all.
Yet, even if a programme is successful in attracting its stated ambitions in terms of participants is no guarantee that it will also achieve positive outcomes in terms seeing their participants construct or retrofit resource efficient buildings, or more efficiently use their existing ones. This then is the second outcome that I am interested in.
In the analysis I focussed on the rewards that come to participants (monetary gains, non-monetary gains, and the ability to have their leadership showcased), the effort involved in participating (the programme requirements they have to meet, and the stringency of enforcement of these), and finally the role governments and NGOs play in these programmes.
Some interesting findings stand out. First, none of the individual design characteristics is in itself necessary for either of the two outcomes. Different design characters interact and combine in causing these outcomes. In short, whilst monetary gain is an important design characteristic for achieving positive outcomes, in itself it is not enough. Only when monetary gains are combined with for instance a possibility to showcase leadership, or low programme participation criteria they will positively affect the outcomes.
Second, different programme designs may result in similar outcomes. Of course, this is not a surprising result. Best of class benchmarking programmes such as LEED and BREEAM are considerably different from programs that build on novel forms of financing such as 1200 Buildings in Melbourne, Australia, or PACE in the United States. Yet, to a certain extent both type of programmes have been successful in attracting participants. My analysis, however, is among the first to illustrate, empirically, how different program designs affect these two outcomes.
Third, and perhaps most importantly, the analysis indicates that only a handful of program designs is related to successful outcomes. I uncovered five designs related to high participant numbers, and another five to high numbers of buildings built or retrofitted, or improved building use.
What is striking is that the two sets of five designs that are positively related to either outcome do not fully overlap. In other word, a design that is positively related to achieving high numbers of participants is not necessarily positively related to achieving high numbers of buildings built or retrofitted, or improved building use. Some of the designs even work against each other – that is, whilst a design is successful in attracting high numbers of participants the specific design works against achieving the other outcome.
These are relevant insights. It implies that we have to think carefully when we develop and implement voluntary environmental programmes. Not just any design will result in anticipated outcomes, and only a few designs will likely result in different outcomes at the same time. The hopeful news is that different designs have proven successful. Thus, there is a bit of variety to choose from.
Are you interested to learn more about this analysis? I will present it in September at the ECPR conference in Glasgow, and am happy to share the draft conference paper. Just sent me an email to get in touch.