Engage The Stakeholders
Step 4: Engage The Stakeholders
Public participation plan (PPP)
Draw a Public participation plan (PPP) using the Tool-KIT. You may want to use a few tools, instead of one, to get rich and multifaceted data. We advise you to shift between modes of working (big groups – small groups) and the knowledge needs (divergence – convergence). As a rule of thumb try to use at least one method per each quadrant of the Fourfold classification of communicative actions.
We, also, recommend to discuss the engagement methodology with the prospective participants, e.g. in a focus group. What are their preferred participation formants? Would they like to participate face-to-face or online, individually or as a group? How much time could they allocate for the participatory exercise? A couple of hours or the whole day? How would they like to contribute? By generating design ideas in a hands-on workshop or by giving their opinions in a form of the interview? An example in Box 1 shows a possible mix of tools and methods while drawing a Public participation plan (PPP) for a district master plan.
Data analysis, representation and archiving
If one of your goals, outlined in the Public participation plan was to collect the data from the stakeholders, then you should conduct data analysis and archiving. The methods for data analysis depend on the nature of collected data (quantitative – qualitative), and, also, on the complexity and depth of analysis.
If you have conducted a PPGIS survey among a large group of respondents, that means you have a set of quantitative data. You can conduct a simple analysis, calculating the number and type of responses per each question, as well as generate maps displaying spatial patterns resulting from geo-referenced responses. These responses may be correlated with some background information about participants, such as gender, age, level of education, as well as with geoinformation layers, like real estate prices, land uses, traffic frows, etc. You may, also, conduct a complex analysis, such as structural equation modelling (SEM). SEM involves building a model of a phenomenon. The model consists of various aspects arranged into a structure, where the relationships between the aspects are of statistical and/or causal nature. Thus, the model and its structural features are described through equations and verified by means of experimental or observational data.
The results of quantitative data analysis are often presented graphically in the form of charts or dots and lines on a map. Digital engagement methods, such as PPGIS, often include data analysis and presentation tools in the software package. However, you can also analyse data using generic tools, such as Excel.
If you have conducted stakeholder interviews with a small group of informants, that means you have a set of qualitative data. One approach would be to listen repeatedly to the interviews, take notes and make a summary of common themes. Another approach would be to make a transcript of each interview and perform a so called thematic analysis, analysing the data sentence by sentence, assigning codes to each sentence, and then grouping the codes into hierarchical categories. Such “deep” analysis is usually using special (commercial) software for qualitative data analysis, such as NVivo or ATLAS.ti. The first approach is quick, but more superficial and subjective, as the person analysing the interviews may pay less or more attention to certain topics whereas the second approach is more resource consuming, rigorous and objective. The second approach usually requires a skilled qualitative researcher.
Qualitative date is more difficult to represent graphically than quantitative data. However, it is possible to make summaries of key themes and illustrate the themes with direct quotes from the data.
Data sets and their summaries should be properly archived for further use. You may repeat similar civic engagement activities in 5-10 years, comparing the “old” and the “new” data, to find out, for instance, the change in attitudes among stakeholders over time. This is so called longitudinal study. Alternatively, you may conduct similar civic engagement activities in different parts of the city or among different age groups at the same time, to find out the differences in attitudes among different spatial communities or age groups. This is a so-called cross-sectional study.
Thus, we recommend to make short summaries of participation activities and their outcomes, as well as to use consistent file naming and structure, so that you (and possible other people) are able to quickly browse through the data.