“I studied economic geography and social sciences and since 2015 I am a lecturer, research assistant and PhD student at the chair PLUS, at the Institute of Spatial and Landscape Development at ETH Zurich, Switzerland. I teach in the fields of spatial planning, environmental planning, GIS, site and project development, in various interdisciplinary project works and I supervise BSc and MSc theses. As a teaching specialist, I am also responsible for the coordination and development of the teaching activities at our chair and support the development of the study programs Spatial Engineering (BSc) and Spatial Development and Infrastructure Systems (MSc) at our department. Besides, I am working on my dissertation about acceptance of spatial planning policies for the management of soil resources, which I have almost finished. Engaging in teaching and teaching development is of particular interest to me, as I believe it is especially important to educate young and talented researchers so that we can join forces and tackle our global challenges posed by the changing climate.”

Sudau Manuel Matthias, a PhD student, lecturer and research assistant at the Institute of Spatial and Landscape Development at ETH in Zurich, Switzerland, applied Q methodology to investigate and characterize the subjective rationales for the acceptance or rejection of different spatial planning instruments*. He proved that although Q methodology naturally shows its strength in small P-sets, it can also be very efficient on large P-sets. In this interview, he explains his choice of the method, share his feelings about his experience with the method and the Q conference 2021.

How did you get started on your first Q study ?

Together with my colleagues Dr. Enrico Celio and Prof. Dr. Adrienne Grêt-Regamey, we were looking for a method to investigate and characterize the subjective rationales for the acceptance or rejection of different spatial planning instruments among the broad population of our case study area. Since interviews or quantitative surveys were not perfectly suited for this purpose for a variety of reasons, we broadly searched for other methods and quickly came across the work of William Stephenson, Steven Brown, Thomas Webler and Aiora Zabala. We learned the method on the basis of the manifold Q-methodology literature, and in the course of this we also came into contact with Maximilian Held, who helped us with the implementation via the qmethod package for R. In addition, the constructive discussions on the Q-methodology listserv were extremely helpful for some more specific challenges.

What did you enjoy the most in doing Q? What was the most challenging?

“The data evaluation and interpretation was particularly exciting. The idealized Q-sorts of the identified Q-factors allowed us to gain a new perspective on the relevance of different arguments for the acceptability of spatial planning instruments. In retrospect, I think the exploratory design of our Q-study, which consisted of an online survey and “classic” face-to-face interviews, was really exciting as well. We discussed the social perspectives identified in the online survey with participants in our interviews and were able to identify significant differences in the way our study participants reasoned depending on whether they conducted the Q-sorting procedure anonymously or face-to-face. The sheer size of our Q-study as well as its complexity (we analyzed several subsamples) also posed a great challenge, which we could only master with a lot of care and effort.”

In the study you presented in Orlando, you had a big p-sample that you broke down into subgroups, anything you’d like to share about having big p-sets vs small?

“Although Q-methodology naturally shows its strength in small P-sets, there are also some examples of large P-sets, which encouraged us to try this as well. By subsampling, we wanted to safeguard ourselves on the one hand (in case our large P-set would be a problem, we would still have the “normal-sized” samples as well as the more “classical” face-to-face interviews), and on the other hand we had to design a compact online survey so that the willingness to participate (of the broad population and on a rather specific topic) would be as high as possible. In the end, however, we obtained exciting results with the large P-set, which we could only strengthen and even further diversify in our subsamples. We could also think of it the other way around, that we combined several “normal” Q studies into one large P-set. This allowed us to be more responsible with our own researcher subjectivity. Reflecting on our results from the online survey with the interview participants also allowed us to gain further insights. Ultimately, however, there are surely other ways to deal responsibly and self-critically with one’s own subjectivity when evaluating a Q-study (e.g., with regard to the determination of the number of Q-factors).”

In the study you presented in Orlando, you also showed the relevance of theory in light of your q-sample, which was some nice work you did. Care to explain?

“Thank you. We assigned each statement of our Q-set to an acceptance factor derived from the literature. In interpreting our Q-factors, we were also able to identify differences in the importance of individual arguments within an acceptance factor through this assignment. In addition, this “categorization” of the statements of a Q-set also offers advantages when visualizing the results of a Q-study. Especially as newcomers in the Q-community, it was sometimes a bit difficult to comprehend and understand the tables and figures of other Q-studies. It would be quite exciting, for example, to see new and experimental representations of the characteristics of Q-factors in the future, of course, as an additional alternative to the inevitable tables.”

Would you recommend the conference to people new to Q and why?

“During our research with Q-methodology we have found the Q-community to be super helpful, welcoming and friendly, especially through the listserv. The fact that every concern, no matter how small, is always addressed with great sympathy and solved constructively and together, was not only helpful but also motivating. With my participation in the Q-conference 2022 I wanted to “give something back” to this great community and I was of course also curious to meet these inspiring and visionary scientists personally. My expectations were exceeded by far, because the atmosphere on site was simply incredible! All participants had a lot of time, there were countless exciting discussions and it was extremely inspiring to get to know the diverse areas of application of the method. I also enjoyed the fact that an equitable exchange was possible, from students to established professors and across countless research disciplines. I hope I will be able to attend again next year and look forward to seeing familiar and new faces!”

*Manuel Sudau, Enrico Celio & Adrienne Grêt-Regamey (2022) Application of Q-methodology for identifying factors of acceptance of spatial planning instruments, Journal of Environmental Planning and Management, DOI: 10.1080/09640568.2022.2043259