Externalizing implicit expectations and assumptions in transdisciplinary research

By Verena Radinger-Peer, Katharina Gugerell and Marianne Penker

1. Verena Radinger-Peer (biography)
2. Katharina Gugerell (biography)
3. Marianne Penker (biography

How can implicit expectations and assumptions of team members in transdisciplinary research collaborations be identified?

We used Q-methodology as a tool to make diverse expectations and perceptions of transdisciplinary research collaborations tangible and thus negotiable.

Q-methodology is an established explorative, semi-quantitative method for investigating distinctive viewpoints of a given population based on inverted factor analysis. While we do not explain Q methodology here, it is increasingly used and we refer those who want to find out more to Watts and Stenner (2012).

One disadvantage of the Q-method is the amount of time and effort that has to be invested in developing the Q-statements. Here we offer the statements we developed through an extensive process in our study for others to use either in their own Q methodology or in surveys.

We developed the 34 Q-statements in the list below (translated from German), to elucidate varying expectations and assumptions about transdisciplinary research collaboration. Most are relevant to any transdisciplinary research, with a few focused on regional research, which will not always be applicable for others.

  1. In my opinion, the most important goal of our transdisciplinary project is to improve the actual situation in the region.
  2. I am concerned with understanding the theoretical and methodological features of transdisciplinary projects.
  3. It is easy for me to put my professional expertise behind me and enter into an open dialog within the team.
  4. I can easily empathize with and understand the priorities and attitudes of other team members.
  5. I believe that the most important aspect of our transdisciplinary project is learning from each other and reflecting together.
  6. I think that transdisciplinary projects promote more problem awareness and a higher level of ownership of solutions among the participants than more traditional research processes.
  7. I think that in our transdisciplinary project the project leader acts as a coordinator and represents the decisions of the groups externally and internally.
  8. I experience the high need for coordination resulting from the heterogeneity of the project team as inefficient.
  9. I think that despite the collaboration in the project team at eye level, the project management has the control and final decision-making power.
  10. The project has failed for me if no direct tangible results (eg., strategy, plans, etc.) are produced.
  11. I think that we work together as equals in our team.
  12. I believe that dealing with complex challenges requires consideration of non-scientific perspectives and knowledge.
  13. I believe that a common language that is easy for everyone to understand is a key success factor.
  14. I think the strength of transdisciplinary projects is to contribute to social change rather than research.
  15. I perceive the open-endedness of the project as uncertainty, since it is not clear where the journey will lead.
  16. I perceive the project as a risk, because by working with heterogeneous partners, results can occur for which I do not want to take responsibility.
  17. I consider it essential that all partners of the transdisciplinary research project are always involved in every step of the process.
  18. Due to the complexity of a transdisciplinary project, a predefined plan with clear goals and structure is essential.
  19. I believe that being involved in our transdisciplinary project provides me with recognition and benefits in my professional environment.
  20. It is important to me that through this project we develop and establish new ways of doing things in regional development practice.
  21. I believe that the heterogeneity of the participants improves the results of the project (compared to classical research collaborations).
  22. The project gives me the opportunity to experience self-efficacy and to actively participate in a transformation process.
  23. I think it is important to give the group building process enough time.
  24. I believe that the result will be worth the extra effort compared to “classically” organized research projects.
  25. I believe that for successful project implementation, disclosure and management of conflicts within the team is inevitable.
  26. I believe that all project partners should bear responsibility for the project – from project start to implementation.
  27. Due to the complexity of a transdisciplinary project, flexibility in planning, goal formulation and implementation is required.
  28. I find it quite difficult when my professional expertise is questioned in the group.
  29. I perceive participation in the transdisciplinary project as an opportunity for personal development.
  30. I consider the open-endedness of the project as an opportunity to experiment and try out new paths.
  31. It is important to me to already set the foundation for the transition to the post-project phase during the project.
  32. The recognition and support of the results by political decision-makers is crucial for our project success.
  33. I think that openness and tolerance are key qualities for collaboration in transdisciplinary processes.
  34. In our collaboration, I experience the willingness and openness to learn from each other and to get engaged in different working practices.

Advantages of using Q-methodology to assess expectations and assumptions in the early phases of transdisciplinary research.

Assessing expectations and assumptions early in the research can:

  • elucidate a variety of expectations about transdisciplinary research collaboration and its outcomes;
  • reveal subjective expectations of all project team members which can be clustered into different viewpoints (in our project, the Q-methodology resulted in two viewpoints that emphasized learning on the one hand and experimenting with new regional development practices on the other);
  • highlight the important role of an epistemediator or knowledge broker in transdisciplinary research collaborations, especially to mediate different expectations between the realm of science and the realm of practice;
  • reveal commonalities but also major discrepancies in the expected outcomes of transdisciplinary research collaboration among the project team members;
  • identify different implicit tensions, especially between:
    • “I” and “We”;
    • disciplinary versus transdisciplinary research;
    • research versus learning;
  • emphasize the importance of reflexive practice in transdisciplinary research teams to bridge different thought collectives, support the research process and ‘robust’ outcomes, and maintain friendly relationships and trust within the transdisciplinary research team;
  • integrate theory-based with context- and place-specific categories necessary for transdisciplinary research projects;
  • provide a basis for allocating resources and planning next project steps in early research phases that are crucial for group formation and trust building.


Our learnings are based on our experiences and research conducted in a regional sustainable development project (Radinger-Peer et al. 2022). How have you gone about assessing expectations and assumptions in transdisciplinary research?

To find out more:

Radinger-Peer, V., Schauppenlehner-Kloyber, E., Penker, M. and Gugerell, K. (2022). Different Perspectives on a Common Goal? The Q-method as a Formative Assessment to Elucidate Varying Expectations Towards Transdisciplinary Research Collaborations. Sustainability Science. (Online – open-access): https://doi.org/10.1007/s11625-022-01192-1


Watts, S. and Stenner, P. (2012). Doing Q Methodological Research: Theory, Method and Interpretation. SAGE Publications: London, United Kingdom.

Biography: Verena Radinger-Peer PhD is a senior researcher at the Department of Economics and Social Sciences, University of Natural Resources and Life Sciences (BOKU), Vienna, Austria. Her research focuses on sustainable landscape development research, in particular processes of institutional change, agency and inter- and transdisciplinary research.

Biography: Katharina Gugerell PhD is appointed as tenure track professor ‘Sustainable Land-Use’ at the Department of Landscape, Spatial- and Infrastructure Science at the University of Natural Resources and Life Sciences (BOKU), Vienna, Austria. Her research interests cover topics such as land-use-governance, creative and foresight methods, transdisciplinary and policy studies.

Biography: Marianne Penker PhD is Professor of Rural Sociology and Rural Development at the Department of Economics and Social Sciences, University of Natural Resources and Life Sciences (BOKU) Vienna, Austria. Her main interests cover sustainable rural development research as well as theoretical and methodological contributions to transdisciplinary research.

6 thoughts on “Externalizing implicit expectations and assumptions in transdisciplinary research”

  1. Dear Marianne,
    The format of this blog welcomes attempts to strengthen the position of the authors of the posts. Therefore, I am trying to draw your attention to those of your statements that your detractors may pay attention to. For example, you write: “Those involved in producing actionable and robust knowledge for uncertain challenges with high decision stakes like pandemics, biodiversity loss or climate change, generally lack a clear-cut job description.” In your opinion, this circumstance leads to the inevitability of ambiguity.

    Silvio Funtowicz and I briefly discussed this topic on October 19, 2021 on the page of this blog https://i2insights.org/2021/10/19/guide-to-post-normal-science/ . In conclusion, he said: “Personally, I’m not in favor of eliminating ambiguity but I understand that others have a different program. I also believe we should focus our attention beyond scientific knowledge, acknowledging a broad range of knowledges”.

    You may be interested in my interpretation of these two theses.

    Knowledge is systematized reliable information that is applied to the field of cognition, in the implementation of actions, in decision–making, in conducting risk analysis. Unsystematic reliable information is the opinions expressed by specialists and non–specialists on a particular occasion, phenomenon and process. Science is one of the ways to systematize reliable information. In science, classifications of disciplinary knowledge and methods of working with them are being formed. Therefore, if we wish to combine opinions and knowledge, then we must include them in the appropriate classification of disciplinary knowledge. Otherwise, opinions that seem important at first glance may be carriers of a different context. It is this circumstance that can cause ambiguity. For example, three statements are possible: the Earth is a spaceship; the Earth is a living organism; the Earth is a space object that supports the life of humankind. Existing opinions can support each statement. Scientific knowledge can justify only one of them. The situation “generally lack a clear-cut job description” is a signal for a specialist to move to a new horizon of scientific worldview and use its theoretical and methodological apparatus. This new level will allow you to rethink the problem, discover the missing knowledge, include reliable opinions in their composition, eliminate ambiguity as much as possible.

    It is this reason that allowed us to build the following series of definitions:
    Transdisciplinarity is a designation of the intellectual activity intensification in the area of interdisciplinary interactions contributing to maximum broadening of the scientific worldview horizon.
    Such a definition of transdisciplinarity supposes availability of the tools that ensure broadening of the scientific worldview horizon. The role of such tools in the area of interdisciplinary interactions is played by the transdisciplinary and systems transdisciplinary approaches. Considering the generalized definition of transdisciplinarity, the definition of the transdisciplinary approach will be as follows:
    Transdisciplinary approach is a method of broadening the scientific worldview horizon in terms of a natural-science worldview by the implementation of integrative trends of disciplinary, interdisciplinary, and multi-disciplinary knowledge and models of the object. In the classification of the academic scientific approaches, the transdisciplinary approach allows maximum integration and synthesis of disciplinary knowledge by the idealized object model.
    In turn, the definition of the systems transdisciplinary approach will be as follows:
    Systems transdisciplinary approach is a method of broadening the scientific worldview horizon within the limits of the philosophic picture of a single world by simulation of the object in the form of the transdisciplinary system by allowing the use of the systems transdisciplinary methodology for its research.

    I want to give examples in which the systems transdisciplinary expansion of the scientific worldview allowed us to combine opinions and knowledge and, thereby, eliminate the ambiguity of some of the high-threshold problems that you reported:
    Mokiy, V. S., & Lukyanova, T. A. (2022). Covid-19: Systems transdisciplinary generalization, technical and technological ideas, and solutions. Informing Science: The International Journal of an Emerging Transdiscipline, 25, 1-21. https://doi.org/10.28945/4893
    Mokiy, V.S., & Lukyanova, T.A. (2022). Sustainable development of nature and society in the context of a systems transdisciplinary paradigm. Transdisciplinary Journal of Engineering & Science, 13, Special Issue on Complex Resilience and Sustainability. Transdisciplinary Perspectives, In G. del Cerro Santamaría (Ed.), 15-35. https://doi.org/10.22545/2022/00192
    Mokiy V.S, Lukyanova T.A. (2022). Prospects of integrating transdisciplinarity and systems thinking in the historical framework of various socio-cultural contexts. Transdisciplinary Journal of Engineering and Science, 13. pp. 143-158. https://doi.org/10.22545/2022/00184
    Mokiy, V. S., & Lukyanova, T. A. (2022). Modern transdisciplinarity: Results of the development of the prime cause and initial ideas. Issues in Informing Science and Information Technology, 19, pp. 97-120. https://doi.org/10.28945/4951
    Mokiy, V.S., Lukyanova, T.A. (2022). Manifesto for systems transdisciplinarity (2023-2030). Universum: Social sciences, 9(88). https://7universum.com/ru/social/archive/item/14313

    • Dr. Mokiy,

      Thank you for coming back to us. Your response addresses a somewhat older discussion emphasizing whether TD
      (i) is a new discipline (based here in Vienna, we firstly think on Ludwig von Bertalanffy or Erich Jantsch, but also on Jean Piaget, or Basarab Nicolescu; from your response, articles and posts, we assume your line of thinking and reasoning corroborates this conceptualisation, where in the extreme case, one single scholar trained as td meta-theorist tackles a complex societal challenges;
      (ii) is a boundary-crossing practice that involves expertise from different academic disciplines and non-academic stakeholders’ expertise, skills, thus, acknowledging ‘other forms of knowing’ for generating actionable and societally relevant knowledge.
      Both conceptualisations exist in parallel, which is illustrated by well-developed, solid bodies of literature and current i-td discourses and documented cases of societally relevant research. Scientific rigor, expertise shared among peers, different methods of knowledge integration and co-production of knowledge are relevant for both approaches.
      It its less an either-or question, with the perspective of the grand challenges that societies are facing, both approaches will be essential: (i) Td meta-theorists, that are working on a unity of reliable scientific knowledge AND (ii) experts who organize and methodise science-society interactions for co-creating societally robust knowledge with those stakeholders that can make change happen.

      Kind regards,
      Katharina Gugerell,
      On behalf of the authors

      • Katharina, you are absolutely right!
        “Both approaches will be needed: (i) Td-metatheorists who work towards the unity of reliable scientific knowledge AND (ii) experts who organize and methodize the interaction of science and societies to co-create socially sound knowledge with those stakeholders who can bring about change”.
        However, for readers who are watching our discussion, it is necessary to clarify why “a both approaches will be needed” today.

        Single scientist trained as a td-metatheorist does not solve complex social problems. Td-metatheorist can rethink a complex high-threshold problem for which “the facts are [unclear], values are debatable, the stakes are high, and decisions are urgent”, and organize its solution (to determine the concept that will play the role of a general context; types of scientific disciplines; number of disciplinary experts; scope and timing of disciplinary research work). In this case, the main research work in the transdisciplinary team will be performed by the experts who organize and methodize the interaction of science and societies to co-create socially sound knowledge with those stakeholders who can bring about change.

        September 14, 2021 in the post “Transdisciplinary Integration: A Multidimensional Interactive Process”, written by Dena Fam, Julie Thompson Klein, Sabine Hoffmann, Cynthia Mitchell and Christian Pohl, I managed to have a fruitful discussion with Julie Thompson Klein https://i2insights.org/2021/09/14/transdisciplinary-integration/. In the course of this discussion, I have proposed a classification of expert groups that may be of interest to you.

        In conclusion, I want to draw your attention to some circumstances. I think that in solving such problems as: substantiating a new model of the world socio-economic order; a method of managing the sustainable development of modern society, ending major international military-political conflicts, it is risky to involve experts from society. The risk is that the role of such experts is usually played by representatives of local, regional or state elites. Elites always pursue certain political goals. In turn, scientific experts can be guided by scientifically-based objective parameters of the development of society. Is it possible that in order to solve such high-threshold problems, experts from society should be replaced with the knowledge of Deep-peoples, carriers of the socio-cultural codes of each state?

        • Dear Vladimir,
          In our contribution we emphasize the role of “experts who organize and methodize the interaction of science and societies” which we refer to as “epistemediators” (Wiek, 2007:57) (also referred to as ‘Knowledge Brokers’ (Miller 2013; Loorbach et al 2011), ‘Intermediaries’ (Hilgeret al 2021). Within our case study in Lower Austria (Austria), their role as intermediary and translator between different actors, worldviews turned out to be crucial to “facilitate the (epistemic) process of joint knowledge generation” (Radinger-Peer et al. 2022). Moreover, their knowledge on and experience in place-specific hierarchies, power structures as well as informal networks was a further aspect, which made their role in our td-research project even more valuable and they successfully facilitated a collaboration on “eye-level”: their knowledge on place-specific hierarchies, power structures as well as informal networks.
          What you name “circumstances” we refer to as “place-specificity”. We are convinced that the initiation and implementation of TDR needs to take into account the (context- and place-) specific situation (Thompson et al. 2017). Epistemediators know when to involve randomly selected representatives of society instead of local elites, or which integration methods are most helpful for particular contexts and help mitigating risks coming with power differentials, vested interests or strategic behaviour.
          We thank you for your interest in our publication and for the multi-faceted discussion on our blog post.

  2. Dear colleagues,
    Recently, an elderly professor exclaimed: “Disciplinarity is a strict order, and interdisciplinarity is a welcome freedom!”. I remembered this thesis when I read your message.

    The term “freedom” can be understood as the absence of a strictly disciplinary order in the organization of interdisciplinary interactions. It seemed to me that you were offering a disciplinary specialist a set of elements of a new, “non-disciplinary freedom” for him. Next, you analyze individual images of non-disciplinary freedom and form expectations and assumptions of team members in transdisciplinary research collaborations to be identified. It is difficult for me to analyze your proposals in the absence of a definition of the terms: interdisciplinarity and transdisciplinarity, which would clarify the context of your message. Therefore, let me philosophize a little on this topic.

    Interdisciplinary interactions are the designation of a set of integrating factors that contribute to the formation of logical structures of complementary disciplines. Within the framework of such logical structures, disciplinary knowledge is integrated and synthesized, as well as their unification and generalization. All this contributes to the expansion of the horizon of the scientific worldview of disciplinary specialists.

    What does “non-disciplinary freedom” mean when integrating, synthesizing, unifying and generalizing disciplinary knowledge? This term means the voluntary adoption of a new interdisciplinary and transdisciplinary order that will exceed the rigor of the disciplinary order. Otherwise, the more “non-disciplinary freedom” there is in the organization of interdisciplinary interactions, the dimmer the prospects for new horizons of the scientific worldview, the lower the scientific rigor of the proposed solutions.

    Now – conclusions.
    Question: How can implicit expectations and assumptions of team members in transdisciplinary research collaborations be identified?
    Answer: I suggest that transdisciplinary research can be applied in solving low-threshold, medium-threshold and high-threshold problems. In the direction from low-threshold to high-threshold problems, the scale of negative consequences from ineffective solutions increases. The basis of such decisions, among other things, are implicit expectations and assumptions of team members. Therefore, in order to solve high-threshold problems, it is advisable to formulate a strict professional job description for a member of a transdisciplinary team. The points of this instruction should initially form a state of personal psychological comfort for each team member. To solve low-threshold problems, it is permissible to use Q-methodology, which allows implicit expectations and assumptions of team members. I hope my philosophizing can be useful to you.

    • Thank you for your thoughts and valuable contributions. We are happy to share our definition of transdisciplinarity and come up with an opposing conclusion on thresholds of problems that might benefit from expectation management and our q-statements.

      Different from your notion of transdisciplinarity as meta-discipline, we are focusing at the transgression of academic boundaries by involving non-academic expertise and skills into our research. In our Sustainability Science article, we conceptualize transdisciplinary research collaboration as a collaboration of scientists and practice partners aiming for both rigorous contributions to scientific progress and the co-creation of ‘workable’ solutions for societal problems.

      Your differentiation in low, medium and high thresholds problems is interesting and resonates with Sivlio Funtowicz and Jerome R. Ravetz, who also classify problems regarding their decision stakes and uncertainty. In contrast to your conclusion, we follow Funtowicz and Ravetz and consider transdisciplinary research collaboration and thus, the involvement of practice partners as most appropriate when “facts [are] uncertain, values in dispute, stakes high and decisions urgent”.

      Those involved in producing actionable and robust knowledge for uncertain challenges with high decision stakes like pandemics, biodiversity loss or climate change, generally lack a clear-cut job-description. For these situations, our q-statements can help to elucidate varying expectations.


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