Proximity lens on structural collaborations
Written by: Hedi Westerduin
Date: 01-09-2022
What is proximity?
Proximity dimensions provide a lens to identify and highlight conditions that enable successful cooperation (e.g. through co-production or co-design) and processes of relationship-building, rather than evaluation of outputs or outcomes of academic projects. The concept of proximity is often used in the innovation literature to explain why knowledge transfer and/or collaboration between different organizations is successful. It usually describes the exchange between organisations and between knowledge institutions and industry. Historically primarily considered as a spatial dimension: smaller geographical distance or actively arranging physical encounters are likely to increase knowledge transfer and cooperation. Over time a wider range of proximity categories emerged, each with their own definition and operationalisation (for an overview see Knoben & Oerlemans, 2006). Following Boschma (2005) we distinguish the following five dimensions of proximity (for more details, see the ‘how’ section):
- Geographical proximity - The spatial or physical closeness between actors.
- Social proximity - Socially embedded relations between actors.
- Organisational proximity - The degree of similarity (or good coordination) in organisational logics, routines, methodologies, practices, governance and incentive mechanisms.
- Cognitive proximity - Similarity in knowledge base between different actors.
- Institutional proximity - Humanly devised elements that structure interaction between individuals and groups at the macro level.
It is important to note that proximity concerns a dynamic perspective: the degree and mix of proximity changes over time. For instance, geographical proximity can stimulate social proximity, because short geographical distances favour social interaction and trust building. In turn, the need to regularly meet face to face might eventually decrease once the relationship is established (Boschma, 2005; Heringa et al., 2014).
Why should it be used?
To tackle current complex societal challenges requires cooperation between science, government, industry and societal stakeholders. Proximity dimensions can provide a useful lens to better understand, evaluate and organise knowledge exchange and/or collaboration between different organizations. The extent to which a certain degree of proximity (or distance) is realised as a process condition, can be an important - possibly necessary - factor in achieving an impact objective. This type of process-based evaluation can help identify strengths and weaknesses and can thus help to assess how the design of a collaboration, including the mix of proximities, matches the practical interpretation and experience of those involved. In addition, it offers a lens to signal which dimensions of proximity (or distance) may deserve attention to strengthen collaborative processes in the future.
When using a proximity lens, it is important to consider a couple of remarks. Proximity dimensions provide an analytical lens rather than practical guidance. A proximity lens can help to conceptualise and identify conditions to improve collaborative processes but not the concrete translation to practically applicable actions.
When should it be used?
Proximity can be a useful lens within structural collaborations or longer-term research projects with elements of co-creation, action research, transdisciplinary research, living lab approaches, or other forms of collaboration and engagement. The proximity lens provides insight into processes of interaction, production and transfer of knowledge and relationships between actors. This lens can be useful at the beginning of establishing a collaboration or collaborative project (ex ante), or during the process of collaboration (ex durante) to inform or improve the design of the collaboration.
Note that the required degree of proximity for successful collaboration may change over time because of changing mechanisms and dynamics between collaborative partners. Be aware that these dynamics may influence the design of your assessment and the conclusions you draw.
How can it be used?
Proximity dimensions can help guide the conversation about conditions that enable successful cooperation in relation to your impact goals and the design of your collaboration. Underlying all of this is the belief that engaging with stakeholders in productive interactions leads to societal impact. Actively thinking about and defining the conditions that contribute to knowledge exchange helps align efforts to establish productive interactions that ultimately contribute towards a project achieving societal impact.
To help identify the conditions for productive interactions in accordance with a proximity lens, the following table summarises key aspects of the interplay between proximity and distance within five dimensions of proximity (based on Boschma (2005) and Knoben & Oerlemans (2006)).
Geographical proximity - The spatial or physical closeness between actors | |
Background | Close (absolute and relative) spatial distances favour contacts, encounters and transfer of implicit knowledge. Particularly important in the establishment of collaboration, where it may stimulate other proximity dimensions. However, too much geographical proximity may weaken innovative performance and impede responses to new developments. |
Aspects to consider | Shared workspace, fixed and/or changing meeting and event venues, places in the city, meeting spots, travel time, access and reachability. |
Social proximity - Socially embedded relations between actors | |
Background | Relationships of trust (friendship, experience, background) stimulate interactive learning and transfer of implicit knowledge. Too little social proximity may lead to a lack of trust and commitment, while too much social proximity can lead to an underestimation of opportunistic behaviour by the trusted partner and may lock out outsiders with new ideas or qualities. |
Aspects to consider | Level of education, prior acquaintance, existing, overlapping, or open networks and the degree of trust and transparency between actors |
Organisational proximity - The degree of similarity (or good coordination) in organisational logics, routines, methodologies, practices, governance and incentive mechanisms | |
Background | Organisational proximity can contribute to the exchange of complementary and complex knowledge while simultaneously reducing opportunism. The easier interaction and coordination attributed to organizational proximity is especially useful when establishing a new collaboration. However, too much organizational proximity may undermine learning and innovation because of a lack of flexibility and the risk of being locked in specific relationships, which may hinder access to other sources of useful information. |
Aspects to consider | Timing and tempo of organisational processes, norms, values, interests and cultural differences within and between organisations. |
Cognitive proximity - Similarity in knowledge base between different actors | |
Background | To communicate and transfer knowledge effectively, actors require similar frames of reference. A shared knowledge base, understanding and expertise relate to how actors perceive, interpret, understand, and evaluate the world. Collaborative partners should be close enough to understand each other and communicate efficiently, while remaining distant enough to yield an innovative collaboration with complimentary knowledge and creativity. Thus, avoiding a narrowed vision. |
Aspects to consider | Educational background, familiarity with scientific methods and similarity in professional, theoretical or practical knowledge base. |
Institutional proximity - Humanly devised elements that structure interaction between individuals and groups at the macro level | |
Background | The extent and the way actors or organisations coordinate their actions is an enabling condition for collaboration, knowledge transfer and interactive learning. Stable conditions for collective action reduce uncertainty and lower transaction costs. A balance needs to be struck between institutional stability, openness and flexibility: enough stability to provide social cohesion and common values while avoiding institutional lock-in and inertia by being open and flexible. Institutional proximity is therefore strongly interconnected with social and organizational proximity. |
Aspects to consider | Formal (such as laws and rules) as well as informal (such as common values, habits and cultural norms) elements. |
What is obtained?
Proximity can be used as an analytical lens to gain a better understanding of factors that enable interaction between different actors and organisations in collaborations. You do not necessarily obtain a tangible product since the added value comes from applying proximity dimensions as an analytical lens. However, the insights gained can potentially be translated into practical, formal, and social preconditions. While doing this it is key to keep in mind that there needs to be a balance in the level of proximity. Although each proximity dimension can improve collaboration, interaction and innovation, too much proximity can have negative effects such as a narrowed view and exclusivity.
Who is a stakeholder and who is involved in an assessment using this method?
All actors who are involved in achieving the societal impact objective, particularly those tied to the knowledge exchange processes. Usually this includes project management, researchers, beneficiaries, and ideally any key stakeholders (i.e., consulted, informed, or involved). When we applied the proximity lens, it was always as an external assessor. We found a certain degree of distance from the actual work helped in using the analytical lens. This is good to keep in mind if you want to apply a proximity lens to a knowledge exchange and/or collaboration you are participating in.
Take a look at the case study at the bottom of this page, where we applied a proximity lens to study structural collaborations between knowledge institutions and government agencies in Rotterdam. Additionally, we made use of the proximity dimensions as an analytical lens to research the long-running collaboration between Nederlandse Spoorwegen (NS) and Econometrics Institute at Erasmus School of Economy of Erasmus University Rotterdam.
Literature
Boschma, R. (2005). Proximity and innovation: a critical assessment. Regional studies, 39(1), 61-74.
Heringa, P. W., Horlings, E., van der Zouwen, M., van den Besselaar, P. & W. van Vierssen. (2014). How do dimensions of proximity relate to the outcomes of collaboration? A survey of knowledge intensive networks in the Dutch water sector. Economics of Innovation and New Technology, 23:7, 689-716.
Knoben, J., & L. A. G. Oerlemans. (2006). “Proximity and Inter-Organizational Collaboration: A Literature Review.” International Journal of Management Reviews 8 (2): 71–89.
Evaluating a knowledge infrastructure between knowledge institutions and government agencies in Rotterdam
Written by: Hedi Westerduin
Date: 01-09-2022
Duration: This research project took place between February 2021 and December 2021
Stakeholders: Gemeente Rotterdam and Erasmus Universiteit Rotterdam
ESI researchers: Jorrit Smit and Hedi Westerduin
In this evaluative study on structural collaborations between the municipality of Rotterdam and the Erasmus University Rotterdam (EUR), we used the concept of boundary management (Parker & Crona, 2012) and proximity (Boschma, 2005) as a conceptual lens to understand the functioning of these collaborations. Our experiences are summarized below.
A knowledge infrastructure between science and policy in Rotterdam
This study focused on a system of local science-policy collaborations in Rotterdam, also referred to as a ‘knowledge infrastructure’. Since 2010, the municipality of Rotterdam and the EUR made an investment in their relationship by initiating, stimulating and facilitating the establishment of thematically oriented structural collaborations between scientific researchers, policymakers and other relevant actors in the city. Their agreement expressed the intention to bring science closer to society and inform and support municipal policy with scientific evidence.
Evaluating Societal Impact (ESI) was requested by both parties to assess the functioning and diversity of this knowledge infrastructure. We made a case selection of eleven structural collaborations in the form of knowledge labs, academic collaborative centres and centres of expertise (from here on referred to as collaborations). Although the collaborations vary in terms of objectives, origin, funding and composition, the selection was based on four common characteristics: all collaborations included municipal policymakers and EUR researchers, received structural financial support from both parties, formalized their collaboration to some extent in the form of an agreement and all collaborations were aimed at topics of societal relevance to the city of Rotterdam.
What did the assessment consist of?
The research process was approached as ‘appreciative inquiry’, meaning that we aimed at understanding the functioning of collaborative processes and the conditions that sustain and nurture existing practices (e.g. knowledge transfer, long-term relationship building) (Douthwaite et al., 2003). The productive interactions between science, policy and practice were the object of study (Spaapen & Van Drooge, 2011).
In our analysis we approached the collaborations as hybrid research spaces (Wehrens, Bekker, & Bal, 2014) where boundaries between the relatively separate worlds of politics, policy, practice and science become temporarily or locally permeable (Guston, 2001). We used the concept of boundary management to interpret the processes that take place within these spaces: the continuous negotiation between the diverse interests and desires of heterogeneous actors (Parker & Crona, 2012). We studied what boundaries were broken down or blurred and what boundaries were simultaneously being perpetuated or even erected. We also studied how boundary management was manifested to establish and facilitate productive interactions and to what extent the way collaborative processes were organised contributed to this. To gain a better understanding of the conditions underlying cooperation in hybrid research spaces, we used dimensions of proximity (Boschma, 2005; Heringa et al., 2014) as an analytical lens. Proximity dimensions (social, cognitive, organisational and physical proximity) helped guide the conversation about conditions that enable successful cooperation in relation to the impact objectives of the collaborations and the design of their collaborative processes.
The research project consisted of document analysis, observations, 58 semi-structured interviews and two focus groups with members of the selected collaborations. To obtain a general sense of the atmosphere and the interactions within and between the collaborations we did observations at several public events. For document analysis, we used pre-designed case study formats (see report page 55) for every collaboration to order the data collected from publicly available and internal sources. From this followed an interview protocol (see report page 63) that focused on the productive interactions between heterogeneous actors (Spaapen & Van Drooge, 2011) and invited respondents to make explicit their views on what constitutes successful cooperation, how they aimed to achieve impact and to what extent they experienced this as successful (evaluative statements). Lastly, we organised two focus groups to validate and enrich findings from the interviews. After the study was documented in a report, we organised reflective sessions with a few of the collaborations to jointly reflect on the findings of the study and the lessons to strengthen cooperation in the future.
What was the result of the analysis?
By analysing the collaborations as hybrid research spaces, we observed at least four types of boundary management taking place: boundary management between 1) policy design and scientific research, 2) political decision-making and science-policy collaborations, 3) knowledge-driven policy design and implementation in practice and 4) science-policy collaborations and urban practices. Each collaboration can be understood as a unique combination of different types of boundary management carried out through various activities; for example, we found that the boundary between scientific research and policymaking blurs as scientists and policymakers design, produce and disseminate knowledge together while dissemination activities, such as workshops and expert meetings are often aimed at practitioners, citizens, or politicians. Participatory research, in which people other than scientists actively participate in data collection, analysis and interpretation, occurred in some collaborations.
Adding another interpretative layer by viewing the hybrid space through a proximity lens provided an instrumentarium to analyse the conditions that facilitate and prohibit productive interactions and knowledge exchange. We found that science-policy collaborations generate different types of proximity and can also deliberately deploy various configurations of proximity to make certain interactions and outcomes more likely. Regarding boundary management between science and policy, we found that the collaborations create spaces where social and cognitive proximity can grow organically. Conversely, strong social networks were in many cases also a condition for the establishment of collaborations. We found that physical proximity (e.g. a shared project space) can play an important role in this. At the level of cognitive proximity, a balance between distance (transparent but traditional division of roles) and proximity (continuous engagement for co-creation) seemed to be the biggest challenge. In relation to politics, we found that appropriate organizational and cognitive distance to (the agenda of) science-policy collaborations is of great importance, but sufficient social proximity is also necessary to connect with the right people at the right time. The greatest challenge for the collaborations we studied relates to boundary management towards the field of practice (e.g. policy implementation, practitioner organisations and civilians). The existence of a relatively large social, organizational and cognitive distance in this regard can explain this. Participatory research methods and explicitly seeking physical proximity have the potential to reach and involve the field of practice more actively and effectively.
The concepts of boundary management and proximity can benefit collaborations between science, policy, and practice as tools for reflection. Over the course of the project, we experienced that facilitating dialogue and exchange on the ‘who’, ‘how’ and ‘why’ of cooperation can be a learning situation in itself. Critically reflecting on this can help establish certain practical, formal and social preconditions that can be important factors for achieving an impact objective.
For more elaborate learnings please find the report ‘Bevlogen grenzenwerk, begrensde nabijheid’ and the summary (both in Dutch) below as downloadable files.
References
Boschma, R. (2005). Proximity and innovation: a critical assessment. Regional studies, 39(1): 61-74.
Douthwaite, B. et al. (2003) ‘Impact pathway evaluation: an approach for achieving and attributing impact in complex systems’, Agricultural systems, 78(2): 243–265.
Guston, D.H. (2001) Boundary organizations in environmental policy and science: an introduction. Sage Publications Sage CA: Thousand Oaks, CA.
Heringa, P. W., Horlings, E., van der Zouwen, M., van den Besselaar, P. & van Vierssen, W. (2014). How do dimensions of proximity relate to the outcomes of collaboration? A survey of knowledge intensive networks in the Dutch water sector. Economics of Innovation and New Technology, 23:7, 689-716. DOI: 10.1080/10438599.2014.882139.
Parker, J., & Crona, B. (2012). On being all things to all people: Boundary organizations and the contemporary research university. Social Studies of Science, 42(2): 262–289.
Spaapen, J. and Van Drooge, L. (2011) ‘Introducing “productive interactions” in social impact assessment’, Research evaluation, 20(3): 211–218.
Wehrens, R., Bekker, M. & Bal, R. (2014). Hybrid management configurations in joint research. Science, Technology, & Human Values, 39(1): 6–41. DOI: 10.1177/0162243913497807.